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ObjectivesThis study was conducted in order to establish the joint Society of Abdominal Radiology (SAR) and European Society of Urogenital Radiology (ESUR) guidelines on placenta accreta spectrum (PAS) disorders and propose strategies to standardize image acquisition, interpretation, and reporting for this condition with MRI.MethodsThe published evidence-based data and the opinion of experts were combined using the RAND–UCLA Appropriateness Method and formed the basis for these consensus guidelines. The responses of the experts to questions regarding the details of patient preparation, MRI protocol, image interpretation, and reporting were collected, analyzed, and classified as “recommended” versus “not recommended” (if at least 80% consensus among experts) or uncertain (if less than 80% consensus among experts).ResultsConsensus regarding image acquisition, interpretation, and reporting was determined using the RAND–UCLA Appropriateness Method. The use of a tailored MRI protocol and standardized report was recommended.ConclusionsA standardized imaging protocol and reporting system ensures recognition of the salient features of PAS disorders. These consensus recommendations should be used as a guide for the evaluation of PAS disorders with MRI.Key Points• MRI is a powerful adjunct to ultrasound and provides valuable information on the topography and depth of placental invasion.• Consensus statement proposed a common lexicon to allow for uniformity in MRI acquisition, interpretation, and reporting of PAS disorders.• Seven MRI features, namely intraplacental dark T2 bands, uterine/placental bulge, loss of low T2 retroplacental line, myometrial thinning/disruption, bladder wall interruption, focal exophytic placental mass, and abnormal vasculature of the placental bed, reached consensus and are categorized as “recommended” for diagnosing PAS disorders.

Objectives The recommendations cover indications for MRI examination including acquisition planes, patient preparation, imaging protocol including multi-parametric approaches such as diffusion-weighted imaging (DWI-MR),  dynamic contrast-enhanced imaging (DCE-MR) and standardised reporting. The document also underscores the value of whole-body 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) and highlights potential future methods. Methods In 2019, the ESUR female pelvic imaging working group reviewed the revised 2018 FIGO staging system, the up-to-date clinical management guidelines, and the recent imaging literature. The RAND-UCLA Appropriateness Method (RAM) was followed to develop the current ESUR consensus guidelines following methodological steps: literature research, questionnaire developments, panel selection, survey, data extraction and analysis. Results The updated ESUR guidelines are recommendations based on ≥ 80% consensus among experts. If ≥ 80% agreement was not reached, the action was indicated as optional. Conclusions The present ESUR guidelines focus on the main role of MRI in the initial staging, response monitoring and evaluation of disease recurrence. Whole-body FDG-PET plays an important role in the detection of lymph nodes (LNs) and distant metastases. Key Points • T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence

ObjectivesTo update the 2009 ESUR endometrial cancer guidelines and propose strategies to standardize image acquisition, interpretation and reporting for endometrial cancer staging with MRI.MethodsThe published evidence-based data and the opinion of experts were combined using the RAND-UCLA Appropriateness Method and formed the basis for these consensus guidelines. The responses of the experts to 81 questions regarding the details of patient preparation, MR imaging protocol, image interpretation and reporting were collected, analysed and classified as “RECOMMENDED” versus “NOT RECOMMENDED” (if at least 80% consensus among experts) or uncertain (if less than 80% consensus among experts).ResultsConsensus regarding patient preparation, MR image acquisition, interpretation and reporting was determined using the RAND-UCLA Appropriateness Method. A tailored MR imaging protocol and a standardized report were recommended.ConclusionsThese consensus recommendations should be used as a guide for endometrial cancer staging with MRI.Key points• MRI is recommended for initial staging of endometrial cancer.• MR imaging protocol should be tailored based on the risk of lymph node metastases.• Myometrial invasion is best assessed using combined axial-oblique T2WI, DWI and contrast-enhanced imaging.• The mnemonic “Clinical and MRI Critical TEAM” summarizes key elements of the standardized report.

ObjectiveTo develop imaging guidelines for the MR work-up of female genital tract congenital anomalies (FGTCA).MethodsThese guidelines were prepared based on a questionnaire sent to all members of the European Society of Urogenital Radiology (ESUR) Female Pelvic Imaging Working Group (FPI-WG), critical review of the literature and expert consensus decision.ResultsThe returned questionnaires from 17 different institutions have shown reasonable homogeneity of practice. Recommendations with focus on patient preparation and MR protocol are proposed, as these are key to optimised examinations. Details on MR sequences and planning of uterus-orientated sequences are provided.ConclusionsThe multiplanar capabilities and soft tissue resolution of MRI provide superb characterisation of the wide spectrum of findings in FGTCA. A standardised imaging protocol and method of reporting ensures that the salient features are recognised, contributing to a correct diagnosis and classification of FGTCA, associated anomalies and complications. These imaging guidelines are based on current practice among expert radiologists in the field and incorporate up to date information regarding MR protocols and essentials of recently published classification systems.Key Points• MRI allows comprehensive evaluation of female genital tract congenital anomalies, in a single examination.• A dedicated MRI protocol comprises uterus-orientated sequences and vaginal and renal evaluation.• Integration of classification systems and structured reporting helps in successful communication of the imaging findings.

Background Semiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients’ survival analysis. Methods Training ( n  = 411) and testing ( n  = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic. Results Although the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis. Conclusions The Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival. Trial registration ClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/ , date of registration: 30th June 2017.

Objectives: The aim of this study was to construct a diagnostic model from MRI features to distinguish complex leiomyomas/degenerating fibroids (DF) from leiomyosarcoma (LMS). Methods: A retrospective case-controlled study was performed comparing MRI features of patients with pathologically proven DF or LMS. MRI in 42 patients with DF (control group) and 46 with LMS (study group) was used to generate a diagnostic model. Imaging features reported in the literature to distinguish these two entities were scored for each uterine mass by two radiologists unaware of the histological diagnosis. Inter observer variation and univariate analysis was undertaken. Imaging characteristics identified on univariate analysis were used to build a multi-variable diagnostic model and sensitivity and specificity of this model calculated. Results: Taking the features identified on the univariate analysis, the final diagnostic model was based on AP length (p = .053), intermediate T2 signal (IT2), volume (p = .002), and nodular border (p = .001). When the model was implemented back into the training dataset it demonstrated a sensitivity of 70.7%, and a specificity of 76.2%. The sensitivity and specificity of radiologist suspicion score was 74.7% and 70.4%. In addition, morphological features showed only poor or moderate inter observer agreement at best. Conclusions: Morphological MRI imaging features alone are not sufficient to obviate the need for pathological confirmation prior to non-surgical management of complex uterine mass lesions. Trial registration: IRAS project ID 251778 Protocol number: CCR 4992 REC reference 19/YH/0134 Date of HRA approval: 29.4.19. Advances in knowledge Morphological features of uterine masses on MRI are not sufficient to distinguish leiomyosarcoma from degenerating fibroids.

PurposeCervical cancer metabolic tumour volume (MTV) derived from [18F]-FDG PET/CT has a role in prognostication and therapy planning. There is no standard method of outlining MTV on [18F]-FDG PET/CT. The aim of this study was to assess the optimal method to outline primary cervical tumours on [18F]-FDG PET/CT using MRI-derived tumour volumes as the reference standard.Methods81 consecutive cervical cancer patients with pre-treatment staging MRI and [18F]-FDG PET/CT imaging were included. MRI volumes were compared with different PET segmentation methods. Method 1 measured MTVs at different SUVmax thresholds ranging from 20 to 60% (MTV20-MTV60) with bladder masking and manual adjustment when required. Method 2 created an isocontour around the tumour prior to different SUVmax thresholds being applied. Method 3 used an automated gradient method. Inter-observer agreement of MTV, following manual adjustment when required, was recorded.ResultsFor method 1, the MTV25 and MTV30 were closest to the MRI volumes for both readers (mean percentage change from MRI volume of 2.9% and 13.4% for MTV25 and − 13.1% and − 2.0% for MTV30 for readers 1 and 2). 70% of lesions required manual adjustment at MTV25 compared with 45% at MTV30. There was excellent inter-observer agreement between MTV30 to MTV60 (ICC ranged from 0.898–0.976 with narrow 95% confidence intervals (CIs)) and moderate agreement at lower thresholds (ICC estimates of 0.534 and 0.617, respectively for the MTV20 and MTV25 with wide 95% CIs). Bladder masking was performed in 86% of cases overall. For method 2, excellent correlation was demonstrated at MTV25 and MTV30 (mean % change from MRI volume of −3.9% and − 8.6% for MTV25 and − 16.9% and 19% for MTV30 for readers 1 and 2, respectively). This method also demonstrated excellent ICC across all thresholds with no manual adjustment. Method 3 demonstrated excellent ICC of 0.96 (95% CI 0.94–0.97) but had a mean percentage difference from the MRI volume of − 19.1 and − 18.2% for readers 1 and 2, respectively. 21% required manual adjustment for both readers.ConclusionMTV30 provides the optimal correlation with MRI volume taking into consideration the excellent inter-reader agreement and less requirement for manual adjustment.

A Correction to this paper has been published: 10.1007/s00330-021-08066-7

ObjectiveThe aim of the Female Pelvic Imaging Working Group of the European Society of Urogenital Radiology (ESUR) was to develop imaging staging guidelines for vulvar cancer and to propose standardised MRI protocols and reporting.MethodsThe guidelines recommended from the ESUR in this article resulted from a questionnaire analysis regarding imaging staging of vulvar cancer that was answered by all members of the Female Pelvic Imaging Working Group. Only the answers with an agreement equal to or more than 80% were considered. Additionally, the literature was reviewed to complement and further support our conclusions.ResultsThe critical review of the literature and consensus obtained among experts allows for recommendations regarding imaging staging guidelines, patient preparation, MRI protocol, and a structured MRI report.ConclusionsStandardising image acquisition techniques and MRI interpretation reduces ambiguity and ultimately improves the contribution of radiology to the staging and management of patients with vulvar cancer. Moreover, structured reporting assists with the communication of clinically relevant information to the referring physician.

Ultrasound-based models exist to support the classification of adnexal masses but are subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine learning (ML) model capable of automating the classification of adnexal masses. In this retrospective study, transvaginal ultrasound scan images with linked diagnoses (ultrasound subjective assessment or histology) were extracted and segmented from Imperial College Healthcare, UK (ICH development dataset; n  = 577 masses; 1444 images) and Morgagni-Pierantoni Hospital, Italy (MPH external dataset; n  = 184 masses; 476 images). A segmentation and classification model was developed using convolutional neural networks and traditional radiomics features. Dice surface coefficient (DICE) was used to measure segmentation performance and area under the ROC curve (AUC), F1-score and recall for classification performance. The ICH and MPH datasets had a median age of 45 (IQR 35–60) and 48 (IQR 38–57) years old and consisted of 23.1% and 31.5% malignant cases, respectively. The best segmentation model achieved a DICE score of 0.85 ± 0.01, 0.88 ± 0.01 and 0.85 ± 0.01 in the ICH training, ICH validation and MPH test sets. The best classification model achieved a recall of 1.00 and F1-score of 0.88 (AUC:0.93), 0.94 (AUC:0.89) and 0.83 (AUC:0.90) in the ICH training, ICH validation and MPH test sets, respectively. We have developed an end-to-end radiomics-based model capable of adnexal mass segmentation and classification, with a comparable predictive performance (AUC 0.90) to the published performance of expert subjective assessment (gold standard), and current risk models. Further prospective evaluation of the classification performance of this ML model against existing methods is required.