Magnetic resonance imaging and clinical features of Mayer-Rokitansky-Küster-Hauser syndrome: A 10-year review from a dedicated specialist centre.

OBJECTIVE: To correlate the clinical history with imaging findings of women with Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome. DESIGN: Retrospective cohort study. SETTING: A UK IOTA and ESGO-certified tertiary referral centre for disorders of reproductive development. POPULATION: All patients with a diagnosis of MRKH and who had undergone an MRI pelvis between 1 January 2011 and 31 April 2021 were included. METHODS: MRI images were analysed by specialist gynaecological radiologists. Clinical data was extracted from an electronic patient record system. Statistical analysis was computed in R (version 4.1.2), R base stats package and ggstatsplot (v0.5.0). MAIN OUTCOME MEASURES: Clinical history and predefined imaging features. RESULTS: One hundred and thirty-four patients were included. Median age at MRI was 18 years (10-64 years). Half (48.2%) of women presenting had a history of pain, most often abdominal (84.6%) or vaginal (9.2%). Remnants were identified in 91.8% of women (n = 123). 4.5% of women had imaging features of endometriosis (n = 6). Women with a functional remnants were significantly more likely to experience pain (p < 0.001). Pain history was not strongly associated with ectopic ovarian position. Common gynaecological pathology such as endometriosis, ovarian cysts and fibroids were also identified. CONCLUSIONS: We identify that majority of women with MRKH will have uterine remnants with a connecting fibrous band, and an ectopic ovarian position 44.0% of cases. Abdominal pain was significantly associated with functional remnants on MRI. Further work is required to identify how other gynaecological pathology impacts women with MRKH.

Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features.

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.

Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound.

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.

Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study.

OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times. MATERIALS AND METHODS: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken. Disease sites were manually labeled using Streamline reference standard. Whole-body MRI scans were randomly allocated to training and testing sets. A model for malignant lesion detection was developed based on convolutional neural networks and a 2-stage training strategy. The final algorithm generated lesion probability heat maps. Using a concurrent reader paradigm, 25 radiologists (18 experienced, 7 inexperienced in WB-/MRI) were randomly allocated WB-MRI scans with or without ML support to detect malignant lesions over 2 or 3 reading rounds. Reads were undertaken in the setting of a diagnostic radiology reading room between November 2019 and March 2020. Reading times were recorded by a scribe. Prespecified analysis included sensitivity, specificity, interobserver agreement, and reading time of radiology readers to detect metastases with or without ML support. Reader performance for detection of the primary tumor was also evaluated. RESULTS: Four hundred thirty-three evaluable WB-MRI scans were allocated to algorithm training (245) or radiology testing (50 patients with metastases, from primary 117 colon [n = 117] or lung [n = 71] cancer). Among a total 562 reads by experienced radiologists over 2 reading rounds, per-patient specificity was 86.2% (ML) and 87.7% (non-ML) (-1.5% difference; 95% confidence interval [CI], -6.4%, 3.5%; P = 0.39). Sensitivity was 66.0% (ML) and 70.0% (non-ML) (-4.0% difference; 95% CI, -13.5%, 5.5%; P = 0.344). Among 161 reads by inexperienced readers, per-patient specificity in both groups was 76.3% (0% difference; 95% CI, -15.0%, 15.0%; P = 0.613), with sensitivity of 73.3% (ML) and 60.0% (non-ML) (13.3% difference; 95% CI, -7.9%, 34.5%; P = 0.313). Per-site specificity was high (>90%) for all metastatic sites and experience levels. There was high sensitivity for the detection of primary tumors (lung cancer detection rate of 98.6% with and without ML [0.0% difference; 95% CI, -2.0%, 2.0%; P = 1.00], colon cancer detection rate of 89.0% with and 90.6% without ML [-1.7% difference; 95% CI, -5.6%, 2.2%; P = 0.65]). When combining all reads from rounds 1 and 2, reading times fell by 6.2% (95% CI, -22.8%, 10.0%) when using ML. Round 2 read-times fell by 32% (95% CI, 20.8%, 42.8%) compared with round 1. Within round 2, there was a significant decrease in read-time when using ML support, estimated as 286 seconds (or 11%) quicker ( P = 0.0281), using regression analysis to account for reader experience, read round, and tumor type. Interobserver variance suggests moderate agreement, Cohen κ = 0.64; 95% CI, 0.47, 0.81 (with ML), and Cohen κ = 0.66; 95% CI, 0.47, 0.81 (without ML). CONCLUSIONS: There was no evidence of a significant difference in per-patient sensitivity and specificity for detecting metastases or the primary tumor using concurrent ML compared with standard WB-MRI. Radiology read-times with or without ML support fell for round 2 reads compared with round 1, suggesting that readers familiarized themselves with the study reading method. During the second reading round, there was a significant reduction in reading time when using ML support.

Prediction of Deep Myometrial Infiltration, Clinical Risk Category, Histological Type, and Lymphovascular Space Invasion in Women with Endometrial Cancer Based on Clinical and T2-Weighted MRI Radiomic Features.

PURPOSE: To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images. METHODS: A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models. RESULTS: Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively. CONCLUSION: It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods.

An Integrated Clinical-MR Radiomics Model to Estimate Survival Time in Patients With Endometrial Cancer.

BACKGROUND: Determination of survival time in women with endometrial cancer using clinical features remains imprecise. Features from MRI may improve the survival estimation allowing improved treatment planning. PURPOSE: To identify clinical features and imaging signatures on T2-weighted MRI that can be used in an integrated model to estimate survival time for endometrial cancer subjects. STUDY TYPE: Retrospective. POPULATION: Four hundred thirteen patients with endometrial cancer as training (N = 330, 66.41 ± 11.42 years) and validation (N = 83, 67.60 ± 11.89 years) data and an independent set of 82 subjects as testing data (63.26 ± 12.38 years). FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T scanners with sagittal T2-weighted spin echo sequence. ASSESSMENT: Tumor regions were manually segmented on T2-weighted images. Features were extracted from segmented masks, and clinical variables including age, cancer histologic grade and risk score were included in a Cox proportional hazards (CPH) model. A group least absolute shrinkage and selection operator method was implemented to determine the model from the training and validation datasets. STATISTICAL TESTS: A likelihood-ratio test and decision curve analysis were applied to compare the models. Concordance index (CI) and area under the receiver operating characteristic curves (AUCs) were calculated to assess the model. RESULTS: Three radiomic features (two image intensity and volume features) and two clinical variables (age and cancer grade) were selected as predictors in the integrated model. The CI was 0.797 for the clinical model (includes clinical variables only) and 0.818 for the integrated model using training and validation datasets, the associated mean AUC value was 0.805 and 0.853. Using the testing dataset, the CI was 0.792 and 0.882, significantly different and the mean AUC was 0.624 and 0.727 for the clinical model and integrated model, respectively. DATA CONCLUSION: The proposed CPH model with radiomic signatures may serve as a tool to improve estimated survival time in women with endometrial cancer. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Diagnostic Accuracy of FEC-PET/CT, FDG-PET/CT, and Diffusion-Weighted MRI in Detection of Nodal Metastases in Surgically Treated Endometrial and Cervical Carcinoma.

PURPOSE: Preoperative nodal staging is important for planning treatment in cervical cancer and endometrial cancer, but remains challenging. We compare nodal staging accuracy of 18F-ethyl-choline-(FEC)-PET/CT, 18F-fluoro-deoxy-glucose-(FDG)-PET/CT, and diffusion-weighted-MRI (DW-MRI) with conventional morphologic MRI. EXPERIMENTAL DESIGN: A prospective, multicenter observational study of diagnostic accuracy for nodal metastases was undertaken in 5 gyne-oncology centers. FEC-PET/CT, FDG-PET/CT, and DW-MRI were compared with nodal size and morphology on MRI. Reference standard was strictly correlated nodal histology. Eligibility included operable cervical cancer stage ≥ 1B1 or endometrial cancer (grade 3 any stage with myometrial invasion or grade 1-2 stage ≥ II). RESULTS: Among 162 consenting participants, 136 underwent study DW-MRI and FDG-PET/CT and 60 underwent FEC-PET/CT. In 118 patients, 267 nodal regions were strictly correlated at histology (nodal positivity rate, 25%). Sensitivity per patient (n = 118) for nodal size, morphology, DW-MRI, FDG- and FEC-PET/CT was 40%*, 53%, 53%, 63%*, and 67% for all cases (*, P = 0.016); 10%, 10%, 20%, 30%, and 25% in cervical cancer (n = 40); 65%, 75%, 70%, 80% and 88% in endometrial cancer (n = 78). FDG-PET/CT outperformed nodal size (P = 0.006) and size ratio (P = 0.04) for per-region sensitivity. False positive rates were all <10%. CONCLUSIONS: All imaging techniques had low sensitivity for detection of nodal metastases and cannot replace surgical nodal staging. The performance of FEC-PET/CT was not statistically different from other techniques that are more widely available. FDG-PET/CT had higher sensitivity than size in detecting nodal metastases. False positive rates were low across all methods. The low false positive rate demonstrated by FDG-PET/CT may be helpful in arbitration of challenging surgical planning decisions.

Ovary: MRI characterisation and O-RADS MRI.

Ultrasound has a high specificity for the diagnosis of a benign lesion in cases of classic appearing simple cyst, hemorrhagic cyst, endometrioma and dermoid. However, ultrasound can sometimes be limited for definitive characterisation and risk stratification of other types of lesions, including those with echogenic content that may appear solid, with or without blood flow. Frequently, MRI can be used to further characterise these types of lesions, due to its ability to distinguish solid tissue from non-tissue solid components such as fat, blood, or debris. Incorporating the MR imaging into the evaluation of adnexal lesions can improve diagnostic certainty and guide clinical management potentially avoiding inappropriate surgery for benign lesions and expediting appropriate treatment for malignant lesions, particularly in the females with sonographically indeterminate adnexal lesions.

Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018.

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.

Adnexal Torsion: Review of Radiologic Appearances.

Adnexal torsion is the twisting of the ovary, and often of the fallopian tube, on its ligamental supports, resulting in vascular compromise and ovarian infarction. The definitive management is surgical detorsion, and prompt diagnosis facilitates preservation of the ovary, which is particularly important because this condition predominantly affects premenopausal women. The majority of patients present with severe acute pain, vomiting, and a surgical abdomen, and the diagnosis is often made clinically with corroborative US. However, the symptoms of adnexal torsion can be variable and nonspecific, making an early diagnosis challenging unless this condition is clinically suspected. When adnexal torsion is not clinically suspected, CT or MRI may be performed. Imaging has an important role in identifying adnexal torsion and accelerating definitive treatment, particularly in cases in which the diagnosis is not an early consideration. Several imaging features are characteristic of adnexal torsion and can be seen to varying degrees across different modalities: a massive, edematous ovary migrated to the midline; peripherally displaced ovarian follicles resembling a string of pearls; a benign ovarian lesion acting as a lead mass; surrounding inflammatory change or free fluid; and the uterus pulled toward the side of the affected ovary. Hemorrhage and absence of internal flow or enhancement are suggestive of ovarian infarction. Pertinent conditions to consider in the differential diagnosis are a ruptured hemorrhagic ovarian cyst, massive ovarian edema, ovarian hyperstimulation, and a degenerating leiomyoma. Online supplemental material is available for this article. ©RSNA, 2021.

Optimal method for metabolic tumour volume assessment of cervical cancers with inter-observer agreement on [18F]-fluoro-deoxy-glucose positron emission tomography with computed tomography.

PURPOSE: Cervical 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. METHODS: 81 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. RESULTS: For 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. CONCLUSION: MTV30 provides the optimal correlation with MRI volume taking into consideration the excellent inter-reader agreement and less requirement for manual adjustment.

2018 FIGO Staging Classification for Cervical Cancer: Added Benefits of Imaging.

Cervical cancer is the fourth most common cancer in women of all ages worldwide. The disease is staged using the International Federation of Gynecology and Obstetrics (FIGO) system, which was updated in 2018. The authors explain the key changes from the 2009 version and the rationale behind them. The changes have been made to reflect common clinical practice, differentiate prognostic outcomes, and guide treatment stratification. Treatment options are dependent on the stage of disease and include fertility-sparing and non-fertility-sparing surgical options as well as chemoradiotherapy for locally advanced disease. The updated FIGO staging gives added importance to MRI as a method of accurately measuring tumor size and depicting the presence of parametrial involvement. With the inclusion of lymph node involvement in the updated 2018 FIGO staging, cross-sectional imaging-and in particular, fluorodeoxyglucose PET/CT-has an increasing role in the depiction of nodal disease. Understanding the radiologic techniques used, the literature supporting them, and common imaging pitfalls ensures accurate staging of disease and optimization of treatment. ©RSNA, 2020 See discussion on this article by Javitt (pp 1823-1824).

Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) Score for Risk Stratification of Sonographically Indeterminate Adnexal Masses.

Importance: Approximately one-quarter of adnexal masses detected at ultrasonography are indeterminate for benignity or malignancy, posing a substantial clinical dilemma. Objective: To validate the accuracy of a 5-point Ovarian-Adnexal Reporting Data System Magnetic Resonance Imaging (O-RADS MRI) score for risk stratification of adnexal masses. Design, Setting, and Participants: This multicenter cohort study was conducted between March 1, 2013, and March 31, 2016. Among patients undergoing expectant management, 2-year follow-up data were completed by March 31, 2018. A routine pelvic MRI was performed among consecutive patients referred to characterize a sonographically indeterminate adnexal mass according to routine diagnostic practice at 15 referral centers. The MRI score was prospectively applied by 2 onsite readers and by 1 reader masked to clinical and ultrasonographic data. Data analysis was conducted between April and November 2018. Main Outcomes and Measures: The primary end point was the joint analysis of true-negative and false-negative rates according to the MRI score compared with the reference standard (ie, histology or 2-year follow-up). Results: A total of 1340 women (mean [range] age, 49 [18-96] years) were enrolled. Of 1194 evaluable women, 1130 (94.6%) had a pelvic mass on MRI with a reference standard (surgery, 768 [67.9%]; 2-year follow-up, 362 [32.1%]). A total of 203 patients (18.0%) had at least 1 malignant adnexal or nonadnexal pelvic mass. No invasive cancer was assigned a score of 2. Positive likelihood ratios were 0.01 for score 2, 0.27 for score 3, 4.42 for score 4, and 38.81 for score 5. Area under the receiver operating characteristic curve was 0.961 (95% CI, 0.948-0.971) among experienced readers, with a sensitivity of 0.93 (95% CI, 0.89-0.96; 189 of 203 patients) and a specificity of 0.91 (95% CI, 0.89-0.93; 848 of 927 patients). There was good interrater agreement among both experienced and junior readers (κ = 0.784; 95% CI, 0.743-0824). Of 580 of 1130 women (51.3%) with a mass on MRI and no specific gynecological symptoms, 362 (62.4%) underwent surgery. Of them, 244 (67.4%) had benign lesions and a score of 3 or less. The MRI score correctly reclassified the mass origin as nonadnexal with a sensitivity of 0.99 (95% CI, 0.98-0.99; 1360 of 1372 patients) and a specificity of 0.78 (95% CI, 0.71-0.85; 102 of 130 patients). Conclusions and Relevance: In this study, the O-RADS MRI score was accurate when stratifying the risk of malignancy in adnexal masses.

Superficial myofibroblastoma of the genital tract: a case report of the imaging findings.

Superficial angiomyofibroblastomas are mesenchymal tumours that occur in the genital tract and are well described pathologically. This case report reviews the imaging appearances and highlights the MRI findings, which have not been previously described. We describe the occurrence of this lesion in a vaginal cyst, which to the authors' knowledge, has also not been previously described. The histological findings are also presented here.

Endometrial Cancer MRI staging: Updated Guidelines of the European Society of Urogenital Radiology.

OBJECTIVES: To update the 2009 ESUR endometrial cancer guidelines and propose strategies to standardize image acquisition, interpretation and reporting for endometrial cancer staging with MRI. METHODS: The 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). RESULTS: Consensus 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. CONCLUSIONS: These 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.

Anti-tumour activity of a first-in-class agent NUC-1031 in patients with advanced cancer: results of a phase I study.

BACKGROUND: Gemcitabine is used to treat a wide range of tumours, but its efficacy is limited by cancer cell resistance mechanisms. NUC-1031, a phosphoramidate modification of gemcitabine, is the first anti-cancer ProTide to enter the clinic and is designed to overcome these key resistance mechanisms. METHODS: Sixty-eight patients with advanced solid tumours who had relapsed after treatment with standard therapy were recruited to a dose escalation study to determine the recommended Phase II dose (RP2D) and assess the safety of NUC-1031. Pharmacokinetics and anti-tumour activity was also assessed. RESULTS: Sixty-eight patients received treatment, 50% of whom had prior exposure to gemcitabine. NUC-1031 was well tolerated with the most common Grade 3/4 adverse events of neutropaenia, lymphopaenia and fatigue occurring in 13 patients each (19%). In 49 response-evaluable patients, 5 (10%) achieved a partial response and 33 (67%) had stable disease, resulting in a 78% disease control rate. Cmax levels of the active intracellular metabolite, dFdCTP, were 217-times greater than those reported for equimolar doses of gemcitabine, with minimal toxic metabolite accumulation. The RP2D was determined as 825 mg/m2 on days 1, 8 and 15 of a 28-day cycle. CONCLUSIONS: NUC-1031 was well tolerated and demonstrated clinically significant anti-tumour activity, even in patients with prior gemcitabine exposure and in cancers not traditionally perceived as gemcitabine-responsive.

What's New in Imaging for Gynecologic Cancer?

Magnetic resonance imaging (MRI) is the optimal modality for local staging of gynecological tumors. Advances in functional MRI with diffusion-weighted and dynamic contrast-enhanced sequences provide more detailed information regarding tumor cellularity, vascularity, and viability. Fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) now has an established role in imaging for gynecological cancers, particularly staging of locally advanced cervical cancers and pre-salvage exenterative therapy in relapsed gynecologic tumors. Novel PET tracers, targeting other aspects of tumor biology, are being evaluated although none are currently in routine clinical use. New PET/MR scanners have the potential to combine the strengths of both modalities in one sitting. This review covers advances in gynecologic imaging concentrating on cervical, endometrial, and ovarian cancers.

Subfertility: What the Radiologist Needs to Know.

The role of imaging in subfertility is well established but is changing. In addition to traditional fertility assessments, there is an emerging role for the radiologist. The role of imaging in fertility-restoring procedures in benign disease and congenital malformations is evolving, and there is a growing need for accurate identification of young candidates suitable for fertility-preserving surgery in the oncologic setting. To facilitate this developing role, knowledge of the key imaging modalities used and potential therapeutic applications is important for accurate diagnosis and interpretation by the radiologist. ©RSNA, 2017.

FDG PET/CT Pitfalls in Gynecologic and Genitourinary Oncologic Imaging.

The role of whole-body positron emission tomography (PET)/computed tomography (CT) with fluorodeoxyglucose ( FDG fluorodeoxyglucose ) is now established in the assessment of many gynecologic and genitourinary malignant tumors. FDG fluorodeoxyglucose PET/CT has been widely adopted for staging assessments in patients with suspected advanced disease, in cases of suspected disease recurrence, and for determining prognosis in a number of malignancies. A number of pitfalls are commonly encountered when reviewing FDG fluorodeoxyglucose PET/CT scans in gynecologic and genitourinary cases; these pitfalls can be classified into those that yield potential false-positive or false-negative results. Potential false positives include physiologic uptake of FDG fluorodeoxyglucose by the endometrium and ovaries in premenopausal patients, physiologic renal excretion of FDG fluorodeoxyglucose into the ureters and the urinary bladder, and increased FDG fluorodeoxyglucose activity in benign conditions such as uterine fibroids, pelvic inflammatory disease, and benign endometriotic cysts. Potential false negatives include low-level FDG fluorodeoxyglucose uptake by necrotic, mucinous, cystic, or low-grade tumors and the masking of serosal and peritoneal disease by adjacent physiologic bowel or bladder activity. In addition, there are inherent technical limitations-such as motion artifact (from respiratory motion and bowel peristalsis) and the limited spatial resolution of PET-that may limit the assessment of small-volume malignant disease. Knowledge of the key imaging features of physiologic and nonphysiologic FDG fluorodeoxyglucose uptake, in addition to understanding the principles of adequate patient preparation and PET scanning protocols, is important for accurate interpretation of gynecologic and genitourinary oncologic FDG fluorodeoxyglucose PET/CT studies. ©RSNA, 2017.