MR imaging of ovarian masses: classification and differential diagnosis

High-throughput viable circulating tumor cell isolation using tapered-slit membrane filter-based chipsets in the differential diagnosis of ovarian tumors

OBJECTIVE

To evaluate the diagnostic performance of circulating tumor cells (CTCs) using tapered-slit membrane filter (TSF)-based chipsets for the differential diagnosis of adnexal tumors.

METHODS

A total of 230 women with indeterminate adnexal tumors were prospectively enrolled. The sensitivity, specificity, and accuracy of the CTC-detecting chipsets were analyzed according to postoperative pathological results and compared with those of cancer antigen (CA)-125 and imaging tests.

RESULTS

Eighty-one (40.3%) benign tumors, 31 (15.4%) borderline tumors, and 89 (44.3%) ovarian cancers were pathologically confirmed. The sensitivity, specificity, and accuracy of CTC-detecting chipsets (75.3%, 58.0%, and 67.1%) for differentiating ovarian cancer from benign tumors were similar to CA-125 (78.7%, 53.1%, and 66.5%), but lower than CT/MRI (94.2%, 77.9%, and 86.5%). "CTC or CA125" showed increased sensitivity (91.0%) and "CTC and CA-125" revealed increased specificity (77.8%), comparable to CT/MRI. CTC detection rates in stage I/II and stage III/IV ovarian cancers were 69.6% and 81.4%, respectively. The sensitivity to detect high-grade serous (HGS) cancer from benign tumors (84.6%) was higher than that to detect non-HGS cancers (68.0%).

CONCLUSION

Although the diagnostic performance of the TSF platform to differentiate between ovarian cancer and benign tumors did not yield significant results, the combination of CTC and CA-125 showed promising potential in the diagnostic accuracy of ovarian cancer.

O-RADS MRI scoring system: key points for correct application in inexperienced hands

OBJECTIVES

To evaluate the efficacy of the O-RADS MRI criteria in the stratification of risk of malignancy of solid or sonographically indeterminate ovarian masses and assess the interobserver agreement of this classification between experienced and inexperienced radiologists.

METHODS

This single-centre retrospective study included patients from 2019 to 2022 with sonographically indeterminate or solid ovarian masses who underwent MRI with a specific protocol for characterisation according to O-RADS MRI specifications. Each study was evaluated using O-RADS lexicon by two radiologists, one with 17 years of experience in gynaecological radiology and another with 4 years of experience in general radiology. Findings were classified as benign, borderline, or malignant according to histology or stability over time. Diagnostic performance and interobserver agreement were assessed.

RESULTS

A total of 183 patients with US indeterminate or solid adnexal masses were included. Fifty-seven (31%) did not have ovarian masses, classified as O-RADS 1. The diagnostic performance for scores 2-5 was excellent with a sensitivity, specificity, PPV, and NPV of 97.4%, 100%, 96.2%, and 100%, respectively by the experienced radiologist and 96.1%, 92.0%, 93.9%, and 94.8% by the inexperienced radiologist. Interobserver concordance was very high (Kappa index 0.92). Almost all the misclassified cases were due to misinterpretation of the classification similar to reports in the literature.

CONCLUSION

The diagnostic performance of O-RADS MRI determined by either experienced or inexperienced radiologists is excellent, facilitating decision-making with high diagnostic accuracy and high reproducibility. Knowledge of this classification and use of assessment tools could avoid frequent errors due to misinterpretation.

CRITICAL RELEVANCE STATEMENT

Up to 31% of ovarian masses are considered indeterminate by transvaginal US and 32% of solid lesions considered malignant by transvaginal US are benign. The O-RADs MRI accurately classifies these masses, even when used by inexperienced radiologists, thereby avoiding incorrect surgical approaches.

KEY POINTS

• O-RADS MRI accurately classifies indeterminate and solid ovarian masses by ultrasound. • There is excellent interobserver agreement between experienced and non-experienced radiologists. • O-RADS MRI is a helpful tool to assess clinical decision-making in ovarian tumours.

O-RADS MRI SCORE: An Essential First-Step Tool for the Characterization of Adnexal Masses

The ovarian-adnexal reporting and data system on magnetic resonance imaging (O-RADS MRI) score is now a well-established tool to characterize pelvic gynecological masses based on their likelihood of malignancy. The main added value of O-RADS MRI over O-RADS US is to correctly reclassify lesions that were considered suspicious on US as benign on MRI. The crucial issue when characterizing an adnexal mass is to determine the presence/absence of solid tissue and thus need to perform gadolinium injection. O-RADS MR score was built on a multivariate analysis and must be applied as a step-by-step analysis: 1) Is the mass an adnexal mass? 2) Is there an associated peritoneal carcinomatosis? 3) Is there any significant amount of fatty content? 4) Is there any wall enhancement? 5) Is there any internal enhancement? 6) When an internal enhancement is detected, does the internal enhancement correspond to solid tissue or not? 7) Is the solid tissue malignant? With its high value to distinguish benign from malignant adnexal masses and its high reproducibility, the O-RADS MRI score could be a valuable tool for timely referral of a patient to an expert center for the treatment of ovarian cancers. Finally, to make a precise diagnosis allowing optimal personalized treatment, the radiologist in gynecological imaging will combine the O-RADS MRI score with many other clinical, biological, and other MR criteria to suggest a pathological hypothesis. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.

Clinical Utility of Whole-Genome Analysis as One-for-All Test for Breast Cancer: A Case Series

Introduction

Breast cancer exhibits vast genomic diversity, leading to varied clinical manifestations. Integrating molecular subtyping with in-depth genomic profiling is pivotal for informed treatment choices and prognostic insights. Whole-genome clinical analysis provides a holistic view of genome-wide variations, capturing structural changes and affirming tumor suppressor gene loss of heterozygosity.

Case Presentation

Here we detail four unique breast cancer cases from Seoul St. Mary's Hospital, highlighting the actionable benefits and clinical value of whole-genome sequencing (WGS). As an all-in-one test, WGS demonstrates significant clinical utility in these cases, including: (1) detecting homologous recombination deficiency with underlying somatic causal variants (case 1), (2) distinguishing double primary cancer from metastasis (case 2), (3) uncovering microsatellite instability (case 3), and (4) identifying rare germline pathogenic variants in TP53 gene (case 4). Our observations underscore the enhanced clinical relevance of WGS-based testing beyond pinpointing a few driver mutations in conventional targeted panel sequencing platforms.

Conclusion

With genomic advancements and decreasing sequencing costs, WGS stands out as a transformative tool in oncology, paving the way for personalized treatment plans rooted in individual genetic blueprints.

MR imaging findings of ovarian lymphoma: differentiation from other solid ovarian tumors

PURPOSE

To evaluate magnetic resonance imaging (MRI) findings for distinguishing ovarian lymphomas from other solid ovarian tumors.

METHODS

This retrospective multicenter study included 14 women (median age, 46.5 years; range, 26-81 years) with surgically proven ovarian lymphoma and 28 women with solid ovarian tumors other than lymphoma. We conducted a subjective image analysis of factors including laterality, shape, composition, T2 signal intensity (SI), heterogeneity, diffusion restriction, enhancement, and presence of peripheral follicles. A generalized estimating equation was used to identify MRI findings that could be used to distinguish ovarian lymphomas from other solid ovarian tumors. Diagnostic performance of the identified MRI findings was assessed using the area under the receiver-operating characteristic curve (AUC).

RESULTS

Ovarian lymphoma more frequently showed homogeneous high SI on T2-weighted imaging (81.8% vs. 19.4%, P < 0.001) and peripheral ovarian follicles (40.9% vs. 8.3%, P = 0.01) than other ovarian solid tumors did. Bilaterality, shape, size, diffusion restriction, and enhancement did not differ between the two groups (P > 0.05 for all). Homogeneous high SI on T2-weighted imaging was the only independent MRI finding (OR = 15.19; 95% CI 3.15-73.33; P = 0.001) in the multivariable analysis. Homogeneous high SI on T2-weighted imaging yielded an AUC of 0.82 with a sensitivity of 81.8% and specificity of 80.6% in distinguishing ovarian lymphomas from other solid ovarian tumors.

CONCLUSION

Homogeneous high signal intensity on T2-weighted imaging was helpful in distinguishing ovarian lymphomas from other solid ovarian tumors. Peripheral ovarian follicles might be an additional clue that suggests a diagnosis of ovarian lymphoma.

Chronic Pelvic Pain: Role of Imaging in the Diagnosis and Management

Chronic pelvic pain (CPP) in women is not uncommon, and it may be difficult to identify the exact cause difficult to manage. It is major health problem for women that affects the quality of their daily lives. The etiology of chronic pelvic pain may be of gynecological or non-gynecological origin and associated with several predisposing and precipitating factors. Psychological and social factors also contribute to the syndrome of CPP and must be evaluated before managing these patients. Due to multifactorial etiology, CPP needs a multidisciplinary approach for diagnosis and management. A detailed history and physical examination supported by appropriate laboratory tests and imaging are the keys to diagnosis. In this paper, the role of imaging in diagnosis and management of CPP is reviewed. Imaging findings should be correlated with detailed clinical examination findings as there are imaging findings that may be unrelated and not the cause of CPP in a particular patient, imaging findings should be correlated with the clinical circumstances.

Coexisting ovarian serous cystadenoma with fibroma: A very unusual combination

Surface epithelial neoplasms are the most common ovarian tumors, constituting around 60% of all ovarian malignancies. They are classified as benign, borderline, and malignant. Ovarian cystadenomas are common benign epithelial neoplasms which carry an excellent prognosis. Ovarian thecoma-fibroma groups are uncommon sex cord-stromal neoplasms, constituting 1.0%-4.0% of all ovarian tumors. Most of them are benign and often found in postmenopausal patients. Combination tumors in the ovary are known. The most common combination is mucinous cystadenoma which occurs in association with Brenner tumor, mature cystic teratoma, Sertoli-Leydig cell tumor, or even a serous cystadenoma. A combination of surface epithelial and thecoma-fibroma group is very rarely encountered. A case of one such combination of serous cystadenoma and fibroma of the ovary is being presented here in a postmenopausal woman.

Imaging of pediatric ovarian tumors: A COG Diagnostic Imaging Committee/SPR Oncology Committee White Paper

Ovarian tumors in children are uncommon. Like those arising in the adult population, they may be broadly divided into germ cell, sex cord, and surface epithelium subtypes; however, germ cell tumors comprise the majority of lesions in children, whereas tumors of surface epithelial origin predominate in adults. Diagnostic workup, including the use of imaging, requires an approach that often differs from that required in an adult. This paper offers consensus recommendations for imaging of pediatric patients with a known or suspected primary ovarian malignancy at diagnosis and during follow-up.

Clear Cell Borderline Tumor of the Ovary: A Case Report

Clear cell borderline ovarian tumor (CCBOT) is quite rare, and only a few cases of CCBOT have been reported. Unlike most borderline ovarian tumors, CCBOTs appear solid because they are almost always pathologically adenofibromatous. Herein, we report the MRI findings of a CCBOT discovered in a 22-year-old female.

Machine learning combined with radiomics and deep learning features extracted from CT images: a novel AI model to distinguish benign from malignant ovarian tumors

BACKGROUND

To develop an artificial intelligence (AI) model with radiomics and deep learning (DL) features extracted from CT images to distinguish benign from malignant ovarian tumors.

METHODS

We enrolled 149 patients with pathologically confirmed ovarian tumors. A total of 185 tumors were included and divided into training and testing sets in a 7:3 ratio. All tumors were manually segmented from preoperative contrast-enhanced CT images. CT image features were extracted using radiomics and DL. Five models with different combinations of feature sets were built. Benign and malignant tumors were classified using machine learning (ML) classifiers. The model performance was compared with five radiologists on the testing set.

RESULTS

 Among the five models, the best performing model is the ensemble model with a combination of radiomics, DL, and clinical feature sets. The model achieved an accuracy of 82%, specificity of 89% and sensitivity of 68%. Compared with junior radiologists averaged results, the model had a higher accuracy (82% vs 66%) and specificity (89% vs 65%) with comparable sensitivity (68% vs 67%). With the assistance of the model, the junior radiologists achieved a higher average accuracy (81% vs 66%), specificity (80% vs 65%), and sensitivity (82% vs 67%), approaching to the performance of senior radiologists.

CONCLUSIONS

 We developed a CT-based AI model that can differentiate benign and malignant ovarian tumors with high accuracy and specificity. This model significantly improved the performance of less-experienced radiologists in ovarian tumor assessment, and may potentially guide gynecologists to provide better therapeutic strategies for these patients.

Surgical Treatment of a Rare Case of Ovarian Fibroma Associated With Elevated CA125 Levels in a Patient of Reproductive Age: A Case Report

Small ovarian fibromas (< 10cm) associated with elevated serum CA125 levels are rarely encountered, particularly in women of reproductive age. We report a rare case diagnosed in a 35-year-old patient after adnexectomy for a solid ovarian mass of approximately 5cm in maximum diameter, accompanied by elevated serum CA125 levels. In preoperative evaluation, no signs of inflammation from the genital tract were found, and no medical history of endometriosis, uterine leiomyomas, or non-gynecological cancer was reported. Intraoperative frozen section biopsy of surgical specimen obtained from the ovarian tumor had negative evaluation for malignancy. Histological examination of the surgical specimen confirmed the diagnosis of ovarian fibroma. The postoperative course was uneventful. Two months after surgery, the blood serum CA125 levels were within normal ranges. The patient is assessed at regular intervals in the gynecology outpatient clinic. In this paper, based on the data of the modern literature, a brief review of this rare nosological entity is made.

MRI Appearance of a Giant Ovarian Sero-mucinous Cystadenofibroma Mimicking Ascites. A Case Report and Brief Literature Review

Introduction: Giant ovarian cystadenofibromas are rare, mostly benign tumors. In the early stages, they are asymptomatic; however, as they grow in size, they begin to produce symptoms, most often due to the compressive effects they exert on surrounding structures. In the early stages, they are frequently diagnosed by ultrasonography, but complicated cases or cystadenofibromas that reach giant dimensions are ideally evaluated by magnetic resonance imaging (MRI) to establish a therapeutic surgical decision that is as safe as possible for the patient.

Case report: We present the case of a 49-year-old perimenopausal patient without vaginal bleeding or other gynecological symptoms who presented to the hospital with abdominal pain and abdominal distension with increasing intensity. Ultrasound examination revealed the presence of a high volume of fluid in the abdomen, and MRI and histopathological examination confirmed the diagnosis of a giant left ovarian type III seromucinous cystadenofibroma. The patient was treated surgically, with favorable postoperative evolution.

Conclusion: Giant cystadenofibromas are rare clinical entities that must always be considered in the differential diagnosis of an abdominopelvic pathology in middle-aged female patients and should ideally be investigated by MRI to accurately define their origin, characteristics, and local invasion.

Acute pelvic pain: A pictorial review with magnetic resonance imaging

Acute uterine emergencies constitute both obstetric and gynecologic conditions. The superior image resolution, superior soft-tissue characterization, and lack of ionizing radiation make magnetic resonance imaging (MRI) preferable over ultrasonography (USG) and computed tomography (CT) in investigating uterine emergencies. Although USG is the first-line imaging modality and is easily accessible, it has limitations. USG is an operator dependent and limited by patient factors such as obesity and muscle atrophy. CT is limited by its risk of teratogenicity in pregnant females, poor tissue differentiation, and radiation effect. The non-specific findings on CT may lead to misinterpretation of the pathology. MRI overcomes all these limitations and is emerging as the most crucial imaging modality in the emergency room (ER). The evolving 3D MR sequences further reduce the acquisition times, expanding its ER role. Although MRI is not the first-line imaging modality, it is a problem-solving tool when the ultrasound and CT are inconclusive. This pictorial review discusses the various MRI techniques used in uterine imaging and the appearances of distinct etiologies of uterine emergencies across different MRI sequences.

Magnetic Resonance Imaging of Acute Abdominal Pain in the Pregnant Patient

Evaluation of a pregnant patient presenting with acute abdominal pain can be challenging to accurately diagnose for a variety of reasons, and particularly late in pregnancy. Noncontrast MR remains a safe and accurate diagnostic imaging modality for the pregnant patient presenting with acute abdominal pain, following often an initially inconclusive ultrasound examination, and can be used in most settings to avoid the ionizing radiation exposure of a computed tomography scan. Pathologic processes discussed in this article include some of the more common gastrointestinal, hepatobiliary, genitourinary, and gynecologic causes of abdominal pain occurring in pregnancy, as well as traumatic injuries.

Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors

Objective

To evaluate the utility of apparent diffusion coefficient (ADC) histogram analysis to differentiate between three types of solid ovarian tumors: granulosa cell tumors (GCTs) of the ovary, ovarian fibromas, and high-grade serous ovarian carcinomas (HGSOCs).

Methods

The medical records of 11 patients with GCTs of the ovary (regions of interest [ROI-cs], 137), 61 patients with ovarian fibromas (ROI-cs, 161), and 14 patients with HGSOCs (ROI-cs, 113) confirmed at surgery and histology who underwent diffusion-weighted imaging were retrospectively reviewed. Histogram parameters of ADC maps (ADCmean, ADCmax, ADCmin) were estimated and compared using the Kruskal-WallisH test and Mann-Whitney U test. The area under the curve of receiver operating characteristic curves was used to assess the diagnostic performance of ADC parameters for solid ovarian tumors.

Results

There were significant differences in ADCmean, ADCmax and ADCmin values between GCTs of the ovary, ovarian fibromas, and HGSOCs. The cutoff ADCmean value for differentiating a GCT of the ovary from an ovarian fibroma was 0.95×10^-3 mm²/s, for differentiating a GCT of the ovary from an HGSOC was 0.69×10^-3 mm²/s, and for differentiating an ovarian fibroma from an HGSOC was 1.24×10^-3 mm²/s.

Conclusion

ADCmean derived from ADC histogram analysis provided quantitative information that allowed accurate differentiation of GCTs of the ovary, ovarian fibromas, and HGSOCs before surgery.

Discriminating Between Benign and Malignant Solid Ovarian Tumors Based on Clinical and Radiomic Features of MRI

RATIONALE AND OBJECTIVES

To develop and validate a combined model integrating clinical and radiomic features to non-invasive discriminate between the benign and malignant solid ovarian tumors.

MATERIALS AND METHODS

A total of 148 patients with 156 solid ovarian tumors (86 benign and 70 malignant tumors) were included in this study. The dataset was split into the training and the test set with a ratio of 8:2 using stratified random sampling. 12 clinical features and 1612 radiomic features were extracted from each tumor. These features were selected by least absolute shrinkage and selection operator (Lasso). Three classification models were built using extreme gradient boosting (XGB) algorithm: clinical model, radiomic model, combined model. The area under the receiver operating characteristic curve (AUC), accuracy, precision and sensitivity were analyzed to evaluate the performance of these models.

RESULTS

All of the three models obtained good performances in differentiating benign with malignant solid ovarian tumors in both training and test sets. The AUC, accuracy, precision, sensitivity of clinical model and radiomic model in test set were 0.847 (95% confidence interval (CI), 0.707-0.986, p <0.01), 0.774, 0.769, 0.714, and 0.807 (95%CI, 0.652-0.961, p <0.05), 0.677, 0.643, 0.643, respectively. Combined model had the best prediction results, the AUC, accuracy, precision and sensitivity were 0.954 (95%CI, 0.862-1.0, p <0.01), 0.839, 0.909 and 0.714 in test set.

CONCLUSION

Radiomics based on machine learning can be helpful for radiologists in differentiating the benign and malignant solid ovarian tumors.

Diagnostic Accuracies of the Ultrasound and Magnetic Resonance Imaging ADNEX Scoring Systems For Ovarian Adnexal Mass: Systematic Review and Meta-Analysis

We conducted a meta-analysis of IOTA (international ovarian tumor analysis) ADNEX (Assessment of Different NEoplasias in the adneXa) as ultrasound system and MRI (magnetic resonance imaging) ADNEX scoring systems as MR system to assess their diagnostic test accuracy for differentiating benign from malignant adnexal masses of the ovary. We performed an electronic search for relevant publications in the English language up to February 2021 using PubMed, CENTRAL (Cochrane Central Register of Controlled Trials), Web of Science, and Google scholar databases and search engines. We computed the pooled sensitivity, pooled specificity, and summary receiver operating characteristics curve (SROC) using the statistical software STATA (Version 13, College Station, TX, StataCorp LP). Based on 11 studies using IOTA-ADNEX, we observed pooled sensitivity, specificity, area under curve, and diagnostic odds ratio were 96% (95% CI, 94% to 97%), 79% (95% CI, 70% to 86 %), 97% (95% CI, 95% to 98%), and 88 (95% CI, 43 to 180). Based on five studies using MR-ADNEX scoring system the pooled sensitivity, specificity, area under curve and diagnostic odds ratio were 91 % (95% CI, 87% to 94 %), 95% (95% CI, 92% to 97 %), 98% (95% CI, 96% to 99%), and 189 (95% CI, 90 to 396) respectively. Our meta-analysis results demonstrate that the MR-ADNEX scoring system had higher specificity however bit lower sensitivity compared to the IOTA-ADNEX scoring system for discriminating benign from malignant ovarian tumors.

T2-weighted imaging hypointensity in an ovarian lesion: is it a benign finding?

Objective

To evaluate whether the presence of a hypointense signal at T2-weighted imaging in a solid ovarian lesion on magnetic resonance imaging is a predictor of stability and benignity.

Methods

This is a single center study, prospectively read with retrospective acquired data. The database was searched for patients who underwent magnetic resonance imaging between January 2008 and October 2019 and whose reports mentioned solid ovarian lesions with low signal on T2-weighted imaging. A total of 47 nodules were included. A radiologist who was blinded to the clinical indication for magnetic resonance imaging and original reports evaluated the cases. Objective and subjective criteria of ovarian lesions in magnetic resonance imaging were evaluated.

Results

Thirty-five nodules were considered benign/stable and 12 were considered non-stable. The analysis showed that the non-stable lesions showed statistically more hyperintensity at T1-weighted imaging compared to the stable lesions.

Conclusion

T2-weighted imaging hypointensity can be considered a predictor of stability in solid ovarian lesions when associated with iso/hypointensity in T1-weighted imaging.

Diagnosing Ovarian Cancer on MRI: A Preliminary Study Comparing Deep Learning and Radiologist Assessments

Simple Summary

As a preliminary experiment to explore the possibility of clinical application as a future reading assist, we present CNNs for the diagnosis of ovarian carcinomas and borderline tumors on MRI, including T2WI, DWI, ADC map, and CE-T1WI, and compare their diagnostic performance with interpretations by experienced radiologists. CNNs were trained using 1798 images from 146 patients and 1865 images from 219 patients with malignant tumors, including borderline tumors, and non-malignant lesions, respectively, for each MRI sequence and tested with 48 and 52 images of patients with malignant and non-malignant lesions. The CNN of each sequence had a sensitivity of 0.77–0.85, specificity of 0.77–0.92, accuracy of 0.81–0.87, and an AUC of 0.83–0.89, demonstrating diagnostic performances that were non-inferior to those of experienced radiologists, and the CNN showed the highest diagnostic performance on the ADC map for each sequence (specificity = 0.85; sensitivity = 0.77; accuracy = 0.81; AUC = 0.89).

Abstract

Background: This study aimed to compare deep learning with radiologists’ assessments for diagnosing ovarian carcinoma using MRI. Methods: This retrospective study included 194 patients with pathologically confirmed ovarian carcinomas or borderline tumors and 271 patients with non-malignant lesions who underwent MRI between January 2015 and December 2020. T2WI, DWI, ADC map, and fat-saturated contrast-enhanced T1WI were used for the analysis. A deep learning model based on a convolutional neural network (CNN) was trained using 1798 images from 146 patients with malignant tumors and 1865 images from 219 patients with non-malignant lesions for each sequence, and we tested with 48 and 52 images of patients with malignant and non-malignant lesions, respectively. The sensitivity, specificity, accuracy, and AUC were compared between the CNN and interpretations of three experienced radiologists. Results: The CNN of each sequence had a sensitivity of 0.77–0.85, specificity of 0.77–0.92, accuracy of 0.81–0.87, and an AUC of 0.83–0.89, and it achieved a diagnostic performance equivalent to the radiologists. The CNN showed the highest diagnostic performance on the ADC map among all sequences (specificity = 0.85; sensitivity = 0.77; accuracy = 0.81; AUC = 0.89). Conclusion: The CNNs provided a diagnostic performance that was non-inferior to the radiologists for diagnosing ovarian carcinomas on MRI.

Brenner tumors

Brenner tumors are rare ovarian neoplasms composed of ovarian transition cells surrounded by dense fibrous tissue. Most of them are small tumors (<2 cm), detected incidentally in asymptomatic women. Its predominantly fibrous content results in relatively low signal on T₂ weighted images, establishing differential diagnosis with ovarian fibroma and thecoma. Their imaging features are very similar, the differentiation is based on secondary characteristics, such as signs or symptoms of estrogen excess and the presence of a second ovarian neoplasm, which has been reported in up to 30% of patients with Brenner tumor. Although originally thought to be universally benign, there have been scattered reports in the past decades of borderline and malignant forms of Brenner tumors.

Application of Multimodal Imaging Biomarker in the Differential Diagnosis of Ovarian Mass: Integration of Conventional and Molecular Imaging

PURPOSE

The aim is to investigate the diagnostic performance of multimodal imaging with 18F-FDG PET/CT, MRI, and contrast-enhanced CT (CECT) in cases with unilateral or bilateral ovarian mass without ancillary findings of malignancy.

METHODS

Retrospectively, 307 patients who had unilateral or bilateral ovarian masses and underwent preoperative FDG PET/CT and/or MRI/CECT were included. The criterion standard for the ovarian mass was the final pathology. The peak standardized uptake value (SULpeak) among benign tumors (BTs), borderline ovarian tumors (BoTs), and malignant ovarian tumors (MTs) were compared. The cutoff value of SULpeak to discriminate between BT/BoT and MT was determined from the training (n = 200) and validation (n = 131) cohorts. Diagnostic performances of SULpeak, Ovarian-Adnexal Reporting Data System (O-RADS) MRI score, CECT findings, and combination of multimodal imagings were analyzed.

RESULTS

SULpeak of MT was significantly higher than that of BT or BoT (P < 0.05). There was no significant difference in SULpeak between BT and BoT (P = 0.147). The cutoff value of SULpeak for discriminating between BT/BoT and MT was 1.76 (sensitivity, 87.0%; specificity, 83.0%). Diagnostic performance for BT/BoT versus MT of O-RADS MRI, CECT, FDG PET/CT plus O-RADS MRI score, and FDG PET/CT plus CECT yielded the respective sensitivities of 100%, 94%, 95%, and 82%, and specificities of 43%, 46%, 88%, and 91%, respectively.

CONCLUSIONS

Multimodal imaging biomarkers including FDG PET/CT and MR/CECT could provide additional information to differentiate ovarian masses.

Impact of Multiparametric MRI (mMRI) on the Therapeutic Management of Adnexal Masses Detected with Transvaginal Ultrasound (TVUS): An Interdisciplinary Management Approach

RATIONALE AND OBJECTIVES

Adnexal masses detected incidentally at transvaginal ultrasound (TVUS) are a common and still challenging diagnostic problem. The primary goal of further imaging is an accurate tissue characterization so an optimal treatment plan can be devised including surgery only for lesions that are indeterminate or malignant. The aim of this prospective study was to evaluate the diagnostic utility of complementary multiparametric magnetic resonance imaging (mMRI) for treatment planning in patients with adnexal masses, and to assess how it ultimately correlates with subsequent histopathologic findings.

MATERIAL AND METHODS

A total of 126 women (mean age: 54.6 years) with indeterminate adnexal masses underwent mMRI at 3T in addition to TVUS and testing to determine their CA-125 levels. The mMRI protocol consisted of a high-resolution T2-TSE in three planes, diffusion weighted images and dynamic contrast enhanced. First the character of the adnexal mass and the associated management decision (follow-up, laparoscopy or laparotomy) were assessed independently for each diagnostic method (TVUS + CA-125 and mMRI). All methods were then assessed in synopsis. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each diagnostic method alone and in combination were calculated. The standard of reference was either final histology in women who underwent surgery or follow-up of at least 24 months in women who underwent follow-up.

RESULTS

In 67.5% (85/126) of all patients, the adnexal mass was benign; a malignant tumor was diagnosed in 28.6% (36/126) and a borderline tumor in the remaining 4% (5/126) of patients. The diagnostic indices were as follows for TVUS + CA 125 alone, mMRI alone and all three methods combined: sensitivity 86% (31/36), 97% (35/36), and 100% (36/36); specificity 32% (29/90), 83% (75/90), and 80% (68/90); PPV 34% (31/91), 70% (35/50), and 74% (40/54); and NPV 65% (29/44), 98% (75/76), and 100% (72/72). Complementary use of mMRI changed the therapeutic management decision in 34% (41/126) of all patients. In 40.7% (37/91) of patients for whom surgery had been recommended based on TVUS + CA-125, MRI revealed a typical benign finding such that those patients underwent follow-up instead of surgery. None of the examined masses exhibited (tumor) progression or malignancy during the follow-up period. A laparotomy was performed instead of a laparoscopy in 8.7% (11/126) based on the mMRI result.

CONCLUSION

MRI helps significantly improve sensitivity and specificity of diagnosis in patients with indeterminate adnexal masses detected at TVUS. Its diagnostic information revised the planned treatment in more than one-third of women.

The role of "penumbra sign" and diffusion-weighted imaging in adnexal masses: do they provide a clue in differentiating tubo-ovarian abscess from ovarian malignancy?

Purpose

To evaluate the role of “penumbra sign”, diffusion-weighted imaging (DWI), and the apparent diffusion coefficient (ADC) value in differentiating tubo-ovarian abscess (TOA) from ovarian malignancy.

Material and methods

Thirty-six patients with 50 adnexal masses (tubo-ovarian abscess, n = 24; ovarian malignancy, n = 26), who underwent magnetic resonance imaging (MRI) with DWI, were retrospectively evaluated. “Penumbra sign” (hyperintense rim on T1W images), diffusion restriction, and mean apparent diffusion coefficient (ADC) values from cystic (c-ADC) and solid (s-ADC) components were evaluated for all the masses.

Results

“Penumbra sign” on T1W images was significantly more common in the TOA group (n = 21, 87.5%) than in the ovarian malignancy group (n = 2, 7.7%) (p < 0.001). Similarly, diffusion restriction in the cystic component was more frequent in the TOA group (n = 24, 100% vs. n = 2, 10.5%; p < 0.001). In contrast, diffusion restriction in the solid component was more common in the ovarian malignancy group (n = 5, 20.8% vs. n = 26, 100%; p < 0.001). The mean c-ADC value was significantly lower in TOAs (p < 0.001). A c-ADC value of 1.31 × 10^-3 mm²/s may be an optimal cut-off in distinguishing TOAs from ovarian malignancies. Conversely, the mean s-ADC value was significantly lower in the ovarian malignancy group (p < 0.001). An s-ADC value of 0.869 × 10^-3 mm²/s may be an optimal cut-off in differentiating ovarian malignancies from TOAs (p < 0.001). ROC curve analysis showed that c-ADC values had a higher diagnostic accuracy than s-ADC values.

Conclusions

“Penumbra sign” on T1W images, diffusion characteristics, and ADC values provide important clues in addition to conventional MR imaging features in differentiating TOA from ovarian malignancy.

Fat-containing pelvic lesions in females

Pelvic tumors are common in females and have a broad differential diagnosis. The clinical management of pelvic tumors varies widely-from observation to surgical resection-and imaging plays a pivotal role in diagnosis and clinical decision-making in these cases. In particular, imaging can help determine the organ of origin and tissue content of these tumors, which are the most important steps to narrowing the differential diagnosis. Fat has a characteristic appearance and is often easily identified on ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI). The amount and distribution of intralesional fat varies in different types of tumors. Macroscopic intralesional fat is often easily recognized by its hyperechoic appearance on US and low attenuation on CT similar to subcutaneous fat. On MRI, macroscopic fat is hyperintense on T1-weighted (T1W) images, with characteristic signal loss on fat-saturated sequences and India-ink artifact on opposed-phase T1W images. Macroscopic fat is the hallmark of teratomas, which are the most common ovarian neoplasms. Uterine lipoleiomyomas, peritoneal loose bodies, intraperitoneal and extraperitoneal primary lipomatous tumors such as lipoma and liposarcomas, and extra-adrenal myelolipomas are other pelvic masses distinguished by the presence of macroscopic fat. However, the imaging diagnosis of pelvic masses containing minimal or microscopic fat, such as immature ovarian teratomas, steroid cell ovarian neoplasms, and extramedullary hematopoiesis, can present a diagnostic challenge owing to their nonspecific appearance on US or CT. Obtaining MRI with in-phase and opposed-phase dual-echo T1W sequences and depicting chemical shift artifacts can be helpful in distinguishing these lesions.

All that glitters are not gold: holds true in female adnexal lesions

Background

Adnexal mass lesions are commonly encountered pathologies that creates diagnostic challenges for radiologist. Diffusion weighted imaging is a vital tool in the radiologist armamentarium for improving the diagnostic accuracy of adnexal lesions other than routine spine echo sequences.

Main body

Functional information about the lesion regarding the mobility of the water molecules in its tissue is assessed by diffusion weighted imaging. In addition to the solid malignant neoplasm, normal blood, fat, necrosis and pus also shows restricted diffusion.

Conclusion

All the lesion that shows restriction in the DWI are not malignant, but converse is mostly true. Knowledge regarding the non-malignant lesion in the ovary that shows restricted diffusion will give a clue in diagnosis, management and treatment of the adnexal lesions.

Magnetic Resonance Spectroscopy for Risk Stratification of Sonographically Indeterminate Ovarian Neoplasms: Preliminary Study

We aim to assess the additional value of diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) for the risk stratification of sonographically indeterminate ovarian neoplasms. A total of 21 patients with diagnosed adnexal masses between 2014 and 2017 were divided into malignant (four serous cystadenocarcinomas, four endometrioid carcinomas, three clear cell carcinomas, and one carcinosarcoma) and benign (four cystadenomas, two teratomas, one fibroma, one endometrioma, and one corpus luteal cyst) groups. An apparent diffusion coefficient (ADC) value of 1.27 × 10^-3 mm²/s was considered as the optimal threshold in distinguishing malignant from benign ovarian tumors (sensitivity and specificity: 100% and 77.8%, respectively). Choline peaks were detected in six of seven O-RADS (Ovarian-Adnexal Imaging-Reporting Data System) 4 lesions and corrected all of the DWI false-negative clear cell carcinoma. Based on the presence of the choline peaks, the diagnostic performance of MRS showed a sensitivity of 77.8%, a specificity of 100%, and an accuracy of 85.7%, respectively. In conclusion, MRS could potentially play a complementary role for DWI in tumor characterization, particularly for O-RADS 4 tumors or clear cell carcinomas.

Evaluating the added benefit of CT texture analysis on conventional CT analysis to differentiate benign ovarian cysts

PURPOSE

We aimed to evaluate the benefit of adding CT texture analysis on conventional CT features of benign adnexal cystic lesions, especially in identifying mucinous cystadenoma.

METHODS

This retrospective study included patients who underwent surgical removal of benign ovarian cysts (44 mucinous cystadenomas, 32 serous cystadenomas, 16 follicular/simple cysts and 43 endometriotic cysts) at our institution between January 2015 and November 2017. The CT images were independently reviewed by an abdominal radiologist (reviewer 1) and a resident (reviewer 2). Both reviewers recorded the conventional characteristics and performed texture analysis. Based on reviewer 1's results, two decision trees for differential diagnosis were developed. Reviewer 2's results were then applied to the decision trees. The diagnostic performances of each reviewer with and without the decision trees were compared.

RESULTS

Several conventional features and texture analysis parameters showed significant differences between mucinous cystadenomas and other benign adnexal cysts. The first decision tree selected septum number and thickness as significant features, whereas the second decision tree selected septum number and the mean values at spatial scaling factor (SSF) 0. Reviewer 1's performance did not change significantly with or without the use of the decision trees. Reviewer 2's interpretations were significantly less sensitive than reviewer 1's interpretations (p = 0.001). However, when aided by the first and second decision trees, Reviewer 2's interpretations were significantly more sensitive than reviewer 1's interpretations (86.4%, p < 0.001; 72.7%, p = 0.001).

CONCLUSION

This study suggests the benefit of CT texture analysis on conventional images to differentiate mucinous cystadenoma from other benign adnexal cysts, particularly for less experienced radiologists.

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

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

A radiomic nomogram based on arterial phase of CT for differential diagnosis of ovarian cancer

Purpose

To develop and validate a radiomic nomogram based on arterial phase of CT to discriminate the primary ovarian cancers (POCs) and secondary ovarian cancers (SOCs).

Methods

A total of 110 ovarian cancer patients in our hospital were reviewed from January 2010 to December 2018. Radiomic features based on the arterial phase of CT were extracted by Artificial Intelligence Kit software (A.K. software). The least absolute shrinkage and selection operation regression (LASSO) was employed to select features and construct the radiomics score (Rad-score) for further radiomics signature calculation. Multivariable logistic regression analysis was used to develop the predicting model. The predictive nomogram model was composed of rad-score and clinical data. Nomogram discrimination and calibration were evaluated.

Results

Two radiomic features were selected to build the radiomics signature. The radiomics nomogram that incorporated 2 radiomics signature and 2 clinical factors (CA125 and CEA) showed good discrimination in training cohort (AUC 0.854), yielding the sensitivity of 78.8% and specificity of 90.7%, which outperformed the prediction model based on radiomics signature or clinical data alone. A visualized differential nomogram based on the radiomic score, CEA, and CA125 level was established. The calibration curve demonstrated the clinical usefulness of the proposed nomogram.

Conclusion

The presented nomogram, which incorporated radiomic features of arterial phase of CT with clinical features, could be useful for differentiating the primary and secondary ovarian cancers.

Diagnostic performance of PET/CT and PET/MR in the management of ovarian carcinoma-a literature review

Ovarian cancer is a challenging disease. It often presents at an advanced stage with frequent recurrence despite optimal management. Accurate staging and restaging are critical for improving treatment outcomes and determining the prognosis. Imaging is an indispensable component of ovarian cancer management. Hybrid imaging modalities, including positron emission tomography/computed tomography (PET/CT) and PET/magnetic resonance imaging (MRI), are emerging as potential non-invasive imaging tools for improved management of ovarian cancer. This review article discusses the role of PET/CT and PET/MRI in ovarian cancer.

Differentiation of Endometriomas from Hemorrhagic Cysts at Magnetic Resonance: The Role of Quantitative Signal Intensity Measurements

BACKGROUND

Endometriomas and functional hemorrhagic cysts (FHCs) are a common gynecological encounter.

OBJECTIVE

This study aimed to assess the diagnostic efficiency of magnetic resonance imaging (MRI) using signal intensity measurements in differentiating endometriomas from FHCs.

METHODS

Forty-six patients who underwent pelvic MRI examinations (endometriomas, n=28; FHCs, n=18) were retrospectively included. The "T2 shading" sign was evaluated subjectively and quantitatively by measuring the T1-T2 signal intensity difference and calculating the percentage of signal decrease between T1 and T2-weighted sequences. The resulted values, along with the measurement of the Apparent Diffusion Coefficient (ADC) and the signal intensity on three diffusion- weighted sequences (DWI) (b⁵⁰, b⁴⁰⁰, and b⁸⁰⁰), were compared between groups by using the Mann-Whitney U test. Also, the receiver operating characteristic analysis was performed for the statistically significant results (P<0.016), and the area under the curve (AUC) was also calculated.

RESULTS

The two quantitative assessment methods showed similar efficiency in detecting endometriomas (P<0.001; sensitivity, 100%; specificity, 81.82%; AUC>0.86), outperforming the classic subjective evaluation of the "T2 shading" sign (sensitivity, 92.86%; specificity, 66.67%). ADC (P=0.52) and DWI measurements (P=0.49, P=0.74, and P=0.78) failed to distinguish between the two entities.

CONCLUSION

The quantitative analysis and interpretation of the "T2 shading" sign can significantly improve the differential diagnosis between endometriomas and FHCs.

Magnetic resonance imaging findings of extrauterine high-grade serous carcinoma based on new pathologic criteria for primary site assignment

BACKGROUND

There has been no study that has reported magnetic resonance imaging (MRI) findings of extrauterine high-grade serous carcinomas (HGSCs) that have been histologically determined by the new criteria.

PURPOSE

To assess MRI findings of extrauterine HGSCs based on new pathologic criteria.

MATERIAL AND METHODS

Fifty patients with histopathologically proven extrauterine HGSCs, who underwent pretreatment gadolinium-enhanced MRI, were included in this study. After surgery, the primary sites were histopathologically determined based on new criteria for primary site assignment in extrauterine HGSCs as follows: fallopian tube (n = 34); ovary (n = 9); primary peritoneal HGSC (n = 1); and tubo-ovarian (n = 6). We retrospectively reviewed MR images and compared the MR findings between tubal and ovarian primaries.

RESULTS

MRI patterns with tubal primaries were classified as ovarian cancer (62%), peritoneal cancer (35%), and fallopian tube cancer (3%). MRI patterns with ovarian primaries were classified as ovarian cancer (78%) and peritoneal cancer (22%). The frequency of the involvement of the fallopian tube, ovary, peritoneum, uterus, and lymph node was not significantly different between the two pathologies. There was no significant difference in the abnormal amount of ascites, hemorrhagic ascites, or characteristics of the ovarian lesions between the two pathologies.

CONCLUSION

On MR images, tubal primaries almost always exhibited ovarian or peritoneal cancer pattern, but rarely exhibited fallopian tube cancer pattern. MR findings could not accurately differentiate between tubal and ovarian primaries; therefore, histopathologic investigation is essential for determination of the primary site of extrauterine HGSCs.

Ovarian Fibromatosis: "The black garland sign"

The main objective in the imaging differential diagnosis of an ovarian mass is to establish whether it is cystic or solid; solid lesions are less common. Ovarian fibromatosis is a benign disease of the ovary that is rarely included in the differential diagnosis of solid ovarian lesions. Characteristic features of masses that have a fibrous component are low signal in T1-weighted MRI sequences and especially in T2-weighted MRI sequences. The presence of peripheral fibrotic tissue around the residual ovarian tissue is specific to ovarian fibromatosis; on MRI, this results in marked hypointensity on T2-weighted images that has been dubbed the "black garland sign". This sign, together with slight peripheral enhancement after the administration of contrast material and the preservation of the ovarian architecture, facilitates the diagnosis, making it possible to avoid unnecessary surgical interventions.

The diagnostic value of magnetic resonance imaging in differentiating benign and malignant pediatric ovarian tumors

BACKGROUND

The diagnostic workup of ovarian tumors in children and adolescents is challenging because preserving fertility, in addition to oncological safety, is of particular importance in this population. Therefore, a thorough preoperative assessment of ovarian tumors is required.

OBJECTIVE

To investigate the diagnostic value of MR imaging in differentiating benign from malignant ovarian tumors in children and adolescents.

MATERIALS AND METHODS

We conducted a retrospective study of all children and adolescents age <18 years who underwent MR imaging of ovarian tumors during 2014-2019 at a pediatric specialty center. Two radiologists reviewed all MR imaging. We used pathology reports to define the histological diagnosis.

RESULTS

We included 30 girls who underwent MR imaging for an ovarian tumor. Signs indicative for malignancy were tumors with a diameter ≥8 cm, with areas of contrast enhancement, irregular margins, extracapsular tumor growth, and ascites. All benign and malignant ovarian tumors were correctly identified by the radiologists.

CONCLUSION

The diagnostic utility of MR imaging in classifying ovarian tumors in children and adolescents as benign or malignant is promising and might aid in defining the indication for ovarian-sparing versus non-ovarian-sparing surgery. We recommend evaluating these tumors with MR imaging prior to deciding on surgical treatment.

Adnexal masses characterized on 3 tesla magnetic resonance imaging - added value of diffusion techniques

Background

To assess different types of adnexal masses as identified by 3T MRI and to discuss the added value of diffusion techniques compared with conventional sequences.

Patients and methods

174 women age between 13 and 87 underwent an MRI examination of the pelvis for a period of three years. Patients were examined in two radiology departments – 135 of them on 3 Tesla MRI Siemens Verio and 39 on 3 Tesla MRI Philips Ingenia. At least one adnexal mass was diagnosed in 98 patients and they are subject to this study. Some of them were reviewed retrospectively. Data from patients’ history, physical examination and laboratory tests were reviewed as well.

Results

124 ovarian masses in 98 females’ group of average age 47.2 years were detected. Following the MRI criteria, 59.2% of the cases were considered benign, 30.6% malignant and 10.2% borderline. Out of all masses 58.1% were classified as cystic, 12.9% as solid and 29% as mixed. Оf histologically proven tumors 74.4% were benign and 25.6% were malignant. All of the malignant tumors had restricted diffusion. 64 out of all patients underwent contrast enhancement. (34 there were a subject of contraindications). 39 (61%) of the masses showed contrast enhancement.

Conclusions

Classifying adnexal masses is essential for the preoperative management of the patients. 3T MRI protocols, in particular diffusion techniques, increase significantly the accuracy of the diagnostic assessment.

Differentiation of borderline tumors from type I ovarian epithelial cancers on CT and MR imaging

PURPOSE

To investigate the value of CT and MR imaging features in differentiating borderline ovarian tumor (BOT) from type I ovarian epithelial cancer (OEC), which could be significant for suitable clinical treatment and assessment of the prognosis of the patient.

METHODS

Thirty-three patients with BOTs and 35 patients with type I OECs proven by pathology were retrospectively evaluated. The clinico-pathological information (age, premenopausal status, CA-125, and Ki-67) and imaging characteristics were compared between two groups of ovarian tumors. The diagnostic performance of the imaging features was evaluated using receiver operating characteristic analysis. The best predictor variables for type I EOCs were recognized via multivariate analyses.

RESULTS

BOTs are more likely to involve younger patients and frequently show lower CA-125 values and lower proliferation indices (Ki-67 < 15%) than type I OECs. Compared with type I OECs, BOTs were more often purely cystic (15/33, 45.45% vs. 1/35, 2.86%; p < 0.001) and displayed less frequent mural nodules (16/33, 48.48% vs. 28/35, 80.00%; p = 0.007), less frequently unclear margin (3/33, 9.09% vs. 11/35, 31.43%; p = 0.023), smaller solid portion (0.56 ± 2.66 vs. 4.51 ± 3.88; p < 0.001), and thinner walls (0.3 ± 0.17 vs. 0.55 ± 0.24; p < 0.001). The maximum wall thickness presented the largest area under the curve (AUC, 0.848). Multivariate analysis revealed that the solid portion size (OR 10.822, p = 0.002) and maximum wall thickness (OR 9.130, p = 0.001) were independent indicators for the differential diagnosis between the two groups of lesions.

CONCLUSION

The solid portion size and maximum wall thickness significantly influenced the classification of the two groups of ovarian tumors.

Algorithmic Approach to Sonography of Adnexal Masses: An Evolving Paradigm

BACKGROUND

Pelvic US remains the workhorse for detection and characterization of adnexal masses in most centers worldwide. While the differentiation of benign from malignant masses remains the foremost concern, it is imperative to narrow the differential diagnosis for management of benign masses as well as prognostication of malignant masses. The IOTA group as well as ACR have described a five category classification system for adnexal lesions based on morphological patterns. In addition, a six category risk stratification has been proposed, incorporating the probability of malignancy as well as management recommendations.

LEARNING OBJECTIVES

1) Understand pattern based approach to adnexal lesion classification and the possible entities fitting into each pattern with the help of illustrations. 2) Classify lesions into appropriate risk categories based on diagnostic algorithms provided at the end of each section.

Radiomic Analysis of MRI Images is Instrumental to the Stratification of Ovarian Cysts

The imaging diagnosis of malignant ovarian cysts relies on their morphological features, which are not always specific to malignancy. The histological analysis of these cysts shows specific fluid characteristics, which cannot be assessed by conventional imaging techniques. This study investigates whether the texture-based radiomics analysis (TA) of magnetic resonance (MRI) images of the fluid content within ovarian cysts can function as a noninvasive tool in differentiating between benign and malignant lesions. Twenty-eight patients with benign (n = 15) and malignant (n = 13) ovarian cysts who underwent MRI examinations were retrospectively included. TA of the fluid component was undertaken on an axial T2-weighted sequence. A comparison of resulted parameters between benign and malignant groups was undertaken using univariate, multivariate, multiple regression, and receiver operating characteristics analyses, with the calculation of the area under the curve (AUC). The standard deviation of pixel intensity was identified as an independent predictor of malignant cysts (AUC = 0.738; sensitivity, 61.54%; specificity, 86.67%). The prediction model was able to identify malignant lesions with 84.62% sensitivity and 80% specificity (AUC = 0.841). TA of the fluid contained within the ovarian cysts can differentiate between malignant and benign lesions and potentially act as a noninvasive tool augmenting the imaging diagnosis of ovarian cystic lesions.

A Nomogram Combined Radiomic and Semantic Features as Imaging Biomarker for Classification of Ovarian Cystadenomas

Objective: To construct and validate a combined Nomogram model based on radiomic and semantic features to preoperatively classify serous and mucinous pathological types in patients with ovarian cystadenoma.

Methods: A total of 103 patients with pathology-confirmed ovarian cystadenoma who underwent CT examination were collected from two institutions. All cases divided into training cohort (N = 73) and external validation cohort (N = 30). The CT semantic features were identified by two abdominal radiologists. The preprocessed initial CT images were used for CT radiomic features extraction. The LASSO regression were applied to identify optimal radiomic features and construct the Radscore. A Nomogram model was constructed combining the Radscore and the optimal semantic feature. The model performance was evaluated by ROC analysis, calibration curve and decision curve analysis (DCA).

Result: Five optimal features were ultimately selected and contributed to the Radscore construction. Unilocular/multilocular identification was significant difference from semantic features. The Nomogram model showed a better performance in both training cohort (AUC = 0.94, 95%CI 0.86–0.98) and external validation cohort (AUC = 0.92, 95%CI 0.76–0.98). The calibration curve and DCA analysis indicated a better accuracy of the Nomogram model for classification than either Radscore or the loculus alone.

Conclusion: The Nomogram model combined radiomic and semantic features could be used as imaging biomarker for classification of serous and mucinous types of ovarian cystadenomas.

MR imaging findings of low-grade serous carcinoma of the ovary: comparison with serous borderline tumor

PURPOSE

To assess MR imaging findings of low-grade serous carcinoma (LGSC) of the ovary compared with those of serous borderline tumor (SBT).

METHODS

Twenty-four patients with histopathologically proven 7 LGSCs and 25 SBTs who underwent preoperative MR imaging were included. We retrospectively reviewed MR images and compared MR findings between the two pathologies.

RESULTS

The predominantly solid lesions were marginally more frequent in LGSCs than in SBTs (43% vs. 8%, p = 0.057). All predominantly cystic LGSCs were multilocular cystic lesions with mural nodules. Predominantly solid LGSCs exhibited pure solid masses in 2 of 3 and solid masses with intratumoral cysts in 1 of 3. Papillary growth pattern with internal branching was observed only in 18 of 25 SBTs. Signal intensity ratio on T2-weighted images (4.48 ± 1.55 vs. 8.40 ± 3.53, p < 0.01) and apparent diffusion coefficient (ADC) values (1.12 ± 0.21 vs. 1.73 ± 0.27 × 10^-3 mm²/s, p < 0.01) of solid components was significantly lower in LGSCs than in SBTs.

CONCLUSION

Compared with SBTs, lower signal intensity on T2-weighted images and lower ADC values were characteristic features of solid components in LGSCs. Papillary growth pattern with internal branching was not observed in LGSCs.

Extrahepatic Fat-Containing Lesions of the Abdomen and Pelvis: An Organ-Based Approach to Differential Diagnoses

The presence of intralesional fat provides an invaluable tool for narrowing the differential diagnosis for both benign and malignant neoplasms of the abdomen and pelvis. The ability to characterize intralesional fat is further expanded by the ability of magnetic resonance imaging to detect small quantities (intravoxel) of fat. While the presence of intralesional fat can help to provide a relatively narrow set of diagnostic possibilities, depending on the type of fat (macroscopic vs intravoxel) that is present and the organ of origin, radiologists must be aware of uncommon mimickers of pathology, both benign and malignant.

Cross-sectional imaging of acute gynaecologic disorders: CT and MRI findings with differential diagnosis-part II: uterine emergencies and pelvic inflammatory disease

Due to the growing use of cross-sectional imaging in emergency departments, acute gynaecologic disorders are increasingly diagnosed on urgent multidetector computed tomography (CT) studies, often requested under alternative presumptive diagnoses in reproductive-age women. If clinical conditions and state-of-the-art scanner availability permit, magnetic resonance imaging (MRI) is superior to CT due to its more in-depth characterisationof abnormal or inconclusive gynaecological findings, owing to excellent soft-tissue contrast, intrinsic multiplanar capabilities and lack of ionising radiation.

This pictorial review aims to provide radiologists with a thorough familiarity with gynaecologic emergencies by illustrating their CT and MRI appearances, in order to provide a timely and correct imaging diagnosis. Specifically, this second instalment reviews with examples and emphasis on differential diagnosis the main non-pregnancy-related uterine emergencies (including endometrial polyps, degenerated leiomyomas and uterine inversion) and the spectrum of pelvic inflammatory disease.

Cross-sectional imaging of acute gynaecologic disorders: CT and MRI findings with differential diagnosis-part I: corpus luteum and haemorrhagic ovarian cysts, genital causes of haemoperitoneum and adnexal torsion

Acute gynaecologic disorders are commonly encountered in daily clinical practice of emergency departments (ED) and predominantly occur in reproductive-age women. Since clinical presentation may be nonspecific and physical findings are often inconclusive, imaging is required for a timely and accurate diagnosis. Although ultrasound is the ideal non-invasive first-line technique, nowadays multidetector computed tomography (CT) is extensively used in the ED, particularly when a non-gynaecologic disorder is suspected and differential diagnosis from gastrointestinal and urologic diseases is needed. As a result, CT often provides the first diagnosis of female genital emergencies. If clinical conditions and scanner availability permit, magnetic resonance imaging (MRI) is superior to CT for further characterisation of gynaecologic abnormalities, due to the excellent soft-tissue contrast, intrinsic multiplanar capabilities and lack of ionising radiation.

The purpose of this pictorial review is to provide radiologists with a thorough familiarity with gynaecologic emergencies by illustrating their cross-sectional imaging appearances. The present first section will review the CT and MRI findings of corpus luteum and haemorrhagic ovarian cysts, gynaecologic haemoperitoneum (from either ruptured corpus luteum or ectopic pregnancy) and adnexal torsion, with an emphasis on differential diagnosis. Additionally, comprehensive and time-efficient MRI acquisition protocols are provided.