Clinical Radiology

Tumour texture features from preoperative CT predict high-risk disease in endometrial cancer

To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients. Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age. High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06). CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.

FDG-PET/MRI with high-resolution DWI characterises the distinct phenotypes of endometrial cancer

To evaluate the capability of integrated 2-[ Thirty-one patients with endometrial cancer (23 with type I, including 17 G1 and six G2 endometrioid adenocarcinomas, and eight with type II, including three G3 endometrioid adenocarcinomas, two carcinosarcomas, and three serous carcinomas) underwent pretreatment FDG-PET/MRI with simultaneous reduced field-of-view diffusion-weighted imaging (DWI). The standardised uptake value (SUV), apparent diffusion coefficient (ADC), and SUV-to-ADC ratio were compared between low-risk (type I and stage I and negative for lymph-vascular space invasion [LVSI]) and high-risk cancers. The diagnostic accuracy for discriminating the cancer phenotypes was evaluated using receiver operating characteristic (ROC) analysis. The SUV was not significantly different between low-risk and high-risk endometrial cancers. High-risk cancers had a significantly lower ADC (756±232×10 The SUV-to-ADC ratio obtained using integrated FDG-PET/MRI with high-resolution DWI reflects tumour aggressiveness including LVSI, and will be useful for lesion characterisation to decide on an appropriate therapeutic strategy for endometrial cancer.

MRI can be used to differentiate between primary fallopian tube carcinoma and epithelial ovarian cancer

To investigate typical features of primary fallopian tube carcinoma (PFTC) on magnetic resonance imaging (MRI) to differentiate it from epithelial ovarian cancer (EOC). Twenty-one patients with PFTC and 35 patients with EOC were included. The clinical and pathological features of patients were analysed. The following MRI features were compared: maximal diameter, laterality, configuration, shape, signal intensity, enhancement pattern, hydrosalpinx, intrauterine fluid accumulation, rim enhancement, and apparent diffusion coefficient (ADC) values within the solid components of tumours in PFTC and EOC. The maximal diameter of PFTC was 4.50±2.10 cm. The shapes of PFTC were mural papillary nodules (2/21, 10%), sausage-like (8/21, 38%), nodular (3/21, 14%), or irregular (8/21, 38%). Enhancement was mild (10/21, 48%), moderate (8/21, 38%), or marked (3/21, 14%). Associated hydrosalpinx and intrauterine fluid accumulation were observed in six (29%) and three (10%) cases, respectively. Significant differences between PFTC and EOC were found in the International Federation of Gynecology and Obstetrics (FIGO) stage, maximal diameter, shape, enhancement pattern, hydrosalpinx, and intrauterine fluid accumulation (p=0.002, 0.004<0.001, <0.001, and 0.048, respectively). Rim enhancement was more prevalent, thicker, and exhibited higher continuity in PFTC than in EOC (p=0.002, <0.001, and 0.002, respectively). Rim enhancement is a useful feature in distinguishing PFTC from EOC, particularly when continuous or seen in combination with a sausage-like shape, hydrosalpinx or intrauterine fluid accumulation. When the tumour is associated with other MRI signs, for example, (i) hydrosalpinx with mural papillary nodules or sausage-like shape with mild-to-moderate enhancement of solid components, (ii) hydrosalpinx, or (iii) intrauterine fluid accumulation, the diagnosis of PFTC should be considered.

Predictive value of R2∗ values derived from blood oxygen level-dependent magnetic resonance imaging for lymph node metastasis after neoadjuvant chemotherapy for cervical squamous cell carcinoma

The aim of this study was to investigate the predictive value of R2∗ values obtained from blood oxygen-level-dependent magnetic resonance imaging (BOLD-MRI) for lymph node metastasis (LNM) after neoadjuvant chemotherapy (NACT) in patients with stage IB-IIA cervical squamous cell carcinoma (CSCC). Patients diagnosed with CSCC and scheduled to undergo radical hysterectomy following NACT were prospectively recruited. Each patient underwent conventional MRI and BOLD-MRI within 1 week before NACT and again within 1 week before surgery. In this study, 67 patients diagnosed with CSCC were recruited. Of the 67 evaluable women, 15 were finally classified as LNM-positive and 52 as LNM-negative. The evaluation based on the Response Evaluation Criteria in Solid Tumours version 1.1 performed within 1 week before surgery showed that none of the patients had progressive disease. No significant differences were observed between the LNM and non-LNM groups in basic clinical information (P > 0.05). Statistical differences were found between the patients who ultimately developed LNM (LNM group) and those who did not (non-LNM group), as well as in Federation of Gynaecology and Obstetrics staging, lymphovascular space invasion (LVSI) status, depth of stromal invasion, and NACT response (P < 0.05). In both groups, R2∗ The R2∗

MRI-based radiomics models for noninvasive evaluation of lymphovascular space invasion in cervical cancer: a systematic review and meta-analysis

Aimed to evaluate the diagnostic performance of preoperative MRI-based radiomic models for noninvasive prediction of lymphovascular space invasion (LVSI) in patients with cervical cancer (CC). A systematic search of the PubMed, Embase, Web of Science, and Cochrane databases was conducted up to December 21, 2023. The quality of the studies was assessed utilizing the Radiomics Quality Score (RQS) system and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Pooled estimates of sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) of the summary receiver operating characteristic curve (SROC) were computed. The clinical utility was evaluated using the Fagan nomogram. Heterogeneity was investigated and subgroup analyses were conducted. Eleven studies were included, with nine studies reporting independent validation sets. In the training sets, the pooled sensitivity, specificity, DOR, and AUC of SROC were 0.81 (95% CI: 0.75-0.85), 0.78 (95% CI: 0.73-0.83), 15 (95% CI: 11-20), and 0.86 (95% CI: 0.79-0.92), respectively. For the validation sets, the overall sensitivity, specificity, DOR, and AUC of SROC were 0.79 (95% CI: 0.73-0.84), 0.73 (95% CI: 0.67-0.78), 10 (95% CI: 7-15), and 0.83 (95% CI: 0.71-0.91), respectively. The Fagan nomogram indicated good clinical utility. Subgroup analysis revealed that multi-sequence MRI-based models exhibited superior diagnostic performance compared to single-sequence MRI-based models in validation sets. This meta-analysis highlights the potential diagnostic efficacy of MRI-based radiomic models for predicting LVSI in CC. Nevertheless, large-sample, multicenter studies are still warranted, and improvements in the standardization of radiomics methodology are necessary.

Impact of superior hypogastric nerve block during uterine fibroid embolisation on pain scores, opioid requirements, and same-day discharge: a case–control study

To assess the safety and efficacy of superior hypogastric nerve block (SHNB) in managing periprocedural pain associated with uterine fibroid embolisation (UFE) and in facilitating same-day discharge. Prospectively enrolled case-control study with retrospective analysis comprising 119 eligible patients who underwent UFE for symptomatic fibroids was undertaken at a UK teaching hospital between January 2016 and September 2022. SHNB was administered to 62 participants in addition to systemic analgesia; 57 participants received systemic analgesia alone. SHNB was performed mid-UFE using 20 ml of 0.25% levobupivacaine. Pain scores were assessed using an 11-point (0-10) verbal numerical rating scale (NRS). The study received research and ethics committee approval. Statistical analysis was performed using the chi-square and independent t-test or Mann-Whitney U-test. A p-value of <0.05 defined significance. Participants who received SHNB experienced significantly less pain during the first 6 h post-procedure (averaged median pain score 2.6 versus 3.8, p=0.031). SHNB reduced the proportion of participants requiring post-procedural anti-emetics (45% versus 63%, p<0.05). For participants entered on the day-case pathway (SHNB = 34, no-SHNB = 16), those who received SHNB had a higher rate of successful same-day discharge (62% versus 31%, p=0.044). This SHNB group required significantly less opioids for periprocedural pain relief (median oral morphine equivalents; 44 mg versus 80 mg, p=0.020). No SHNB-related adverse events occurred. SHNB is safe and effective in reducing perioperative pain, opioid requirements, and anti-emetic use in patients undergoing UFE for symptomatic fibroids. SHNB, as an adjunct to analgesic optimisation, facilitates same-day discharge, which is often limited by severe post-embolisation pain.

Relationships between intravoxel incoherent motion parameters and expressions of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) in patients with cervical cancer

To determine the associations of intravoxel incoherent motion (IVIM) parameters with expression of programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1), and evaluate the performance of the combined model established based on IVIM and clinicopathological parameters in predicting PD-L1and PD-1 status of cervical cancer (CC) patients. Seventy-eight consecutive CC patients were enrolled prospectively and underwent magnetic resonance imaging (MRI) including IVIM. IVIM quantitative parameters were measured, compared, and correlated with PD-L1 and PD-1 expression. Independent factors related to PD-L1 and PD-1 positivity were identified and were used to establish the combined model. The combined model's diagnostic performance was evaluated using the receiver operating characteristic (ROC) analysis. The Shapley additive explanation (SHAP) algorithm was used to explain the contribution of each parameter in the combined model. The real diffusion coefficient (D) value was significantly lower in the PD-L1-positive group than in the PD-L1-negative group (0.64 ± 0.12 versus 0.72 ± 0.11, p=0.021). The PD-1-positive and PD-1-negative groups showed similar trends (0.63 ± 0.13 versus 0.73 ± 0.09, p=0.003). Parametrial invasion, lymph node status, pathological grade, FIGO (International Federation of Gynecology and Obstetrics) staging, and D values were independently associated with PD-L1 and PD-1expression. A combined model incorporating these parameters showed good discrimination with the sensitivity, specificity of 90.9%, 82.6% for PD-L1, and 93.5%, 72% for PD-1. According to the SHAP value, FIGO staging and pathological grade were the most influential features of the prediction model. IVIM parameters were found to correlate with PD-L1 and PD-1 expression. The combined model, incorporating parametrial invasion, lymph node status, pathological grade, FIGO staging, and D values, showed good discrimination in predicting PD-L1 and PD-1 status, providing the basis for CC immunotherapy.

Does dual-energy CT differentiate benign and malignant ovarian tumours?

To assess the ability of dual-energy computed tomography (DECT) to distinguish benign from malignant ovarian tumours (OTs). Following approval of the institutional review board, the institutional database was mined for treatment-naive patients who underwent primary cytoreduction for OT. Thirty-seven patients were included and divided into those with benign OTs (n = 11) and malignant OTs (n = 26), including high-grade (n = 20) and low-grade (n = 6) malignant OTs. Advanced processing and region of interest delineation on the ovarian mass were performed using the preoperative staging DECT examination using the Advantage Workstation. The pixel-level data of the CT attenuation values at 50, 70, and 120 keV and the effective atomic number (Z Malignant OTs had significantly higher Z DECT may be a tool to help distinguish malignant and benign OTs and predict tumour grade.

Hereditary ovarian tumour syndromes: current update on genetics and imaging

Hereditary ovarian tumour syndromes are a diverse group of hereditary syndromes characterised by the development of specific histotypes of ovarian neoplasms. While BRCA syndromes are exclusively associated with high-grade serous carcinomas, patients with Lynch syndrome show a preponderance of endometrioid subtype of ovarian and endometrial carcinomas. Distinct non-epithelial phenotypes, such as sex cord stromal tumours with annular tubules, Sertoli-Leydig cell tumours, and small cell carcinoma of the hypercalcaemic type occur in patients with Peutz-Jeghers, DICER1, and rhabdoid tumour predisposition syndromes, respectively. Gorlin-Goltz syndrome is characterised by the development of bilateral, multiple ovarian fibromas in 14-24% of patients. Ovarian steroid cell tumours and broad ligament papillary cystadenomas are characteristically found in women with von Hippel-Lindau syndrome. Recent studies have allowed the characterisation of tumour genetics and associated oncological pathways that contribute to tumourigenesis. Implications of the diagnosis of these syndromes on screening, management, and prognosis are discussed.

MRI characteristics for differentiating mucinous borderline ovarian tumours from mucinous ovarian cancers

To investigate the magnetic resonance imaging (MRI) characteristics that could differentiate mucinous borderline ovarian tumours (MBOTs) from mucinous ovarian cancers (MOCs). MRI data from 75 patients with MBOTs and 38 patients with MOCs were reviewed retrospectively. The clinicopathological and MRI features, including age, bilaterality, maximum diameter (MD), shape, margin, configuration, cystic-solid interface, papillae, MD of the cyst walls and septa, MD of the solid components, number of cysts, honeycomb loculi, signal of the cystic and solid components, apparent diffusion coefficient (ADC) value and enhancement ratio of the solid components, peritoneal implants and ascites, were compared using univariable analysis and multivariable logistic regression analysis. There were 76 MBOTs and 39 MOCs, and median patient age was 41 years (range 16-77 years) and 51 years (range 15-90 years), respectively (p=0.004). There were significant differences between MBOTs and MOCs regarding the presence of papillae (p=0.013), MD of the solid components (p=0.001), enhancement ratio of the solid components (p=0.003), ADC value (p<0.001), and ascites (p<0.001). The optimal cut-off ADC value was 1.16 × 10 Compared with MOCs, MBOTs had fewer papillae or solid components, lower enhancement ratio, higher ADC values, and were less likely to have moderate or massive ascites.

Application of contrast-enhanced dual-energy spectral CT for differentiating borderline from malignant epithelial ovarian tumours

To investigate the value of contrast-enhanced dual-energy spectral computed tomography (CT) in differentiating borderline epithelial ovarian tumours (BEOTs) from malignant epithelial ovarian tumours (MEOTs). Sixty patients who underwent pelvic contrast-enhanced spectral CT were divided into two groups for analysis based on the tumour types confirmed at histopathological examination (26 BEOTs and 34 MEOTs). The regions of interest (ROIs) were selected on solid tumour components to measure attenuation values on monochromatic image sets (40-140 keV) in all imaging phases and tumour iodine concentrations (IC) on material decomposition images. Differences in the attenuation value between the unenhanced and contrast-enhanced phases (enhancement degree) and between energy strengths (slope k, k = [attenuation at 40 keV- attenuation at 140 keV]/100) were calculated. All measurements between the two groups were compared with independent t-test. Receiver operating characteristic (ROC) curves were generated to calculate the sensitivity, specificity and area under the ROC curve (AUC). Logistic regression analysis was used to evaluate the diagnostic efficacy of using combined parameters in two-phase contrast-enhanced images. In the arterial phase (AP) and venous phase (VP), the BEOTs had significantly lower enhancement than MEOTs from 40 to 100 keV (p<0.05). The k values and IC values both showed significant differences in the AP and VP (p<0.05). Combining parameters in two contrast-enhanced phases provided 80.8% sensitivity and 82.4% specificity in differentiating MEOTs from BEOTs with an AUC of 0.844. Dual-energy spectral CT provides a multiparametric approach in differentiating BEOTs from MEOTs with the best diagnostic efficacy using combined parameters in the AP and VP images.

Benign Brenner tumour of the ovary: CT and MRI features

To evaluate the computed tomography (CT) and magnetic resonance imaging (MRI) features of benign Brenner tumours (BBT) of the ovary. This was a retrospective two-centre study comprising 35 female patients with a definitive diagnosis of BBT at histology in whom CT and/or MRI examinations had been performed. Two experienced radiologists reviewed the CT and MRI features of 39 ovarian BBT retrospectively with consensus reading. The morphological appearance and size of each tumour were recorded. The presence or absence of calcifications within the solid portion was noted at CT. The reviewed characteristics at MRI included qualitative assessment of the signal intensity of the solid portion on diffusion sequence and contrast enhancement, compared to that of the myometrium. CT and MRI images were available for 27 and 28 lesions, respectively. Sixteen patients had both CT and MRI examinations. BBT were unilateral in 89% of patients, and 49% of lesions were solid and 51% were mixed. Calcifications were depicted at CT in 70.4% of lesions. When present, the cystic portion was multilocular in 85% of cases and corresponded to a mucinous lesion in 74% of cases. Enhancement of the solid portion at MRI was inferior or equal to that of the myometrium in 89% of cases and signal on high b-values diffusion images was deemed low or moderate in 93% of cases. The combined CT and MRI findings of a unilateral fibrous ovarian mass containing punctate calcifications often associated with a multilocular cyst suggest the diagnosis of ovarian BBT.

Advancing personalised care in ovarian cancer using CT and MRI radiomics

Radiomics, utilising quantitative feature extraction from CT and MR imaging, offers significant potential in advancing the diagnosis and management of ovarian cancer. Through the analysis of high-dimensional imaging data, radiomics models may capture subtle phenotypic variations in tumour heterogeneity, texture, and shape that extend beyond the capabilities of traditional imaging interpretation. CT-based radiomics excels in evaluating the prognostic significance of peritoneal disease dissemination and treatment response, while MRI-based models provide enhanced soft tissue characterisation, particularly in assessing tumour microstructure, vascularity, and cellularity. Studies demonstrate that these models can improve diagnostic accuracy, predict therapeutic outcomes and assist in risk stratification. However, standardisation of imaging acquisition protocols, feature extraction techniques and validation across diverse patient cohorts remains a challenge for the incorporation of radiomics into routine clinical practice. Evidence strongly supports the incorporation of radiomic features with molecular, genomic and clinical data in developing high-performance integrated radiomics models, which can facilitate precision oncology in ovarian cancer.

Clinical analysis of prophylactic para-aortic intensity-modulated radiation in cervical cancer

This study aimed to compare the survival and toxicity of patients with International Federation of Gynecology and Obstetrics (FIGO) 2009 stage IB1-IIIC cervical cancer without common iliac node metastasis treated with extended-field intensity-modulated radiotherapy (EF-IMRT) or pelvic IMRT (P-IMRT). Thirty-one patients treated with EF-IMRT and 37 patients who underwent P-IMRT were analysed retrospectively. Both groups were treated with high-dose-rate The median follow-up time of EF-IMRT group and P-IMRT group was 22 and 30 months, respectively. The 3-year overall survival (OS), progression-free survival (PFS), and para-aortic lymph node metastasis-free survival (PAMFS) in the EF-IMRT group and P-IMRT group were 87% versus 74.6%, 83.6% versus 61.7%, and 96% versus 80.5%, respectively. Treatment regimens, tumour size, and radiation time were independent prognostic factors of OS and PFS. Treatment regimens, tumour size, and total equivalent dose in 2 Gy/f (EQD2) of point A were independent prognostic factors of PAMFS. Five patients in the EF-IMRT group and 14 patients in P-IMET group experienced treatment failure. The cumulative incidence of grade 3 and 4 acute leukopenia in the EF-IMRT group was 51.6%, in comparison with 27.03% in the pelvic group. No difference was found in thrombocytopenia between two groups. Patients with FIGO 2009 stage IB1-IIIC cervical cancer without common iliac node metastases may be benefit from EF-IMRT. Notably, EF-IMRT exhibits increased toxicity incidence; however, this remains within an acceptable range.

Feasibility of using synthetic MRI to predict lymphatic vascular space invasion status in early-stage cervical cancer: added value to morphological MRI

To investigate the feasibility of synthetic magnetic resonance imaging (syMRI) in predicting the lymphatic vascular space invasion (LVSI) status of early-stage cervical cancer, and its added value to morphological MRI. A total of 72 patients with pathology-confirmed early-stage cervical cancer were enrolled, and classified into LVSI- positive (n=41) and LVSI- negative (n=31) groups. Together with morphological parameters including gross tumor volume (GTV) and maximum tumor diameter (MTD), the T1, T2, and proton density (PD) values of the tumors were also measured and compared between two groups. Binary logistic regression analysis was used to identify the independent variable associated with LVSI. Receiver operating characteristic curve analyses and DeLong tests were used to evaluate and compare the performances of significant parameters or their combination in predicting LVSI. LVSI- positive group showed significantly higher GTV (P=0.008) and MTD (P=0.019), and lower T1 (P<0.001) and PD values (P=0.041) than LVSI- negative group. However, no statistical significance was observed regarding the T2 values (P=0.331). Binary logistic regression indicated that T1 value (odds ratio [OR] = 0.993; P=0.001) and MTD (OR=1.903, P=0.027) were independent variables associated with LVSI in early cervical cancer. Optimal performance could be achieved [area under ROC curve (AUC) = 0.784; cut-off value = 0.56; sensitivity = 80.5%; specificity = 71.0%] when combining T1 and MTD for predicting LVSI. Its performance was significantly better than that of MTD alone (AUC, 0.784 vs 0.662, P=0.035). syMRI might be a feasible approach, and it can provide added value to morphological MRI in predicting the LVSI status of early-stage cervical cancer.

Roles of DWI and T2-weighted MRI volumetry in the evaluation of lymph node metastasis and lymphovascular invasion of stage IB–IIA cervical cancer

To determine whether magnetic resonance imaging volumetry on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) could be used to assess lymph node metastases (LNM) and lymphovascular invasion (LVSI) in resectable cervical cancer. Sixty-five consecutive patients with cervical cancer were enrolled retrospectively. Tumour size, including maximum transverse diameter, tumour length, and gross tumour volume (GTV), was evaluated on DWI and T2WI. Apparent diffusion coefficient (ADC) values were measured. Univariate, multivariate, and receiver operating characteristic (ROC) curve analyses were performed to determine whether tumour size and ADC could be used to assess LNM and LVSI. Tumour length on both T2WI and DWI, and T2WI-based and DWI-based GTVs could be used to assess LNM (p=0.002, 0.004, 0.001, and <0.001, respectively). Tumour length on T2WI, T2WI-based GTV, DWI-based GTV, and ADC value could be used assess LVSI (p=0.039, 0.038, 0.012, 0.039, respectively). Multivariate analyses showed both T2WI-based GTV (odds ratio [OR] = 1.044; p=0.008) and DWI-based GTV (OR=1.941; p=0.019) were independent risk factors for LNM. T2WI-based GTV (OR=1.023, p=0.038) and DWI-based GTV (OR=3.275, p=0.008) were independent risk factors for LVSI. No statistically significant difference was identified between the area under the ROC curve (AUC) of the DWI-based GTV and the T2WI-based GTV (0.790 versus 0.775, p=0.113), or the tumour length on both T2WI (0.790 versus 0.734, p=0.185) and DWI (0.790 versus 0.737, p=0.333) for LNM. For LVSI, the AUC of DWI-based GTV was higher than T2WI-based GTV (0.720 versus 0.682, p=0.006). GTV on both T2WI and DWI could be used assess LNM and LVSI. DWI-based GTV might show the greatest potential for assessing LNM and LVSI in resectable cervical cancer.

Utility of diffusion-weighted signal intensity ratio measurements for predicting malignancy in adnexal mass lesions and its comparison with ORADS MRI scoring: Can an abbreviated MRI protocol predict malignancy accurately?

To assess if diffusion-weighted signal intensity ratio (DW-SIR) is a good parameter for differentiating malignant from benign and borderline ovarian lesions. The MRI studies of histopathologically diagnosed cases of ovarian tumors were reviewed by two groups of radiologists, both calculating the DW SIR for individual cases. The correlation between the DW SIR and ORADS scoring was tested statistically and the positive likelihood ratio of ORADS scoring for predicting malignancy when used solely as well as in conjunction with DW-SIR was calculated. A total of 184 cases were included, of which 74 cases were Benign/borderline (40 %) and 110 cases were malignant (60 %). A DW SIR cut off of 0.375 calculated after the first cycle of reading had an accuracy of 68.5 % and positive predictive value (PPV) of 73 % in predicting malignancy. The PPV for malignancy for each ORADS score increased especially in the ORADS 3 group when the DW SIR cut off was applied. Higher DW SIR values were associated with a higher ORADS score (p<0.001). A marginal increase in the positive likelihood ratio for malignancy was observed in the combined ORADS 4 and 5 groups upon using the DW-SIR cut off. DW-SIR can serve as an adjunctive tool to improve confidence in interpreting intermediate-risk ORADS cases or as a standalone triage tool when contrast MRI is contraindicated, keeping in mind its limitations in sensitivity.

Preoperative clinical scores compared with dual-energy computed tomography parameters in predicting complete resection of ovarian advanced high-grade serous carcinoma

The aim of this study was to compare clinical scores with dual-energy computed tomography (CT) parameters of ovarian advanced high-grade serous carcinoma (HGSC) in prediction of complete (R0) resection. Between November 2021 and July 2024, 56 advanced HGSC patients with complete dual-energy CT images and clinicopathological information were enrolled. Clinical scores, including the Suidan score, computed tomography-based peritoneal cancer index (CT-PCI), computed tomography-based Eisenkop (CT-Eisenkop) score, and Aletti score, were evaluated, and surgical outcomes were prospectively collected. Dual-energy CT parameters were measured from the solid primary tumour component in two-phase contrast-enhanced images. Receiver operating characteristic curves and logistic regression analysis were used to evaluate the diagnostic efficacy in predicting R0 resection. Of the 56 advanced HGSC patients, 32 (57.14%) had R0 resection and 24 (42.86%) had tumour residue. Virtual monoenergetic images at 40 keV (VMI40) were analysed using the ratio of venous phase (VP) to arterial phase (AP) enhancement, expressed as (VP-AP)/AP. The VMI40 (VP-AP)/AP ratio was identified as the only independent risk factor for R0 prediction (odds ratio: 0.019; P=0.022). The VMI40 (VP-AP)/AP ratio showed considerable area under the curve (AUC) performance (AUC of 0.724) for R0 resection, as did the CT-PCI and the CT-Eisenkop scores (both with an AUC of 0.722), compared to the Suidan score. Using CT-Eisenkop score + VMI40 (VP-AP)/AP showed the highest AUC for R0 resection (AUC: 0.853, sensitivity: 94.7%, and specificity: 69.0%). The VMI40 (VP-AP/AP) ratio, a dual-energy CT parameter, outperforms traditional CT-based clinical scores for predicting R0 resection in advanced HGSC. Predictive accuracy is further improved when combined with the CT-Eisenkop score.

Open- source computed tomography (CT)-based sarcopenia assessment in women with suspicious adnexal masses: a feasibility and reproducibility study

Ovarian cancer is the most lethal gynecologic malignancy, with prognosis linked to stage at diagnosis. Ultrasonography is the first-line tool for adnexal mass evaluation, while computed tomography (CT) supports staging and surgical planning. Sarcopenia-low skeletal muscle mass-is a prognostic factor in oncology and measurable on routine CT. Its role in women with indeterminate or malignant adnexal masses remains unclear. This study aimed to assess the feasibility, reproducibility, and clinical utility of CT-based sarcopenia analysis using open-source software in this population. In this prospective pilot study, 38 women with suspicious adnexal masses (classified as indeterminate or malignant by International Ovarian Tumor Analysis Simple Rules, Ovarian-Adnexal Reporting and Data System, or subjective assessment) underwent CT-based sarcopenia analysis. Axial CT images at the L3 level were segmented using 3D Slicer. Skeletal muscle index (SMI, cm²/m²) was calculated, with sarcopenia defined as SMI <38.5 cm Sarcopenia analysis was feasible and reproducible (κ = 0.839). Significant associations were observed with advanced tumor stage (P = .028) and peritoneal carcinomatosis (P = .033), but not with histopathological malignancy, lymphadenopathy, adjacent invasion, or suspicion of alternative primary tumor. Diagnostic performance for malignancy prediction was limited. CT-based sarcopenia analysis using open-source software is feasible and reproducible. Although associated with advanced disease, sarcopenia did not enhance malignancy prediction and should not guide preoperative risk stratification. Its potential value may lie in identifying patients who could benefit from prehabilitation or targeted nutritional support before treatment.

Advanced MRI prediction model for anatomical site identification in uterine carcinoma: enhancing diagnostic accuracy

The uterine carcinoma is the most commonly diagnosed malignancy in the female pelvis. Accurate identification of tumour origin is crucial for determining appropriate treatment approaches. This study aims to develop a prediction model using multiple MRI parameters to accurately diagnose uterine cancer with an indistinctive origin and those involving both the endometrium and cervix prior to treatment. This prospective cohort study included patients who were newly diagnosed with uterine carcinoma who underwent MRI and were considered for hysterectomy within 6 months after MRI. A total of 78 patients with uterine carcinoma were enrolled. Certain imaging features were found to be consistent with cervical carcinoma, included parametrial, vaginal, stromal invasion, and peripheral rim enhancement. Cervical cancer appeared hyperintense compared to the myometrium unlike endometrial cancer. The study found that certain morphologic features were reliable indicators for detecting cervical carcinoma.

Ultrasound-based ADNEX model for differentiating between benign, borderline, and malignant epithelial ovarian tumours

The purpose of this study was to evaluate the ability of the International Ovarian Tumor Analysis-Assessment of Different NEoplasias in the adneXa (IOTA-ADNEX) model to distinguish among benign, borderline, and malignant epithelial ovarian tumours (BeEOTs, BEOTs, and MEOTs, respectively). The study included 813 patients with BeEOTs, BEOTs, and MEOTs who underwent ultrasound examinations and pelvic operations. Comparisons were made between the clinical information and ultrasonographic features of the three patient groups, and the histopathological diagnosis was the gold standard. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) of the ADNEX model were calculated. This was a single-centre retrospective study. Of the 813 patients, 257 (31.6%) had BeEOTs, 114 (14.0%) had BEOTs, and 442 (54.4%) had MEOTs. For a cut-off value of 10% to identify the overall risk for ovarian cancer (OC), the sensitivity and specificity were 99.1% and 73.2%, respectively. According to the receiver operating characteristicscurves, the AUC was 0.987 (95% CI: 0.981-0.993) for BeEOTs compared with MEOTs, 0.820 (95% CI: 0.768-0.872) for BeEOTs compared with BEOTs, 0.912 (95% CI: 0.876-0.948) for BeEOTs compared with stage I OC, and 0.995 (95% CI: 0.992-0.998) for BeEOTs compared with stages II-IV OC. The AUC was 0.614 (95% CI: 0.519-0.709) for BEOTs compared with stage I OC, 0.903 (95% CI: 0.869-0.937) for BEOTs compared with stages II-IV OC, and 0.851 (95% CI: 0.800-0.902) for stage I OC compared with stages II-IV OC. The IOTA-ADNEX model demonstrated good diagnostic performance for the three categories of EOTs and may have the potential to be popularised in assisting radiologists in the assessment of adnexal masses in the future.

“The dilemma of GTN versus benign causes of secondary PPH that were indeterminate by ultrasound examination: How to differentiate?: A new prospective diagnostic criterion of functional MRI and ultrasound"

Early differentiation between causes of secondary postpartum hemorrhage (PPH) can sometimes be difficult and can cause serious complications if diagnosis and treatment are delayed. The study aimed to assess the efficacy of different imaging diagnostic criteria, which would help in differentiating between gestational trophoblastic neoplasia (GTN) from indeterminate benign causes; thus, aiding in making clinical decisions in a timely fashion. A comparative prospective study, were 33 patients complaining of 2ry PPH, with indeterminate diagnosis referred to the Radiology department female imaging unit between October 2020 and November 2022 for further assessment. Transvaginal ultrasound examination as well as functional MRI was done. The lesions were characterized and certain diagnostic criteria were evaluated. The lesion epicenter, margin and depth of myometrial invasion detected by dynamic MRI have significant role to differentiate between GTN and other benign conditions mainly RPOC with higher sensitivity, specificity and accuracy of MRI compared to US. The p value, sensitivity and specificity as well as the accuracy of MRI were: 0.006, 50 %, 92 %, and 81.8 %; 0.000, 87.5 %, 92 % and 90.9 %; 0.002, 87.5 %, 92 % and 90.9 % compared to 0.5, 50 %, 64 % and 60.6 %; 0.01, 87.5 %, 64 % and 69.7 %; 0.2, 87.5 %, 40 % and 51.5 % by US respectively. The overall performance of MRI to reach accurate final diagnosis is higher than the US with accuracy rate of 97 % compared to 63.6 % in indeterminate cases. MRI was found to show higher performance, compared to US in differentiating inconclusive cases of 2ry PPH.

Diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with Ovarian−Adnexal Reporting and Data System (O-RADS) ultrasound risk stratification for adnexal masses: a systematic review and meta-analysis

A number of studies have reported that contrast-enhanced ultrasound (CEUS) imaging might be used for the early diagnosis of adnexal masses. A meta-analysis was performed to evaluate the diagnostic accuracy of CEUS combined with Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound risk stratification for adnexal masses. Related articles were retrieved from PubMed, Web of Science, Embase, and the Cochrane Library in strict accordance with established standards, and data (including true positive, false positive, false negative, and true negative values) was extracted from the original articles. The Quality Assessment of Diagnostic Accuracy Studies 2 was used to evaluate the quality of articles and the possibility of bias. STATA 12.0 software was used to perform statistical analysis. Five articles that included 598 patients were analyzed in this meta-analysis. The pooled sensitivity and specificity of CEUS combined with O-RADS for the diagnosis of adnexal masses were 0.95 (95% confidence interval [CI]: 0.91-0.98) and 0.86 (95% CI: 0.79-0.91). Moreover, the positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve (AUC) were 6.81 (95% CI: 4.61-10.08), 0.05 (95% CI: 0.03-0.11), 111.30 (95% CI: 65.32-189.65), and 0.97 (95% CI: 0.95-0.98), respectively. The pooled AUC and DOR for the detection of CEUS combined with O-RADS were superior to O-RADS US. Our findings revealed that O-RADS combined with CEUS can improve the diagnostic accuracy of ovarian adnexal masses.

Nomogram based on MRI and clinical features to predict progression-free survival in patients with stage IIIC1r cervical squamous cell carcinoma: A two-center study

To develop a nomogram based on MRI and clinical features to predict progression-free survival (PFS) of 2018 FIGO stage ⅢC1r cervical squamous cell carcinoma (CSCC). 144 consecutive patients with stage ⅢC1r CSCC from two independent institutions were stratified into training cohort (from Institution 1, n=100) and independent validation cohort (from Institution 2, n=44). Univariate and multivariate Cox regression analyses of MRI and clinical features before treatment were performed to determine independent risk factors for PFS in training cohort. Nomogram was developed based on them. Concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) analyses were performed to assess and validate the nomogram. In training cohort, 2009 FIGO stage, maximum length of the primary tumor, short diameter and roundness index of the maximum metastatic lymph node were independent risk factors of PFS in patients with stage IIIC1r CSCC (all P-values < 0.05). Nomogram based on them to predict 1- and 3-year PFS achieved C-indexes of 0.835 (95% confidence interval (CI): 0.809-0.862) and 0.789 (95%CI: 0.683-0.895) in the training and validation cohorts, respectively. Areas under ROC curves for the nomogram to predict 1- and 3-year PFS were 0.891 (95%CI: 0.829-0.954), 0.921 (95%CI: 0.861-0.981) in training cohort, and 0.902 (95%CI: 0.803-0.999), 0.885 (95%CI: 0.778-0.992) in validation cohort, respectively. Calibration curves indicated the nomogram predictions were in good agreement with actual observations. The nomogram based on MRI and clinical features has high accuracy and stability in predicting PFS of patients with stage IIIC1r CSCC.

Mimics of primary ovarian cancer and primary peritoneal carcinomatosis – A pictorial review

Numerous conditions can mimic ovarian malignancy. Identifying the origin of a pelvic mass or disseminated peritoneal abnormality on imaging is important to ensure that the patient receives optimal management by the appropriate clinical team. Ovarian cancer mimics include infections and other neoplastic processes, for example, actinomycosis, lymphoma, and sarcoma. We will illustrate intraperitoneal and extraperitoneal ovarian and non-ovarian mimics. Primary peritoneal carcinomatosis mimics include processes such as deep infiltrating endometriosis and rare causes such as gliomatosis peritonei and diffuse peritoneal leiomyomatosis. We aim to illustrate the multimodality key imaging appearances of common and rarer types of mimics.

Advanced multicompartment diffusion model for noninvasive grading of endometrial cancer: comparative analysis with apparent diffusion coefficient (ADC) histogram parameters

To evaluate the predictive ability of restricted spectrum imaging (RSI) model-derived parameters for grading endometrial cancer (EC) and compare their performance with the histogram parameters of the mono-exponential model. A total of 63 patients with EC were enrolled. Regions of interest were manually delineated, and voxel-wise fitting was performed using both a mono-exponential model and 2-4-compartments RSI models. The optimal model was determined based on the Bayesian Information Criterion. Histogram parameters of the apparent diffusion coefficient (ADC) (mean, variance, 10/25/50/75/90th percentile, minimum, maximum, kurtosis, skewness) were extracted. One-way analysis of variance (ANOVA) or Kruskal-Wallis tests were employed to analyse differences in magnetic resonance imaging (MRI) parameters across histological grades. Receiver operating characteristic curve analysis was used to assess their diagnostic performance. The four-compartment RSI model was identified as the optimal model for characterising EC lesions. RSI4-F1/F3 exhibited significant differences between G1/G2 or G1+G2/G3 lesions, and their combination achieved the highest diagnostic performance (AUC = 0.872, 0.759), outperforming all ADC histogram parameters. Significant differences in RSI4-F1/F2/F3 were observed between G1/G3 lesions, with their combination yielding an AUC of 0.922, comparable to ADCmin (AUC = 0.918). Only RSI4-F1/F3 effectively differentiated between G2/G3 or lesions, with their combination yielding the highest AUC (0.729). Incorporating tumour size further enhanced diagnostic performance across all grades (AUC = 0.913, 0.946, 0.757, 0.791 for G1/G2, G1/G3, G2/G3, G1+G2/G3, respectively). The four-compartment RSI model provides valuable insights into the component weights of tumour microenvironment across EC grades. This approach enhances the noninvasive grading of EC lesions.

Elucidating the biological function of computed tomography (CT)-based radiomics biomarkers in serous ovarian cancer

This study aims to elucidate the biological mechanisms in the tumour microenvironment as read from images by comprehensive Gene Set Enrichment Analysis (GSEA) based on radiomic features that predict survival. Furthermore, this study enables biological interpretation of survival prediction using radiomic features, which in turn allows for optimal treatment feedback to improve clinical outcomes. This retrospective study included serous ovarian cancer patients with pretreatment computed tomography (CT) images. Prognostic radiomic features were selected using least absolute shrinkage and selection operator (LASSO)-Cox regression and calculated as a Rad-score. Patients were classified into low- and high-risk groups (HRGs), and a survival prediction model was constructed. Model performance was evaluated with Kaplan-Meier curves, the log-rank test, and the C-index. GSEA identified gene sets associated with radiomic features linked to survival. The Kaplan-Meier curve using the log-rank test (p<0.01) and C-index values (0.768; 95% CI: 0.694-0.842) of the predictive models showed significant differences. GSEA was performed on the low- and HRGs, and the results identified a set of genes associated with cell proliferation, including the G2M checkpoint (p=0.006, FDR=0.138), mitotic spindle (p=0.006, FDR=0.156), and E2F targets (p=0.032, FDR=0.133). This study revealed the biological functions underlying imaging features crucial for survival prediction and introduced an innovative approach to radiogenomics. This comprehensive approach promises to provide novel insights into the tumour microenvironment and potentially contribute to advancements in ovarian cancer treatment.

Dynamic versus nondynamic magnetic resonance imaging (MRI) protocols in Ovarian-Adnexal Reporting and Data System for magnetic resonance imaging (O-RADS MRI) scoring of adnexal masses: a comparative performance analysis

AİM: To compare the diagnostic performance of the Ovarian-Adnexal Reporting and Data System for magnetic resonance imaging (O-RADS MRI) using dynamic and nondynamic contrast-enhanced protocols in the characterisation of adnexal masses. MATERİALS AND METHODS: This retrospective study included 369 patients (mean age, 43.6 ± 15 years) with 479 adnexal lesions who underwent pelvic MRI between January 2020 and March 2025. Dynamic contrast-enhanced MRI (DCE-MRI) was performed in 97 lesions and nondynamic contrast-enhanced MRI in 382. Two radiologists, with 8 and 4 years of experience, independently reviewed all examinations while blinded to clinical and histopathological data. Lesions scored as O-RADS 2-3 were classified as benign and O-RADS 4-5 as malignant. Histopathology or ≥12 months of imaging follow-up served as the reference standard. Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for both protocols. RESULTS: Among 479 lesions, 302 (76.8%) were benign, 28 (7.1%) borderline, and 63 (16.0%) malignant. The dynamic protocol achieved a sensitivity of 97.4%, specificity of 93.2%, PPV of 90.2%, NPV of 98.2%, and accuracy of 94.8%. The nondynamic protocol showed comparable results (sensitivity 96.4%, specificity 94.6%, PPV 91.2%, NPV 97.9%, accuracy 95.0%), with no significant difference in diagnostic accuracy (P =0.794). Malignancy rates increased progressively with higher O-RADS categories in both protocols. CONCLUSION: O-RADS MRI provides a reliable framework for risk stratification of adnexal masses. Nondynamic contrast-enhanced MRI achieves diagnostic performance equivalent to DCE-MRI and can be confidently used when dynamic acquisition is not feasible, supporting broader clinical adoption of simplified O-RADS MRI protocols.

CT and MRI characteristics of ovarian mucinous tumors associated with mature teratomas

This study aimed to evaluate the CT and MRI features of ovarian mucinous tumors associated with mature teratomas. The present study enrolled a total of 34 patients with histopathologically proven ovarian mucinous tumors associated with mature teratomas, including collision tumors composed of mucinous tumors and mature teratomas and mucinous tumors arising from mature teratomas. All patients underwent preoperative pelvic CT and/or MRI. Imaging findings were retrospectively reviewed. Histopathological diagnosis of mucinous tumors included mucinous cystadenoma in 22 patients, mucinous borderline tumor (MBT) in 10 patients, and mucinous carcinoma in two patients. The mean maximum tumor diameter was 168 mm (range, 39-314 mm). All tumors were unilateral, well-defined, predominantly cystic, and multilocular. A total of 14 tumors (41 %) had fewer than 10 loculi, while 12 tumors (35 %) had 30 or more. Fatty components were observed in 30 tumors (88 %), and 20 of 30 tumors (67 %) had multiple fatty components. On MRI, stained glass appearance was observed in 20 of 29 tumors (69 %). On CT, nodular calcifications within fatty components were observed in 12 of 21 tumors (57 %), whereas flattened calcifications within the septa of non-fatty components were observed in 7 of 21 tumors (33 %). Pseudomyxoma peritonei (PMP) was observed in three patients (9 %) with MBT. Ovarian mucinous tumors associated with mature teratomas typically presented as large, multilocular cystic lesions with fatty components and teratoma/mucinous tumor-associated calcifications. Although PMP was uncommon, it was rarely observed in patients with MBT.

Ultrasound Ovarian-Adnexal Reporting and Data System (O-RADS) and modified ultrasound simple rules comparison in evaluation of surgically proven adnexal masses

The aim of this study was validating Ovarian-Adnexal Reporting and Data System (O-RADS) 2022 risk estimates in surgically treated ovarian/adnexal masses comparing accuracy of O-RADS with modified ultrasound simple rules (mUSR) differentiating malignant from benign lesions. The mUSR was a simplified version of the International Ovarian Tumor Analysis (IOTA) using a binary classification of adnexal masses into benign/suspicious for malignancy. multisite retrospective study was conducted including patients with pathology-proven adnexal masses between January 2008 and December 2018. All ultrasound (US) video clips reviewed by an experienced radiologist with randomly selected subset were reviewed by two additional radiologists. Areas under receiver operator characteristic curves (AUCs) were compared without and with CA-125. 791 ovarian masses in 765 patients (26 bilateral) (mean age: 44 ± 15 years) (628 benign, 49 borderline, and 114 malignancies) demonstrated malignancy rates of 0.3%, 3.0%, 24.9%, and 82.4% for O-RADS 2, 3, 4, and 5, respectively. O-RADS and mUSR had a sensitivity of 0.96 (confidence interval [CI]: 0.92-0.99) and 0.96 (CI: 0.91-0.98), negative predictive values (NPVs) of 0.99 (CI: 0.97-1.00) and 0.99 (CI: 0.98-1.00) (P>0.05), specificities 0.75 [CI: 0.71-0.78] and 0.88 [CI: 0.85-0.91], and positive predictive values (PPVs) 0.50 (CI: 0.44-0.55) and 0.68 (CI: 0.61-0.74) (P 0.86). CA 125 improved performance of mUSR (P=0.002) and O-RADS (P=0.005) only in perimenopausal/postmenopausal patients. O-RADS and mUSR both with high sensitivity and NPV for detection of ovarian malignancy but mUSR with significantly higher specificity and PPV than O-RADS. This finding endorses the American College of Radiology (ACR) recommendation for expert sonologist consultation for O-RADS 3 and 4.

Computed tomography (CT) and magnetic resonance imaging (MRI) findings of ovarian sclerosing stromal tumour

The aim of this study was to elucidate the computed tomography (CT) and magnetic resonance imaging (MRI) characteristics of sclerosing stromal tumours (SSTs) to facilitate accurate diagnosis and differentiation of ovarian tumours. This multicenter retrospective study included 34 patients who underwent preoperative CT and/or MRI scans and were subsequently diagnosed with SST through surgical pathology. Three radiologists independently evaluated the CT and MRI images. The variables assessed encompassed demographic information, imaging features, and pathological findings. The 34 lesions were categorised as cystic-solid (58.8%), predominantly cystic (32.4%), or nearly solid (8.8%). The lake-island sign was identified in 30 cases (88.2%), while the serrated sign was observed in 26 cases (76.5%). Marked haemangioma-like enhancement was noted in 24 cases (70.6%), whereas mild to moderate enhancement was observed in 10 cases (29.4%). Vascular pedicles adjacent to the tumour were present in 18 cases (52.9%). SSTs characteristically manifest as cystic-solid masses exhibiting a peripheral serrated sign along the wall and a central lake-island sign, accompanied by significant haemangioma-like prolonged enhancement.

Prognosis risk stratification in patients with cervical adenocarcinoma after surgery: Development and validation of integrated biomarkers

Currently, there is a lack of prognostic assessment tools for cervical adenocarcinoma (CAC). To develop a prognostic tool for patients with CAC after surgery, we innovatively integrated radiomic features from contrast-enhanced computed tomography (CECT) images, clinicopathologic variables, and DNA methylation data. We retrospectively collected the clinical and imaging data of patients with CAC. Pre-, post-, and fusion radiomic models were constructed using a support-vector-machine classifier. Clinical, radiomic features, and DNA methylation data were integrated to develop the combined model. Model performance for the prediction of progression-free survival was evaluated using Harrell' concordance index (C-index). Kaplan-Meier curves were used to show the survival difference between high- and low-risk groups stratified by the models. A total of 127 CAC patients (training cohort, n=86; validation cohort, n=41) were included. In the validation cohort, the clinical model based on chemoradiotherapy and invasion depth achieved a C-index of 0.811 (95%CI: 0.784-0.838). The pre-contrast, post-contrast, and fusion radiomic models yielded a C-index of 0.745 (95%CI: 0.688-0.802), 0.723 (95%CI: 0.668-0.778), 0.757 (95%CI: 0.708-0.806), respectively. The combined model based on chemoradiotherapy, ZNF582, and post-contrast radiomic features obtained the highest C-index of 0.872 (95%CI: 0.835-0.909). The Kaplan-Meier curves display that the high-risk patients had significantly shorter PFS compared to the low-risk patients (all P<0.05). The combined model can be used as a prognosis stratification tool for patients with CAC, which can facilitate disease monitoring and clinical decision-making.

Application of Early Dynamic 18F-FDG PET/CT in T1 and T2 Cervical Cancer

Early 10-minute dynamic F18-fluorodeoxyglucose positron emission tomography/computed tomography (ED Twenty-six patients with confirmed cervical cancer underwent both ED ED ED

Characteristics of the magnetic resonance imaging findings of cervical gastric-type adenocarcinoma

This study identified the distinct magnetic resonance imaging findings of cervical gastric-type adenocarcinoma (GAS) that can help differentiate it from squamous cell carcinoma (SCC) and usual-type endocervical adenocarcinoma (UEA) and reveal the radiologic-pathologic correlation. All consecutive patients with cervical GAS treated at our hospital from November 2009 to August 2021 were included. The SCC and UEA cases were considered controls. Tumor location, tumor shape, presence and size of cysts, presence of uterine fluid, and apparent diffusion coefficient (ADC) were evaluated. Overall, 18 GAS, 55 SCC, and 23 UEA cases were evaluated. The tumor was located in the entire cervix in 13/18 GAS cases, whereas it was predominantly located in the lower cervix in 38/55 SCC cases and 14/23 UEA cases. Most GAS cases exhibited a diffuse infiltration growth pattern (17/18), whereas most SCC and UEA cases exhibited a mass-forming pattern (39/55 and 20/23, respectively). Moreover, the percentages of cases presenting microcysts or macrocysts and undergoing uterine fluid collection were significantly higher in the GAS group (14/18 and 13/18) than in the SCC and UEA groups. ADC was significantly higher in the GAS group than in the SCC group (1.092 × 10 This study revealed that GAS is characterized by tumor presence in the entire cervix, infiltrative growth pattern, intrauterine fluid collection, and frequent microcyst or macrocyst formation. Moreover, ADC was significantly higher in the GAS group than in the SCC group.

Dynamic contrast-enhanced magnetic resonance imaging in cervical cancer: correlation between quantitative parameters and molecular markers hypoxia-inducible factors-1-alpha, vascular endothelial growth factor, and Ki-67

To investigate whether dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has the potential to non-invasively detect microenvironmental condition by quantitatively measuring blood perfusion, vessel wall permeability, and vascularity, and to elucidate the possible correlations between DCE-MRI quantitative parameters and the expression level of hypoxia, vascularity, and cell proliferation related molecular biomarkers. In this prospective single center clinical study, 58 patients diagnosed with cervical cancer underwent DCE-MRI before anticancer treatment were enrolled. K In HIF-1α low-expression group, K Our results suggest that DCE-MRI quantitative parameters could be potentially used as imaging markers for non-invasively detecting microenvironmental hypoxia, vascularity and proliferation in cervical cancer patients.

Substantial discordance between structured pre-operative computed tomography (CT) reports and intraoperative findings in advanced ovarian cancer cytoreductive surgery, affecting treatment decisions

The aim of this study was to assess the agreement and diagnostic accuracy of structured preoperative computed tomography (CT) findings compared to intraoperative findings in advanced ovarian cancer patients undergoing primary or interval cytoreductive surgery. Patients with CT scans suggesting advanced ovarian cancer were enrolled in the study. Agreement between CT reports, reviewed using European Society of Urogenital Radiology (ESUR) criteria, and surgical findings were evaluated with the kappa coefficient. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each radiologic feature. From February 2018 to September 2020, 258 patients with International Federation of Gynaecology and Obstetrics (FIGO) stage IIIB-IV epithelial ovarian cancer were enrolled. Agreement between ESUR-reviewed CT reports and surgical findings was slight to fair (kappa = 0.115-0.352). The most common CT findings were peritoneal carcinomatosis, omental metastases, and bowel involvement. Sensitivity and specificity of peritoneal carcinomatosis were 0.91 (95% confidence interval [CI]: 0.86-0.94) and 0.19 (95% CI: 0.10-0.31), with an area under the receiver operating characteristic curve (AUC) of 0.55 (95% CI: 0.46-0.64). Omental metastases had a sensitivity of 0.91 (95% CI: 0.87-0.95) and specificity of 0.27 (95% CI: 0.16-0.40) with an AUC of 0.59 (95% CI: 0.52-0.65). Bowel involvement showed a sensitivity of 0.61 (95% CI: 0.54-0.67), specificity of 0.71 (95% CI: 0.58-0.83), and AUC of 0.66 (95% CI: 0.58-0.74). This study demonstrates limited concordance between ESUR-reviewed CT reports and intraoperative findings in advanced ovarian cancer. Even when interpreted by expert radiologists, CT imaging alone may inadequately reflect disease burden. These findings emphasise the ongoing challenges of imaging-based surgical planning and support the need for further development and validation of more accurate preoperative assessment tools.

Accuracy of transvaginal ultrasound versus MRI in the PreOperative Diagnostics of low-grade Endometrial Cancer (PODEC) study: a prospective multicentre study

To investigate if the diagnostic accuracy of transvaginal ultrasound (TVUS) performed by gynaecologists is sufficient for preoperative assessment of low-grade endometrial cancer (EC) compared to magnetic resonance imaging (MRI). MRI and TVUS performed by gynaecologists were assessed at the participating centres. The MRI examinations were interpreted by two radiologists at the tertiary centre. Deep myometrial and cervical stroma invasion were visually assessed and compared to postoperative histopathology. Two hundred and fifty-nine patients were included. There was a statistically significant difference in specificity assessing deep myometrial invasion between MRI and TVUS (MRI 0.88, TVUS 0.68). There was no difference in sensitivity (MRI 0.73, TVUS 0.68). When assessing cervical stroma infiltration, MRI had a higher specificity (MRI 0.96, TVUS 0.90), but there was no difference in sensitivity (MRI 0.41, TVUS 0.32). MRI has higher specificity than TVUS performed by gynaecologists for assessing deep MI and CSI in low-grade EC, but similar sensitivities. The use of TVUS as a first-line test, rather than MRI, may be supported by this study in centres where access to MRI may be limited.

Development of a radiomic–clinical nomogram for prediction of survival in patients with serous ovarian cancer

To develop and validate a radiomic-clinical nomogram to evaluate overall survival (OS) postoperatively in patients with serous ovarian cancer. Eighty serous ovarian cancer patients from The Cancer Imaging Archive (TCIA) database were used as the training set, and 39 eligible patients treated at Affiliated Huadu Hospital were used as the independent validation set. In total, 1,301 radiomics features were extracted from ovarian cancer lesions on venous-phase computed tomography (CT) images. Then, a radiomics signature was developed using the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm in the training set. Moreover, a radiomic-clinical nomogram was constructed incorporating the radiomics signature and clinical predictors based on a multivariable Cox regression analysis. The performance of the nomogram was evaluated. Consisting of three selected features, the radiomics signature showed good discrimination in the training and validation sets with C-indexes of 0.694 (95% confidence interval [CI]: 0.613-0.775) and 0.709 (95% CI: 0.517-0.901), respectively. The radiomic-clinical nomogram contained the radiomics signature and four clinical predictors, including age, tumour size, pathological staging, and tumour grade. The nomogram showed favourable discrimination in the training set (C-index [95% CI], 0.754 [0.678-0.830]), which was confirmed in the validation set (C-index [95% CI], 0.727 [0.569-0.885]). According to the model, all patients were classified into high-risk and low-risk groups. Kaplan-Meier curves showed that there was a significant distinction between the OS of the high-risk and low-risk patients. The proposed radiomic-clinical nomogram can increase the predictive accuracy of OS in patients with serous ovarian cancer after surgery, which may aid in clinical decision-making.

The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters

To investigate whether mono-exponential and bi-exponential diffusion-weighted imaging (DWI)-related parameters of the primary tumour can evaluate the status of lymphovascular space invasion (LVSI) and lymph node metastasis (LNM) in patients with cervical carcinoma preoperatively. Eighty patients with cervical carcinoma were enrolled, who underwent preoperative multi b-value DWI and radical hysterectomy. They were classified into LVSI(+) versus LVSI(-) and LNM(+) versus LNM(-) according to postoperative pathology. The apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D∗), and perfusion fraction (f) were calculated from the whole tumour (_ f_ The parameters generated from mono-exponential and bi-exponential DWI of the primary cervical carcinoma could help discriminate its status regarding LVSI (f_

DW-MRI predictive factors for radiation-induced vaginal stenosis in patients with cervical cancer

To find diffusion-weighted (DW) magnetic resonance imaging (MRI) parameters predictive for radiation-induced vaginal stenosis (VS) in locally advanced cervical cancer (LACC) treated with neoadjuvant chemoradiation therapy (CRT). Retrospective analysis of 43 patients with LACC who underwent 1.5 T DW-MRI before (baseline), after 2 weeks (early), and at the end of CRT (final). At MRI, vaginal length, thickness, width, and cervical tumour volume (TV) were measured. Vaginal signal intensity at DW-MRI was analysed at final MRI. CRT-induced VS was graded using Common Terminology Criteria for Adverse Events (CTCAE) v4.03. Correlations between DW-MRI and clinical data were made using Wilcoxon's test, Mann-Whitney test, Fisher's exact test, or chi-squared test as appropriate. Receiver operating characteristic (ROC) curves were generated for variables to evaluate diagnostic ability to predict CRT-induced VS using a logistic regression model. Asymptomatic vaginal toxicity (CTCAE Grade 1) was observed in 14 patients and symptomatic CRT-induced VS (CTCAE Grade ≥2) was detected in 29 patients. Baseline TV was higher in Grade 1 than in Grade ≥2 (p=0.013). Median vaginal length, thickness, and width decreased between baseline and final MRI in all patients (p<0.0001) without significant variances between CTCAE grades. Significant differences were observed in DW-MRI patterns (p<0.0001). In Grade ≥2, DWI showed signal loss of vaginal mucosa in 17 patients (63%) and diffuse restricted diffusion of vaginal wall in eight patients (30%). AUC was 0.938 (coefficient=4.72; p<0.001) for DWI and 0.712 (coefficient=-2.623×10 This is the first study using DW-MRI for predicting CRT-induced VS. DWI is useful tool in patients with LACC after CRT for early prevention and management strategies for VS.

Endometrioid adenocarcinoma: combined multiparametric MRI and tumour marker HE4 to evaluate tumour grade and lymphovascular space invasion

To assess the value of semi-quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and quantitative diffusion-weighted imaging parameters combined with human epididymis protein 4 (HE4) in predicting the pathological grade and lymphovascular space invasion (LVSI) of endometrioid adenocarcinoma (EAC). Between October 2018 and December 2021, 60 women (mean age, 55 [range, 32-77] years) with EAC underwent preoperative pelvic MRI and HE4 level measurements. The positive enhancement integral (PEI), time to peak, maximum slope of increase (MSI), and maximum slope of decrease were measured by manually drawing a region of interest on the neoplastic tissue. The receiver operating characteristic curve was used to calculate the diagnostic efficiency of the single parameter and combined factors. Lower apparent diffusion coefficients (ADCs) were observed in high-grade tumours (G3) than in low-grade tumours (G1/G2). PEI, MSI, and HE4 levels were higher in the high-grade tumours than in the low-grade tumours (p<0.05). The area under the curve (AUC) for G3 diagnosis using multiparametric MRI combined with HE4 was 0.929. ADC values were significantly lower in the EAC with LVSI than in those without LVSI. Tumours with LVSI showed higher PEI and HE4 levels than those without LVSI (p<0.05). The AUC for LVSI-positive diagnosis using multiparametric MRI combined with HE4 was 0.814. Semi-quantitative DCE-MRI, ADC values, and serum HE4 levels can be used to predict tumour grade and LVSI, and the prediction efficiency of multiparametric MRI combined with serum HE4 is better than that of any single factor.

Accuracy of machine learning in the preoperative identification of ovarian borderline tumors: a meta-analysis

The objective of this study is to explore the diagnostic value of machine learning (ML) in borderline ovarian tumors through meta-analysis. Pubmed, Embase, Web of Science, and Cochrane Library databases were comprehensively retrieved from database inception untill February 16, 2023. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was adopted to evaluate the risk of bias in the original studies. Sub-group analyses of ML were conducted according to clinical features and radiomics features. We separately discussed the discriminative value of ML for borderline vs benign and borderline vs malignant tumors. Eighteen studies involving 12,778 subjects were included in our analysis. The modeling variables mainly consisted of radiomics features (n=13) and a small number of clinical features (n=5). When distinguishing between borderline and benign tumors, the ML model based on radiomic features achieved a c-index of 0.782 (95% CI: 0.732-0.831), sensitivity of 0.75 (95% CI: 0.67-0.82), and specificity of 0.75 (95% CI: 0.67-0.81) in the validation set. When distinguishing between borderline and malignant tumors, the ML model based on radiomic features achieved a c-index of 0.916 (95% CI: 0.891-0.940), sensitivity of 0.86 (95% CI: 0.78-0.91), and specificity of 0.88 (95% CI: 0.82-0.92) in the validation set. In addition, we analyzed the discriminatory ability of radiologists and found that their sensitivity was 0.26 (95% CI: 0.12-0.46) and specificity was 0.94 (95% CI: 0.90-0.97). ML has tremendous potential in the preoperative diagnosis and differentiation of borderline ovarian tumors and may be more accurate than radiologists in diagnosing and differentiating borderline ovarian tumors.

Construction and validation of a prediction model for preoperative prediction of Ki-67 expression in endometrial cancer patients by apparent diffusion coefficient

Ki-67 is a marker of cell proliferation and is increasingly being used as a primary outcome measure in preoperative window studies of endometrial cancer (EC). This study explored the feasibility of using apparent diffusion coefficient (ADC) values in noninvasive prediction of Ki-67 expression levels in EC patients before surgery, and constructs a nomogram by combining clinical data. This study retrospectively analyzed 280 EC patients who underwent preoperative magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) in our hospital from January 2017 to February 2023. Evaluate the potential nonlinear relationship between ADC values and Ki-67 expression using the nomogram. The included patients were randomized into a training set (n = 186) and a validation set (n = 84). Using a combination of logistic regression and LASSO regression results, from which the four best predictors were identified for the construction of the nomogram. The accuracy and clinical applicability of the nomogram were assessed using the receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). The results of this study showed a nonlinear correlation between ADCmin and Ki-67 expression (nonlinear P = 0.019), and the nonlinear correlation between ADCmean and Ki-67 expression (nonlinear P = 0.019). In addition, this study constructed the nomogram by incorporating ADCmax, International Federation of Gynecology and Obstetrics (FIGO), and chemotherapy. The area under the curve (AUC) values of the ROC for nomogram, ADCmax, FIGO, chemotherapy and grade in the training set were 0.783, 0.718, 0.579, 0.636, and 0.654, respectively. In the validation set, the AUC values for nomogram, ADCmax, FIGO, chemotherapy, and grade were 0.820, 0.746, 0.558, 0.542, and 0.738, respectively. In addition, the calibration curves and the DCA curves suggested a better predictive efficacy of the model. A nomogram prediction model constructed on the basis of ADCmax values combined with clinical data can be used as an effective method to noninvasively assess Ki-67 expression in EC patients before surgery.

MRI-based radiomics model to preoperatively predict mesenchymal transition subtype in high-grade serous ovarian cancer

To develop a magnetic resonance imaging (MRI)-based radiomics model for the preoperative identification of mesenchymal transition (MT) subtype in high-grade serous ovarian cancer (HGSOC). One hundred and eighty-nine patients with histopathologically confirmed HGSOC were enrolled retrospectively. Among the included patients, 55 patients were determined as the MT subtype and the remaining 134 were non-MT subtype. After extracting a total of 204 features from T2-weighted imaging (T2WI) and contrast-enhanced (CE)-T1WI images, the Mann-Whitney U-test, Spearman correlation test, and Boruta algorithm were adopted to select the optimal feature set. Three classifiers, including logistic regression (LR), support vector machine (SVM), and random forest (RF), were trained to develop radiomics models. The performance of established models was evaluated from three aspects: discrimination, calibration, and clinical utility. Seven radiomics features relevant to MT subtypes were selected to build the radiomics models. The model based on the RF algorithm showed the best performance in predicting MT subtype, with areas under the curves (AUCs) of 0.866 (95 % confidence interval [CI]: 0.797-0.936) and 0.852 (95 % CI: 0.736-0.967) in the training and testing cohorts, respectively. The calibration curves, supported with Brier scores, indicated very good consistency between observation and prediction. Decision curve analysis (DCA) showed that the RF-based model could provide more net benefit, which suggested favorable utility in clinical application. The RF-based radiomics model provided accurate identification of MT from the non-MT subtype and may help facilitate personalised management of HGSOC.

British Society of Urogenital Radiology (BSUR) commentary: FIGO staging of endometrial cancer 2023 update - implications for imaging

Diagnostic accuracy of TVUS and MRI in the preoperative evaluation of myometrial infiltration in patients with endometrial cancer: A meta-analysis

The incidence of endometrial cancer is on the rise worldwide. Accurate preoperative evaluation of myometrial infiltration is crucial for developing treatment strategies. This study compares the diagnostic accuracy of transvaginal ultrasound (TVUS) and magnetic resonance imaging (MRI) for myometrial infiltration (MI) in endometrial cancer (EC). We performed a systematic review and meta-analysis of observational studies, identified by screening Web of Science, SCOPUS, MEDLINE, PubMed, Google Scholar, and EMBASE databases. Studies published between January 1964 and June 2024 comparing the diagnostic accuracy of TVUS and MRI for MI were included. The data analysis focused on sensitivity, specificity, and overall diagnostic accuracy. Twenty-two studies in EC patients were included. The diagnostic odds ratio (OR) for TVUS and for MRI was 18 (95% CI: 22-26) and 20 (95% CI: 14-28), respectively. TVUS was associated with a sensitivity and specificity of 76% (95% CI: 72-82%) and 84% (95% CI: 79-88%), respectively, while MRI had a sensitivity and specificity of 79% (95% CI: 73-84%) and 84% (95% CI: 80-88%), respectively. The area under the receiver operating characteristic curve (AUCROC) was 0.88 for TVUS and 0.89 for MRI. No significant publication bias was detected. Both TVUS and MRI demonstrated comparable diagnostic accuracy for the preoperative evaluation of MI in EC.

Radiomics nomogram in aiding preoperatively dilatation and curettage in differentiating type II and type I endometrial cancer

To established a radiomics nomogram for improving the dilatation and curettage (D&C) result in differentiating type II from type I endometrial cancer (EC) preoperatively. EC patients (n=875) were enrolled retrospectively and divided randomly into a training cohort (n=437) and a test cohort (n=438), according to the ratio of 1:1. Radiomics signatures were extracted and selected from apparent diffusion coefficient (ADC) maps. A multivariate logistic regression analysis was used to identify the independent clinical risk factors. An ADC based-radiomics nomogram was built by integrating the selected radiomics signatures and the independent clinical risk factors. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the radiomics nomogram. The net reclassification index (NRI) and total integrated discrimination index (IDI) were calculated to compare the discrimination performances between the radiomics nomogram and the D&C result. Receiver operating characteristic (ROC) curves showed that the clinical risk factors, the D&C, and the ADC based-radiomics nomogram yielded areas under the ROC curves (AUCs) of 0.70 (95% CI: 0.64-0.76), 0.85 (95% CI: 0.80-0.89), and 0.93 (95% CI: 0.90-0.96) in the training cohort and 0.64 (95% CI: 0.57-0.71), 0.82 (95% CI: 0.77-0.87) and 0.91 (95% CI: 0.87-0.95) in the test cohort, respectively. The DCA, NRI, and IDI demonstrated the clinically usefulness of the ADC based-radiomics nomogram. The ADC-based radiomics nomogram could be used to improve the D&C result in differentiating type II from type I EC preoperatively.

Periprocedural imaging compared to endometrial biopsy: is biopsy required prior to uterine artery embolisation?

To compare the detection rate of magnetic resonance imaging (MRI) and ultrasound relative to endometrial biopsy for endometrial abnormalities in both pre- and post-menopausal women. The present study was an institutional review board-approved, single-institution retrospective analysis of patients who underwent pelvic MRI within 1 year of diagnostic-quality biopsies from 2008-2018 (n=668). There were 303 patients who received uterine artery embolisation (UAE) and 478 patients who received pelvic ultrasound within the study period. Medical records were evaluated for radiological-histopathological correlation, demographics, laboratory studies, and clinical follow-up. In this cohort of 668 patients, there were 37 biopsies positive for malignancy; women with malignancy were older (58 versus 47 years, p<0.0001) and more likely to be post-menopausal (66% versus 12%, p<0.0001). There were 303 patients who underwent UAE and underwent a diagnostic-quality endometrial biopsy during the pre-procedural evaluation, none of whom were post-menopausal and had a mean age of 45 years. In women with abnormal uterine bleeding (AUB) or post-menopausal bleeding (PMB), the sensitivity of MRI for detecting endometrial cancer was 96.2%, with a negative predictive value (NPV) of 99.8%, compared to 68% and 97% for ultrasound, respectively. The receiver operating characteristic (ROC) curve of pre-biopsy MRI in identifying pre-malignant and malignant endometrial pathology demonstrated an AUC of 0.8920 (p<0.0001). In women with AUB or PMB, MRI has a 99.8% NPV in ruling out endometrial cancer. Further consideration should be made towards optimising pre-procedural evaluation for UAE.