British Journal of Radiology

Determining the library size for the optimal output plan in the RapidPlan knowledge-based planning system using multicriteria optimization

Abstract Objectives The aim of this study was to determine the number of trade-off explored (TO) library plans required for building a RapidPlan (RP) library that would generate the optimal clinical treatment plan. Methods We developed 2 RP models, 1 each for the 2 clinical sites, head and neck (HN) and cervix. The models were created using 100 plans and were validated using 70 plans (VP) for each site respectively. Each of the 2 libraries comprising 100 TO plans was divided into 5 different subsets of library plans comprising 20, 40, 60, 80, and 100 plans, leading to 5 different RP models for each site. For every validation patient, a TO plan (TO_VP) was created. For every patient, 5 RP plans were automatically generated using RP models. The dosimetric parameters of the 6 plans (TO_VP + 5 RP plans) were compared using Pearson correlation and Greenhouse-Geisser analysis. Results Planning target volume (PTV) dose volume parameters PTVD95% in 6 competing plans varied between 97.6 ± 0.7% and 98.1 ± 0.6% in HN cases and 98.8 ± 0.3% and 99.0 ± 0.4% in cervix cases. Overall, for both sites, the mean variations in organ at risk (OAR) doses or volumes were within 50 cGy, 0.5%, and 0.2 cc between library plans, and if TO_VP was included the variations deteriorated to 180 cGy, 0.4%, and 15 cc. All OARs in both sites, except D0.1 ccspine, showed a statistically insignificant variation between all plans. Conclusions Dosimetric variation among various output plans generated from 5 RP libraries is minimal and clinically insignificant. The optimal output plan can be derived from the least-weighted library consisting of 20 plans. Advances in knowledge This article shows that, when the constituent plans are subjected to trade-off exploration, the number of constituent plans for a knowledge-based planning module is not relevant in terms of its dosimetric output.

The impact of an educational tool in cervix image registration across three imaging modalities

Objectives Accurate image registration is vital in cervical cancer where changes in both planning target volume (PTV) and organs at risk (OARs) can make decisions regarding image registration complicated. This work aims to determine the impact of a dedicated educational tool compared with experience gained in MR-guided radiotherapy (MRgRT). Methods 10 therapeutic radiographers acted as observers and were split into two groups based on previous experience with MRgRT and Monaco treatment planning system. Three CBCT-CT, three MR-CT and two MR-MR registrations were completed per patient by each observer. Observers recorded translations, time to complete image registration and confidence. Data were collected in two phases; prior to and following the introduction of a cervix registration guide. Results No statistically significant differences were noted between imaging modalities. Each group was assessed independently pre- and post-education, no statistically significant differences were noted in either CBCT-CT or MR-CT imaging. Group 1 MR-MR imaging showed a statistically significant reduction in interobserver variability (p=0.04), in Group 2, the result was not statistically significant (p=0.06). Statistically significant increases in confidence were seen in all three modalities (p≤0.05). Conclusions At The Christie NHS Foundation Trust, radiographers consistently registered images across three different imaging modalities regardless of their previous experience. The implementation of an image registration guide had limited impact on inter- and intraobserver variability. Radiographers’ confidence showed statistically significant improvements following the use of the registration manual. Advances in knowledge This work helps evaluate training methods for novel roles that are developing in MRgRT.

Radiogenomic profiling to determine BRCA alteration status—a systematic review and meta-analysis

Abstract Objectives Approximately 10% of breast and 20% of ovarian cancers are hereditary in nature. The most commonly implicated genes are the BRCA genes, and the current gold standard for testing is by direct DNA sequencing. This process is expensive, time-consuming, and has a turnaround time of several weeks. Radiogenomics involves extracting quantitative data from medical imaging and using mathematical models to predict the underlying genetic makeup of tissues. Aim To perform a systematic review and meta-analysis evaluating the accuracy of radiogenomics in determining BRCA alteration status. Methods A systematic review was performed in accordance with PRISMA guidelines. Diagnostic test accuracy analyses (i.e. pooled sensitivity and specificity) were performed. Statistical analyses were performed using RevMan V5.4. Results Thirteen studies compromising 2835 patients were included. Of these, 857 were BRCA alteration carriers. The mean age of patients was 46 years. Radiogenomic methods correctly identified BRCA alteration with a strong diagnostic test accuracy (pooled sensitivity: 0.82, 95% confidence interval [CI]: 0.79-0.84, pooled specificity: 0.81, 95% CI: 0.78-0.83). Conclusions Radiogenomics may be an accurate method to predict BRCA alterations. However, these findings should be validated in larger, prospective studies to determine their utility in clinical practice. Until further refinement of these methods, DNA sequencing should remain the gold standard. Advances in knowledge To the best of our knowledge, this is the first systematic review and meta-analysis that has been carried out on this topic. We believe that our results demonstrate the potential clinical utility radiogenomics could have in the BRCA alteration testing process.

Radioproteomics in patients with ovarian cancer

Radioproteomics is the integration of proteomics, the systematic study of the protein expression of an organism, with radiomics, the extraction and analysis of large numbers of quantitative features from medical images. This article examines this developing field, and it’s application in high grade serous ovarian carcinoma. Seminal proteomic studies in the area of ovarian cancer, such as the PROVAR and CPTA studies are discussed, along side recent research, such as that highlighting the central role of methyltransferase nicotinamide N-methyltransferase as the metabolic regulation of cancer progression in the tumour stroma. Finally, this article considers a novel, hypothesis generating approach to integrate CT-based qualitative and radiomic features with proteomic analysis, and the future direction of the field. Combined advances in radiomic, proteomic and genomic analysis has the potential to signal the age of true precision medicine, where treatment is centered specifically on the molecular profile of the tumour, rather than based on empirical knowledge, thus altering the course of a disease that has the highest mortality of all cancers of the female reproductive system.

T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study

Objective: To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer. Methods: Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0–2000 s/mm2). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADCmean, ADCmin, Dmean, Dmin, D*, f, MDmean, MDmin, MKmean, and MKmax) were compared based on histological type, grade, and LVSI status. Results: Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MKmean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADCmin, Dmin, and MDmin were significantly lower while MKmax was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MKmean than LVSI-negative SCC (p < 0.05). Conclusion: Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients. Advances in knowledge: Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.

Radiomics in cervical and endometrial cancer

Radiomics is an emerging field of research that aims to find associations between quantitative information extracted from imaging examinations and clinical data to support the best clinical decision. In the last few years, some papers have been evaluating the role of radiomics in gynecological malignancies, mainly focusing on ovarian cancer. Nonetheless, cervical cancer is the most frequent gynecological malignancy in developing countries and endometrial cancer is the most common in western countries. The purpose of this narrative review is to give an overview of the latest published papers evaluating the role of radiomics in cervical and endometrial cancer, mostly evaluating association with tumor prognostic factors, with response to therapy and with prediction of recurrence and distant metastasis.

The role of CT, PET-CT, and MRI in ovarian cancer

New treatment developments in ovarian cancer have led to a renewed interest in staging advanced ovarian cancer. The treatment of females with ovarian cancer patients has a strong multidisciplinary character with an essential role for the radiologist. This review aims to provide an overview of the current position of CT, positron emission tomography-CT, and MRI in ovarian cancer and how imaging can be used to guide multidisciplinary team discussions.

Brenner tumors

Brenner tumors are rare ovarian neoplasms composed of ovarian transition cells surrounded by dense fibrous tissue. Most of them are small tumors (<2 cm), detected incidentally in asymptomatic women. Its predominantly fibrous content results in relatively low signal on T  2 weighted images, establishing differential diagnosis with ovarian fibroma and thecoma. Their imaging features are very similar, the differentiation is based on secondary characteristics, such as signs or symptoms of estrogen excess and the presence of a second ovarian neoplasm, which has been reported in up to 30% of patients with Brenner tumor. Although originally thought to be universally benign, there have been scattered reports in the past decades of borderline and malignant forms of Brenner tumors.

Serous borderline ovarian tumours: an extensive review on MR imaging features

Serous borderline ovarian tumours (SBOTs) are an intermediate group of neoplasms, which have features between benign and malignant ovarian tumours and for which, fertility-sparing surgery can be offered. MRI in imaging of SBOTs is, therefore, crucial in raising the possibility of the diagnosis, in order to present the patient with the most appropriate treatment options. There are characteristic MRI features that SBOTs demonstrate. In addition, recent advanced techniques, and further classification into subtypes within the borderline group have been developed. The aim of this article is to review the MRI features of SBOT and provide the reporter with an awareness of the imaging tips and tricks in the differential diagnosis of SBOT.

Differentiation between endometriosis-associated ovarian cancers and non- endometriosis-associated ovarian cancers based on magnetic resonance imaging

Objectives: Endometriosis-associated ovarian cancer (EAOC) patients show different clinical characteristics compared with non-EAOC patients. However, a few studies are focused on the imaging characteristics of EAOC until now. We assessed MRI characteristics in differentiating EAOC and non-EAOC. Methods: We retrospectively analyzed clinical and MRI characteristics from 54 patients with 67 lesions diagnosed with primary epithelial ovarian carcinoma at the Third Affiliated Hospital of Guangzhou Medical University between January 2012 and October 2020. We studied MRI findings such as maximum diameter, morphology, configuration, locularity, features of mural nodules, lymphadenopathy, peritoneal implants, the presence of hyperintensity on T1WI, and hypointensity on T2WI. We also studied the clinical characteristics. Significant MRI variables in univariate analysis were selected for subsequent multivariate regression analysis. This study evaluated the diagnostic performance of the significant MRI variables in univariate analysis. Results: We found that the patients with EAOC, compared with those with non-EAOC, were younger, more unilateral, and had earlier FIGO stage. Univariate analysis revealed that morphology, locularity, growth pattern of mural nodules, and hypointensity on T2WI were factors that significantly differed between EAOC and non-EAOC. In the multivariate logistic regression analysis, locularity and hypointensity on T2WI were independent predictors to distinguish EAOC from non-EAOC. Conclusions: EAOC typically presented as a unilocular mass with hypointensity on T2WI in cystic components. MRI could help distinguish EAOC from non-EAOC. Advances in knowledge: MRI is a promising tool for preoperative diagnosis of EAOC.

Application of synthetic magnetic resonance imaging and DWI for evaluation of prognostic factors in cervical carcinoma: a prospective preliminary study

Objectives: To determine the values of quantitative metrics derived from synthetic MRI (SyMRI) and apparent diffusion coefficient (ADC) in evaluating the prognostic factors of cervical carcinoma (CC). Methods: In this prospective study, 74 patients with pathologically confirmed CC were enrolled. Pretreatment quantitative metrics including T1, T2 and ADC values were obtained from SyMRI and diffusion-weighted imaging (DWI) sequences. The values of all metrics were compared for different prognostic features using Student’s t-test or Mann-Whitney U-test. The receiver operating characteristic (ROC) curve and multivariate logistic regression analysis were utilized to evaluate the diagnostic performance of quantitative variables. Results: T1 and T2 values of parametrial involvement (PMI)-negative were significantly higher than those of PMI-positive (p = 0.002 and < 0.001), while ADC values did not show a significant difference. The area under curve (AUC) of T1 and T2 values for identifying PMI were 0.743 and 0.831. Only the T2 values showed a significant difference between the lymphovascular space involvement (LVSI)-negative and LVSI-positive (p < 0.001), and the AUC of T2 values for discriminating LVSI was 0.814. The differences of T1, T2, and ADC values between the well/moderately and the poorly differentiated CC were significant (all p < 0.001). The AUCs of T1, T2 and ADC values for predicting differentiation grades were 0.762, 0.830, and 0.808. The combined model of all metrics proved to achieve good diagnostic performance with the AUC of 0.866. Conclusion: SyMRI may be a potential noninvasive tool for assessing the prognostic factors such as PMI, LVSI, and differentiation grades in CC. Moreover, the overall diagnostic performances of synthetic quantitative metrics were superior to the ADC values, especially in identifying PMI and LVSI. Advances in knowledge: This is the first study to assess the utility of SyMRI-derived parameters and ADC value in evaluating the prognostic factors in CC.

Multiparametric MRI radiomics models for preoperative assessment of lymph vascular space invasion status in early-stage cervical cancer: a 2-centre retrospective study

Abstract Objective To preoperatively predict lymphovascular space invasion (LVSI) in early-stage cervical cancer (CC) using multiparametric MRI (mpMRI) radiomics models. Methods This dual-centre study included 196 early-stage CC patients (Centre A: 142, Dec 2020-Apr 2023; Centre B: 54, May-Oct 2023). Centre A was partitioned into training (n = 99) and internal validation (n = 43) cohorts; Centre B served as external validation. Radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted MRI (CE-MRI) sequences. Feature stability was assessed via intraclass correlation and Dice coefficient, with selection through linear correlation and F-tests. Seven radiomics models (single/combined sequences) were built using the top-performing algorithm among 11 machine learning methods. A combination model (CMIC) integrated the optimal mpMRI model’s rad-score with clinical factors. Performance was evaluated by ROC, calibration curves, and DCA across all cohorts. Results The AdaBoost-based mpMRI model (CE-MRI + DWI + T2WI) utilized 12 selected features. It achieved AUCs of 0.953 (95% CI: 0.916-0.989) in training, 0.868 (0.755-0.981) in internal validation, and 0.797 (0.677-0.916) externally. The CMIC model showed comparable performance (training: 0.957; validation: 0.864; external: 0.847), with no significant differences versus the mpMRI model (P > .05 all cohorts). Conclusion The AdaBoost-driven mpMRI radiomics model effectively predicts LVSI in early-stage CC. Both mpMRI and CMIC models demonstrate robust preoperative predictive capability. Advances in knowledge This mpMRI radiomics approach using AdaBoost outperforms single-sequence models for LVSI prediction, enabling personalized treatment strategies for early-stage CC.

MRI radiomics combined with clinicopathologic features to predict disease-free survival in patients with early-stage cervical cancer

Objective To establish a comprehensive model including MRI radiomics and clinicopathological features to predict post-operative disease-free survival (DFS) in early-stage (pre-operative FIGO Stage IB-IIA) cervical cancer. Methods A total of 183 patients with early-stage cervical cancer admitted to our Jiangsu Province Hospital underwent radical hysterectomy were enrolled in this retrospective study from January 2013 to June 2018 and their clinicopathology and MRI information were collected. They were then divided into training cohort (n = 129) and internal validation cohort (n = 54). The radiomic features were extracted from the pre-operative T1 contrast-enhanced (T1CE) and T  2 weighted image of each patient. Least absolute shrinkage and selection operator regression and multivariate Cox proportional hazard model were used for feature selection, and the rad-score (RS) of each patient were evaluated individually. The clinicopathology model, T1CE_RS model, T1CE + T2_RS model, and clinicopathology combined with T1CE_RS model were established and compared. Patients were divided into high- and low-risk groups according to the optimum cut-off values of four models. Results T1CE_RS model showed better performance on DFS prediction of early-stage cervical cancer than clinicopathological model (C-index: 0.724 vs 0.659). T1CE+T2_RS model did not improve predictive performance (C-index: 0.671). The combination of T1CE_RS and clinicopathology features showed more accurate predictive ability (C-index=0.773). Conclusion The combination of T1CE_RS and clinicopathology features showed more accurate predictive performance for DFS of patients with early-stage (pre-operative IB-IIA) cervical cancer which can aid in the design of individualised treatment strategies and regular follow-up. Advances in knowledge A radiomics signature composed of T1CE radiomic features combined with clinicopathology features allowed differentiating patients at high or low risk of recurrence.

Multiparametric MRI radiomics nomogram for predicting lymph-vascular space invasion in early-stage cervical cancer

Objective: To develop a radiomics nomogram based on multiparametric MRI (mpMRI) to pre-operatively predict lymph-vascular space invasion (LVSI) in patients with early-stage cervical cancer. Methods: This retrospective study included 233 consecutive patients with Stage IB–IIB cervical cancer. According to the ratio of 2:1, 154 patients and 79 patients were randomly assigned to the primary and validation cohorts, respectively. Features with intraclass and interclass correlation coefficient (ICCs) greater than 0.75 were selected for radiomics features. The significant features for predicting LVSI were selected using the least absolute shrinkage and selection operator (LASSO) algorithm based on the primary cohort. The rad-score for each patient was constructed via a linear combination of selected features that were weighted by their respective coefficients. The radiomics nomogram was developed using multivariable logistic regression analysis by incorporating the rad-score and clinical risk factors. Results: A total of 19 radiomics features and 3 clinical risk factors were selected. The rad-score exhibited a good performance in discriminating LVSI with a C-index of 0.76 and 0.81 in the primary and validation cohorts, respectively. The radiomics nomogram also exhibited a good discriminating performance in two cohorts (C-index of 0.78 and 0.82). The calibration curve of the radiomics nomogram demonstrated no significant differences was found between prediction and observation outcomes for the probability of LVSI in two cohorts (p = 0.86 and 0.98, respectively). The decision curve analysis indicated that clinician and patients could benefit from the use of radiomics nomogram and rad-score. Conclusion: The nomogram and rad-score could be used conveniently and individually to predict LVSI in patients with early-stage cervical cancer and facilitate the treatment decision for clinician and patients. Advances in knowledge: The nomogram could pre-operatively predict LVSI in early-stage cervical cancer.

Added value of radiomics analysis in MRI invisible early-stage cervical cancers

Objectives: To determine the diagnostic ability of cervical mucosa radiomics signature of sagittal T2WI and T1 contrast-enhanced (CE) imaging in detecting early-stage cervical cancers with negative MRI. Methods: Preoperative images of postoperative pathology confirmed early-stage cervical cancer patients and normal cervix patients admitted to our hospital between January 2013 and December 2020 were retrospectively reviewed. Patients with cancer signals on T2WI, T1CE and DWI were deleted. Regions of interests (ROIs) were delineated on cervical mucosa (from cervical canal to cervical dome) with 5 mm width on sagittal T2WI and T1CE. The maximum-relevance and minimumredundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used for the calculation of radiomics signature scores. Diagnostic performance was assessed and compared between radiomics prediction models (model 1: T1CE; model 2: T2WI; model 3: model one combined with model 2). Differential diagnostic ability of radiomics signature in detecting lymphatic vascular space invasion (LVSI) was further explored. Results: Diagnostic performance of model three was higher than model 1 and model 2 both in primary (model 3 0.874, model 1 0.857, model 2 0.816) and validation (model 3 0.853, model 1 0.847, model 2 0.634) cohorts. Model 3 showed statistical diagnostic difference compared with model 2 (primary p = 0.008, validation p = 0.000). However, the diagnostic improvement ability of model 3 showed no statistical difference compared with model 1 (primary p = 0.351, validation p = 0.739). Diagnostic efficiency of model 3 in detecting LVSI was not apparent (AUC 0.64). Conclusions: Radiomics analysis of cervical mucosa combining T1CE and T2WI is promising for predicting MRI invisible early-stage cervical cancers, however further ability in detecting LVSI was not apparent. Advances in knowledge: Conventional MRI was originally defined as meaningless in very early-stage cervical cancers. However, whether MRI radiomics analysis of cervical mucosa can detecting tiny changes of invisible early stage cervical cancers has not been researched yet.

Value of MRI and diffusion-weighted imaging in diagnosing normal-sized pelvic lymph nodes metastases in patients with cervical cancer

Objectives: To investigate the value of conventional MRI and diffusion-weighted imaging (DWI) in diagnosing normal-sized pelvic lymph nodes metastases in patients with cervical cancer. Methods: 102 patients with cervical cancer who underwent MRI and DWI scan were included. 137 lymph nodes were analyzed, including 44 metastatic lymph nodes (MLNs) and 93 non-metastatic lymph nodes (non-MLNs). The morphology and apparent diffusion coefficient (ADC) value of lymph nodes were measured including short-axis diameter (DS), long-axis diameter (DL), ratio of short-to-long-axis diameter (DR), fatty hilum, asymmetry, ADCmax, ADCmean and ADCmin. The Mann-Whitney U-test, independent sample t-test and Chi-square test were employed to compare the differences of all criteria between MLNs and non-MLNs. Logistic regression and decision tree were used to develop the combined diagnostic model. ROC analyses were used to evaluate the diagnostic performance. Results: The DS and DR of MLNs were significantly higher than those of non-MLNs (p < 0.05), the ADCmax, ADCmean and ADCmin of MLNs were significantly lower than those of non-MLNs (p < 0.05). Presence of fatty hilum and asymmetric lymph nodes between MLNs and non-MLNs were significantly different (p＜0.05). Combined measurement of ADCmin, DS and DR had the highest AUC 0.937 with 90.9% sensitivity and 87.1% specificity. The accuracy of decision tree was 88.3%. Conclusion: MRI with DWI had potential in diagnosing normal-sized pelvic lymph nodes metastases in patients with cervical cancer. The combined evaluation of DS, DR and ADCmin of lymph nodes and decision tree of the combined measure showed better diagnostic performances than sole criteria. Advances in knowledge: The short-axis diameter, ratio of short-to-long-axis diameter and ADCmin of lymph nodes have moderate value in the diagnosis of the metastases of the normal-sized lymph nodes for the patient with cervical cancer as the sole indices. The combined evaluation of DS, DR and ADCmin is much more valuable in the detection of metastatic lymph nodes.

The impact of plan complexity on dose delivery deviations resulting from multileaf collimator positioning errors in volumetric modulated arc therapy

Abstract Objectives This study aimed to assess the effect of plan complexity on dosimetric alterations induced by multileaf collimator (MLC) misplacements in volumetric modulated arc therapy (VMAT). Methods Volumetric modulated arc therapy plans for 14 cervical and 10 lung cancer cases were reoptimized utilizing 3 distinct aperture shape controller (ASC) settings (none, very high, and very low), resulting in 3 plan groups: ASC-none, ASC-vh, and ASC-vl. Four types of MLC position errors were simulated: total shifts (Type 1), open/closed (Type 2), right-side shifts (Type 3), and left-side shifts (Type 4). Plan complexity was assessed using the small aperture score (SAS). Dose deviations resulting from various MLC positioning errors and SAS values were calculated and compared among the 3 ASC groups. Results The variations in planning target volume (PTV) D95% for cervical cancer were approximately 0.6%, 3.7%, 1.9%, and 1.8% per millimetre for Types 1-4 errors, respectively. In the case of lung cancer, the changes were 2.3%, 9.3%, 5.3%, and 4.6% per millimetre. The ASC-vh and ASC-vl groups exhibited significantly reduced dose changes and SAS values in response to MLC errors, as compared to the ASC-none group (P < .05). Conclusions Highly complex plans exhibit greater dose sensitivity to MLC positional errors. The application of ASC proves effective in reducing plan complexity and mitigating the influence of MLC errors on dose deviation. Advances in knowledge By elucidating the relationship between dosimetric impacts from MLC errors and plan complexity, this study offers valuable guidance for the design of radiotherapy plans, helping to enhance the accuracy and effectiveness of VMAT treatments.

MRI of the endometrium - from normal appearances to rare pathology

MRI was recently included as a standard pre-operative diagnostic tool for patients with endometrial cancer. MR findings allow a better risk assessment and ultimately guides the surgical planning. Therefore, it is vital that the radiological interpretation is as accurate as possible. This requires essential knowledge regarding the appropriate MRI protocol, as well as different appearances of the endometrium, ranging from normal peri- and post-menopausal changes, benign findings (e.g. endometrial hyperplasia, polyp, changes due to exogenous hormones) to common and rare endometrium-related malignancies. Furthermore, this review will emphasize the role of MRI in staging endometrial cancer patients and highlight pitfalls that could result in the underestimation or overestimation of the disease extent.

Ovarian cancer staging: What the surgeon needs to know

Ovarian cancer (OC) is the leading cause of gynecological cancer death, and most cases are diagnosed at advanced stages due to a nonspecific and insidious clinical presentation. Radiologists play a critical role in the decision of which patients are candidates for primary debulking surgery and who may benefit from neoadjuvant chemotherapy. This pictorial review summarizes the dissemination patterns of OC, main imaging findings of metastatic disease, and which findings may alter the treatment plan or predict suboptimal tumor resection.

Ultrasound evaluation of ovarian masses and assessment of the extension of ovarian malignancy

The current review sums up the literature on the diagnostic performance of models to predict malignancy in adnexal masses and the ability of ultrasound to make a specific diagnosis in adnexal masses. A summary of the role of ultrasound in assessing the extension of malignant ovarian disease is also provided.

Nomogram based on ultrasound radiomics score and clinical variables for predicting histologic subtypes of epithelial ovarian cancer

Objective: Ovarian cancer is one of the most common causes of death in gynecological tumors, and its most common type is epithelial ovarian cancer (EOC). This study aimed to establish a radiomics signature based on ultrasound images to predict the histopathological types of EOC. Methods: Overall, 265 patients with EOC who underwent preoperative ultrasonography and surgery were eligible. They were randomly sorted into two cohorts (training cohort: test cohort = 7:3). We outlined the region of interest of the tumor on the ultrasound images of the lesion. Then, the radiomics features were extracted. Clinical, Rad-score and combined models were constructed based on the least absolute shrinkage, selection operator, and logistic regression analysis. The performance of the models was evaluated using receiver operating characteristic curves and decision curve analysis (DCA). A nomogram was formulated based on the combined prediction model. Results: The combined model had good performance in predicting EOC histopathological types, with an AUC of 0.83 (95% CI: 0.77–0.90) and 0.82 (95% CI: 0.71–0.93) in the training and test cohorts, respectively. The calibration curves showed that the nomogram estimation was consistent with the actual observations. DCA also verified the clinical value of the combined model. Conclusions: The combined model containing clinical and ultrasound radiomics features showed an excellent performance in predicting type I and type II EOC. Advances in knowledge: This study presents the first application of ultrasound radiomics features to distinguish EOC histopathological types. The proposed clinical-radiomics nomogram could help gynecologists non-invasively identify EOC types before surgery.

Comparison of radiographer interobserver image registration variability using cone beam CT and MR for cervix radiotherapy

Objectives: The aim of this study was to assess the consistency of therapy radiographers performing image registration using cone beam computed tomography (CBCT)-CT, magnetic resonance (MR)-CT, and MR-MR image guidance for cervix cancer radiotherapy and to assess that MR-based image guidance is not inferior to CBCT standard practice. Methods: 10 patients receiving cervix radiation therapy underwent daily CBCT guidance and magnetic resonance (MR) imaging weekly during treatment. Offline registration of each MR image, and corresponding CBCT, to planning CT was performed by five radiographers. MR images were also registered to the earliest MR interobserver variation was assessed using modified Bland–Altman analysis with clinically acceptable 95% limits of agreement (LoA) defined as ±5.0 mm. Results: 30 CBCT-CT, 30 MR-CT and 20 MR–MR registrations were performed by each observer. Registration variations between CBCT-CT and MR-CT were minor and both strategies resulted in 95% LoA over the clinical threshold in the anteroposterior direction (CBCT-CT ±5.8 mm, MR-CT ±5.4 mm). MR–MR registrations achieved a significantly improved 95% LoA in the anteroposterior direction (±4.3 mm). All strategies demonstrated similar results in lateral and longitudinal directions. Conclusion: The magnitude of interobserver variations between CBCT-CT and MR-CT were similar, confirming that MR-CT radiotherapy workflows are comparable to CBCT-CT image-guided radiotherapy. Our results suggest MR–MR radiotherapy workflows may be a superior registration strategy. Advances in knowledge: This is the first publication quantifying interobserver registration of multimodality image registration strategies for cervix radical radiotherapy patients.

Impact of dosimetric differences between CT and MRI derived target volumes for external beam cervical cancer radiotherapy

Objectives: The use of MRI is becoming more prevalent in cervical cancer external beam radiotherapy (RT). The aim of this study was to investigate the impact of dosimetric differences between CT and MRI-derived target volumes for cervical cancer external beam RT. Methods: An automated planning technique for volumetric modulated arc therapy was developed. Two automated planning plans were generated for 18 cervical cancer patients where planning target volumes (PTVs) were generated based on CT or MRI data alone. Dose metrics for planning target volumes and organs at risk (OARs) were compared to analyse any differences based on imaging modality. Results: All treatment plans were clinically acceptable. Bladder doses (V40) were lower in MRI-based plans (p = 0.04, 53.6 ± 17.2 % vs 60.3 ± 13.1 % for MRI vs CT, respectively). The maximum dose for left iliac crest showed lower doses in CT-based plans (p = 0.02, 47.8 ± 0.7 Gy vs 47.4 ± 0.4 Gy MRI vs CT, respectively). No significant differences were seen for other OARs. Conclusions: The dosimetric differences of CT- and MRI-based contouring variability for this study was small. CT remains the standard imaging modality for volume delineation for these patients. Advances in knowledge: This is the first study to evaluate the dosimetric implications of imaging modality on target and OAR doses in cervical cancer external beam RT.

Modulation of nanoparticle uptake, intracellular distribution, and retention with docetaxel to enhance radiotherapy

Objective: One of the major issues in current radiotherapy (RT) is the normal tissue toxicity. A smart combination of agents within the tumor would allow lowering the RT dose required while minimizing the damage to healthy tissue surrounding the tumor. We chose gold nanoparticles (GNPs) and docetaxel (DTX) as our choice of two radiosensitizing agents. They have a different mechanism of action which could lead to a synergistic effect. Our first goal was to assess the variation in GNP uptake, distribution, and retention in the presence of DTX. Our second goal was to assess the therapeutic results of the triple combination, RT/GNPs/DTX. Methods: We used HeLa and MDA-MB-231 cells for our study. Cells were incubated with GNPs (0.2 nM) in the absence and presence of DTX (50 nM) for 24 h to determine uptake, distribution, and retention of NPs. For RT experiments, treated cells were given a 2 Gy dose of 6 MV photons using a linear accelerator. Results: Concurrent treatment of DTX and GNPs resulted in over 85% retention of GNPs in tumor cells. DTX treatment also forced GNPs to be closer to the most important target, the nucleus, resulting in a decrease in cell survival and increase in DNA damage with the triple combination of RT/ GNPs/DTX vs RT/DTX. Our experimental therapeutic results were supported by Monte Carlo simulations. Conclusion: The ability to not only trap GNPs at clinically feasible doses but also to retain them within the cells could lead to meaningful fractionated treatments in future combined cancer therapy. Furthermore, the suggested triple combination of RT/GNPs/DTX may allow lowering the RT dose to spare surrounding healthy tissue. Advances in knowledge: This is the first study to show intracellular GNP transport disruption by DTX, and its advantage in radiosensitization.

The feasibility of reduced field-of-view diffusion-weighted imaging in evaluating bladder invasion of uterine cervical cancer

Objectives: Uterine cervical cancer with bladder mucosal invasion is classified as FIGO stage IVA with poor prognosis. MRI can rule out the bladder invasion and skipping cystoscopy may be possible; however, high false-positive rate may be problematic. The purpose of this study is to evaluate the diagnostic performance of reduced field-of-view (FOV) diffusion-weighted imaging (DWI) in evaluating bladder mucosal invasion of cervical cancer. Methods: 3T MRI including T2WI and reduced FOV DWI in 15 women with histologically proven cervical cancer (two stage IIIB, six stage IVA, seven stage IVB) were retrospectively evaluated compared with cystoscopic findings. Results: Cystoscopy revealed mucosal invasion in 13 of 15 cases. The border between the tumor and the bladder wall was unclear on T2WI and clear on reduced FOV DWI in all 15 cases. The diagnosis of mucosal invasion on reduced FOV DWI had a sensitivity of 100%, specificity of 50%, accuracy of 93%, PPV of 93%, and NPV of 100%. Conclusions: Addition of reduced FOV DWI may improve the staging accuracy of MRI for cervical cancer in assessing the bladder mucosal invasion. Advances in knowledge: Reduced FOV DWI may improve the staging accuracy of cervical cancer in assessing bladder mucosal invasion with high NPV and PPV, which may be helpful for avoiding unnecessary cystoscopy.

Borderline and malignant ovarian epithelial tumors: differentiating using multiparameter MRI

Abstract Objectives To evaluate the value of multiparameter MRI (mp-MRI) including conventional MRI image features, diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) in differentiating borderline from malignant ovarian epithelial tumors (OETs). Methods Forty-three patients with borderline OETs (BOETs) and 119 patients with malignant OETs (MOETs) who underwent mp-MRI examinations for pre-treatment assessment were respectively enrolled. Conventional MRI features (eg, tumor shape, configuration, signal intensity [SI] on T1WI and T2WI) were retrospectively analyzed. Apparent diffusion coefficient (ADC), and DCE-MRI derived parameters (rel-enhancement [RELENH], time to peak [TTP], wash-in-rate [WIR], and wash-out-rate [WOR]) were evaluated. Independent samples t-test, Mann-Whitney U test, χ2 test, multivariate logistic regression analysis, binary logistic regression, and receiver operating characteristic (ROC) curve analyses were employed as appropriate. Results BOETs group showed significantly lower age than MOETs group (P < .001). Multivariate logistic regression analysis indicated that tumor configuration was the independent imaging features associated with MOETs (P < .001). BOETs group showed significantly higher ADC value than MOETs group (P < .001). Among DCE-MRI derived parameters, MOETs group showed significantly shorter TTP than BOETs (P = .014). ROC analyses indicated that a combination of age ≥ 43.5 years old + non-cystic predominant type + ADC ≤ 1.05 × 10−3 mm2/s + TTP ≤ 238.87 s showed the highest efficiency (AUC, 0.930; sensitivity, 84.9%; specificity, 86.0%) in diagnosing MOETs, which was significantly higher than that of age (P = .002), configuration (P < .001), ADC (P = .027), and TTP (P < .001) alone. Conclusions mp-MRI might be effective in differentiating MOETs from BOETs. Advances in knowledge The study which combining conventional MRI, DWI, and DCE-MRI for differentiating BOETs from MOETs is still lacked until now. What is more, the study may be more accurate for the differentiation of borderline malignancy or low-grade malignant potential tumors.

Ovarian-adnexal reporting and data system MRI scoring: diagnostic accuracy, interobserver agreement, and applicability to machine learning

Abstract Objectives To evaluate the interobserver agreement and diagnostic accuracy of ovarian-adnexal reporting and data system magnetic resonance imaging (O-RADS MRI) and applicability to machine learning. Methods Dynamic contrast-enhanced pelvic MRI examinations of 471 lesions were retrospectively analysed and assessed by 3 radiologists according to O-RADS MRI criteria. Radiomic data were extracted from T2 and post-contrast fat-suppressed T1-weighted images. Using these data, an artificial neural network (ANN), support vector machine, random forest, and naive Bayes models were constructed. Results Among all readers, the lowest agreement was found for the O-RADS 4 group (kappa: 0.669; 95% confidence interval [CI] 0.634-0.733), followed by the O-RADS 5 group (kappa: 0.709; 95% CI 0.678-0.754). O-RADS 4 predicted a malignancy with an area under the curve (AUC) value of 74.3% (95% CI 0.701-0.782), and O-RADS 5 with an AUC of 95.5% (95% CI 0.932-0.972) (P < .001). Among the machine learning models, ANN achieved the highest success, distinguishing O-RADS groups with an AUC of 0.948, a precision of 0.861, and a recall of 0.824. Conclusion The interobserver agreement and diagnostic sensitivity of the O-RADS MRI in assigning O-RADS 4-5 were not perfect, indicating a need for structural improvement. Integrating artificial intelligence into MRI protocols may enhance their performance. Advances in knowledge Machine learning can achieve high accuracy in the correct classification of O-RADS MRI. Malignancy prediction rates were 74% for O-RADS 4 and 95% for O-RADS 5.

Diagnostic value of the ovarian adnexal reporting and data system ultrasound in ovarian masses: a 2-center study

Abstract Objective This study aimed to assess the diagnostic efficacy of the ovarian adnexal reporting and data system (O-RADS) and ultrasound (US) and its sub-classification system for distinguishing ovarian masses. Methods O-RADS US was used for the retrospective analysis of 606 ovarian masses of Chinese from 2 medical centres by 2 gynaecologic sonographers with varying experience. The O-RADS 4 categories masses were further sub-classified into O-RADS 4a and O-RADS 4b through 3 different approaches (O-RADS A1/A2/A3). Results The AUC of O-RADS US for differentiating benign from malignant ovarian masses was 0.927 (95% CI, 0.903-0.946, P < .001). The optimal cut-off value for predicting malignancy was >O-RADS 3, with sensitivity and specificity of 98.60% and 68.90%, respectively. The diagnostic efficacy of the 3 sub-classification systems surpassed that of O-RADS US (P < .05). Specifically, A2 approach (within O-RADS 4 lesions, unilocular and multilocular cysts with solid components were sub-classified as O-RADS 4b, whereas the remaining O-RADS 4 lesions were sub-classified as O-RADS 4a) resulted in an AUC of 0.942 (95% CI, 0.921-0.960, P < .001). The best cut-off value predicting malignancy was >O-RADS 4a, exhibiting relatively high specificity (82.51%) and maintaining a high sensitivity (93.01%). Conclusion The diagnostic efficacy of O-RADS US for identifying ovarian tumours is good, but specificity is slightly lower. This study enhanced diagnostic specificity after subclassifying O-RADS 4 lesions, especially A2 approach. It holds significant clinical value for Chinese women and merits further clinical promotion and application. Advances in knowledge The sub-classification of O-RADS US allows better identifying ovarian tumours, facilitating informed preoperative clinical management and diagnosis.

Diagnostic imaging analysis to differentiate struma ovarii from mucinous carcinomas, encompassing T2*-based imaging, diffusion-weighted imaging, and dynamic contrast-enhanced imaging

Abstract Objectives To clarify the differences between struma ovarii (SO) and mucinous carcinomas (MC) on CT and MRI, including T2*-based images, diffusion-weighted images (DWI), and time-intensity curve (TIC) patterns, which have not been previously reported. Methods We retrospectively compared the presence of low intensity on T2-weighted and T2*-based images, high intensity on T1-weighted images, hyperattenuation on non-contrast CT, TIC pattern, T2 ratio, T1 ratio, CT value, and apparent diffusion coefficient (ADC) value in 15 patients with SO and 27 patients with MC. Results SO exhibited a significantly higher frequency of low intensity on T2-weighted and T2*-based images, and hyperattenuation on non-contrast CT than MC (P < .001, <.001, and .006, respectively). The T2 ratios and CT attenuation of the locules were also significantly different (P < .001, and .006, respectively). In SO, sites of low intensity on T2-weighted and T2*-based images and sites of hyperattenuation on CT images always coincided. Regarding the TIC pattern, most SO showed a high-risk pattern, with a significant difference (P = .003). The ADC values of SO were significantly lower, and only one case of SO showed high signal intensity on DWI. Conclusions SO were more frequently with low intensity on T2-weighted and T2*-based images, and hyperattenuation on non-contrast CT, and showed high-risk TIC patterns without diffusion restriction. Advances in knowledge SO shows a high-risk TIC pattern but can be specifically diagnosed in combination with the lack of diffusion restriction and loculi with marked hypointensity on T2-weighted and T2*-based images consistent with hyperattenuation on non-contrast CT.

MRI combined with clinical features to differentiate ovarian thecoma-fibroma with cystic degeneration from ovary adenofibroma

Abstract Objective To explore the value of magnetic resonance imaging (MRI) and clinical features in identifying ovarian thecoma-fibroma (OTF) with cystic degeneration and ovary adenofibroma (OAF). Methods A total of 40 patients with OTF (OTF group) and 28 patients with OAF (OAF group) were included in this retrospective study. Univariable and multivariable analyses were performed on clinical features and MRI between the two groups, and the receiver operating characteristic (ROC) curve was plotted to estimate the optimal threshold and predictive performance. Results The OTF group had smaller cyst degeneration degree (P < .001), fewer black sponge sign (20% vs. 53.6%, P = .004), lower minimum apparent diffusion coefficient value (ADCmin) (0.986 (0.152) vs. 1.255 (0.370), P < .001), higher age (57.4 ± 14.2 vs. 44.1 ± 15.9, P = .001) and more postmenopausal women (72.5% vs. 28.6%, P < .001) than OAF. The area under the curve of MRI, clinical features and MRI combined with clinical features was 0.870, 0.841, and 0.954, respectively, and MRI combined with clinical features was significantly higher than the other two (P < .05). Conclusion The cyst degeneration degree, black sponge sign, ADCmin, age and menopause were independent factors in identifying OTF with cystic degeneration and OAF. The combination of MRI and clinical features has a good effect on the identification of the two. Advances in knowledge This is the first time to distinguish OTF with cystic degeneration from OAF by combining MRI and clinical features. It shows the diagnostic performance of MRI, clinical features, and combination of the two. This will facilitate the discriminability and awareness of these two diseases among radiologists and gynaecologists.

The volumetric ADC histogram analysis in differentiating stage IA endometrial carcinoma from endometrial polyp

Abstract Objective This study aimed to explore the value of apparent diffusion coefficient (ADC) histogram based on whole lesion volume in distinguishing stage IA endometrial carcinoma from the endometrial polyp. Methods MRI of 108 patients with endometrial lesions confirmed by pathology were retrospectively analysed, including 65 cases of stage IA endometrial carcinoma and 43 cases of endometrial polyp. The volumetric ADC histogram metrics and general imaging features were evaluated and measured simultaneously. All the features were compared between the 2 groups. The receiver operating characteristic curve was utilized to evaluate the diagnostic performance. Results The mean, max, min, and percentiles (10th, 25th, 50th, 75th, 95th) ADC values of endometrial carcinoma were significantly lower than that of polyp (all P < .05). The skewness and kurtosis of ADC values in the endometrial carcinoma group were significantly higher than those in the endometrial polyp group, and the variance of ADC values in the endometrial carcinoma group was lower than those in the endometrial polyp group (all P < .05). Endometrial carcinoma demonstrated more obvious myometrial invasion combined with intralesion haemorrhage than polyp (all P < .05). The 25th percentile of ADC values achieved the largest areas under the curve (0.861) among all the ADC histogram metrics and general imaging features, and the sensitivity and specificity were 83.08% and 76.74%, with the cut-off value of 1.01 × 10−3 mm2/s. Conclusion The volumetric ADC histogram analysis was an effective method in differentiating endometrial carcinoma from an endometrial polyp. The 25th percentile of ADC values has satisfactory performance for detecting malignancy in the endometrium. Advances in knowledge The ADC histogram metric based on whole lesion is a promising imaging-maker in differentiating endometrial benign and malignant lesions.

Determination of p53abn endometrial cancer: a multitask analysis using radiological-clinical nomogram on MRI

Abstract Objectives We aimed to differentiate endometrial cancer (EC) between TP53mutation (P53abn) and Non-P53abn subtypes using radiological-clinical nomogram on EC body volume MRI. Methods We retrospectively recruited 227 patients with pathologically proven EC from our institution. All these patients have undergone molecular pathology diagnosis based on the Cancer Genome Atlas. Clinical characteristics and histological diagnosis were recorded from the hospital information system. Radiomics features were extracted from online Pyradiomics processors. The diagnostic performance across different acquisition protocols was calculated and compared. The radiological-clinical nomogram was established to determine the nonendometrioid, high-risk, and P53abn EC group. Results The best MRI sequence for differentiation P53abn from the non-P53abn group was contrast-enhanced T1WI (test AUC: 0.8). The best MRI sequence both for differentiation endometrioid cancer from nonendometrioid cancer and high-risk from low- and intermediate-risk groups was apparent diffusion coefficient map (test AUC: 0.665 and 0.690). For all 3 tasks, the combined model incorporating all the best discriminative features from each sequence yielded the best performance. The combined model achieved an AUC of 0.845 in the testing cohorts for P53abn cancer identification. The MR-based radiomics diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682). Conclusion In the present study, the diagnostic model based on the combination of both radiomics and clinical features yielded a higher performance in differentiating nonendometrioid and P53abn cancer from other EC molecular subgroups, which might help design a tailed treatment, especially for patients with high-risk EC. Advances in knowledge (1) The contrast-enhanced T1WI was the best MRI sequence for differentiation P53abn from the non-P53abn group (test AUC: 0.8). (2) The radiomics-based diagnostic model performed better than the clinical-based model in determining P53abn EC (AUC: 0.834 vs 0.682). (3) The proposed model derived from multi-parametric MRI images achieved a higher accuracy in P53abn EC identification (AUC: 0.845).

Imaging of endometrial polypoidal lesions of the uterus with Rad-Path correlation

Abstract Endometrial polypoidal lesions of the uterus are very commonly encountered, and may pose a diagnostic dilemma. Ultrasound is used for initial screening, with MRI being used for further characterization. This pictorial review elucidates the imaging appearances of various types of such polyps, along with the classical histopathological appearances. Understanding the imaging features is crucial for accurate diagnosis and management, although histopathological diagnosis remains the gold standard.

Rare and uncommon tumours of the female pelvis: what the radiologist should know

Abstract Gynaecological tumours present a broad spectrum of histological subtypes due to the diverse anatomical and tissue origin of the reproductive organs. Rare tumours affect less than 6 per 100 000 individuals annually, posing significant challenges in diagnosis and management due to limited clinical awareness. Indeed, treatment protocols rely on options developed for more common histotypes, which may have limited efficacy on these rare tumours. In recent years, collaborative international efforts have started to address these gaps, improving standards of care. A comprehensive understanding of rare tumours’ clinical and imaging features is necessary for radiologists in order to provide clinicians with useful information for treatment planning. In this review, we adopted an organ-based outline, describing rare tumours of the uterine corpus (leiomyosarcoma, endometrial stromal sarcoma, carcinosarcoma), cervix (gastric-type adenocarcinoma), and ovary (cystadenofibroma, lipid-poor teratoma, struma ovarii, immature teratoma, dysgerminoma). Additionally, tumours occurring at multiple sites, including lymphoma, neuroendocrine tumours, aggressive angiomyxoma and metastases are discussed. The objective is to help radiologists become familiar with these uncommon entities, ultimately increasing awareness on this topic.

An MR-based radiomics nomogram including information from the peritumoral region to predict deep myometrial invasion in stage I endometrioid adenocarcinoma: a preliminary study

Objective: To develop and validate an MR-based radiomics nomogram combining different imaging sequences (ADC mapping and T2 weighted imaging (T2WI)), different tumor regions (combined intra- and peritumoral regions), and different parameters (clinical features, tumor morphological features, and radiomics features) while considering different MR field strengths in predicting deep myometrial invasion (MI) in Stage I endometrioid adenocarcinoma (EEA). Methods: A total of 202 patients were retrospectively analyzed and divided into two cohorts (training cohort, 1.5 T MR, n = 131; validation cohort, 3.0 T MR, n = 71). Axial ADC mapping and T2WI were conducted. Radiomics features were extracted from intra- and peritumoral regions. Least absolute shrinkage and selection operator regression, univariate analysis, and multivariate logistic regression were used to select radiomics features and tumor morphological and clinical parameters. The area under the receiver operator characteristic curve (AUC) was calculated to evaluate the performance of the prediction model and radiomics nomogram. Results: Ten radiomics features, 4 morphological parameters and 1 clinical characteristic were selected. The radiomics nomogram achieved good discrimination between the superficial and deep MI cohorts. The AUC was 0.927 (95% confidence interval [CI]: 0.865, 0.967) in the training cohort and 0.921 (95% CI: 0.872, 0.948) in the validation cohort. The specificity and sensitivity were 92.0 and 78.9% in the training cohort and 83.0 and 77.8% in the validation cohort, respectively. Conclusion: The radiomics nomogram showed good performance in predicting the depth of MI in Stage I EEA before surgery and might be useful for surgical patient management. Advances in knowledge: An MR-based radiomics nomogram was useful for predicting deep MI in Stage I EEA patients (AUCtrain = 0.927, AUCvalidation = 0.921). The intra- and peritumoral radiomics features complemented each other. The nomogram was developed and validated with different MR field strengths, suggesting that the model demonstrates good generalizability.

Multisequence MRI-based radiomics model for predicting POLE mutation status in patients with endometrial cancer

Objectives: Preoperative identification of POLE mutation status would help tailor the surgical procedure and adjuvant treatment strategy. This study aimed to explore the feasibility of developing a radiomics model to pre-operatively predict the pathogenic POLE mutation status in patients with EC. Methods: The retrospective study involved 138 patients with histopathologically confirmed EC (35 POLE-mutant vs 103 non-POLE-mutant). After selecting relevant features with a series of steps, three radiomics signatures were built based on axial fat-saturation T2WI, DWI, and CE-T1WI images, respectively. Then, two radiomics models which integrated features from T2WI + DWI and T2WI + DWI+CE-T1WI were further developed using multivariate logistic regression. The performance of the radiomics model was evaluated from discrimination, calibration, and clinical utility aspects. Results: Among all the models, radiomics model2 (RM2), which integrated features from all three sequences, showed the best performance, with AUCs of 0.885 (95%CI: 0.828–0.942) and 0.810 (95%CI: 0.653–0.967) in the training and validation cohorts, respectively. The net reclassification index (NRI) and integrated discrimination improvement (IDI) analyses indicated that RM2 had improvement in predicting POLE mutation status when compared with the single-sequence-based signatures and the radiomics model1 (RM1). The calibration curve, decision curve analysis, and clinical impact curve suggested favourable calibration and clinical utility of RM2. Conclusions: The RM2, fusing features from three sequences, could be a potential tool for the non-invasive preoperative identification of patients with POLE-mutant EC, which is helpful for developing individualized therapeutic strategies. Advances in knowledge: This study developed a potential surrogate of POLE sequencing, which is cost-efficient and non-invasive.

Multiparametric transvaginal ultrasound in the diagnosis of endometrial cancer in post-menopausal bleeding: diagnostic performance of a transvaginal algorithm and reproducibility amongst less experienced observers

Objective: (a) To comparatively evaluate the performance of grayscale ultrasound features, power Doppler (PD) blood flow characteristics, and gel infusion sonography (GIS) in diagnosing endometrial cancer during real-time examination, (b) to compare the performance of real-time diagnosis of endometrial cancer by experienced observers with offline analysis by blinded observers using similar sonographic criteria during review of cine loop clips. Methods: 152 females with post-menopausal bleeding (PMB) had ET ≥ 4 mm at first-line ultrasound were included. Two experienced radiologists evaluated endometrial patterns at real-time evaluation (grayscale ultrasound, PD, and GIS), then examinations were stored as video clips for later evaluation by two less-experienced radiologists. The reference standard was hysteroscopy (HY) and/or hysterectomy with the histopathological examination. The area under (AUC) the receiver operating characteristic (ROC) curve was calculated to assess the diagnostic performance for the prediction of endometrial cancer. Results: Among 152 females with ET ≥ 4 mm at first line TVUS, 88 (57.9%) patients had endometrial cancer on final pathologic analysis. Real-time ultrasound criteria (ET ≥ 5 mm with the presence of irregular branching endometrial blood vessels or multiple vessels crossing EM or areas with densely packed color-splash vessels with non-intact or interrupted EMJ at the grayscale ultrasound and/or GIS) correctly diagnosed 95% of endometrial cancers with 92% diagnostic efficiency. There is comparable accuracy of real-time evaluation (96%) and offline analysis (92%) after the exclusion of poor quality videos from the analysis. The diagnostic criteria showed good to an excellent agreement between real-time ultrasound and offline analysis. Conclusion: When real-time ultrasound is performed with good technique, utilizing multiple parameters, it is possible to diagnose endometrial cancer with a high degree of accuracy and reproducibility. Advances in knowledge: when real-time ultrasound is performed with good technique, utilizing multiple parameters, it is possible to diagnose endometrial cancer with a high degree of accuracy and reproducibility.

Utility of histogram analysis for apparent diffusion coefficient values in evaluating the pathological characteristics of endometrial cancer

Pathological characteristics and risk stratification in patients with stage I endometrial cancer: utility of apparent diffusion coefficient histogram analysis

Objectives: Accurate pre-operative prediction of risk stratification using a non-invasive imaging tool is clinically important for planning optimal treatment strategies, particularly in early-stage endometrial cancer (EC). This study aimed to investigate the utility of apparent diffusion coefficient (ADC) histogram analysis in evaluating the pathological characteristics and risk stratification in patients with Stage I EC. Methods: Between October 2009 and December 2014, a total of 108 patients with surgically proven Stage I EC (endometrioid type = 91; non-endometrioid type = 17) excluding stage ≥II that underwent preoperative 3T-diffusion-weighted imaging without administration of contrast medium were enrolled in this retrospective study. Risk stratification was divided into four risk categories based on the ESMO-ESGO-ESTRO Guidelines: low, intermediate, high-intermediate, and high risk. The ADC histogram parameters (minimum, mean [ADCmean], 10th–90th percentile, and maximum [ADCmax]) of the tumor were generated using an in-house software. The ADC histogram parameters were compared between patients with endometrioid type and non-endometrioid type, between Stage IA and IB, between histological grades, and evaluated for differentiating non-high risk group from high risk group. Inter-reader agreement for tumor ADC measurements was also evaluated. Statistical analyses were performed using the Student’s t-test, Mann–Whitney U test, receiver operating characteristics (ROC) analysis, or intraclass correlation coefficient (ICC). Results: In differentiating endometrioid type from non-endometrioid type EC, all ADC histogram parameters were statistically significant (p < 0.05). In differentiating histological grades, 90th percentile ADC and ADCmax showed significantly higher values in tumor Grade III than in tumor Grade I-II (p < 0.05). In differentiating superficial myometrial invasion from deep myometrial invasion, all ADC histogram parameters were statistically significant (p < 0.05), except ADCmax. In differentiating non-high risk group from high risk group, ADCmean, 75th–90th percentile ADC, and ADCmax were statistically significant (p < 0.05). For predicting the high risk group, the area under the ROC curve of ADCmax was 0.628 and the highest among other histogram parameters. All histogram parameters revealed moderate to good inter-reader reliability (ICC = 0.581‒0.769). Conclusion: The ADC histogram analysis as reproducible tool may be useful for evaluating the pathological characteristics and risk stratification in patients with early-stage EC. Advances in knowledge: ADC histogram analysis may be useful for evaluating risk stratification in early-stage endometrial cancer patients.

Major complications and surgical reintervention after ultrasound-guided transcervical radiofrequency ablation of uterine fibroids: a 10-year experience

Abstract Objectives To evaluate the incidence of and risk factors for major complications and surgical reintervention following transcervical ultrasound-guided radiofrequency ablation (RFA) of uterine fibroids. Methods In this retrospective study, 1290 patients with 1358 symptomatic uterine fibroids underwent outpatient transcervical ultrasound-guided RFA between July 2009 and July 2021. Medical records were reviewed to assess major complications and surgical reintervention rates. Results The overall incidence of major complications was 5.1% (66/1290), including intestinal perforation (n = 1, 0.08%), infection (n = 39, 3.0%), intrauterine adhesions (n = 24, 1.9%), and deep venous thrombosis (n = 2, 0.15%). The 10-year cumulative surgical reintervention rate was 8.5%. Indications for reintervention included persistent fibroid-related symptoms (n = 65, 5.0%), fibroid recurrence (n = 35, 2.7%), intracavitary free myoma (n = 9, 0.7%), and malignant uterine mesenchymal neoplasia (n = 1, 0.08%). Multivariate analysis identified increased puncture frequency as a risk factor for postoperative infection (OR = 3.32, 95% CI: 1.02–10.7; P = 0.046). Conclusions Transcervical ultrasound-guided RFA is a well-tolerated outpatient procedure with an acceptably low rate of major complications and surgical reintervention for treatment of uterine fibroids. Advances in knowledge More punctures may contribute to higher infection rate. There is a need to keep all the uterine fibroids in check after RFA since malignant neoplasia may occur over a period.

Using diffusion-weighted imaging and blood inflammatory markers to preoperatively differentiate between leiomyosarcoma and atypical leiomyomas

Abstract Objectives This study aims to compare apparent diffusion coefficient (ADC) findings between leiomyosarcoma (LMS) and atypical/degenerate leiomyoma (LM) and evaluate the usefulness of this biomarker for diagnosis. Additionally it will explore the potential of preoperative neutrophil-lymphocyte ratio (NLR) as a haematological marker to aid in the differentiation of LMS from atypical LM. Methods Histologically proven LMS and LM patients between 2013 and 2023 were included. For all patients (191 LM, 18 LMS), the preoperative full blood count was analysed, and the NLR calculated. Whole volume of interest (VOI) and focal region of interest (ROI) areas were manually segmented on patients with DW-MRI sequences available (52 LM, 12 LMS). Mann–Whitney and Fishers exact test were used to assess statistical significance and receiver operating characteristic (ROC) curves for diagnostic performance. Results VOI and ROI mean ADC values were significantly lower for LMS than LM, with ROI mean ADC demonstrating greater diagnostic accuracy (area under the curve, [AUC] 0.817 vs 0.755). Applying a threshold ROI mean ADC value of ≤1.00 × 10−3 mm2/s achieved a sensitivity and specificity of 88.3% and 65.4%, respectively. A higher NLR was suggestive of LMS (median 2.8 vs 1.7 for LM). Conclusions ADC, particularly a focal ROI is useful in differentiating LMS from LM. Differences in preoperative blood markers, suggest an inflammatory-malignancy relationship. Future risk stratification models of ADC and haematological parameters should be explored. Advances in knowledge This study adds to few studies comparing using both ROI- and VOI-based methods, and no study has assessed both haematological markers and ADC metrics to aid differentiation.

Assessing local invasion in cervical cancer: the diagnostic performance of transrectal contrast-enhanced ultrasonography

Abstract Objectives To evaluate the diagnostic performance of transrectal ultrasound (TR-US) combined with contrast-enhanced TR-US (TR-CEUS) against MRI and histopathology for assessing cervical cancer local invasion, and to validate the “rim sign” as a biomarker for parametrial exclusion. Methods A retrospective study of 69 cervical cancer patients (54 surgical, 15 neoadjuvant therapy recipients) undergoing TR-US, TR-CEUS, and MRI was conducted. Tumour dimensions, vaginal/parametrial invasion, and the “rim sign” were evaluated. Diagnostic agreement was assessed using intraclass correlation coefficients (ICC) and Cohen’ s κ, while the specificity and negative predictive value (NPV) of the “rim sign” were calculated. Results TR-CEUS improved TR-US reliability in tumour measurement (ICC = 0.751 to 0.784), achieving MRI-comparable accuracy (ICC = 0.804 vs. histopathology). Combined TR-US/TR-CEUS enhanced interobserver consistency for vaginal infiltration (κ = 0.621 to 0.694) and parametrial invasion (κ = 0.579 to 0.678) compared to TR-US alone. TR-US/TR-CEUS showed good agreement with histopathology (κ = 0.672) and MRI (κ = 0.789) for parametrial assessment than TR-US (κ = 0.563/0.679). The “rim sign” demonstrated 95.8% specificity and 92.0% NPV for parametrial exclusion. Conclusions TR-US/TR-CEUS achieves diagnostic accuracy comparable to MRI while improving observer consistency. The “rim sign” serves as a high-specificity biomarker for preoperative parametrial exclusion, offering a cost-effective alternative to MRI. Advances in knowledge This study provides quantitative evidence of TR-CEUS improving diagnostic reproducibility for cervical cancer invasion. The “rim sign” is identified as a novel imaging biomarker with high specificity for parametrial preservation.

MRI localization evaluation to distinguish gastric-type adenocarcinoma and lobular endocervical glandular hyperplasia from other cystic lesions

Abstract Objectives To quantitatively differentiate MRI localization of gastric-type adenocarcinoma (GAS) and lobular endocervical glandular hyperplasia (LEGH) from other benign cystic lesions (OBC). Methods We retrospectively reviewed T1-weighted (T1WI) and T2-weighted images (T2WI) and measured the lesion volume, the ratio of cervical canal position at the maximum cross-section (deviation ratio), the ratio of the lesion’s centre within the craniocaudal length (longitudinal location ratio), distance from the internal and external os, maximum cyst diameter, and signal intensities of the cyst content on T1WI and T2WI (T1 and T2 ratios). These parameters were compared between GAS or LEGH and OBC, where OBC was clinically suspected of LEGH. Results Seventeen patients with GAS, 18 with LEGH (52 ± 11 years), and 42 with OBC (45 ± 10 years) were included. GAS/LEGH were larger in volume (29.25/15.24 cm3, P < .001), and had a greater deviation ratio (0.82/0.84, P < .001), shorter distance to the internal and external os (3.4/3.6 mm, P = .040, and 3.3/3.3 mm, P = .003, respectively), and a lower T1 ratio (1.08/0.91, P < .001). The area under the curve (AUC) of these parameters using their respective optimal cut-off values was 0.818, 0.756, 0.629, 0.711, and 0.731, respectively. When 3 or more positive criteria were considered, the AUC increased to 0.896. Conclusions Compared with OBC, GAS/LEGH displayed a larger volume, cervical canal deviation, proximity to the internal and external os, and a lower T1 ratio of cyst content. Advances in knowledge Considering both the lesion and its relationship to the cervical canal is imperative for differentiating between the conditions.

A dual-center study: can ultrasound radiomics differentiate type I and type II epithelial ovarian cancer patients with normal CA125 levels?

Abstract Objective CA125 is recommended by many countries as the primary screening test for ovarian cancer. But there are patients with ovarian cancer having normal CA125. We hope to identify the types of EOC with normal CA125 levels better by building a refined model based on the ultrasound radiomics, thus providing precise medical treatment for patients. Methods We included 58 patients with EOC with normal CA125 from 2 centres, who were confirmed by preoperative ultrasound and pathology. We extracted 1130 radiomics features based on the tumour’s region of interest from the most typical ultrasound image of each patient. We selected radiomics and clinical features by LASSO and logistic regression to construct Rad-score and clinical models, respectively. Receiver operating characteristic curves judged their test efficacy. On the basis of the combined model, we developed a nomogram. Results Area under the curves (AUCs) of 0.93 and 0.83 were achieved in both the training and test groups for the combined model. There were similar AUCs between the Rad-score and clinical models of 0.82 and 0.80, respectively. By analysing the calibration curves, it was determined that the nomogram matched actual observations in the training cohort. Conclusion Ultrasound radiomics can differentiate type I and type II EOC with normal CA125 levels. Advances in knowledge This study is the first to focus on EOC cases with normal level of CA125. The subset of patients constituting 20% of the disease population may require more refined radiomics models.

Enhancing parametrial invasion assessment in cervical squamous cell carcinoma: the collaborative impact of diffusion kurtosis imaging and T2-weighted imaging, exploring tumour core and 5-mm peritumoural tissue

Abstract Objective To evaluate the efficacy of magnetic resonance diffusion kurtosis imaging (DKI) combined with MRI T2-weighted imaging (T2WI) in assessing parametrial invasion (PI) in cervical squamous cell carcinoma. Methods 30 patients with cervical cancer underwent routine MRI and DKI scans. DKI parameters (mean diffusivity [MD], mean kurtosis [MK], fractional anisotropy [FA], and kurtosis anisotropy [KA]) were measured in the tumour parenchyma and surrounding 5 mm tissue. The integrity of the low-signal ring around the cervix on T2WI was recorded. LASSO regression identified optimal DKI parameters and ROC curves compared the diagnostic performance of each parameter and T2WI. Results Compared to the non-parametrial infiltration group (NPI), the parametrial infiltration group (PI) had higher values of MKT, KAT, and KAP (P = .018, .008, .042), while MDT was higher in NPI (P = .038). LASSO regression showed strong correlations between MKT, KAT, and KAP with PI. ROC analysis revealed the AUC, sensitivity, and specificity for MKT, KAT, and KAP were 0.765, 0.706, 0.846; 0.778, 0.882, 0.615; and 0.719, 0.529, 0.923, respectively. Combining T2WI with DKI (MKT + T2WI, KAT + T2WI, KAP + T2WI) improved AUCs to 0.846, 0.828, and 0.774. MKT + KAP and KAT + KAP yielded AUCs of 0.792 and 0.787, with sensitivity of 0.706 and specificity of 0.846. Conclusion DKI parameters (tumour MK, KA, and peritumoural KA) are valuable for assessing PI. Combining tumour and peritumoural parameters, along with T2WI, enhances diagnostic accuracy. Advances in knowledge This study presented an approach that combined DKI parameters with T2WI, integrating tumour and peritumoural parameter analysis to enhance the accuracy of assessing PI.

Post-uterine artery embolization: 3-day MRI changes and their predictive value for therapeutic efficacy in symptomatic uterine fibroids

Abstract Objectives To summarize and discuss 3-day MRI changes after uterine artery embolization (UAE) and their predictive value for efficacy. Methods From August 2016 to April 2023, 52 patients underwent enhanced MRI within 3 days post-embolization. We retrospectively analysed clinical and imaging data, focusing on MR characteristics at the 3-day mark, comparing pre- and post-embolization images. Patients were categorized based on 3-day MR findings into complete and incomplete necrosis groups, with clinical efficacy compared over 6 months. Results Our study included 30 cases of multiple leiomyomas and 22 of single leiomyomas. Postoperative MRI revealed complete necrosis in 31 tumours and incomplete necrosis in 21 tumours. At 3 days, MR ADC imaging showed increased signals in necrotic areas, mildly increased signals on T2-weighted images, and minimal changes on T1-weighted images. Six-month follow-up showed no significant difference in symptom improvement between groups (P = .524, P = .587, P = .615). However, a significant difference was found in leiomyoma volume reduction, with 70.63 ± 15.53% in the complete necrosis group and 51.36 ± 25.20% in the incomplete necrosis group (P < .001), highlighting the impact of necrosis extent on volumetric reduction. Conclusion Short-term MRI changes after UAE can reflect changes in blood supply to fibroids and normal uterine tissue, and have good predictive value for medium-term embolization efficacy. Advances in knowledge This study describes short-term MR manifestations of complete and incomplete embolism, aiding in predicting long-term outcome.

MRI accuracy and interobserver agreement in locally advanced cervix carcinoma

Objectives: The main standard of care for locally advanced cervix carcinoma (LACC) is radiochemotherapy (RCT) followed by brachytherapy. A surgical approach may still be discussed based on pelvic MRI-derived residual tumour evaluation. As no interobserver agreement study has ever been conducted to our knowledge, the aim of the present study was to report on pelvic MRI accuracy and interobserver agreement in LACC. Methods: We carried out a retrospective study in a French university hospital. Medical records of all consecutive patients treated with curative intent for LACC by RCT followed by brachytherapy and completion pelvic surgery between January 2014 and January 2020 were reviewed. Local response was assessed through pelvis MRI and histological analysis after completion surgery. MRI data were independently evaluated by two radiologists with varying experience. The two main interobserving criteria we used were complete response and residual tumour. Results: 23 patients fulfilled the inclusion criteria. Agreement between the junior and senior radiologist was moderate to strong. Indeed, regarding main criteria, κ was 0.65 for complete response and 0.57 for residual tumour. Interestingly, the present study shows a lower sensitivity whatever the radiologists than in the international literature. Conclusion: The present study highlights a low interobserver variability regarding pelvic MRI in the assessment of RCT followed by brachytherapy in LACC. Yet, sensitivity was lower than in literature. Advances in knowledge: Radiology is part of treatment decision-making, the issue of heterogeneity regarding radiologists’ training and experience to cancer (sensitivity and specificity) turns essential, so does MRI accuracy.

Management of cervical cancer during the corona virus disease-19 (COVID-19) era

COVID-19 pandemic has had a catastrophic impact on the society, economy and heath-care system all over the globe with virus showing no signs of losing potency. As the situation appears to worsen, extra burden on other specialities like oncology seems to increase. Specific recommendations are necessary for management of cervical cancer in the current context. All concerned specialities must work together in the best interest of the patient. Attempts should be made at managing cervical cancer while limiting the viral spread among the patients and health-care workers without the loss of opportunity. Surgical intervention for early cervical cancer should be postponed or alternative modalities be considered. In a locally advanced disease, concurrent chemoradiation is the treatment of choice. In addition, the following under mentioned suggestions aim to discuss ways of minimizing infection spread, workload rationalization and providing guidance for management of cervical cancer in the presence of COVID-19 infection.

Quantitative diffusion and perfusion MRI in the evaluation of endometrial cancer: validation with histopathological parameters

Objectives: To investigate the role of quantitative Magnetic Resonance Imaging (MRI) in preoperative assessment of tumour aggressiveness in patients with endometrial cancer, correlating multiple parameters obtained from diffusion and dynamic contrast-enhanced (DCE) MR sequences with conventional histopathological prognostic factors and inflammatory tumour infiltrate. Methods: Forty-four patients with biopsy-proven endometrial cancer underwent preoperative MR imaging at 3T scanner, including DCE imaging, diffusion-weighted imaging (DWI) and intravoxel incoherent motion imaging (IVIM). Images were analysed on dedicated post-processing workstations and quantitative parameters were extracted: Ktrans, Kep, Ve and AUC from the DCE; ADC from DWI; diffusion D, pseudo diffusion D*, perfusion fraction f from IVIM and tumour volume from DWI. The following histopathological data were obtained after surgery: histological type, grading (G), lympho-vascular invasion (LVI), lymph node status, FIGO stage and inflammatory infiltrate. Results: ADC was significantly higher in endometrioid histology, G1-G2 (low grade), and stage IA. Significantly higher D* were found in endometrioid subptype, negative lymph nodes and stage IA. The absence of LVI is associated with higher f values. Ktrans and Ve values were significantly higher in low grade. Higher D*, f and AUC occur with the presence of chronic inflammatory cells, D * was also able to distinguish chronic from mixed type of inflammation. Larger volume was significantly correlated with the presence of mixed-type inflammation, LVI, positive lymph nodes and stage ≥IB. Conclusions: Quantitative biomarkers obtained from pre-operative DWI, IVIM and DCE-MR examination are an in vivo representation of the physiological and microstructural characteristics of endometrial carcinoma allowing to obtain the fundamental parameters for stratification into Risk Classes. Advances in knowledge: Quantitative imaging biomarkers obtained from DWI, DCE and IVIM may improve preoperative prognostic stratification in patients with endometrial cancer leading to a more informed therapeutic choice.

Development of an improved diagnostic nomogram for preoperative prediction of small cell neuroendocrine cancer of the cervix

Objectives: Accurate preoperative diagnosis of small cell neuroendocrine cancer of the cervix (SCNECC) is crucial for establishing the best treatment plan. This study aimed to develop an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information. Methods: A total of 105 pathologically confirmed cervical cancer patients (35 SCNECC, 70 non-SCNECC) from multiple centres with complete clinical and MR records were included. Whole lesion histogram analysis of the ADC was performed. Multivariate logistic regression analysis was used to develop diagnostic models based on clinical, morphological, and histogram data. The predictive performance in terms of discrimination, calibration, and clinical usefulness of the different models was assessed. A nomogram for preoperatively discriminating SCNECC was developed from the combined model. Results: In preoperative SCNECC diagnosis, the combined model, which had a diagnostic AUC (area under the curve) of 0.937 (95% CI: 0.887–0.987), outperformed the clinical-morphological model, which had an AUC of 0.869 (CI: 0.788–0.949), and the histogram model, which had an AUC of 0.872 (CI: 0.792–0.951). The calibration curve and decision curve analyses suggest that the combined model achieved good fitting and clinical utility. Conclusions: Non-invasive preoperative diagnosis of SCNECC can be achieved with high accuracy by integrating clinical, MR morphological, and ADC histogram features. The nomogram derived from the combined model can provide an easy-to-use clinical preoperative diagnostic tool for SCNECC. Advances in knowledge: It is clear that the therapeutic strategies for SCNECC are different from those for other pathological types of cervical cancer according to V 1.2021 of the NCCN clinical practice guidelines in oncology for cervical cancer. This research developed an improved, non-invasive method for the preoperative diagnosis of SCNECC by integrating clinical, MR morphological, and apparent diffusion coefficient (ADC) information.

Susceptibility-weighted MR sequence for the evaluation of ovarian masses with torsion

Objective: Adnexal torsion is a rare gynecologic emergency caused by twisting of an adnexal mass. Twisted vascular pedicle is the most specific imaging finding for adnexal torsion, however, identification of twisted vascular pedicle can be challenging. The purpose of this study is to evaluate the feasibility of susceptibility-weighted MR sequence (SWS) for the diagnosis of adnexal torsion. Methods: MR imaging including SWS (SWAN: susceptibility-weighted angiography) of surgically proven four benign ovarian masses with torsion (one acute and three subacute to chronic torsions) were retrospectively evaluated. Three cystic masses and one solid mass were included in this study. Results: High signal intensity venous thrombus within the twisted vascular pedicle on T  1-weighted imaging (T  1WI) was detected in three lesions with subacute to chronic torsion (75%) but not in one lesion with acute torsion, whereas susceptibility-induced signal voids within the twisted vascular pedicle on SWAN were detected in all four lesions (100%). Conclusion: The demonstration of venous thrombus in the twisted vascular pedicle by SWS may be diagnostic for adnexal torsion. Advances in knowledge: SWS can detect blood products sensitively and can reveal venous thrombus in the twisted vascular pedicle, which may be helpful for the diagnosis of adnexal torsion.

CT review of ovarian fibrothecoma

Objective: The aim of this study was to investigate the CT imaging characteristics of ovarian fibrothecoma which may aid in the differentiation from early stage epithelial tumours. Methods: Comparison of 36 patients (41 lesions) with pathologically proven ovarian fibrothecoma tumours and 36 (52 lesions) serous papillary carcinomas (SPCs) lesions. We noted their laterality, size, density, calcifications, Hounsfield units (HUs) and introduced a novel HU comparison technique with the psoas muscle or the uterus. Patients’ clinical findings such as ascites, pleural effusion, carbohydrate antigen-125 levels, and lymphadenopathy findings were also included. Results: Average age was 67.8 and 66 across the fibrothecoma and SPC cohort respectively. Fibrothecoma tumours had diameters ranging from 24 to 207 mm (Median: 94 mm). 80.6% of the fibrothecoma cohort had ascites which was comparable to the 72.2% in the SPC cohort. 70.7% of fibrothecoma tumour favour a purely to predominantly solid structural configuration (p < 0.001). The average HU value for the fibrothecoma solid component was 44 ± 11.7 contrasting the SPC HU value of 66.8 ± 15. The psoas:tumour mass ratio demonstrated a median of 0.7, whereas SPCs shows a median of 1.1 (p < 0.001). Conclusion: Suspicion of ovarian fibrothecoma should be considered through interrogation of their structural density configuration, low psoas to mass HU ratio and a presence of ascites. Advances in knowledge: CT imaging can be a useful tool in diagnosing fibrothecoma tumours and subsequently reducing oncogynaecological tertiary centre referrals, financial burden and patient operative morbidity and mortality.

Spectrum of Ovarian Incidentalomas: Diagnosis and Management

Incidental ovarian lesions are asymptomatic lesions that are accidentally discovered during a CT or MRI examinations that involves the pelvic cavity or during a routine obstetric ultrasound study. Incidental ovarian masses are usually benign with a very low risk of malignancy yet underlying malignant pathology may be discovered during the diagnostic work-up of these lesions. Suspicion of malignancy is directly correlating with the increase in the patient’s age, the increase in the size of the lesion, the presence of the solid components or thick septa and a high color scale of the ovarian mass. Following standard reporting and management protocols are essential to choose the proper work-up of these lesions to avoid unnecessary additional imaging and operative intervention. In this article, we will provide a review of the characteristic imaging features of some incidental and yet commonly encountered ovarian lesions. We will also summarize the recently published algorithms that are important for consistent reporting and standard management of these lesions.

Tree-based exploration of the optimization objectives for automatic cervical cancer IMRT treatment planning

Objective: To develop and evaluate a practical automatic treatment planning method for intensity-modulated radiation therapy (IMRT) in cervical cancer cases. Methods: A novel algorithm named as Optimization Objectives Tree Search Algorithm (OOTSA) was proposed to emulate the planning optimization process and achieve a progressively improving IMRT plan, based on the Eclipse Scripting Application Programming Interface (ESAPI). 30 previously treated cervical cancer cases were selected from the clinical database and comparison was made between the OOTSA-generated plans and clinical treated plans and RapidPlan-based (RP) plans. Results: In clinical evaluation, compared with plan scores of the clinical plans and the RP plans, 22 and 26 of the OOTSA plans were considered as clinically improved in terms of plan quality, respectively. The average conformity index (CI) for the PTV in the OOTSA plans was 0.86 ± 0.01 (mean ± 1 standard deviation), better than those in the RP plans (0.83 ± 0.02) and the clinical plans (0.71 ± 0.11). Compared with the clinical plans, the mean doses of femoral head, rectum, spinal cord and right kidney in the OOTSA plans were reduced by 2.34 ± 2.87 Gy, 1.67 ± 2.10 Gy, 4.12 ± 6.44 Gy and 1.15 ± 2.67 Gy. Compared with the RP plans, the mean doses of femoral head, spinal cord, right kidney and small intestine in the OOTSA plans were reduced by 3.31 ± 1.55 Gy, 4.25 ± 3.69 Gy, 1.54 ± 2.23 Gy and 3.33 ± 1.91 Gy, respectively. In the OOTSA plans, the mean dose of bladder was slightly increased, with 2.33 ± 2.55 Gy (versus clinical plans) and 1.37 ± 1.74 Gy (vs RP plans). The average elapsed time of OOTSA and clinical planning were 59.2 ± 3.47 min and 76.53 ± 5.19 min. Conclusion: The plans created by OOTSA have been shown marginally better than the manual plans, especially in preserving OARs. In addition, the time of automatic treatment planning has shown a reduction compared to a manual planning process, and the variation of plan quality was greatly reduced. Although improvement on the algorithm is warranted, this proof-of-concept study has demonstrated that the proposed approach can be a practical solution for automatic planning. Advances in knowledge: The proposed method is novel in the emulation strategy of the physicists’ iterative operation during the planning process. Based on the existing optimizers, this method can be a simple yet effective solution for automated IMRT treatment planning.

A preoperative radiomics model for the identification of lymph node metastasis in patients with early-stage cervical squamous cell carcinoma

Objectives: To develop and validate a radiomics model for preoperative identification of lymph node metastasis (LNM) in patients with early-stage cervical squamous cell carcinoma (CSCC). Methods: Total of 190 eligible patients were randomly divided into training (n = 100) and validation (n = 90) cohorts. Handcrafted features and deep-learning features were extracted from T2W fat suppression images. The minimum redundancy maximum relevance algorithm and LASSO regression with 10-fold cross-validation were used for key features selection. A radiomics model that incorporated the handcrafted-signature, deep-signature, and squamous cell carcinoma antigen (SCC-Ag) levels was developed by logistic regression. The model performance was assessed and validated with respect to its calibration, discrimination, and clinical usefulness. Results: Three handcrafted features and three deep-learning features were selected and used to build handcrafted- and deep-signature. The model, which incorporated the handcrafted-signature, deep-signature, and SCC-Ag, showed satisfactory calibration and discrimination in the training cohort (AUC: 0.852, 95% CI: 0.761–0.943) and the validation cohort (AUC: 0.815, 95% CI: 0.711–0.919). Decision curve analysis indicated the clinical usefulness of the radiomics model. The radiomics model yielded greater AUCs than either the radiomics signature (AUC = 0.806 and 0.779, respectively) or the SCC-Ag (AUC = 0.735 and 0.688, respectively) alone in both the training and validation cohorts. Conclusion: The presented radiomics model can be used for preoperative identification of LNM in patients with early-stage CSCC. Its performance outperforms that of SCC-Ag level analysis alone. Advances in knowledge: A radiomics model incorporated radiomics signature and SCC-Ag levels demonstrated good performance in identifying LNM in patients with early-stage CSCC.

The clinical utility of imaging methods used to measure hypoxia in cervical cancer

While it is well-established that hypoxia is a major factor that affects clinical outcomes in cervical cancer, widespread usage of clinically available methods to detect and evaluate hypoxia during the course of treatment have not been established. This review compares these methods, summarizes their strengths and weaknesses, and assesses the pathways for their useful employment to alter clinical practice. We conducted a search on PubMed for literature pertaining to imaging hypoxic cervical cancer, and implemented keywords related to oxygen measurement tools to improve the relevance of the search results. Oxygenation level-dependent applications of MRI have demonstrated hypoxia-induced radioresistance, and changes in cervix tumor oxygenation from hyperoxic therapy. The hypoxic areas within tumors can be indirectly identified in dynamic contrast-enhanced images, where they generally display low signal enhancement, and diffusion-weighted images, which demonstrates areas of restricted diffusion (which correlates with hypoxia). Positron emmision tomography, used independently and with other imaging modalities, has demonstrated utility in imaging hypoxia through tracers specific for low oxygen levels, like Cu-ATSM tracers and nitroimidazoles. Detecting hypoxia in the tumors of patients diagnosed with cervical cancer via medical imaging and non-imaging tools like electron paramagnetic resonance oximetry can be utilized clinically, such as for guiding radiation and post-treatment surveillance, for a more personalized approach to treatment. The merits of these methods warrant further investigation via comparative effectiveness research and large clinical trials into their clinical applications.

UK audit of target volume and organ at risk delineation and dose optimisation for cervix radiotherapy treatments

Objective: Assessment of the extent of variation in delineations and dose optimisation performed at multiple UK centres as a result of interobserver variation and protocol differences. Methods: CT/MR images of 2 cervical cancer patients previously treated with external beam radiotherapy (EBRT) and Brachytherapy were distributed to 11 UK centres. Centres delineated structures and produced treatment plans following their local protocol. Organ at risk delineations were assessed dosimetrically through application of the original treatment plan and target volume delineations were assessed in terms of variation in absolute volume and length, width and height. Treatment plan variation was assessed across all centres and across centres that followed EMBRACE II. Treatment plans were assessed using total EQD2 delivered and were compared to EMBRACE II dose aims. Variation in combined intracavitary/interstitial brachytherapy treatments was also assessed. Results: Brachytherapy target volume delineations contained variation due to differences in protocol used, window/level technique and differences in interpretations of grey zones. Planning target volume delineations were varied due to protocol differences and extended parametrial tissue inclusion. All centres met EMBRACE II plan aims for PTV V95 and high-riskclinical target volume D90 EQD2, despite variation in prescription dose, fractionation and treatment technique. Conclusion: Brachytherapy target volume delineations are varied due to differences in contouring guidelines and protocols used. Planning target volume delineations are varied due to the uncertainties surrounding the extent of parametrial involvement. Dosimetric optimisation is sufficient across all centres to satisfy EMBRACE II planning aims despite significant variation in protocols used. Advances in knowledge: Previous multi-institutional audits of cervical cancer radiotherapy practices have been performed in Europe and the USA. This study is the first of its kind to be performed in the UK.

Implications of the new FIGO staging and the role of imaging in cervical cancer

International Federation of Gynecology and Obstetrics (FIGO) staging, which is the fundamentally important cancer staging system for cervical cancer, has changed in 2018. New FIGO staging includes considerable progress in the incorporation of imaging findings for tumour size measurement and evaluating lymph node (LN) metastasis in addition to tumour extent evaluation. MRI with high spatial resolution is expected for tumour size measurements and the high accuracy of positron emmision tomography/CT for LN evaluation. The purpose of this review is firstly review the diagnostic ability of each imaging modality with the clinical background of those two factors newly added and the current state for LN evaluation. Secondly, we overview the fundamental imaging findings with characteristics of modalities and sequences in MRI for accurate diagnosis depending on the focus to be evaluated and for early detection of recurrent tumour. In addition, the role of images in treatment response and prognosis prediction is given with the development of recent technique of image analysis including radiomics and deep learning.

Noninvasive CT radiomic model for preoperative prediction of lymph node metastasis in early cervical carcinoma

Objective: To build and validate a CT radiomic model for pre-operatively predicting lymph node metastasis in early cervical carcinoma. Methods and materials: A data set of 150 patients with Stage IB1 to IIA2 cervical carcinoma was retrospectively collected from the Nanfang hospital and separated into a training cohort (n = 104) and test cohort (n = 46). A total of 348 radiomic features were extracted from the delay phase of CT images. Mann–Whitney U test, recursive feature elimination, and backward elimination were used to select key radiomic features. Ridge logistics regression was used to build a radiomic model for prediction of lymph node metastasis (LNM) status by combining radiomic and clinical features. The area under the receiver operating characteristic curve (AUC) and κ test were applied to verify the model. Results: Two radiomic features from delay phase CT images and one clinical feature were associated with LNM status: log-sigma-2–0 mm-3D_glcm_Idn (p = 0.01937), wavelet-HL_firstorder_Median (p = 0.03592), and Stage IB (p = 0.03608). Radiomic model was built consisting of the three features, and the AUCs were 0.80 (95% confidence interval: 0.70 ~ 0.90) and 0.75 (95% confidence intervalI: 0.53 ~ 0.93) in training and test cohorts, respectively. The κ coefficient was 0.84, showing excellent consistency. Conclusion: A non-invasive radiomic model, combining two radiomic features and a International Federation of Gynecology and Obstetrics stage, was built for prediction of LNM status in early cervical carcinoma. This model could serve as a pre-operative tool. Advances in knowledge: A noninvasive CT radiomic model, combining two radiomic features and the International Federation of Gynecology and Obstetrics stage, was built for prediction of LNM status in early cervical carcinoma.

An MRI-based radiomics signature and clinical characteristics for survival prediction in early-stage cervical cancer

Objectives: To investigate the prognostic role of magnetic resonance imaging (MRI)-based radiomics signature and clinical characteristics for overall survival (OS) and disease-free survival (DFS) in the early-stage cervical cancer. Methods: A total of 207 cervical cancer patients (training cohort: n = 144; validation cohort: n = 63) were enrolled. 792 radiomics features were extracted from T2W and diffusion-weighted imaging (DWI). 19 clinicopathological parameters were collected from the electronic medical record system. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to select significant features to construct prognostic model for OS and DFS. Kaplan-Meier (KM) analysis and log-rank test were applied to identify the association between the radiomics score (Rad-score) and survival time. Nomogram discrimination and calibration were evaluated as well. Associations between radiomics features and clinical parameters were investigated by heatmaps. Results: A radiomics signature derived from joint T2W and DWI images showed better prognostic performance than that from either T2W or DWI image alone. Higher Rad-score was associated with worse OS (p < 0.05) and DFS (p < 0.05) in the training and validation set. The joint models outperformed both radiomics model and clinicopathological model alone for 3-year OS and DFS estimation. The calibration curves reached an agreement. Heatmap analysis demonstrated significant associations between radiomics features and clinical characteristics. Conclusions: The MRI-based radiomics nomogram showed a good performance on survival prediction for the OS and DFS in the early-stage cervical cancer. The prediction of the prognostic models could be improved by combining with clinical characteristics, suggesting its potential for clinical application. Advances in knowledge: This is the first study to build the radiomics-derived models based on T2W and DWI images for the prediction of survival outcomes on the early-stage cervical cancer patients, and further construct a combined risk scoring system incorporating the clinical features.

PREDICTing Post-Embolization Syndrome after uterine fibroid embolization: the PREDICT-PES study

Abstract Objectives To identify the rate of clinically significant post-embolization syndrome (csPES) in our cohort of patients after uterine artery embolization (UAE) for symptomatic fibroids and to identify risk factors associated with the development of csPES. Methods Retrospective case-control study. All patients who underwent UAE for symptomatic fibroids between the 18-month period of March 1, 2022 and September 1, 2023 were recruited. csPES was defined as maximum pain score on visual analogue scale of >5 out of 10, plus at least 1 of: morphine patient-controlled analgesia dose >10 mg, fever, or use of 2 or more antiemetics. Results A total of 69 patients were included, mean age 46.2 years, and median uterine volume 393 mL (range 80-2288 mL). The rate of csPES was 47.8% (33 patients). After adjusting for confounding using multiparametric logistic regression, a positive association was seen between nulliparity and developing csPES (OR: 5.51, 95% CI: 1.297-23.410, P = .021). In addition, a trend was shown between increasing age and a reduced odds of developing csPES (OR: 0.87, 95% CI: 0.748-1.002, P = .054). Conclusion The rate of csPES in our cohort was 47.8%, and nulliparity was strongly associated with the development of csPES. We can use this to better counsel our patients regarding the odds of csPES when these risks are present at pre-procedure consultation and target additional interventions at reducing csPES in this population. Advances in knowledge Clinically significant post-embolization syndrome is common after UAE for symptomatic fibroids. This study showed that nulliparity is a risk factor for developing, previously not known or reported.

Role of MRI in diagnosing the primary site of origin in indeterminate cases of uterocervical carcinomas: a systematic review and meta-analysis

Objective: To perform a literature review assessing role of MRI in predicting origin of indeterminate uterocervical carcinomas with emphasis on sequences and imaging parameters. Methods: Electronic literature search of PubMed was performed from its inception until May 2020 and PICO model used for study selection; population was female patients with known/clinical suspicion of uterocervical cancer, intervention was MRI, comparison was by histopathology and outcome was differentiation between primary endometrial and cervical cancers. Results: Eight out of nine reviewed articles reinforced role of MRI in uterocervical primary determination. T2 and Dynamic contrast were the most popular sequences determining tumor location, morphology, enhancement, and invasion patterns. Role of DWI and MR spectroscopy has been evaluated by even fewer studies with significant differences found in both apparent diffusion coefficient values and metabolite spectra. The four studies eligible for meta-analysis showed a pooled sensitivity of 88.4% (95% confidence interval 70.6 to 96.1%) and a pooled specificity of 39.5% (95% confidence interval 4.2 to 90.6%). Conclusions: MRI plays a pivotal role in uterocervical primary determination with both conventional and newer sequences assessing important morphometric and functional parameters. Socioeconomic impact of both primaries, different management guidelines and paucity of existing studies warrants further research. Prospective multicenter trials will help bridge this gap. Meanwhile, individual patient database meta-analysis can help corroborate existing data. Advances in knowledge: MRI with its classical and functional sequences helps in differentiation of the uterine ‘cancer gray zone’ which is imperative as both primary endometrial and cervical tumors have different management protocols.

PARP inhibitors and immunotherapy in ovarian and endometrial cancers

Advanced ovarian and endometrial cancers have historically been associated with poor prognosis and few treatment options, limited to single or doublet chemotherapy regimens. The introduction of novel target therapies has transformed the management of these cancers. In contrast to chemotherapy, which inhibits DNA replication and mitosis, targeted therapies target cancer signalling pathways, stroma, immune-microenvironment and vasculature in tumour tissues. The most notable advances in gynaecological cancers have come from the introduction of PARP inhibitors and immune checkpoint inhibitors for ovarian and endometrial cancer, respectively. Several PARP inhibitors, which target defective DNA repair, have been approved as maintenance therapy for advanced ovarian cancer in both the first line and platinum-sensitive relapsed settings. Immune checkpoint inhibitors such as anti-PD-1/PD-L1 antibodies have proven successful in advanced mismatch repair deficient endometrial cancers with use now being investigated beyond this population. This review will explore the biological rationale and clinical evidence behind the use of PARP inhibitors and immunotherapy in ovarian and endometrial cancers.

Normalized apparent diffusion coefficient: a novel paradigm for characterization of endometrial and subendometrial lesions

Objectives: To assess the role of normalized apparent diffusion coefficient (ADC) in characterization of endometrial and subendometrial masses, measured as a ratio of the mean ADC of the pathology to mean ADC of two different internal controls, normal myometrium and gluteus maximus muscle, referred to as nADCm and nADCg respectively. Methods: 55 females with pathologically proven endometrial and subendometrial lesions, including 27 cases of endometrial carcinoma, and 28 cases of benign masses were enrolled in this prospective study and assessed with single-shot echoplanar diffusion-weighted imaging. The normalized and absolute ADC of the lesions, measured by two radiologists, were compared in different pathologies and receiver operating characteristics (ROC) performed to distinguish benign and malignant endometrial masses. In the endometrial carcinoma group, the ADC values were further compared with tumor grade and subtype. Results: There was good interobserver agreement (>0.800) for both internal controls, however it was higher for myometrium [intraclass correlation coefficient-0.92; confidence interval (0.86–0.95)] than gluteus maximus muscle [ICC-0.84; CI (0.72–0.90)]. There were statistically significant differences in absolute ADC (p-0.02), nADCm (p-0.02) and nADCg (p < 0.0001) of benign and malignant endometrial masses. Conclusion: Normalized ADC is useful to distinguish benign and malignant masses with comparable accuracy as absolute ADC. Advances in knowledge: Normalized ADC represents an easily measurable quantitative parameter which limits the influence of endogenous and exogenous factors that affect its reproducibility.