Francesca Moro

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review

AbstractThe aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound imaging in gynecology oncology. Web of Science, PubMed, and Scopus databases were searched. All studies were imported to RAYYAN QCRI software. The overall quality of the included studies was assessed using QUADAS‐AI tool. Fifty studies were included, of these 37/50 (74.0%) on ovarian masses or ovarian cancer, 5/50 (10.0%) on endometrial cancer, 5/50 (10.0%) on cervical cancer, and 3/50 (6.0%) on other malignancies. Most studies were at high risk of bias for subject selection (i.e., sample size, source, or scanner model were not specified; data were not derived from open‐source datasets; imaging preprocessing was not performed) and index test (AI models was not externally validated) and at low risk of bias for reference standard (i.e., the reference standard correctly classified the target condition) and workflow (i.e., the time between index test and reference standard was reasonable). Most studies presented machine learning models (33/50, 66.0%) for the diagnosis and histopathological correlation of ovarian masses, while others focused on automatic segmentation, reproducibility of radiomics features, improvement of image quality, prediction of therapy resistance, progression‐free survival, and genetic mutation. The current evidence supports the role of AI as a complementary clinical and research tool in diagnosis, patient stratification, and prediction of histopathological correlation in gynecological malignancies. For example, the high performance of AI models to discriminate between benign and malignant ovarian masses or to predict their specific histology can improve the diagnostic accuracy of imaging methods.

Patient satisfaction with ultrasound, whole-body CT and whole-body diffusion-weighted MRI for pre-operative ovarian cancer staging: a multicenter prospective cross-sectional survey

In addition to the diagnostic accuracy of imaging methods, patient-reported satisfaction with imaging methods is important. To report a secondary outcome of the prospective international multicenter Imaging Study in Advanced ovArian Cancer (ISAAC Study), detailing patients' experience with abdomino-pelvic ultrasound, whole-body contrast-enhanced computed tomography (CT), and whole-body diffusion-weighted magnetic resonance imaging (WB-DWI/MRI) for pre-operative ovarian cancer work-up. In total, 144 patients with suspected ovarian cancer at four institutions in two countries (Italy, Czech Republic) underwent ultrasound, CT, and WB-DWI/MRI for pre-operative work-up between January 2020 and November 2022. After having undergone all three examinations, the patients filled in a questionnaire evaluating their overall experience and experience in five domains: preparation before the examination, duration of examination, noise during the procedure, radiation load of CT, and surrounding space. Pain perception, examination-related patient-perceived unexpected, unpleasant, or dangerous events ('adverse events'), and preferred method were also noted. Ultrasound was the preferred method by 49% (70/144) of responders, followed by CT (38%, 55/144), and WB-DWI/MRI (13%, 19/144) (p7 of 10) during the ultrasound examination. We did not identify any factors related to patients' preferred method. Ultrasound was the imaging method preferred by most patients despite being associated with more pain during the examination in comparison with CT and WB-DWI/MRI. NCT03808792.

Added value of cell‐free DNA over clinical and ultrasound information for diagnosing ovarian cancer

ABSTRACT Objective We previously proposed two cell‐free (cf) DNA‐based scores (genome‐wide Z ‐score and nucleosome score) as candidate non‐invasive biomarkers to further improve the presurgical diagnosis of ovarian malignancy. We aimed to investigate the added value of these cfDNA‐based scores in combination with the clinical and ultrasound predictors of the Assessment of Different NEoplasias in the adneXa (ADNEX) model to estimate the risk of ovarian malignancy. Methods In this prospective cohort study, 526 patients with an adnexal mass scheduled for surgery were recruited consecutively in three oncology referral centers. All patients underwent a transvaginal ultrasound examination, and adnexal masses were described according to the International Ovarian Tumor Analysis terms and definitions. cfDNA was extracted from preoperative plasma samples and genome‐wide Z ‐scores and nucleosome scores were calculated. Logistic regression models were fitted for ADNEX predictors alone and after inclusion of the cfDNA‐based scores. We report likelihood ratios, area under the receiver‐operating‐characteristics curve (AUC), sensitivity, specificity and net benefit for thresholds between 5% and 40%, to assess the diagnostic performance of the models in discriminating between benign and malignant ovarian masses. Results The study included 272 benign, 86 borderline, 36 Stage‐I invasive, 113 Stage‐II–IV invasive, and 19 secondary metastatic tumors. The likelihood ratios for adding the cfDNA‐based scores to the ADNEX model were statistically significant ( P  < 0.001 for ADNEX without CA 125; P  = 0.001 for ADNEX including CA 125). The accompanying increases in AUC were 0.013 when the cfDNA biomarkers were added to the ADNEX model without CA 125, and 0.003 when added to the ADNEX model including CA 125. Net benefit, sensitivity and specificity were similar for all models. The increase in net benefit at the recommended 10% threshold estimated risk of malignancy when adding the cfDNA‐based scores was 0.0017 and 0.0020, respectively, for the ADNEX model without CA 125 and the ADNEX model with CA 125. According to these results, adding cfDNA markers would require at least 453 patients per additional true‐positive test result at the 10% risk threshold. Conclusion Although statistically significant, cfDNA‐based biomarker scores have limited clinical utility in addition to established clinical and ultrasound‐based ADNEX predictors for discriminating between benign and malignant ovarian masses. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

Imaging modalities in fertility preservation in patients with gynecologic cancers

Fertility preservation is an integral component of clinical decision-making and treatment design. However, the selection criteria on imaging for patients eligible for fertility preservation is still unclear. The present review aimed to summarize the main findings reported in both the literature and international guidelines on the role of imaging in the selection of patients for fertility preservation. A search strategy was developed and applied to PubMed, Scopus, Web of Science, and EMBASE to identify previous citations reporting imaging and fertility preservation in patients with gynecological cancer. We also retrieved the published guidelines on the eligibility criteria for fertility-sparing treatment of gynecological neoplasms. A description of the internal multidisciplinary guidelines, clinically in use in our institution, is provided with representative clinical cases. The literature review revealed 1291 articles and 18 of these were selected for the analysis. Both ultrasound and MRI represented the primary imaging methods for selecting patients for fertility preservation in cervical and endometrial cancers. Eligibility criteria of fertility-sparing management in patients with cervical cancer were: tumor size 1 cm, and no parametrium invasion. For patients with endometrial cancer, these included no myometrial and cervical stroma invasion. Both ultrasound and MRI play a key role in characterizing adnexal masses. These modalities provide a useful tool in identifying small ovarian lesions, thus key in the surveillance of patients after fertility sparing surgery. However, efficacy in excluding disease beyond the ovary remains limited. This review provides an update of the literature and schematic outline for the counseling and management of patients with the desire for fertility preservation.

Developing and validating ultrasound‐based radiomics models for predicting high‐risk endometrial cancer

AbstractObjectivesThe primary aim of this study was to develop and validate radiomics models, applied to ultrasound images, capable of differentiating from other cancers high‐risk endometrial cancer, as defined jointly by the European Society for Medical Oncology, European Society of Gynaecological Oncology and European Society for Radiotherapy & Oncology (ESMO‐ESGO‐ESTRO) in 2016. The secondary aim was to develop and validate radiomics models for differentiating low‐risk endometrial cancer from other endometrial cancers.MethodsThis was a multicenter, retrospective, observational study. From two participating centers, we identified consecutive patients with histologically confirmed diagnosis of endometrial cancer who had undergone preoperative ultrasound examination by an experienced examiner between 2016 and 2019. Patients recruited in Center 1 (Rome) were included as the training set and patients enrolled in Center 2 (Milan) formed the external validation set. Radiomics analysis (extraction of a high number of quantitative features from medical images) was applied to the ultrasound images. Clinical (including preoperative biopsy), ultrasound and radiomics features that were statistically significantly different in the high‐risk group vs the other groups and in the low‐risk group vs the other groups on univariate analysis in the training set were considered for multivariate analysis and for developing ultrasound‐based machine‐learning risk‐prediction models. For discriminating between the high‐risk group and the other groups, a random forest model from the radiomics features (radiomics model), a binary logistic regression model from clinical and ultrasound features (clinical‐ultrasound model) and another binary logistic regression model from clinical, ultrasound and previously selected radiomics features (mixed model) were created. Similar models were created for discriminating between the low‐risk group and the other groups. The models developed in the training set were tested in the validation set. The performance of the models in discriminating between the high‐risk group and the other groups, and between the low‐risk group and the other risk groups for both validation and training sets was compared.ResultsThe training set comprised 396 patients and the validation set 102 patients. In the validation set, for predicting high‐risk endometrial cancer, the radiomics model had an area under the receiver‐operating‐characteristics curve (AUC) of 0.80, sensitivity of 58.7% and specificity of 85.7% (using the optimal risk cut‐off of 0.41); the clinical‐ultrasound model had an AUC of 0.90, sensitivity of 80.4% and specificity of 83.9% (using the optimal cut‐off of 0.32); and the mixed model had an AUC of 0.88, sensitivity of 67.3% and specificity of 91.0% (using the optimal cut‐off of 0.42). For the prediction of low‐risk endometrial cancer, the radiomics model had an AUC of 0.71, sensitivity of 65.0% and specificity of 64.5% (using the optimal cut‐off of 0.38); the clinical‐ultrasound model had an AUC of 0.85, sensitivity of 70.0% and specificity of 80.6% (using the optimal cut‐off of 0.46); and the mixed model had an AUC of 0.85, sensitivity of 87.5% and specificity of 72.5% (using the optimal cut‐off of 0.36).ConclusionsRadiomics seems to have some ability to discriminate between low‐risk endometrial cancer and other endometrial cancers and better ability to discriminate between high‐risk endometrial cancer and other endometrial cancers. However, the addition of radiomics features to the clinical‐ultrasound models did not result in any notable increase in performance. Other efficacy studies and further effectiveness studies are needed to validate the performance of the models. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Radiomics analysis of ultrasound images to discriminate between benign and malignant adnexal masses with solid morphology on ultrasound

ABSTRACT Objective The primary aim was to identify radiomics ultrasound features that can distinguish between benign and malignant adnexal masses with solid ultrasound morphology, and between primary malignant (including borderline and primary invasive) and metastatic solid ovarian masses, and to develop ultrasound‐based machine learning models that include radiomics features to discriminate between benign and malignant solid adnexal masses. The secondary aim was to compare the discrimination performance of our newly developed radiomics models with that of the Assessment of Different NEoplasias in the adneXa (ADNEX) model and that of subjective assessment by an experienced ultrasound examiner. Methods This was a retrospective, observational single‐center study conducted at Fondazione Policlinico Universitario A. Gemelli IRCC, in Rome, Italy. Included were patients with a histological diagnosis of an adnexal tumor with solid morphology according to International Ovarian Tumor Analysis (IOTA) terminology at preoperative ultrasound examination performed in 2014–2020, who were managed with surgery. The patient cohort was split randomly into training and validation sets at a ratio of 70:30 and with the same proportion of benign and malignant tumors in the two subsets, with malignant tumors including borderline, primary invasive and metastatic tumors. We extracted 68 radiomics features, belonging to two different families: intensity‐based statistical features and textural features. Models to predict malignancy were built based on a random forest classifier, fine‐tuned using 5‐fold cross‐validation over the training set, and tested on the held‐out validation set. The variables used in model‐building were patient age and radiomics features that were statistically significantly different between benign and malignant adnexal masses and assessed as not redundant based on the Pearson correlation coefficient. We evaluated the discriminative ability of the models and compared it to that of the ADNEX model and that of subjective assessment by an experienced ultrasound examiner using the area under the receiver‐operating‐characteristics curve (AUC) and classification performance by calculating sensitivity and specificity. Results In total, 326 patients were included and 775 preoperative ultrasound images were analyzed. Of the 68 radiomics features extracted, 52 differed statistically significantly between benign and malignant tumors in the training set, and 18 uncorrelated features were selected for inclusion in model‐building. The same 52 radiomics features differed significantly between benign, primary malignant and metastatic tumors. However, the values of the features manifested overlapped between primary malignant and metastatic tumors and did not differ significantly between them. In the validation set, 25/98 (25.5%) tumors were benign and 73/98 (74.5%) were malignant (6 borderline, 57 primary invasive, 10 metastatic). In the validation set, a model including only radiomics features had an AUC of 0.80, sensitivity of 0.78 and specificity of 0.76 at an optimal cut‐off for risk of malignancy of 68%, based on Youden's index. The corresponding results for a model including age and radiomics features were AUC of 0.79, sensitivity of 0.86 and specificity of 0.56 (cut‐off 60%, based on Youden's index), while those of the ADNEX model were AUC of 0.88, sensitivity of 0.99 and specificity of 0.64 (at a 20% risk‐of‐malignancy cut‐off). Subjective assessment had a sensitivity of 0.99 and specificity of 0.72. Conclusions Our radiomics model had moderate discriminative ability on internal validation and the addition of age to this model did not improve its performance. Even though our radiomics models had discriminative ability inferior to that of the ADNEX model, our results are sufficiently promising to justify continued development of radiomics analysis of ultrasound images of adnexal masses. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Transvaginal ultrasound-guided biopsy in patients with suspicious primary advanced tubo-ovarian carcinoma

To assess the accuracy of pathological diagnosis by transvaginal ultrasound-guided biopsy versus surgery in patients with suspicious primary advanced tubo-ovarian carcinoma. The Feasibility, adequacy, and safety of the procedure were also evaluated. Consecutive women with pre-operative suspicious primary advanced tubo-ovarian carcinoma presenting between July 2019 and September 2021 were enrolled. Accuracy was calculated including only cases who underwent surgery. Feasibility was defined as the number of cases in which ultrasound-guided biopsy was possible according to tumor characteristics (morphology and site). Adequacy was defined as the number of conclusive diagnoses out of the samples collected. Safety was defined by the number of major complications which were defined as hospitalization, surgery, and/or blood transfusion. A total of 278 patients were eligible for the study; 158 were enrolled, while 120 were excluded for logistic reasons or patient refusal. Ultrasound-guided biopsy was not feasible in 30 (19%) patients. The samples obtained in the remaining 128 patients were all adequate (100%), and no major complications were noted. A total of 26 (20%) patients started neoadjuvant chemotherapy on the basis of the diagnosis obtained by ultrasound, whereas 102 (80%) patients underwent surgery. Accuracy of ultrasound-guided biopsy versus surgery was 94% (96/102), with six false negative cases at ultrasound (6%). Site (prevesical peritoneum) and size (<8 mm) of the nodules resulted as major predictive factors for ultrasound-guided biopsy failure (false negative). Ultrasound-guided biopsy correctly identified 86 primary invasive tubo-ovarian carcinomas and 10 metastatic tumors. Ultrasound-guided biopsy is a feasible, safe, and accurate method to provide histological diagnosis in suspicious advanced tubo-ovarian cancer patients.

Management of ovarian masses in pregnancy: patient selection for interventional treatment

The management of pregnant women with an adnexal tumor is still challenging and in the literature few data are available. The aim of this study was to describe the management and outcome of patients with ovarian masses detected during pregnancy. As secondary aims, we evaluated the prevalence of malignancy in the International Ovarian Tumor Analysis (IOTA) morphological classes of ovarian masses diagnosed during pregnancy, and created an algorithm for the management of patients with adnexal masses during pregnancy. This was a retrospective single centered study including patients with adnexal masses detected at any trimester during pregnancy between January 2000 and December 2019. Clinical, ultrasound, surgical, and histological data were retrieved from medical records as well as information on management (ultrasound follow-up vs surgery). Indications for surgery were recorded in terms of suspicion of malignancy based on pattern recognition of the ultrasound examiner or on symptoms or prevention of complications, such as torsion, rupture, or obstacle to normal full-term pregnancy. All masses were described using IOTA terminology. A total of 113 patients were selected for the analysis. Of these, 48 (42%) patients had surveillance and 65 (58%) patients underwent surgery (11 primary ovarian tumors, one recurrence of ovarian cancer, four metastases to the ovary, 20 borderline tumors, and 29 benign lesions). Indications for surgery were suspicious malignancy in 41/65 (63.1%) cases and symptoms or prevention of complications in 24/65 (36.9%) cases. All patients in the surveillance group showed no morphological changes of the ovarian lesions at 6 months after delivery. According to the IOTA ultrasound morphological category, the prevalence of malignancy was 0% (0/37) in the unilocular cyst group, 27% (4/15) in the multilocular group, 35% (11/31) in the unilocular solid group, 70% (14/20) in the multilocular solid group, and 70% (7/10) in the solid group. Neither obstetric nor neonatal complications were reported for patients in the surveillance group or in those with benign, borderline, or primary epithelial invasive histology. In contrast, two neonatal deaths were observed in patients with ovarian choriocarcinoma and ovarian metastases. Three of the four patients with ovarian metastases died after pregnancy. IOTA ultrasound morphological classification seems useful in the characterization of ovarian masses during pregnancy. A clinical and morphological based algorithm for counseling patients has been designed.

Imaging in gynecological disease (22): clinical and ultrasound characteristics of ovarian embryonal carcinomas, non‐gestational choriocarcinomas and malignant mixed germ cell tumors

ABSTRACTObjectiveTo describe the clinical and ultrasound characteristics of three types of rare malignant ovarian germ cell tumor: embryonal carcinoma, non‐gestational choriocarcinoma and malignant mixed germ cell tumor.MethodsThis was a retrospective multicenter study. From the International Ovarian Tumor Analysis (IOTA) database, we identified patients with a histological diagnosis of ovarian embryonal carcinoma, non‐gestational choriocarcinoma or malignant mixed germ cell tumor, who had undergone preoperative ultrasound examination by an experienced ultrasound examiner between 2000 and 2020. Additional patients with the same histology were identified from the databases of the departments of gynecological oncology in the participating centers. All tumors were described using IOTA terminology. Three examiners reviewed all available ultrasound images and described them using pattern recognition.ResultsOne patient with embryonal carcinoma, five patients with non‐gestational ovarian choriocarcinoma and seven patients with ovarian malignant mixed germ cell tumor (six primary tumors and one recurrence) were identified. Seven patients were included in the IOTA studies and six patients were examined outside of the IOTA studies. The median age at diagnosis was 26 (range, 14–77) years. Beta‐human chorionic gonadotropin levels were highest in non‐gestational choriocarcinomas and alpha‐fetoprotein levels were highest in malignant mixed germ cell tumors. Most tumors were International Federation of Gynecology and Obstetrics (FIGO) Stage I (9/12 (75.0%)). All tumors were unilateral, and the median largest diameter was 129 (range, 38–216) mm. Of the tumors, 11/13 (84.6%) were solid and 2/13 (15.4%) were multilocular‐solid; 9/13 (69.2%) manifested abundant vascularization on color Doppler examination. Using pattern recognition, the typical ultrasound appearance was a large solid tumor with inhomogeneous echogenicity of the solid tissue and often dispersed cysts which, in most cases, were small and irregular. Some tumors had smooth contours while others had irregular contours.ConclusionsA unilateral, large solid tumor with inhomogeneous echogenicity of the solid tissue and with dispersed small cystic areas in a young woman should raise the suspicion of a rare malignant germ cell tumor. This suspicion can guide the clinician to test tumor markers specific for malignant germ cell tumors. © 2020 International Society of Ultrasound in Obstetrics and Gynecology

Ultrasound features of appendiceal adenoneuroendocrine carcinoma metastatic to ovaries

Ultrasound features of ovarian recurrence of medullary thyroid carcinoma

Ultrasound, macroscopic and histological features of serous epithelial ovarian carcinomas

We present a video showing two cases of serous epithelial ovarian carcinomas. The first video shows clinical, ultrasound, macroscopic, and histological features of a patient with high grade serous ovarian carcinoma. The second video presents clinical, ultrasound, macroscopic, and histological features of a patient with low grade serous ovarian carcinoma.

Ultrasound, macroscopic and histological features of borderline ovarian tumors

Diagnostic performance of ultrasound in assessing the extension of the disease in patients with suspicion of malignant ovarian tumor: correlation between ultrasound parameters and Fagotti’s score

A radical surgical approach represents the mainstay treatment for gynecological malignancy, and preoperative staging of ovarian cancer is crucial. Ultrasound evaluation is widely recognized as the gold standard technique for the characterization of ovarian masses due to a high sensitivity for malignancy. In addition, its accuracy in defining intra-abdominal ovarian cancer spread has been previously proposed. To analyze the agreement between preoperative ultrasound examination and laparoscopic findings in assessing the extension of intra-abdominal disease using six parameters as described by Fagotti's score. When performed by expert examiners, ultrasound can be an accurate technique to assess tumor spread in ovarian cancer and therefore to predict surgical resectability. This is a single-center prospective observational study. Patients with clinical and/or radiological suspicion of advanced ovarian or peritoneal cancer will be assessed with preoperative ultrasound and assigned a score based on the six Fagotti's laparoscopic score parameters. Each parameter will then be correlated with laparoscopic findings. Eligible patients include women 18-75 years of age with clinical and/or imaging suggestive of advanced ovarian or peritoneal cancer, and an ECOG performance status 0-3. Sensitivity and specificity of ultrasound in detecting carcinomatosis, using the parameters of Fagotti's score as a reference standard. Agreement between preoperative ultrasound examination and laparoscopic findings in assessing the extension of intra-abdominal disease as described in Fagotti's score. 240 patients. The accrual started in January 2019. Enrollment should be completed approximately by October 2020 and the results will be analyzed by December 2020. The study received the Ethical Committee approval on July 19 2018 (Protocol 28967/18 ID:2172).

Ultrasound, macroscopic and histological features of malignant ovarian tumors

Longitudinal ultrasound evaluation of clear‐cell ovarian carcinoma

Ultrasound features of chromophobe renal cell carcinoma metastasized to ovary

Pearls and Potential Pitfalls for Correct Diagnosis of Ovarian Cystadenofibroma in MRI: A Pictorial Essay

Ovarian cystadenofibroma is a benign ovarian tumor that is characterized by a consistent percentage of masses, which remain indeterminate in ultrasonography and require magnetic resonance (MR) investigation; they may mimic borderline or malignant lesions. Three main morphologic patterns, resembling different ovarian neoplasms, can be identified in cystadenofibromas: multilocular solid lesions, unilocular cystic lesions with parietal thickening, and purely cystic masses. However, a cystoadenofibroma has typical features, such as T2-weighted hypointensity associated with no restrictions in diffusion-weighted imaging (the so-called "dark-dark appearance") and progressive post-contrast enhancement (type I perfusion curve). The purpose of this study was to review the features of ovarian cystadenofibromas in MR imaging and to suggest pearls and pitfalls regarding their correct diagnosis.

Ultrasound, macroscopic and histological features of malignant ovarian tumors. Metastatic tumors to the ovary: ovarian metastases from biliary tract and ovarian metastases from colon cancer

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.

Fusion imaging in preoperative assessment of extent of disease in patients with advanced ovarian cancer: feasibility and agreement with laparoscopic findings

ABSTRACTObjectivesFusion imaging is an emerging technique that combines real‐time ultrasound examination with images acquired previously using other modalities, such as computed tomography (CT), magnetic resonance imaging and positron emission tomography. The primary aim of this study was to evaluate the feasibility of fusion imaging in patients with suspicion of ovarian or peritoneal cancer. Secondary aims were: to compare the agreement of findings on fusion imaging, CT alone and ultrasound imaging alone with laparoscopic findings, in the assessment of extent of intra‐abdominal disease; and to evaluate the time required for the fusion imaging technique.MethodsPatients with clinical and/or radiographic suspicion of advanced ovarian or peritoneal cancer who were candidates for surgery were enrolled prospectively between December 2019 and September 2020. All patients underwent a CT scan and ultrasound and fusion imaging to evaluate the presence or absence of the following abdominal‐cancer features according to the laparoscopy‐based scoring model (predictive index value (PIV)): supracolic omental disease, visceral carcinomatosis on the liver, lesser omental carcinomatosis and/or visceral carcinomatosis on the lesser curvature of the stomach and/or spleen, involvement of the paracolic gutter(s) and/or anterior abdominal wall, involvement of the diaphragm and visceral carcinomatosis on the small and/or large bowel (regardless of rectosigmoid involvement). The feasibility of the fusion examination in these patients was evaluated. Agreement of each imaging method (ultrasound, CT and fusion imaging) with laparoscopy (considered as reference standard) was calculated using Cohen's kappa coefficient.ResultsFifty‐two patients were enrolled into the study. Fusion imaging was feasible in 51 (98%) of these patients (in one patient, it was not possible for technical reasons). Two patients were excluded because laparoscopy was not performed, leaving 49 women in the final analysis. Kappa values for CT, ultrasound and fusion imaging, using laparoscopy as the reference standard, in assessing the PIV parameters were, respectively: 0.781, 0.845 and 0.896 for the great omentum; 0.329, 0.608 and 0.847 for the liver surface; 0.472, 0.549 and 0.756 for the lesser omentum and/or stomach and/or spleen; 0.385, 0.588 and 0.795 for the paracolic gutter(s) and/or anterior abdominal wall; 0.385, 0.497 and 0.657 for the diaphragm; and 0.336, 0.410 and 0.469 for the bowel. The median time needed to perform the fusion examination was 20 (range, 10–40) min.ConclusionFusion of CT images and real‐time ultrasound imaging is feasible in patients with suspicion of ovarian or peritoneal cancer and improves the agreement with surgical findings when compared with ultrasound or CT scan alone. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Imaging in gynecological disease (24): clinical and ultrasound characteristics of ovarian mature cystic teratomas

ABSTRACTObjectiveTo describe the clinical and ultrasound features of ovarian mature cystic teratomas (MCTs).MethodsThis was a retrospective study. From the International Ovarian Tumor Analysis (IOTA) database, we identified patients with a histologically confirmed diagnosis of MCT who had undergone transvaginal ultrasound examination between 1999 and 2016 (IOTA phases 1, 2, 3 and 5) in one of five centers. Ultrasound was performed by an experienced examiner who used the standardized IOTA examination technique and terminology. In addition to extracting data from the IOTA database, available two‐dimensional grayscale and color or power Doppler images were reviewed retrospectively to identify typical ultrasound features of MCT described previously and detect possible new features using pattern recognition. All images were reviewed by two independent examiners and further discussed with two ultrasound experts to reach consensus.ResultsIncluded in the study were 454 patients with histologically confirmed MCT. Median age was 33 (range, 8–90)  years and 66 (14.5%) patients were postmenopausal. Most MCTs were described by the original ultrasound examiner as unilocular (262/454 (57.7%)) or multilocular (70/454 (15.4%)) cysts with mixed echogenicity of cystic fluid (368/454 (81.1%)), acoustic shadowing (328/454 (72.2%)) and no or little vascularization on color Doppler (color score 1, 240/454 (52.9%); color score 2, 123/454 (27.1%)). The median largest lesion diameter was 66 (range, 15–310)  mm. A correct preoperative diagnosis of MCT was suggested by the original ultrasound examiner in 372/454 (81.9%) cases. On retrospective review of ultrasound images of 334 MCTs that had quality sufficient for assessment, ‘dots and/or lines’ and/or ‘echogenic white ball’ (typical features according to the literature) were present in 271/334 (81.1%) masses. We identified four new ultrasound features characteristic of MCT: ‘cotton wool tufts’, ‘mushroom cap sign’, ‘completely hyperechogenic lesion’ and ‘starry sky sign’. At least one classical or novel ultrasound feature was present in 315/334 (94.3%) MCTs. Twenty‐nine (8.7%) MCTs manifested vascularized solid tissue, of which seven exhibited no typical features.ConclusionWe provide a comprehensive overview of conventional and newly described ultrasound features of MCTs. Only a small proportion of MCTs did not manifest any of the typical features. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.

Imaging in gynecological disease (23): clinical and ultrasound characteristics of ovarian carcinosarcoma

ABSTRACTObjectiveTo describe the clinical and ultrasound characteristics of ovarian carcinosarcoma.MethodsThis was a retrospective multicenter study. Patients with a histological diagnosis of ovarian carcinosarcoma, who had undergone preoperative ultrasound examination between 2010 and 2019, were identified from the International Ovarian Tumor Analysis (IOTA) database. Additional patients who were examined outside of the IOTA study were identified from the databases of the participating centers. The masses were described using the terms and definitions of the IOTA group. Additionally, two experienced ultrasound examiners reviewed all available images to identify typical ultrasound features using pattern recognition.ResultsNinety‐one patients with ovarian carcinosarcoma who had undergone ultrasound examination were identified, of whom 24 were examined within the IOTA studies and 67 were examined outside of the IOTA studies. Median age at diagnosis was 66 (range, 33–91) years and 84/91 (92.3%) patients were postmenopausal. Most patients (67/91, 73.6%) were symptomatic, with the most common complaint being pain (51/91, 56.0%). Most tumors (67/91, 73.6%) were International Federation of Gynecology and Obstetrics (FIGO) Stage III or IV. Bilateral lesions were observed on ultrasound in 46/91 (50.5%) patients. Ascites was present in 38/91 (41.8%) patients. The median largest tumor diameter was 100 (range, 18–260) mm. All ovarian carcinosarcomas contained solid components, and most were described as solid (66/91, 72.5%) or multilocular‐solid (22/91, 24.2%). The median diameter of the largest solid component was 77.5 (range, 11–238) mm. Moderate or rich vascularization was found in 78/91 (85.7%) cases. Retrospective analysis of ultrasound images and videoclips using pattern recognition in 73 cases revealed that all tumors had irregular margins and inhomogeneous echogenicity of the solid components. Forty‐seven of 73 (64.4%) masses appeared as a solid tumor with cystic areas. Cooked appearance of the solid tissue was identified in 28/73 (38.4%) tumors. No pathognomonic ultrasound sign of ovarian carcinosarcoma was found.ConclusionsOvarian carcinosarcomas are usually diagnosed in postmenopausal women and at an advanced stage. The most common ultrasound appearance is a large solid tumor with irregular margins, inhomogeneous echogenicity of the solid tissue and cystic areas. The second most common pattern is a large multilocular‐solid mass with inhomogeneous echogenicity of the solid tissue. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Clinical and ultrasound characteristics of vaginal lesions

Ultrasound examination represents the most important diagnostic method to preoperatively assess gynecological diseases. However, the ultrasound characteristics of vaginal pathologies are poorly investigated. The aim of this study was to describe the clinical and ultrasound characteristics of vaginal lesions detected at ultrasound. This was a single center, prospective, observational study including patients with vaginal masses examined from January 2017 to May 2019. Morphologic sonographic characteristics of the lesions were described as unilocular, multilocular, unilocular-solid, multilocular-solid, and solid. For the analysis, patients were grouped into a 'malignant group', including patients with confirmed malignancy at final histology, and a 'benign group', including patients with a confirmed benign pathology at final histology and patients without a histological diagnosis but with a lesion that manifested no changes during follow-up. 44 patients were enrolled. 22 (50%) of 44 lesions were benign: 12 (54.5%) of these underwent ultrasound follow-up and did not show any changes at the 12 month follow-up whereas 10 (45.5%) lesions had surgical excision which confirmed the benign nature. The remaining 22 (50%) of 44 lesions underwent surgery because of suspicion of malignancy: histology confirmed a malignancy in 20 (90.9%) of 22 cases. Benign lesions were described as follow: 11/24 (45.8%) unilocular, 3/24 (12.5%) multilocular with two locules, and 10/24 (41.7%) solid lesions. Malignant lesions were solid in 19/20 (95%) cases and multilocular-solid in 1/20 (5%). Most benign lesions had a color score of 1-2 (20/24, 83.4%) while malignant lesions had a color score of 3-4 (18/20, 90%). A typical ultrasound image of a benign lesion was a unilocular cyst or hypoechoic solid mass with no or minimal vascularization on color Doppler examination. Malignant vaginal lesions were hypoechoic solid tumors with irregular margins and moderate/rich vascularization or multilocular-solid. Ultrasound should be used to supplement the clinician in the management of vaginal lesions.

Ultrasound morphometric and cytologic preoperative assessment of inguinal lymph‐node status in women with vulvar cancer: MorphoNode study

ABSTRACTObjectiveTo assess the accuracy of preoperative ultrasound examination for predicting lymph‐node (LN) status in patients with vulvar cancer.MethodsThis was a single‐institution retrospective observational study of all women with a histological diagnosis of vulvar cancer triaged to inguinal surgery within 30 days following ultrasound evaluation between December 2010 and January 2016. For each groin examined, 15 morphological and dimensional sonographic parameters associated with suspicion for LN involvement were examined. A morphometric ultrasound pattern (MUP) was expressed for each groin, classifying the inguinal LN status into five groups (normal; reactive‐but‐negative; minimally suspicious/probably negative; moderately suspicious; and highly suspicious/positive) according to subjective judgment, followed by stratification as positive or negative for metastasis according to morphometric binomial assessment (MBA). In cases of positive MBA, fine‐needle aspiration cytology was performed. Combining the information obtained from MUP and cytologic results, a binomial final overall assessment (FOA) was assigned for each groin. The final histology was considered as the reference standard. Comparison was performed between patients with negative and those with positive LNs on histology, and receiver‐operating‐characteristics curves were generated for statistically significant variables on univariate analysis, to evaluate their diagnostic ability to predict negative LN status.ResultsOf 144 patients included in the analysis, 87 had negative inguinal LNs and 57 had positive LNs on histology. A total of 256 groins were analyzed, of which 171 were negative and 85 showed at least one metastatic LN on histology. The following parameters showed the greatest accuracy, with the best balance between specificity and sensitivity, in predicting negative LN status: cortical (C) thickness of the dominant LN (cut‐off, 2.5 mm; sensitivity, 90.0%; specificity, 77.9%); short‐axis (S) length of the dominant LN (cut‐off, 8.4 mm; sensitivity, 63.9%; specificity, 90.6%); C/medulla (M) thickness ratio of the dominant LN (cut‐off, 1.2 mm; sensitivity, 70.4%; specificity, 91.5%), the combination of S length and C/M thickness ratio (sensitivity, 88.9%; specificity, 82.4%); and the FOA analysis (sensitivity, 85.9%; specificity, 84.2%).ConclusionsPreoperative ultrasound assessment, with or without the addition of cytology, has a high accuracy in assessing inguinal LN status in patients with vulvar cancer. In particular, the combination of two ultrasound parameters (S length and C/M thickness ratio) provided the greatest accuracy in discriminating between negative and positive LNs. Copyright © 2019 ISUOG. Published by John Wiley &amp; Sons Ltd.

Imaging in gynecological disease (29): clinical and ultrasound features of primary ovarian immature teratoma

ABSTRACT Objective To describe the clinical and ultrasound characteristics at the time of diagnosis of primary ovarian immature teratoma with no other germ cell tumor components described on histopathology. Methods This was a retrospective study of women with a histological diagnosis of primary ovarian immature teratoma who had undergone a preoperative ultrasound examination between 1998 and 2024. Cases were identified from the databases of 17 contributing ultrasound centers and the International Ovarian Tumor Analysis (IOTA) database. The descriptions of the ultrasound images of the tumors made by the original ultrasound examiners using IOTA terminology were reported. In addition, grayscale and color or power Doppler ultrasound images or videoclips were retrieved for all tumors. Two independent ultrasound examiners reviewed the retrieved material and searched for specific ultrasound characteristics of immature teratomas using pattern recognition. We present their agreed description of the tumors. Results In total, 64 patients with ovarian immature teratoma were included, of which 38 (59.4%) were obtained from the IOTA database (IOTA studies phase 1, 1b, 2, 3, 5 and 7). The median age of the patients at diagnosis was 24.5 (interquartile range (IQR), 18.8–31.0; range, 12–50) years. The most common presenting symptoms were abdominal or pelvic pain (38/60, 63.3%) and abdominal swelling (30/60, 50.0%). All immature teratomas were unilateral. The median largest diameter of the tumor was 149.5 (IQR, 125.0–183.8; range, 27–400) mm. Using IOTA terminology, most tumors were described as multilocular‐solid (32/64, 50.0%) or solid lesions (22/64, 34.4%). When present, the solid component had a median largest diameter of 98.5 (IQR, 59.8–146.8; range 6–400) mm. Most masses showed minimal (19/63, 30.2%) or moderate (35/63, 55.6%) vascularization on color or power Doppler ultrasound examination. Using pattern recognition, the most typical ultrasound feature was heterogeneous, bizarre echogenicity of the solid components, with hyperechogenic areas, cystic spaces and acoustic shadows. This feature, which we consider pathognomonic, was present in 48/57 (84.2%) immature teratomas in which the solid components were adequately assessable. Conclusions The typical ultrasound appearance of an ovarian immature teratoma is a large unilateral adnexal mass with large solid components that is poorly or moderately vascularized. The pathognomonic feature is heterogeneous echogenicity of the solid components with hyperechogenic areas, cystic spaces and acoustic shadows. Preoperative suspicion of immature teratoma can guide treatment, such as offering fertility‐sparing surgery. © 2025 The Author(s). Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Imaging in gynecological disease (27): clinical and ultrasound characteristics of recurrent ovarian stromal cell tumors

ABSTRACTObjectiveTo describe the clinical and ultrasound characteristics of recurrent granulosa cell and Sertoli–Leydig cell tumors.MethodsThis was a retrospective observational study performed at Fondazione Policlinico Universitario A. Gemelli, Istituto di Ricovero e Cura a Carattere Scientifico, IRCCS, Rome (Gemelli center), Italy. Patients with a histological diagnosis of recurrent granulosa cell tumor or Sertoli–Leydig cell tumor were identified from the database of the Department of Gynecological Oncology. Those who had undergone a preoperative ultrasound examination at the Gemelli center between 2012 and 2020 were included, and the data retrieved from the original ultrasound reports. In all of these reports, the recurrent tumors were described using International Ovarian Tumor Analysis (IOTA) terminology. If a patient had more than one episode of relapse, information from all episodes was collected. If there was more than one recurrent tumor at the same ultrasound examination, all tumors were included. One expert sonographer also reviewed all available ultrasound images to identify typical ultrasound patterns using pattern recognition.ResultsWe identified 30 patients with a histological diagnosis of recurrent granulosa cell tumor (25 patients, 55 tumors) or Sertoli–Leydig cell tumor (five patients, seven tumors). All 30 had undergone at least one preoperative ultrasound examination at the Gemelli center and were included. These women had a total of 66 episodes of relapse, of which a preoperative ultrasound examination had been performed at the Gemelli center in 34, revealing 62 recurrent lesions: one in 22/34 (64.7%) episodes of relapse, two in 4/34 (11.8%) episodes and three or more in 8/34 (23.5%) episodes. Most recurrent granulosa cell tumors (38/55, 69.1%) and recurrent Sertoli–Leydig tumors (6/7, 85.7%) were classified as solid or multilocular‐solid tumors, while 8/55 (14.5%) recurrent granulosa cell tumors and 1/7 (14.3%) recurrent Sertoli–Leydig cell tumors were unilocular cysts and 9/55 (16.4%) recurrent granulosa cell tumors were multilocular cysts. The nine unilocular cysts had contents that were anechoic (n = 2) or had low‐level echogenicity (n = 7), had either smooth (n = 4) or irregular (n = 5) internal cyst walls, and ranged in largest diameter from 8 to 38 mm, with three being &lt; 20 mm and five being 20–30 mm. On retrospective review of the images, two typical ultrasound patterns were described: small solid tumor measuring &lt; 2 cm (15/62, 24.2%) and tumor with vascularized echogenic ground‐glass‐like content (12/62, 19.4%).ConclusionsSome granulosa cell and Sertoli–Leydig cell recurrences manifest one of two typical ultrasound patterns, while some appear as unilocular cysts. These are usually classified as benign, but in patients being followed up for a granulosa cell tumor or Sertoli–Leydig cell tumor, a unilocular cyst should be considered suspicious of recurrence. © 2023 The Authors. Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Subjective assessment and IOTA ADNEX model in evaluation of adnexal masses in patients with history of breast cancer

ABSTRACTObjectiveTo evaluate the performance of subjective assessment and the Assessment of Different NEoplasias in the adneXa (ADNEX) model in discriminating between benign and malignant adnexal tumors and between metastatic and primary adnexal tumors in patients with a personal history of breast cancer.MethodsThis was a retrospective single‐center study including patients with a history of breast cancer who underwent surgery for an adnexal mass between 2013 and 2020. All patients had been examined with transvaginal or transrectal ultrasound using a standardized examination technique and all ultrasound reports had been stored and were retrieved for the purposes of this study. The specific diagnosis suggested by the original ultrasound examiner in the retrieved report was analyzed. For each mass, the ADNEX model risks were calculated prospectively and the highest relative risk was used to categorize each into one of five categories (benign, borderline, primary Stage I, primary Stages II–IV or metastatic ovarian cancer) for analysis of the ADNEX model in predicting the specific tumor type. The performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal tumors and between primary and metastatic adnexal tumors was evaluated, using final histology as the reference standard.ResultsIncluded in the study were 202 women with a history of breast cancer who underwent surgery for an adnexal mass. At histology, 93/202 (46.0%) masses were benign, 76/202 (37.6%) were primary malignancies (four borderline and 72 invasive tumors) and 33/202 (16.3%) were metastases. The original ultrasound examiner classified correctly 79/93 (84.9%) benign adnexal masses, 72/76 (94.7%) primary adnexal malignancies and 30/33 (90.9%) metastatic tumors. Subjective ultrasound evaluation had a sensitivity of 93.6%, specificity of 84.9% and accuracy of 89.6%, while the ADNEX model had higher sensitivity (98.2%) but lower specificity (78.5%), with similar accuracy (89.1%), in discriminating between benign and malignant ovarian masses. Subjective evaluation had a sensitivity of 51.5%, specificity of 88.8% and accuracy of 82.7% in distinguishing metastatic and primary tumors (including benign, borderline and invasive tumors), and the ADNEX model had a sensitivity of 63.6%, specificity of 84.6% and similar accuracy (81.2%).ConclusionsThe performance of subjective assessment and the ADNEX model in discriminating between benign and malignant adnexal masses in this series of patients with history of breast cancer was relatively similar. Both subjective assessment and the ADNEX model demonstrated good accuracy and specificity in discriminating between metastatic and primary tumors, but the sensitivity was low. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of ultrasound with computed tomography and whole‐body diffusion‐weighted MRI in prediction of surgical outcome using ESMO ‐ ESGO criteria in patients with tubo‐ovarian carcinoma: prospective ISAAC study

ABSTRACT Objective To test the non‐inferiority of extended abdominopelvic ultrasound examination compared with contrast‐enhanced computed tomography (CT) and whole‐body diffusion‐weighted magnetic resonance imaging (WB‐DWI/MRI) in discriminating preoperatively between resectable and non‐resectable disease based on the European Society for Medical Oncology (ESMO) and European Society of Gynecological Oncology (ESGO)‐defined criteria in patients with tubo‐ovarian carcinoma. Methods The Imaging Study on Advanced ovArian Cancer was a prospective multicenter observational study conducted in five European gynecological oncology centers. All centers had ESGO accreditation to perform advanced ovarian cancer surgery, and ultrasound examinations were performed by a European Federation of Societies for Ultrasound in Medicine and Biology level‐III examiner in a standardized manner. Included in the analysis were patients enrolled between 2020 and 2022 with suspected or histologically proven primary tubo‐ovarian (including peritoneal) carcinoma who, for the purposes of the study, underwent ultrasound and CT imaging, as well as WB‐DWI/MRI if available, prior to surgery. The index tests, which included the preoperative imaging modalities as well as intraoperative exploration at the start of surgery, supplemented by biopsy or follow‐up imaging for extra‐abdominal locations, evaluated the presence of disease at eight anatomical sites that, if infiltrated, would indicate non‐resectability of the tumor according to the ESMO‐ESGO criteria. Surgical outcome, described by the surgeons at the end of the procedure, was used as the reference standard and non‐resectability was defined as the presence of residual disease &gt; 1 cm or when debulking surgery was not feasible. The area under the receiver‐operating‐characteristics curve (AUC) and F 1  score were used to assess the performance of the preoperative imaging methods and surgical exploration in discriminating between patients with resectable and those with non‐resectable disease, based on the ESMO‐ESGO criteria. We also calculated the percentage agreement between imaging findings and surgical exploration findings at the start of surgery, supplemented when applicable by biopsy or follow‐up imaging for extra‐abdominal locations, regarding the presence of tumor infiltration at each of the eight anatomical sites associated with non‐resectability. Results Of 279 patients enrolled during the study period, 242 were included in the final analysis. In the subgroup of 167 patients who underwent surgery and had been examined by all three imaging methods, the AUC of the three imaging modalities and surgical exploration for discriminating between resectable and non‐resectable disease based on the ESMO‐ESGO criteria was 0.835 (95% CI, 0.756–0.915) for ultrasound, for CT it was 0.754 (95% CI, 0.664–0.843), for WB‐DWI/MRI it was 0.720 (95% CI, 0.626–0.814) and for surgical exploration it was 0.952 (95% CI, 0.915–0.988). Ultrasound was not inferior to CT or WB‐DWI/MRI, based on the AUC and F 1 score, in discriminating between patients with resectable and those with non‐resectable tubo‐ovarian carcinoma. At surgical exploration, at least one non‐resectability criterion was present in 32.2% cases. The criteria observed most frequently at surgical exploration were small‐bowel involvement (23.6% of cases), diffuse deep infiltration of the root of the small‐bowel mesentery (18.2% of cases) and hepatic hilum involvement (5.4% of cases). The percentage agreement between ultrasound and surgical exploration in assessing the presence of disease in at least one of the eight anatomical sites that, if infiltrated, would indicate non‐resectability of tumor, was 83.9%, surpassing the percentage agreement with surgical exploration of both CT (77.7%) and WB‐DWI/MRI (75.8%). Conclusion When performed by an experienced examiner, ultrasound is not inferior to either CT or WB‐DWI/MRI in discriminating between resectable and non‐resectable disease in patients with tubo‐ovarian carcinoma, based on evaluation of the presence of the disease in at least one of eight anatomical sites that, if infiltrated, would indicate non‐resectability of the tumor. © 2025 The Author(s). Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Imaging in gynecological disease (28): clinical and ultrasound characteristics of serous and mucinous cystadenomas in the adnexa

ABSTRACTObjectiveTo describe the clinical and ultrasound characteristics of serous and mucinous cystadenomas in the adnexa.MethodsThis was a retrospective international multicenter study. Using the International Ovarian Tumor Analysis (IOTA) database, patients with a histological diagnosis of serous or mucinous cystadenoma who had undergone preoperative ultrasound examination between 1999 and 2016 (IOTA studies phase 1, 1b, 2, 3 and 5) were identified. All masses were described using the standardized IOTA terminology. The diagnosis assigned by the original ultrasound examiner based on subjective assessment was recorded. Two reviewers assessed the available digital ultrasound images using pattern recognition to identify typical sonographic features of cystadenomas.ResultsA total of 1318 patients were included: 687 (52.1%) with serous cystadenomas and 631 (47.9%) with mucinous cystadenomas. Based on the data recorded prospectively in the IOTA database, for serous cystadenomas the median diameter of the largest tumor was 68 (range, 14–320) mm. Most serous cystadenomas were described as unilateral (588/687 (85.6%)), with unilocular (274/687 (39.9%)) or multilocular (221/687 (32.2%)) morphology, and most had anechoic cyst content (508/687 (73.9%)). Most serous cystadenomas were not vascularized (color score of 1; 327/687 (47.6%)) or were poorly vascularized (color score of  2; 253/687 (36.8%)) on color Doppler examination. The original ultrasound examiner correctly classified 91.1% (626/687) of serous cystadenomas as benign and suggested the correct specific diagnosis in 51.5% (354/687) of tumors. For mucinous cystadenomas, the median diameter of the largest tumor was 93 (range, 12–550) mm. Most mucinous cystadenomas were described as unilateral (594/631 (94.1%)) with multilocular morphology (357/631 (56.6%)), and most manifested low‐level echogenicity (334/631 (52.9%)). Most mucinous cystadenomas were poorly (color score of 2; 248/631 (39.3%)) or moderately (color score of 3; 194/631 (30.7%)) vascularized on color Doppler examination. The original ultrasound examiner correctly classified 87.5% (552/631) of mucinous cystadenomas as benign and suggested the correct specific diagnosis in 42.9% (271/631) of tumors. Based on pattern recognition (review of ultrasound images available for 433 tumors), the most typical sonographic features of serous cystadenomas were unilocular cyst (100/211 (47.4%)) or multilocular cyst with &lt; 10 cyst locules (71/211 (33.6%)), whereas the typical features of mucinous cystadenomas were multilocular cyst with &lt; 10 cyst locules (99/222 (44.6%)), unilocular cyst (78/222 (35.1%)) or multilocular cyst with &gt; 10 cyst locules (31/222 (14.0%)). A honeycomb nodule was found in some mucinous cystadenomas (31/222 (14.0%)) but was not found in serous cystadenomas.ConclusionsSerous and mucinous cystadenomas exhibit typical sonographic features, allowing ultrasound examiners to assign a correct specific diagnosis to most tumors. Recognizing the ultrasound features of cystadenomas and avoiding misdiagnosing them as malignant can help prevent surgery for these benign tumors in asymptomatic patients. © 2025 The Author(s). Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Radiomics‐based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas ( ROMUS ): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer ( MITO ) study

ABSTRACT Objective To develop machine‐learning models that incorporate clinical information and radiomics features extracted from ultrasound images to distinguish uterine sarcomas from leiomyomas. Methods This retrospective, multicenter, pilot case–control study included 200 patients (100 with a uterine sarcoma and 100 with a usual‐type leiomyoma, i.e. including no benign leiomyoma variants) who underwent preoperative ultrasound examination between January 2010 and June 2022. The patient cohort was split (70:30) into training and validation sets, with the same proportion of leiomyomas and sarcomas in each subset. We extracted radiomics features belonging to different families: intensity‐based statistical features and textural features. The variables used in model building were patient age and the radiomics features that differed statistically significantly between sarcomas and leiomyomas and that were not redundant based on Spearman's correlation coefficient. Logistic regression, random forest, extreme gradient boosting (XGBoost) and support vector machine models were tested in the model development process. We evaluated the performance of the models in differentiating between sarcomas and leiomyomas using the area under the receiver‐operating‐characteristics curve (AUC), accuracy, sensitivity and specificity. We compared these results to those of subjective assessment by the original ultrasound examiner and to those of two independent expert ultrasound examiners who, blinded to clinical history, reviewed the same grayscale ultrasound images as those used for the radiomics analysis. Results Sixty‐three radiomics features were extracted. Of these, eight differed statistically significantly between sarcomas and leiomyomas and were not correlated, so were selected for inclusion in model building. In the validation set, the model that performed best in differentiating between sarcomas and leiomyomas was an XGBoost model integrating patient age and radiomics features. In the validation set, this model had an AUC of 0.93, sensitivity of 0.93 and specificity of 0.83, at a risk‐of‐malignancy cut‐off of 47% (the cut‐off that yielded the highest number of correct classifications based on Youden's index in the training set). The corresponding results for the model integrating only the radiomics features were: AUC of 0.87, sensitivity of 0.87 and specificity of 0.83. Subjective assessment by the original ultrasound examiner had a sensitivity of 0.87 and specificity of 1 in the validation set, while retrospective review of grayscale ultrasound images by ultrasound experts had a sensitivity of 0.87 and specificity of 0.80 (same results for both reviewers). Conclusion A model including eight radiomics features and patient age demonstrated reasonably good discriminative and classification performance for distinguishing uterine sarcomas from leiomyomas. Its classification ability was similar to that of subjective assessment by the original ultrasound examiner, being more sensitive but less specific. To confirm the role of radiomics for discriminating between uterine sarcomas and leiomyomas, large prospective studies including benign leiomyoma variants are needed. If good performance of radiomics models can be confirmed, integrating automated radiomics analysis into ultrasound machine software may help ultrasound examiners to discriminate between sarcomas and benign leiomyomas. © 2026 The Author(s). Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Developing and validating ultrasound‐based machine‐learning models incorporating radiomics features to predict malignancy in adnexal masses

ABSTRACT Objective The primary aim of this study was to develop and internally validate ultrasound‐based radiomics models to discriminate between all types of benign and malignant adnexal masses. The secondary aim was to compare the performance of the radiomics models with that of the Assessment of Different NEoplasias in the adneXa (ADNEX) model. Methods This was a retrospective, observational, single‐center study, for which all patients with an adnexal mass that were included in the ongoing International Ovarian Tumor Analysis phase‐5 and phase‐7 studies and were examined using ultrasound between January 2012 and December 2023 at Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy, were eligible for inclusion. Inclusion criteria were: adnexal mass detected by ultrasound; surgical removal of the adnexal mass within 180 days after the ultrasound examination; histological confirmation of an adnexal mass; and absence of a synchronous malignant tumor. Patients without digital ultrasound images saved in DICOM format were excluded. The patient cohort was split randomly into training and validation sets using a stratified split with a ratio of 70:30, to preserve the proportion of benign and malignant cases in the two sets. Two machine‐learning models for discriminating between benign and malignant adnexal masses were built using one image per tumor, with 5‐fold cross‐validation for hyperparameter tuning, and were tested on the validation set. The variables used in model building were patient age, serum CA 125 level and the radiomics features that differed significantly between benign and malignant tumors (determined using the Mann–Whitney U ‐test with Benjamini–Hochberg correction) and were not redundant based on Pearson correlation analysis. Histology was the reference standard. We assessed the discriminative performance of the radiomics models using the area under the receiver‐operating‐characteristics curve (AUC) and classification performance using sensitivity and specificity at the optimal cut‐off of each model to classify the mass as malignant, as determined by Youden's index. The diagnostic performance of the developed radiomics models was compared with that of the ADNEX model (AUC, sensitivity and specificity at the 10% risk‐of‐malignancy cut‐off, which is the recommended threshold for clinical use of the ADNEX model). Results In total, 4501 patients met the inclusion criteria. Among these, 2428 patients were excluded owing to an absence of ultrasound images or images unsuitable for radiomics analysis. Overall, a total of 2073 patients were included in the analysis, of whom 803 (38.7%) had a histologically confirmed malignant tumor. In the validation set ( n  = 622, including 254 malignancies), the clinical–radiomics model trained using the eXtreme Gradient Boosting algorithm, including age, serum CA 125 level and 14 selected radiomics features, achieved the highest performance, with an AUC of 0.89 (95% CI, 0.86–0.92), sensitivity of 0.83 (95% CI, 0.79–0.88) and specificity of 0.81 (95% CI, 0.77–0.85) at the optimal cut‐off (31% risk of malignancy, based on Youden's index). At a 10% risk‐of‐malignancy cut‐off, it had a sensitivity of 0.94 (95% CI, 0.91–0.97) and specificity of 0.48 (95% CI, 0.42–0.53). The ADNEX model had an AUC of 0.95 (95% CI, 0.93–0.97), sensitivity of 0.97 (95% CI, 0.95–0.99) and specificity of 0.72 (95% CI, 0.68–0.77) at the 10% risk‐of‐malignancy cut‐off in the validation set. Conclusions Our results support further exploration of radiomics analysis for distinguishing between benign and malignant adnexal masses in larger study populations. Future studies should consider using multiple images per tumor and testing alternative model‐building methods, and should perform external validation to assess the generalizability of the radiomics models. © 2026 The Author(s). Ultrasound in Obstetrics &amp; Gynecology published by John Wiley &amp; Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Prospective Validation of the ADNEX Model for Discrimination Between Benign and Malignant Adnexal Masses in Pregnancy: International Ovarian Tumour Analysis in Pregnancy Study (p-IOTA)

Prospective Validation of the ADNEX Model for discrimination between benign and malignant adnexal masses in pregnancy: International Ovarian Tumour Analysis in pregnancy study (p-IOTA)

Imaging Study in Advanced Ovarian Cancer

The aim of the study is the assessment of tumour sites critical for the achievement of optimal cytoreduction in patients with advanced ovarian cancer using Ultrasound, CT and WB-DWI/MRI. The study uses an equivalence design with a hypothesis that cases with non-resectable disease identified by Index test (Ultrasound, CT and WB-DWI MRI) are equivalent to a portion of cases identified during surgery.