Staging endometrial cancer: role of magnetic resonance imaging

Values of tumor volume on magnetic resonance imaging for a surgical approach to endometrial cancer

OBJECTIVE

To analyze the relationship between tumor volume in Endometrial Cancer (EC) on Magnetic Resonance Imaging (MRI) and lymph node metastasis to establish which patients benefit from omitting the lymphadenectomy.

METHODS

A retrospective observational study with 194 patients with EC identified between 2016 and 2021 at the Juan Ramón Jiménez University Hospital, Huelva (Spain) was carried out. Preoperative MRI of 127 patients was assessed. The tumor volume was analyzed on MRI by the ellipsoid formula and another alternative method with a manual ROI in different sections. Risk factors for node metastases were analyzed to understand its relationship and to identify an optimum criterion for the tailored surgery.

RESULTS

Univariate analysis showed risk factors for lymph node metastases were histological grade (p = 0.001), tumor with a volume greater than >25 cm3 (p < 0.001), lymphovascular space invaded (p = 0.007), and preoperative Ca 125 serum >28 (p < 0.001). Multivariate analysis indicated that tumor volume index >25 cm3 was an independent risk factor for lymph node metastases. The patients without significant proposed risk factors (volume index >25 cm3  [OR = 0.64], Ca 125 > 28 [OR = 0.32], and high histological grade [OR = 2.6]) did not present lymph node metastases, independent of myometrial invasion.

CONCLUSIONS

Lymphadenectomy can be omitted in patients with Endometrioid carcinoma that do not have any of the following risk factors: high-grade tumor, elevated Ca 125 (>28), and tumor volume on MRI greater than 25 cm3 . Tumor volume might predict the state of lymph nodes in EC and it could give information regarding surgical management.

Radiomics-based fertility-sparing treatment in endometrial carcinoma: a review

In recent years, with the increasing incidence of endometrial carcinoma in women of child-bearing age, to decision of whether to preserve patients' fertility during treatment has become increasingly complex, presenting a formidable challenge for both physicians and patients. Non-fertility-sparing treatment can remove lesions more thoroughly than fertility-sparing treatment. However, patients will permanently lose their fertility. In contrast, fertility-sparing treatment can treat tumors without impairing fertility, but the risk of disease progression is high as compared with non-fertility-sparing treatment. Therefore, it is extremely important to accurately identify patients who are suitable for fertility-sparing treatments. The evaluation of prognostic factors, including myometrial invasion, the presence of lymph node metastases, and histopathological type, is vital for determining whether a patient can receive fertility-sparing treatment. As a non-invasive and quantitative approach, radiomics has the potential to assist radiologists and other clinicians in determining more precise judgments with regard to the above factors by extracting imaging features and establishing predictive models. In this review, we summarized currently available fertility-sparing strategies and reviewed the performance of radiomics in predicting risk factors associated with fertility-sparing treatment. This review aims to assist clinicians in identifying patients suitable for fertility-sparing treatment more accurately and comprehensively and informs more appropriate and rigorous treatment decisions for endometrial cancer patients of child-bearing age.Critical relevance statement: Radiomics is a promising tool that may assist clinicians identify risk factors about fertility-sparing more accurately and comprehensively.

Management of Endometrial Cancer: French Society of Onco-Gynecology's Evaluation through a Delphi Survey

Our aim was to assess the opinion of a panel of experts and obtain a consensus on the management of endometrial cancer in France and French Switzerland. A Delphi survey was carried out among a panel of French and French-speaking Swiss experts. The first questionnaire included 65 questions divided into eight categories: characterization of experts, histo-molecular characteristics and radiological data of endometrial cancer, and management of low-risk, intermediate-risk, intermediate-high-risk, high-risk, and metastatic cancers. The experts were asked to reply on a 9-point scale, both on the validity and the clarity of each question. After the answers were analyzed, a second questionnaire was sent to the same experts. The study took place between December 2021 and March 2022. Further, 58 (57.4%) of the 101 experts responded in the first round, and 39 recommendations were obtained (60%). Six questions were voted redundant and 20 discordant. These questions were reformulated, and, at the end of the second round, 17 recommendations were validated (85%). In total, the study presents an analysis of 56 questions and related responses. Expert advice helps to clarify non-consensual issues, standardize the management of endometrial cancer, and optimize clinical practices.

MRI-based radiomics model for distinguishing endometrial carcinoma from benign mimics: A multicenter study

PURPOSE

To develop and validate an MRI-based radiomics model for preoperatively distinguishing endometrial carcinoma (EC) with benign mimics in a multicenter setting.

METHODS

Preoperative MRI scans of EC patients were retrospectively reviewed and divided into training set (158 patients from device 1 in center A), test set #1 (78 patients from device 2 in center A) and test set #2 (109 patients from device 3 in center B). Two radiologists performed manual delineation of tumor segmentation on the map of apparent diffusion coefficient (ADC), diffusion-weighted imaging (DWI) and T2-weighted imaging (T2WI). The features were extracted and firstly selected using Chi-square test, followed by refining using binary least absolute shrinkage and selection operator (LASSO) regression. The support vector machine (SVM) was employed to build the radiomics model, which is tuned in the training set using 10-fold cross-validation, and then assessed on the test set. Performance of the model was determined by area under the receiver-operating characteristic curve (AUC), accuracy, sensitivity, specificity and F1-score.

RESULTS

Five most informative features are selected from the extracted 3142 features. The SVM with linear kernel was employed to build the radiomics model. The AUCs of the model were 0.989 (95% confidence interval [CI]: 0.968-0.997) for the training set, 0.999 (95% CI: 0.991-1.000) for test set #1, 0.961 (95% CI: 0.902-0.983) for test set #2. Accuracies of the model were 0.937 for the training set (precision: 0.919, recall: 0.963, F1-score: 0.940), 0.974 for test set #1 (precision: 0.949, recall: 1.000, F1-score: 0.974) and 0.908 for test set #2 (precision: 0.899, recall: 0.954, F1-score: 0.925). These results confirmed the efficacy of this model in predicting EC in different centers.

CONCLUSION

The MRI-based radiomics model showed promising potential for distinguishing EC with benign mimics and might be useful for surgical management of EC.

Hyaluronic Acid-Functionalized Nanomicelles Enhance SAHA Efficacy in 3D Endometrial Cancer Models

Simple Summary

One of the major limitations to cancer therapies are the side effects caused by the drug interacting with any tissue in the body. There is often a balance between patient health and effectively treating the disease. To by-pass this balancing act nanoparticles are being used to deliver therapeutics straight to the tumors, acting as “Trojan Horses”. Endometrial cancers are known to have more of the cell surface protein CD44 than healthy tissues. Here, to efficiently target endometrial cancer, hyaluronic acid, which naturally binds to the CD44 protein was attached to the surface of nanoparticles and tested on microtissues or spheroids to better model a tumor and understand drug delivery performance. We show that our hyaluronic acid-nanoparticle formulations improve drug effects and interact with the cancer cells more than without this targeting agent.

Abstract

Histone Deacetylase (HDAC) enzymes are upregulated in cancer leading to the development of HDAC inhibiting compounds, several of which are currently in clinical trials. Side effects associated with toxicity and non-specific targeting indicate the need for efficient drug delivery approaches and tumor specific targeting to enhance HDAC efficacy in solid tumor cancers. SAHA encapsulation within F127 micelles functionalized with a surface hyaluronic acid moiety, was developed to target endometrial cancer cells expressing elevated levels of CD44. In vitro viability and morphology analyses was conducted in both 2D and 3D models to assess the translational potential of this approach. Encapsulation enhanced SAHA delivery and activity, demonstrating increased cytotoxic efficacy in 2D and 3D endometrial cancer models. High-content imaging showed improved nanoparticle internalization in 2D and CD44 enhanced penetration in 3D models. In addition, the nano-delivery system enhanced spheroid penetration resulting in cell growth suppression, p21 associated cell cycle arrest, as well as overcoming the formation of an EMT associated phenotype observed in free drug treated type II endometrial cancer cells. This study demonstrates that targeted nanoparticle delivery of SAHA could provide the basis for improving its efficacy in endometrial cancer. Using 3D models for endometrial cancer allows the elucidation of nanoparticle performance and CD44 targeting, likely through penetration and retention within the tumor model.

MRI Findings and Differential Diagnosis of Benign and Malignant Tumors of the Uterine Corpus

자궁은 크게 자궁체부와 자궁경부로 나뉜다. 이 중 자궁내막과 자궁근층으로 이루어진 자궁체부에는 양성에서 악성 종양까지 다양한 질환이 발생한다. 비침습적인 일차적 평가로 초음파와 컴퓨터단층촬영이 있으나 비특이적인 영상 소견으로 감별이 어려운 경우가 있다. 반면높은 해상도와 병리학적 특성 파악이 가능한 자기공명영상은 병변의 위치 확인뿐만 아니라 조직학적 특징, 그 리고 악성 종양의 병기 설정에도 도움을 준다. 이 종설에서는 영상의학과의사들이 알아야 할 자궁체부에서 볼 수 있는 다양한 양성과 악성 종양들의 특징적인 자기공명영상 소견들과 이들의 감별점에 대해 정리했다.

Endometrial Cancer, the Current International Federation of Gynecology and Obstetrics Staging System, and the Role of Imaging

Imaging plays a crucial role in the diagnosis, staging, and follow-up of endometrial cancer. Endometrial cancer is staged surgically using the International Federation of Gynecology and Obstetrics (FIGO) staging system. Preoperative imaging can complement surgical staging but is not yet considered a required component in the current FIGO staging system. Preoperative imaging can help identify some tumor characteristics and tumor spread, both locally and distally. More accurate assessment of endometrial cancers optimizes management and treatment plan, including degree of surgical intervention. In this article, we review the epidemiology, FIGO staging system, and the importance of imaging in the staging of endometrial cancer.

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

BACKGROUND

To enable more individualised treatment of endometrial cancer, improved methods for preoperative tumour characterization are warranted. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in oncological imaging, but largely unexplored in endometrial cancer AIM: To explore whether tumour texture features from preoperative computed tomography (CT) are related to known prognostic histopathological features and to outcome in endometrial cancer patients.

MATERIALS AND METHODS

Preoperative pelvic contrast-enhanced CT was performed in 155 patients with histologically confirmed endometrial cancer. Tumour ROIs were manually drawn on the section displaying the largest cross-sectional tumour area, using dedicated texture analysis software. Using the filtration-histogram technique, the following texture features were calculated: mean, standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis. These imaging markers were evaluated as predictors of histopathological high-risk features and recurrence- and progression-free survival using multivariable logistic regression and Cox regression analysis, including models adjusting for high-risk status based on preoperative biopsy, magnetic resonance imaging (MRI) findings, and age.

RESULTS

High tumour entropy independently predicted deep myometrial invasion (odds ratio [OR] 3.7, p=0.008) and cervical stroma invasion (OR 3.9, p=0.02). High value of MPP (MPP5 >24.2) independently predicted high-risk histological subtype (OR 3.7, p=0.01). Furthermore, high tumour kurtosis tended to independently predict reduced recurrence- and progression-free survival (HR 1.1, p=0.06).

CONCLUSION

CT texture analysis yields promising imaging markers in endometrial cancer and may supplement other imaging techniques in providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies.

Multiparametric MRI-Based Radiomics Nomogram for Predicting Lymphovascular Space Invasion in Endometrial Carcinoma

BACKGROUND

Lymphovascular space invasion (LVSI) of endometrial carcinoma (EMC) is one of the important prognostic factors, which is not usually visible subjectively. Therefore, clinicians lack imaging-based evidence about LVSI for preoperative treatment decision-making.

PURPOSE

To develop a multiparametric MRI (mpMRI)-based radiomics nomogram for predicting LVSI in EMC and provide decision-making support to clinicians.

STUDY TYPE

Retrospective.

POPULATION

In all, 144 patients with histologically confirmed EMC, 101 patients in a training cohort, and 43 patients in a test cohort.

FIELD STRENGTH/SEQUENCE

T₂ WI, contrast enhanced-T₁ WI, and diffusion-weighted imaging (DWI) at 3.0T MRI.

ASSESSMENT

Tumors were independently segmented images by two radiologists. Two pathologists reviewed the tissue specimens of the tumors to identify the existence of LVSI in consensus.

STATISTICAL TESTS

The intraclass correlation coefficient was used to test the reliability and least absolute shrinkage and selection operator (LASSO) regression for features selection and then developed a radiomics signature named Rad-score. A nomogram was developed in the training cohort. The diagnostic performance of the nomogram model was assessed by area under the curve (AUC) of the receiver operator characteristic (ROC) in the training and test cohort, respectively.

RESULTS

LVSI was identified in 32 patients (22.2%). Older age and high grade were correlated with LVSI at univariate analysis. There were five radiomics features that were identified as independent risk factors for LVSI by LASSO regression. Based on age, grade, and Rad-score, the AUC values of the nomogram model to predict LVSI in the training and test cohort were 0.820 (95% confidence interval [CI]: 0.725, 0.916; sensitivity: 82.6%, specificity: 72.9%), 0.807 (95% CI: 0.673, 0.941; sensitivity: 77.8%, specificity: 78.6%), respectively.

DATA CONCLUSION

The radiomic-based machine-learning model using a nomogram algorithm achieved high diagnostic performance for predicting LVSI of EMC preoperatively, which could enhance risk stratification and provide support for therapeutic decision-making.

LEVEL OF EVIDENCE

2.

TECHNICAL EFFICACY STAGE

3. J. Magn. Reson. Imaging 2020;52:1257-1262.

[Magnetic Resonance Imaging for local preoperative staging in endometrial cancer: Nantes local experience]

OBJECTIVES

To determine the diagnostic accuracy of magnetic resonance imaging (MRI) for local preoperative staging in endometrial cancer in our center (Centre Hospitalier Universitaire de Nantes: CHU), since the French National Cancer Institute's surgery recommendations publication in 2010, especially for the prediction of myometrial and cervical stromal invasion.

METHODS

Retrospective monocentric study of consecutive women operated of endometrial cancer in gynecology department of CHU de Nantes, who underwent preoperative pelvic MRI in our Radiology department from November 2010 to November 2016. MRI data collected from initial report and compared to surgical histological findings as gold standard.

RESULTS

Sixty-four patients were included. Deep myometrial invasion was present in 35 patients in MRI versus 34 patients on postoperative histology (5 false positives, 4 false negatives). Cervical stromal invasion was present in 9 patients in MRI versus 19 patients on postoperative histology (2 false positives, 12 false negatives). The sensitivity and the specificity were respectively 88.23% (95% confidence intervals (CI) [0.71-0.96]) and 83.33% (CI [0.64-0.93]) for the deep myometrial invasion; 36.84% (CI [0.17-0.61]) and 95.55% (CI [0.83-0.99]) for the cervical stromal invasion.

CONCLUSION

Our results were comparable to the literature data, with a low sensitivity for the cervical stromal invasion detection, driving us to change our MRI protocol with optional high-resolution T2 sequences perpendicular to the cervical canal if necessary.

FDG-PET for Assessment of Endometrial and Vulvar Cancer

Fluorodeoxyglucose positron emission tomography computed tomography (FDG-PET/CT) provides a comprehensive whole body evaluation in patients with endometrial and vulvar cancer. Here, we discuss the role of FDG-PET/CT in defining the disease extent in patients presenting with these cancers. Detection of lymph node and distant metastases has implications for staging, treatment planning, and patient prognosis. Procedures for image acquisition and interpretation for optimum accuracy and essential elements that should be included in the PET-CT report are described. Common imaging pitfalls are presented and illustrated with examples.

Integrated Bioinformatic Analysis of a Competing Endogenous RNA Network Reveals a Prognostic Signature in Endometrial Cancer

In endometrial carcinoma, the clinical outcome directly correlates with the TNM stage, but the lack of sufficient information prevents accurate prediction. The molecular mechanism underlying the competing endogenous RNA (ceRNA) hypothesis has not been investigated in endometrial cancer. Multi-bioinformatic analyses, including differentially expressed gene analysis, ceRNA network construction, Cox regression analysis, function enrichment analysis, and protein-protein network analysis, were performed on the sequence data acquired from The Cancer Genome Atlas (TCGA) data bank. A ceRNA network comprising 366 mRNAs, 27 microRNAs (miRNAs), and 66 long non-coding RNAs (lncRNAs) was established. Survival analysis performed with the univariate Cox regression analysis revealed nine lncRNAs with prognostic power in endometrial carcinoma. In multivariate Cox regression analysis, a signature comprising LINC00491, LINC00483, ADARB2-AS1, and C8orf49 showed remarkable prognostic power. Risk score and neoplasm status, but not TNM stage, were independent prognostic factors of endometrial carcinoma. A ceRNA network comprising differentially expressed mRNAs, miRNAs, and lncRNAs may reveal the molecular events involved in the progression of endometrial carcinoma. In addition, the signature with prognostic value may discriminate patients with increased risk for poor outcome, which may allow physicians to take accurate decisions.

No. 291-Epidemiology and Investigations forSuspected Endometrial Cancer

OBJECTIVE

To review the evidence relating to the epidemiology of endometrial cancer and its diagnostic workups.

OPTIONS

Women with possible endometrial cancer can undergo an endometrial evaluation by office biopsy, hysteroscopy, or dilatation and curettage. To assist in treatment planning, pelvic ultrasound, CT scan, or MRI may be considered.

OUTCOMES

The identification of optimal diagnostic tests to evaluate patients with possible endometrial cancer.

EVIDENCE

Published literature was retrieved through searches of PubMed, CINAHL, and The Cochrane Library, using appropriate controlled vocabulary (e.g., endometrial neoplasms) and key words (e.g., endometrium cancer, endometrial carcinoma). Results were restricted to systematic reviews, randomized control trials/controlled clinical trials, and observational studies. There were no date or language restrictions. Searches were updated on a regular basis and incorporated in the guideline to December 31, 2011. Grey (unpublished) literature was identified through searching the websites of health technology assessment and health technology assessment-related agencies, clinical practice guideline collections, clinical trial registries, national and international medical specialty societies, and recent conference abstracts.

VALUES

The quality of evidence was rated using the criteria described in the Report of the Canadian Task Force on Preventive Health Care (Table 1).

BENEFITS, HARMS, AND COSTS

This document is intended to guide the development of a standardized cost-effective investigation of patients with suspected endometrial cancer.

VALIDATION

The guideline was reviewed for accuracy by experts in pathology, radiation oncology, and medical oncology. Guideline content was also compared with relevant documents from the American Congress of Obstetricians and Gynecologists.

RECOMMENDATIONS

Preoperative tumor texture analysis on MRI predicts high-risk disease and reduced survival in endometrial cancer

BACKGROUND

Improved methods for preoperative risk stratification in endometrial cancer are highly requested by gynecologists. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in various cancer types, but largely unexplored in endometrial cancer.

PURPOSE

To explore whether tumor texture parameters from preoperative MRI are related to known prognostic features (deep myometrial invasion, cervical stroma invasion, lymph node metastases, and high-risk histological subtype) and to outcome in endometrial cancer patients.

STUDY TYPE

Prospective cohort study.

POPULATION/SUBJECTS

In all, 180 patients with endometrial carcinoma were included from April 2009 to November 2013 and studied until January 2017.

FIELD STRENGTH/SEQUENCES

Preoperative pelvic MRI including contrast-enhanced T₁ -weighted (T₁ c), T₂ -weighted, and diffusion-weighted imaging at 1.5T.

ASSESSMENT

Tumor regions of interest (ROIs) were manually drawn on the slice displaying the largest cross-sectional tumor area, using the proprietary research software TexRAD for analysis. With a filtration-histogram technique, the texture parameters standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis were calculated.

STATISTICAL TESTS

Associations between texture parameters and histological features were assessed by uni- and multivariable logistic regression, including models adjusting for preoperative biopsy status and conventional MRI findings. Multivariable Cox regression analysis was used for survival analysis.

RESULTS

High tumor entropy in apparent diffusion coefficient (ADC) maps independently predicted deep myometrial invasion (odds ratio [OR] 3.2, P lt  0.001), and high MPP in T₁ c images independently predicted high-risk histological subtype (OR 1.01, P = 0.004). High kurtosis in T₁ c images predicted reduced recurrence- and progression-free survival (hazard ratio [HR] 1.5, P lt  0.001) after adjusting for MRI-measured tumor volume and histological risk at biopsy.

DATA CONCLUSION

MRI-derived tumor texture parameters independently predicted deep myometrial invasion, high-risk histological subtype, and reduced survival in endometrial carcinomas, and thus, represent promising imaging biomarkers providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies in endometrial cancer.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1637-1647.

Inchworm sign of endometrial cancer on diffusion-weighted MRI: radiology-pathology correlation

AIM

To perform radiology-pathology correlation of the inchworm sign on diffusion-weighted imaging (DWI) in patients with endometrial cancer.

MATERIALS AND METHODS

Consecutive patients (345) with histopathologically proven endometrial cancer who underwent preoperative magnetic resonance imaging (MRI), including DWI images, and hysterectomy were included in the present study. The inchworm sign was defined as a hypointense stalk between hyperintense endometrial cancer and hypointense myometrium on DWI images. A genitourinary pathologist reviewed the resected specimen at the site of the inchworm sign.

RESULTS

The inchworm sign on DWI images was observed in 32 (9.3%) patients. On T2-weighted images, areas of hypointense stalk on DWI images showed hypointensity in 31 (97%) patients and hyperintensity in one (3%). Among them, the depth of myometrial invasion at histopathology was superficial (<50% myometrial invasion) in 28 (87.5%) patients and deep (≥50% myometrial invasion) in four (12.5%). As a result of histopathological investigation, the hypointense stalk of the inchworm sign was mainly composed of various degrees of stromal proliferation, including smooth muscle cells and metaplastic fibromuscular stroma, with or without intervening endometrial cancer.

CONCLUSION

The inchworm sign of endometrial cancer on DWI images usually indicated superficial myometrial invasion and was caused by a stalk composed of stromal proliferation with or without intervening endometrial cancer.

A Predictor of Tumor Recurrence in Patients With Endometrial Carcinoma After Complete Resection of the Tumor: The Role of Pretreatment Apparent Diffusion Coefficient

Objectives

The aim of this study was to assess the prognostic and incremental value of pretreatment apparent diffusion coefficient (ADC) values of tumors for the prediction of tumor recurrence after complete resection of the tumor in patients with endometrial cancer.

Methods

This study enrolled 210 patients with stages IA to IIIC endometrial cancer who had undergone complete resection of the tumor and pretreatment magnetic resonance imaging. The minimum and mean ADC values (ADCmin, ADCmean) of tumors and normalized ADC (nADCmin, nADCmean) were calculated from magnetic resonance imaging. The primary outcome was recurrence-free survival (RFS). Receiver operating characteristic analysis was performed to compare the diagnostic performance of ADC values of 4 types. The Kaplan-Meier method, log-rank tests, and Cox regression were used to explore associations between recurrence and the ADC values with adjustment for clinicopathological factors.

Results

In receiver operating characteristic curve analysis, the areas under the curve were significant for ADCmean and nADCmean predicting tumor recurrence but were not significant for ADCmin and nADCmin. Regarding univariate analysis, ADCmean and nADCmean were significantly associated with increased risk of recurrence. Multivariate analysis showed that ADCmean and nADCmean remained independently associated with shorter RFS. In the high-risk group, the RFS of patients with lower ADC values (ADCmean and nADCmean) was significantly shorter than that of patients in the higher ADC value group.

Conclusions

Pretreatment tumor ADCmean and nADCmean were important imaging biomarkers for predicting recurrence in patients after complete resection of the tumor. They might improve existing risk stratification.

Prediction of histological grade of endometrial cancer by means of MRI

OBJECTIVES

To evaluate the ability of MRI in predicting histological grade of endometrial cancer (EC).

METHODS

IRB-approved retrospective study; requirement for informed consent was waived. 90 patients with histologically proven EC who underwent preoperative MRI and surgery at our Institution between Sept2011 and Nov2016 were included. Myometrial invasion (</>50%) was assessed. Neoplasm and uterus volumes were estimated according to the ellipsoid formula; neoplasm/uterus volume ratio (N/U) was calculated. ADC maps were generated and histogram analysis was performed using commercially available software. MRI parameters were compared with the definitive histological grade (G1 = 28 patients, G2 = 29, G3 = 33) using ANOVA and Tukey-Kramer tests.

RESULTS

Deep myometrial invasion was significantly more frequent in G2-G3 lesions than in G1 ones (p < 0,005). N/U ratio was significantly higher for high-grade neoplasms (mean 0,08 for G1, 0,16 for G2 and 0,21 in G3; P = 0,002 for G1 vs. G2-G3); a cut off value of 0,13 enabled to distinguish G1 from G2-G3 lesions with 50% sensibility and 89% specificity. ADC values didn't show any statistically significant correlation with tumour grade.

CONCLUSIONS

N/U ratio >0.13 and deep myometrial invasion are significantly correlated with high grade EC, whereas ADC values are not useful for predicting EC grade.

In vivo MR spectroscopy predicts high tumor grade in endometrial cancer

Background In vivo magnetic resonance spectroscopy (MRS) enables non-invasive measurements of tumor metabolites. Choline-containing metabolites play a key role in tumor metabolism. Purpose To explore whether preoperative MRS-derived tumor choline levels are associated with clinical and histological features in endometrial carcinomas. Material and Methods Preoperative pelvic magnetic resonance imaging (MRI) (1.5T), including structural and diffusion-weighted imaging and localized multivoxel proton MR (1H-MR) spectroscopy, was performed in 77 prospectively included patients with histologically confirmed endometrial carcinomas. Relative levels of total choline-containing metabolites (tCho) in tumor and myometrium were measured using the ratios: tCho/Creatine; tCho/Water; and tCho/Noise. MRS parameters were analyzed in relation to histological subtype and grade, surgicopathological staging parameters, MRI-measured tumor volume, and tumor apparent diffusion coefficient (ADC) value and clinical outcome. Results Tumor tissue had significantly higher ratios for tCho/Creatine, tCho/Water, and tCho/Noise than normal myometrial tissue ( P < 0.001 for all). High tumor tCho/Water ratio was significantly associated with high tumor grade in endometrioid tumors ( P = 0.02). Tumor tCho/Creatine ratio was positively correlated to MRI-measured tumor volume (r_s = 0.25; P = 0.03). Conclusion High choline levels in tumor are associated with high-risk features. In vivo MRS may potentially aid in the preoperative risk stratification in endometrial cancer.

Magnetic Resonance Imaging in Local Staging of Endometrial Carcinoma: Diagnostic Performance, Pitfalls, and Literature Review

Aims and background

To assess the diagnostic accuracy of magnetic resonance imaging in local staging of endometrial carcinoma, and to review the results and pitfalls described in the literature.

Methods

Thirty women with a histological diagnosis of endometrial carcinoma underwent magnetic resonance imaging. Unenhanced T2-weighted and dynamic contrast-enhanced T1-weighted sequences were obtained. Hysterectomy and salpingo-oophorectomy was performed in all patients. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated for the detection of deep myometrial and cervical infiltration.

Results

For deep myometrial infiltration T2-weighted sequences reached a sensitivity of 85%, specificity of 76%, PPV of 73%, NVPof 87%, and accuracy of 80%, while contrast-enhanced scans reached a sensitivity of 90%, specificity of 80%, PPV of 82%, NPV of 89%, and accuracy of 85%. For cervical infiltration T2-weighted sequences reached a sensitivity of 75%, specificity of 88%, PPV of 50%, NPV of 96%, and accuracy of 87%, while contrast-enhanced scans reached a sensitivity of 100%, specificity of 94%, PPV of 75%, NPV of 100%, and accuracy of 95%.

Conclusions

Unenhanced and dynamic gadolinium-enhanced magnetic resonance allows accurate assessment of myometrial and cervical infiltration. Information provided by magnetic resonance imaging can define prognosis and management.

Evaluating Myometrial Invasion in Endometrial Cancer: Comparison of Reduced Field-of-view Diffusion-weighted Imaging and Dynamic Contrast-enhanced MR Imaging

PURPOSE

To compare the diagnostic ability of reduced FOV diffusion-weighted (DW) MR imaging with that of 3D dynamic contrast-enhanced (DCE) MR imaging in evaluating the depth of myometrial invasion in patients with endometrial cancer.

METHODS

Three tesla MR images including T₂-weighted imaging, reduced FOV DW imaging and 3D DCE MR imaging in sagittal and oblique axial (short axis) planes in 25 women with surgically proven endometrial cancer were retrospectively evaluated. The depth of myometrial invasion (stage S: < 50% vs stage D: ≥ 50%) on MR imaging was correlated with surgical pathology results.

RESULTS

The 25 endometrial cancers included 16 stage S and 9 stage D tumors. The depth of myometrial invasion could be accurately evaluated in 68% of the cases for T₂-weighted imaging, 92% for 3D DCE MR imaging, and 96% for reduced FOV DW imaging. In two patients with coexisting adenomyosis, both T₂-weighted imaging and 3D DCE MR imaging failed to reveal the deep myometrial invasion, and reduced FOV DW imaging clearly demonstrated the tumor margin in the cases. Combination of reduced FOV DW imaging reading together with T₂-weighted imaging improved the assessment of myometrial invasion with a diagnostic accuracy of up to 100%.

CONCLUSIONS

Addition of reduced FOV DW imaging may improve the staging accuracy of MR imaging for endometrial cancer in assessing the depth of myometrial invasion. Especially, reduced FOV DW imaging has an advantage in assessing the depth of myometrial invasion for patients with coexisting adenomyosis. Reduced FOV DW imaging can be an alternative to 3D DCE MR imaging in evaluating myometrial invasion of endometrial cancer without the use of contrast medium.

Endometrial Carcinoma: MR Imaging-based Texture Model for Preoperative Risk Stratification-A Preliminary Analysis

Purpose To evaluate the associations among mathematical modeling with the use of magnetic resonance (MR) imaging-based texture features and deep myometrial invasion (DMI), lymphovascular space invasion (LVSI), and histologic high-grade endometrial carcinoma. Materials and Methods Institutional review board approval was obtained for this retrospective study. This study included 137 women with endometrial carcinomas measuring greater than 1 cm in maximal diameter who underwent 1.5-T MR imaging before hysterectomy between January 2011 and December 2015. Texture analysis was performed with commercial research software with manual delineation of a region of interest around the tumor on MR images (T2-weighted, diffusion-weighted, and dynamic contrast material-enhanced images and apparent diffusion coefficient maps). Areas under the receiver operating characteristic curve and diagnostic performance of random forest models determined by using a subset of the most relevant texture features were estimated and compared with those of independent and blinded visual assessments by three subspecialty radiologists. Results A total of 180 texture features were extracted and ultimately limited to 11 features for DMI, 12 for LVSI, and 16 for high-grade tumor for random forest modeling. With random forest models, areas under the receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were estimated at 0.84, 79.3%, 82.3%, 81.0%, 76.7%, and 84.4% for DMI; 0.80, 80.9%, 72.5%, 76.6%, 74.3%, and 79.4% for LVSI; and 0.83, 81.0%, 76.8%, 78.1%, 60.7%, and 90.1% for high-grade tumor, respectively. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of visual assessment for DMI were 84.5%, 82.3%, 83.2%, 77.7%, and 87.8% (reader 3). Conclusion The mathematical models that incorporated MR imaging-based texture features were associated with the presence of DMI, LVSI, and high-grade tumor and achieved equivalent accuracy to that of subspecialty radiologists for assessment of DMI in endometrial cancers larger than 1 cm. However, these preliminary results must be interpreted with caution until they are validated with an independent data set, because the small sample size relative to the number of features extracted may have resulted in overfitting of the models. ^© RSNA, 2017 Online supplemental material is available for this article.

What Is the Best Preoperative Imaging for Endometrial Cancer?

Although endometrial cancer is surgicopathologically staged, preoperative imaging is recommended for diagnostic work-up to tailor surgery and adjuvant treatment. For preoperative staging, imaging by transvaginal ultrasound (TVU) and/or magnetic resonance imaging (MRI) is valuable to assess local tumor extent, and positron emission tomography-CT (PET-CT) and/or computed tomography (CT) to assess lymph node metastases and distant spread. Preoperative imaging may identify deep myometrial invasion, cervical stromal involvement, pelvic and/or paraaortic lymph node metastases, and distant spread, however, with reported limitations in accuracies and reproducibility. Novel structural and functional imaging techniques offer visualization of microstructural and functional tumor characteristics, reportedly linked to clinical phenotype, thus with a potential for improving risk stratification. In this review, we summarize the reported staging performances of conventional and novel preoperative imaging methods and provide an overview of promising novel imaging methods relevant for endometrial cancer care.

Magnetic Resonance Imaging of Pelvic Masses: A Compartmental Approach

Magnetic resonance imaging (MRI) is often "one stop shop" for evaluating female pelvic masses that helps in diagnosis, staging, and restaging of these tumors. A pelvic mass can arise from any tissue present within the pelvis. Although most masses in the female pelvis arise from the reproductive organs, masses may also arise from the gastrointestinal tract, urinary system, adjacent soft tissues, peritoneum, etc. It may not always be possible to determine the site of origin or distinguish these masses based on imaging characteristics. However, familiarity with the clinicopathologic and MRI features of most common pelvic masses helps in narrowing the differential diagnosis. Diagnosis of these masses needs a holistic approach as required for any tumor including clinical history, laboratory data, and imaging characteristics. We focus on MRI characteristics of commonly encountered pelvic masses. A compartmental imaging approach is discussed in this article that helps in identifying and characterizing these masses.

Diffusion-Weighted Mri of Postmenopausal Women with Vaginal Bleeding and Endometrial Thickening: Differentiation of Benign and Malignant Lesions

Purpose:

To investigate the feasibility of diffusion-weighted magnetic resonance imaging (DWI) with apparent diffusion coefficient (ADC) values in differentiating endometrial cancer from benign endometrial lesions in postmenopausal patients with vaginal bleeding and endometrial thickening and to predict the depth of myometrial invasion in endometrial cancer.

Materials and Methods:

Postmenopausal patients with vaginal bleeding and endometrial thickening were enrolled in this prospective study. T2-weighted, pre- and postcontrast T1-weighted and diffusion-weighted images were obtained. The ADC values of all the patients with endometrial pathologies were recorded. The staging accuracies of DWI and postcontrast T1-weighted images in the assessment of myometrial invasion were evaluated in histopathologically proven endometrial cancer patients.

Results:

Fifty-two patients (mean age: 57 ± 10, range: 41–79) were enrolled in the study. Thirty-eight of the lesions were benign (27 as hyperplasia and endometritis; 11 as polyps). Fourteen of the 52 endometrial lesions were pathologically proven as cancers and underwent hysterectomy, and all the specimens were reported as endometrioid adenocarcinomas. The mean ADC value (10^–3 mm²/second) of cancer (0.88 ± 0.10) was significantly lower than that of benign lesions (1.78 ± 0.27, p = 0,001). There was no significant difference between ADC values of endometrial tissue in patients with FIGO stage 1A (0.87 ± 0.11, n = 9) and FIGO stage 1B (0.91 ± 0.07, n = 5). The staging accuracy was 92.9 per cent (13/14) for DWI and 85.7 per cent (12/14) for postcontrast T1-weighted images.

Conclusion:

ADC values allow benign endometrial lesions to be differentiated from endometrial cancer in postmenopausal patients but do not correlate with the depth of myometrial invasion and histological tumor grading.

FDG PET-CT of gynecologic cancers: pearls and pitfalls

FDG PET-CT plays an important role in treatment planning and in prognosis assessment of gynecologic cancer patients. Detection of hypermetabolic tissue with FDG PET, when combined with the high spatial resolution of CT, results in improved cancer detection and localization not afforded by either modality independently. This article is a primer for a radiologist performing PET-CT on gynecologic cancer patients and includes the imaging protocol, normal pattern of FDG distribution in the female pelvis and the lymph node drainage pathways from the gynecologic organs. Clinically relevant imaging findings that should be included in the report are discussed. Case examples illustrate how potential errors in exam interpretation can be avoided by concurrently performing a high-quality diagnostic CT with the FDG PET scan and by analyzing both the stand-alone and the fusion images.

Preoperative tumor size at MRI predicts deep myometrial invasion, lymph node metastases, and patient outcome in endometrial carcinomas

Supplemental digital content is available in the text.

Objective

The aim of this study was to explore the relation between preoperative tumor size based on magnetic resonance imaging (MRI) and the surgical pathologic staging parameters (deep myometrial invasion, cervical stroma invasion, and metastatic lymph nodes) and to assess the prognostic impact of tumor size in endometrial carcinomas. Interobserver variability for the different tumor size measurements was also assessed.

Methods/Materials

Preoperative pelvic MRI of 212 patients with histologically confirmed endometrial carcinomas was read independently by 3 radiologists. Maximum tumor diameters were measured in 3 orthogonal planes (anteroposterior, transverse, and craniocaudal planes [CC]), and tumor volumes were estimated. Tumor size was analyzed in relation to surgical staging results and patient survival. The multivariate analyses were adjusted for preoperative risk status based on endometrial biopsy. Intraclass correlation coefficients and receiver operating characteristics curves for the different tumor measurements were also calculated.

Results

Anteroposterior tumor diameter independently predicted deep myometrial invasion (P < 0.001), whereas CC tumor diameter tended to independently predict lymph node metastases (P = 0.06). Based on receiver operating characteristic curves, the following tumor size cutoff values were identified: anteroposterior diameter greater than 2 cm predicted deep myometrial invasion (unadjusted odds ratio [OR], 12.4; P < 0.001; adjusted OR, 6.7; P < 0.001) and CC diameter greater than 4 cm predicted lymph node metastases (unadjusted OR, 6.2; P < 0.001; adjusted OR, 4.9; P = 0.009). Large tumor size was associated with reduced progression/recurrence-free survival (P ≤ 0.005 for all size parameters), and CC diameter had an independent impact on survival (adjusted hazards ratio, 1.04; P = 0.009). The interobserver variability for the different size measurements was very low (intraclass correlation coefficient, 0.78–0.85).

Conclusions

Anteroposterior tumor diameter greater than 2 cm predicts deep myometrial invasion, and CC tumor diameter greater than 4 cm predicts lymph node metastases. Tumor size is a strong prognostic factor in endometrial carcinomas. Preoperative tumor measurements based on MRI may potentially improve preoperative risk stratification models and thus enable better tailored surgical treatment in endometrial cancer.

Optimization of MR imaging for pretreatment evaluation of patients with endometrial and cervical cancer

Endometrial and cervical cancer are the most common gynecologic malignancies in the world. Accurate staging of cervical and endometrial cancer is essential to determine the correct treatment approach. The current International Federation of Gynecology and Obstetrics (FIGO) staging system does not include modern imaging modalities. However, magnetic resonance (MR) imaging has proved to be the most accurate noninvasive modality for staging endometrial and cervical carcinomas and often helps with risk stratification and making treatment decisions. Multiparametric MR imaging is increasingly being used to evaluate the female pelvis, an approach that combines anatomic T2-weighted imaging with functional imaging (ie, dynamic contrast material-enhanced and diffusion-weighted imaging). MR imaging helps guide treatment decisions by depicting the depth of myometrial invasion and cervical stromal involvement in patients with endometrial cancer and tumor size and parametrial invasion in those with cervical cancer. However, its accuracy for local staging depends on technique and image quality, namely thin-section high-resolution multiplanar T2-weighted imaging with simple modifications, such as double oblique T2-weighting supplemented by diffusion weighting and contrast enhancement.

Magnetic Resonance Imaging of Benign and Malignant Uterine Neoplasms

Benign and malignant uterine masses can be seen in the women. Some of these are asymptomatic and incidentally discovered, whereas others can be symptomatic. With the soft tissue contrast resolution magnetic resonance imaging can render a definitive diagnosis, which can further help streamline patient management. In this article we show magnetic resonance imaging examples of benign and malignant masses of the uterus and their treatment strategies.

Diagnostic accuracy of preoperative tests for lymph node status in endometrial cancer: a systematic review

Background: Approximately 72% of endometrial cancers are FIGO stage I at diagnosis and about 10% have lymph node metastases. An ideal diagnostic test for nodal disease would be able to prevent both overtreatment (i.e. unnecessary lymphadenectomy) and undertreatment (i.e. withholding lymphadenectomy or adjuvant postoperative treatment to patients with lymph node metastases). Objectives: In this review we compare the accuracy of preoperative tests (computed tomography, magnetic resonance imaging, positron emission tomography-computed tomography, CA-125 serum levels, and ultrasonography) for the detection of lymph node metastases in endometrial cancers with the final histopathologic diagnosis after complete pelvic and para-aortic lymphadenectomy as the gold standard. Method: A systematic search in MEDLINE (using PubMed), Embase and The Cochrane Library was performed up to 23 July 2012. Results: We found one article that met our inclusion criteria for computed tomography, none for magnetic resonance imaging, 2 for positron emission tomography/computed tomography), 2 for CA-125 and none for ultrasonography. Conclusions: Due to the lack of high-quality articles on a preoperative test for lymph node status in endometrial cancer, no proper comparison between these modalities can be made.

Diagnostic Value of Pelvic MRI for Assessment of the Depth of Myometrial Invasion and Cervical Involvement in Endometrial Cancer: Comparison of New Versus Old FIGO Staging

BACKGROUND

Endometrial carcinoma is a highly prevalent gynecologic malignancy. The International Federation of Gynecology and Obstetrics (FIGO) staging system underwent significant revision on 2009. Key changes in the FIGO staging system include simplification of stage I endometrial cancer and removal of cervical mucosal invasion as a separate stage. MRI is a noninvasive diagnostic method for preoperative staging of endometrial cancer.

OBJECTIVES

The main purpose of this study was to investigate the diagnostic efficacy of pelvic MRI in determining the depth of myometrial invasion and cervical involvement in endometrial carcinoma. The other aim was to compare the accuracy of pelvic MRI using the old and new FIGO staging systems in endometrial carcinoma.

PATIENTS AND METHODS

Between November 2010 and January 2012, 54 patients underwent primary surgical staging in our department due to endometrial adenocarcinoma. Pre-operative pelvic MRI was performed and MRI staging was done according to old and new FIGO staging, separately. The sensitivity, specificity, positive and negative predictive values as well as the accuracy of MRI for deep myometrial invasion and cervical infiltration were calculated. MRI accuracy was also compared for old and new FIGO staging. Pathological staging was the standard of reference.

RESULTS

The mean age was 53.31 (SD = 11.52) and the most common histological subtype was the endometrioid type of endometrial adenocarcinoma (90.8%). In the evaluation of deep tumoral invasion of the myometrium (> 50%), sensitivity, specificity, diagnostic accuracy and positive and negative predictive values of MRI were 82.35%, 94.59%, 90.74%, 87.5% and 92.1%, respectively. For cervical stromal involvement, these values were 54.54%, 100%, 90.74%, 100% and 89.58%, respectively. In case of cervical mucosal involvement (in old FIGO staging), the positive predictive value was only 50% and the accuracy decreased to 74.07%. Agreement between MRI and the final histology using the old and new FIGO classification was appropriate with Kappa = 0.62 and 0.72, respectively (P < 0.001).

CONCLUSION

Using 2009 FIGO classification increases the accuracy of pelvic MR imaging for preoperative staging of patients with early stages of endometrial cancer.

Radiological assessment of gynecologic malignancies

Patients with gynecologic malignancies are evaluated with a combination of imaging modalities including ultrasonography (US), computed tomography (CT), and magnetic resonance (MR) imaging. US has a primary role in detecting and characterizing endometrial and adnexal pathology. CT is one of the primary modalities in staging malignancy and detecting recurrence. MR imaging is characterized by superior contrast resolution and specificity. This article reviews the role of radiologic imaging for the characterization of gynecologic masses and for staging, planning, and monitoring treatment, as well as for the assessment of tumor recurrence of the most common gynecologic malignancies.

[Diagnostic imaging of menometrorrhagia]

Menometrorrhagia is a frequent cause of medical consulting. After a clinical examination showing the uterine origin of bleeding and that excludes a cervical or vulvo-vaginal origin, transvaginal sonography (TVS) represents the first-line technique examination. TVS allows to identify endometrial diseases (atrophy, polyps or diffuse hyperplasia), endometrial carcinoma, myometrial disorders (adenomyosis, leiomyoma or vascular abnormalities), and adnexal disorders. Color Doppler sonography and hysterosonography are useful complementary tools for ultrasound performance improvement. MR imaging should be performed if TVS is not contributive or is highly recommended for staging of uterine cancers. All these techniques provide useful information for optimal planning treatment.

Preoperative assessment of deep myometrial and cervical invasion in endometrial carcinoma: Comparison of magnetic resonance imaging and histopathologic evaluation

This study aimed to evaluate the accuracy of magnetic resonance imaging (MRI) in the detection of deep myometrial invasion and cervical extension by endometrial carcinoma. This prospective study included 101 patients with histologically documented endometrial carcinoma, between July 1998 and April 2004. The findings of preoperative pelvic MRI were compared with histological diagnosis. From 101 cases studied by pelvic MRI, 43 were classified as deep myometrial invasion (>or=50% of myometrium), where the pathological evaluation confirmed as having deep myometrial invasion. Cervical extension in the MRI study was found in 19 cases. Pathologic study found cervical extension and/or invasion in 31 cases including all cases identified by MRI. The accuracy, sensitivity and specificity of MRI were 95%, 89%, 100%, detecting deep myometrial invasion and 88%, 61%, 100%, detecting cervical invasion, respectively. The high accuracy achieved makes MRI an adequate method for determine the depth of myometrial and cervical invasion in endometrial carcinoma.