The Diagnostic Value of MRI for Preoperative Staging in Patients with Endometrial Cancer: A Meta-Analysis

Magnetic resonance imaging-based radiomics model for preoperative assessment of risk stratification in endometrial cancer

BACKGROUND

Preoperative risk stratification is significant for the management of endometrial cancer (EC) patients. Radiomics based on magnetic resonance imaging (MRI) in combination with clinical features may be useful to predict the risk grade of EC.

AIM

To construct machine learning models to predict preoperative risk stratification of patients with EC based on radiomics features extracted from MRI.

METHODS

The study comprised 112 EC patients. The participants were randomly separated into training and validation groups with a 7:3 ratio. Logistic regression analysis was applied to uncover independent clinical predictors. These predictors were then used to create a clinical nomogram. Extracted radiomics features from the T2-weighted imaging and diffusion weighted imaging sequences of MRI images, the Mann-Whitney U test, Pearson test, and least absolute shrinkage and selection operator analysis were employed to evaluate the relevant radiomic features, which were subsequently utilized to generate a radiomic signature. Seven machine learning strategies were used to construct radiomic models that relied on the screening features. The logistic regression method was used to construct a composite nomogram that incorporated both the radiomic signature and clinical independent risk indicators.

RESULTS

Having an accuracy of 0.82 along with an area under the curve (AUC) of 0.915 [95% confidence interval (CI): 0.806-0.986], the random forest method trained on radiomics characteristics performed better than expected. The predictive accuracy of radiomics prediction models surpassed that of both the clinical nomogram (AUC: 0.75, 95%CI: 0.611-0.899) and the combined nomogram (AUC: 0.869, 95%CI: 0.702-0.986) that integrated clinical parameters and radiomic signature.

CONCLUSION

The MRI-based radiomics model may be an effective tool for preoperative risk grade prediction in EC patients.

Training radiology residents to evaluate deep myometrial invasion in endometrial cancer patients on MRI: A learning curve study

PURPOSE

To evaluate the impact of a four-month training program on radiology residents' diagnostic accuracy in assessing deep myometrial invasion (DMI) in endometrial cancer (EC) using MRI.

METHOD

Three radiology residents with limited EC MRI experience participated in the training program, which included conventional didactic sessions, case-centric workshops, and interactive classes. Utilizing a training dataset of 120 EC MRI scans, trainees independently assessed subsets of cases over five reading sessions. Each subset consisted of 30 scans, the first and the last with the same cases, for a total of 150 reads. Diagnostic accuracy metrics, assessment time (rounded to the nearest minute), and confidence levels (using a 5-point Likert scale) were recorded. The learning curve was obtained plotting the diagnostic accuracy of the three trainees and the average over the subsets. Anatomopathological results served as the reference standard for DMI presence.

RESULTS

The three trainees exhibited heterogeneous starting point, with a learning curve and a trend to more homogeneous performance with training. The diagnostic accuracy of the average trainee raised from 64 % (56 %-76 %) to 88 % (80 %-94 %) across the five subsets (p < 0.001). Reductions in assessment time (5.92 to 4.63 min, p < 0.018) and enhanced confidence levels (3.58 to 3.97, p = 0.12) were observed. Improvements in sensitivity, specificity, positive predictive value, and negative predictive value were noted, particularly for specificity which raised from 56 % (41 %-68 %) in the first to 86 % (74 %-94 %) in the fifth subset (p = 0.16). Although not reaching statistical significance, these advancements aligned the trainees with literature performance benchmarks.

CONCLUSIONS

The structured training program significantly enhanced radiology residents' diagnostic accuracy in assessing DMI for EC on MRI, emphasizing the effectiveness of active case-based training in refining oncologic imaging skills within radiology residency curricula.

Estrogen/Progesterone Receptor Expression and Cancer Antigen 125 Level as Preoperative Predictors to Estimate Lymph Node Metastasis in Endometrioid Endometrial Cancer

Loss of estrogen receptor/progesterone receptor (ER/PR) in endometrial cancer (EC) is associated with tumor progression and poor outcomes. Elevated pretreatment cancer antigen 125 (CA 125) level is a risk factor for lymph node metastasis (LNM). We evaluated whether the combination of ER/PR expression and CA 125 level could be used as a biomarker to predict LNM. We retrospectively investigated patients with endometrioid EC who underwent complete staging surgery during January 2015 to December 2020. We analyzed ER/PR status using immunohistochemical staining, and quantified its expression using the sum of both ER/PR H -scores. Receiver operating characteristic curves were used to identify optimal cutoff values of H -score and CA 125 levels for predicting LNM. A nomogram for predicting LNM was constructed and validated by bootstrap resampling. In 396 patients, the optimal cutoff values of the ER/PR H -score and CA 125 were 407 (area under the receiver operating characteristic curve: 0.645, P =0.001) and 40 U/mL (area under the receiver operating characteristic curve: 0.762, P <0.001), respectively. Multivariate analysis showed that CA 125 ≥40 UmL (odds ratio: 10.02; 95% CI: 4.74-21.18) and ER/PR H -score <407 (odds ratio: 4.20; 95% CI: 1.55-11.32) were independent predictors. An LNM predictive nomogram was constructed using these 2 variables and our model yielded a negative predictive value and negative likelihood ratio of 98.3% and 0.14, respectively. ER/PR expression with pretreatment CA 125 levels can help estimate LNM risk and aid in decision-making regarding the need for lymphadenectomy in patients with endometrioid EC.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups. Employing univariate and multivariate logistic regression, we identified independent predictors of FTN and MFTN, and subsequently develop a nomogram for FTN and a risk score system (RSS) for MFTN prediction. We assessed performance of nomogram through its discrimination, calibration, and clinical utility. The diagnostic performance of the RSS for MFTN was further compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS). The nomogram, integrating independent predictors, demonstrated robust discrimination and calibration in differentiating FTN from non-FTN in both training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Key risk factors for differentiating MFTN from BFTN included tumor size, restricted diffusion, and cystic degeneration. The AUC of the RSS for MFTN prediction was 0.902 (95% CI 0.798-0.971), outperforming five TIRADS with a sensitivity of 73.3%, specificity of 95.1%, accuracy of 92.4%, and positive and negative predictive values of 68.8% and 96.1%, respectively, at the optimal cutoff. MRI-based models demonstrate excellent diagnostic performance for preoperative predicting of FTN and MFTN, potentially guiding clinicians in optimizing therapeutic decision-making.

Accuracy of MRI in predicting deep myometrial invasion in endometrial cancer and the influence of leiomyoma, adenomyosis and the microcystic elongated and fragmented tumour pattern

INTRODUCTION

The most common form of endometrial cancer is Type 1 endometrioid adenocarcinoma. Depth of myometrial invasion is the most important prognostic factor correlating with overall patient survival. The objective was to investigate how accurate magnetic resonance imaging (MRI) is in predicting the depth of myometrial invasion in preoperative assessment, and the influence of leiomyoma and/or adenomyosis, or microcystic, elongated and fragmented (MELF) pattern of invasion on MRI diagnostic performance.

METHOD

Retrospective audit of 235 endometrial cancer patients from the regional Gynaecology Oncology multidisciplinary meeting at Auckland City Hospital, between January 2020 and January 2021. Radiologist assigned stage was compared to histopathology. Presence of leiomyoma, adenomyosis and MELF pattern evaluated followed by analysis under a Biostatistician's supervision.

RESULTS

Overall MRI diagnostic accuracy for depth of myometrial invasion was 86%. For deep myometrial invasion, MRI had a sensitivity of 72% and specificity 91%. Out of the misreported 32/235 cases, 16 demonstrated fibroids and/or adenomyosis leading to a sensitivity of 57% and specificity 93% for deep invasion, compared with 94% and 74% respectively in the population without, demonstrating statistical significance. Thirty seven cases with MELF pattern of invasion showed a sensitivity of 81% and specificity 80% for deep invasion, compared with 63% and 92% respectively in the group without, demonstrating no statistical significance.

CONCLUSION

MRI assessment of the depth of myometrial invasion in endometrial cancer has high accuracy. In the presence of background uterine fibroids/adenomyosis, pre-operative MRI accuracy of evaluating deep invasion shows a statistically significant reduction.

Role of ultrasound in detection of lymph-node metastasis in gynecological cancer: systematic review and meta-analysis

OBJECTIVE

To assess the diagnostic performance of transvaginal sonography (TVS) for the preoperative evaluation of lymph-node metastasis in gynecological cancer.

METHODS

This was a systematic review and meta-analysis of studies published between January 1990 and May 2023 evaluating the role of ultrasound in detecting pelvic lymph-node metastasis (index test) in gynecological cancer, using histopathological analysis as the reference standard. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and diagnostic odds ratio were estimated.

RESULTS

The literature search identified 2638 citations. Eight studies reporting on a total of 967 women were included. The mean prevalence of pelvic lymph-node metastasis was 24.2% (range, 14.0-65.6%). The risk of bias was low for most domains assessed. Pooled sensitivity, specificity and diagnostic odds ratio of TVS were 41% (95% CI, 26-58%), 98% (95% CI, 93-99%) and 32 (95% CI, 14-72), respectively. High heterogeneity was found between studies for both sensitivity and specificity.

CONCLUSION

TVS showed a high pooled specificity for the detection of pelvic lymph-node metastasis in gynecological cancer, but pooled sensitivity was low. © 2024 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Multiparametric MRI radiomics improves preoperative diagnostic performance for local staging in patients with endometrial cancer

PURPOSE

To determine whether multiparametric magnetic resonance imaging (MRI) radiomics-based machine learning methods can improve preoperative local staging in patients with endometrial cancer (EC).

METHODS

Data of patients with histologically confirmed EC who underwent preoperative MRI were retrospectively analyzed and divided into a training or test set. Radiomic features extracted from multiparametric MR images were used to train and test the prediction of deep myometrial invasion (DMI) and cervical stromal invasion (CSI). Two radiologists assessed the presence of DMI and CSI on conventional MR images. A combined model incorporating a radiomic signature and conventional MR images was constructed and presented as a nomogram. Performance of the predictive models was assessed using the area under curve (AUC) in the receiver operating curve analysis and pairwise comparison using DeLong's test with Bonferroni correction.

RESULTS

This study included 198 women (training set = 138, test set = 60). Conventional MRI achieved AUCs of 0.837 and 0.799 for detecting DMI and 0.825 and 0.858 for detecting CSI in the training and test sets, respectively. The nomogram achieved AUCs of 0.928 and 0.869 for detecting DMI and 0.913 and 0.937 for detecting CSI in the training and test sets, respectively. The ability of the nomogram to detect DMI and CSI in the two sets was superior to that of conventional MRI (adjusted p < 0.05), except for the ability to detect CSI in the test set (adjusted p > 0.05).

CONCLUSION

A nomogram incorporating radiomics signature into conventional MRI improved the efficacy of preoperative local staging of EC.

Diagnostic Accuracy of Transvaginal Ultrasound and Magnetic Resonance Imaging for the Detection of Myometrial Infiltration in Endometrial Cancer: A Systematic Review and Meta-Analysis

In endometrial cancer (EC), deep myometrial invasion (DMI) is a prognostic factor that can be evaluated by various imaging methods; however, the best method of choice is uncertain. We aimed to compare the diagnostic performance of two-dimensional transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) in the preoperative detection of DMI in patients with EC. Pubmed, Embase and Cochrane Library were systematically searched in May 2023. We included original articles that compared TVS to MRI on the same cohort of patients, with final histopathological confirmation of DMI as reference standard. Several subgroup analyses were performed. Eighteen studies comprising 1548 patients were included. Pooled sensitivity and specificity were 76.6% (95% confidence interval (CI), 70.9-81.4%) and 87.4% (95% CI, 80.6-92%) for TVS. The corresponding values for MRI were 81.1% (95% CI, 74.9-85.9%) and 83.8% (95% CI, 79.2-87.5%). No significant difference was observed (sensitivity: p = 0.116, specificity: p = 0.707). A non-significant difference between TVS and MRI was observed when no-myometrium infiltration vs. myometrium infiltration was considered. However, when only low-grade EC patients were evaluated, the specificity of MRI was significantly better (p = 0.044). Both TVS and MRI demonstrated comparable sensitivity and specificity. Further studies are needed to assess the presence of myometrium infiltration in patients with fertility-sparing wishes.

Evaluation of pre-therapeutic imaging work-up in the staging of endometrial cancer: Interest in a systematic second opinion in a cancer center

RATIONALE AND OBJECTIVES

To evaluate the interest of a systematic second opinion in quality assessment and FIGO staging in the pretherapeutic imaging work-up.

MATERIALS AND METHODS

A retrospective observational study was conducted on 156 patients who underwent surgery for endometrioid cancer in our institution. 42 % had their initial MRI scans performed in expert centers (University Hospital and Cancer center) and 58 % in non-expert centers. Quality assessment, concordances between initial reports, and second opinions by a junior and a senior ICL radiologist versus histopathological data were analyzed.

RESULTS

MRI scans performed in expert centers were more complete and more likely to be rated as higher quality. The overall accuracy of T staging from initial reports vs gold standard was 0.59 (95 % CI, 0.46-0.71) in expert centers and 0.49 (95 % CI, 0.38-0.60) in non-expert centers. The overall accuracy and Kappa of a second opinion for FIGO 2009 staging from expert center and non-expert center examinations were 0.61 (95 % CI, 0.48-0.72) vs 0.50 (95 % CI, 0.39-0.60) and 0.37 vs 0.27 for junior reader and 0.62 (95 % CI, 0.49-0.74) vs 0.48 (95 % CI, 0.37-0.58) and 0.39 vs 0.24 for senior reader, respectively. There was also a significant lower confidence level of the junior radiologist in MRI FIGO staging for non-expert center examinations (p 0.003).

CONCLUSION

Accuracy in the FIGO 2009 staging and quality assessment are higher for MR examinations performed from expert centers than in non-expert centers. A systematic second opinion by radiologists in expert centers should be proposed before pre-treatment multidisciplinary consultation.

Artificial Intelligence and Radiomics for Endometrial Cancer MRI: Exploring the Whats, Whys and Hows

Endometrial cancer (EC) is intricately linked to obesity and diabetes, which are widespread risk factors. Medical imaging, especially magnetic resonance imaging (MRI), plays a major role in EC assessment, particularly for disease staging. However, the diagnostic performance of MRI exhibits variability in the detection of clinically relevant prognostic factors (e.g., deep myometrial invasion and metastatic lymph nodes assessment). To address these challenges and enhance the value of MRI, radiomics and artificial intelligence (AI) algorithms emerge as promising tools with a potential to impact EC risk assessment, treatment planning, and prognosis prediction. These advanced post-processing techniques allow us to quantitatively analyse medical images, providing novel insights into cancer characteristics beyond conventional qualitative image evaluation. However, despite the growing interest and research efforts, the integration of radiomics and AI to EC management is still far from clinical practice and represents a possible perspective rather than an actual reality. This review focuses on the state of radiomics and AI in EC MRI, emphasizing risk stratification and prognostic factor prediction, aiming to illuminate potential advancements and address existing challenges in the field.

The value of machine learning in preoperative identification of lymph node metastasis status in endometrial cancer: a systematic review and meta-analysis

Background

The early identification of lymph node metastasis status in endometrial cancer (EC) is a serious challenge in clinical practice. Some investigators have introduced machine learning into the early identification of lymph node metastasis in EC patients. However, the predictive value of machine learning is controversial due to the diversity of models and modeling variables. To this end, we carried out this systematic review and meta-analysis to systematically discuss the value of machine learning for the early identification of lymph node metastasis in EC patients.

Methods

A systematic search was conducted in Pubmed, Cochrane, Embase, and Web of Science until March 12, 2023. PROBAST was used to assess the risk of bias in the included studies. In the process of meta-analysis, subgroup analysis was performed according to modeling variables (clinical features, radiomic features, and radiomic features combined with clinical features) and different types of models in various variables.

Results

This systematic review included 50 primary studies with a total of 103,752 EC patients, 12,579 of whom had positive lymph node metastasis. Meta-analysis showed that among the machine learning models constructed by the three categories of modeling variables, the best model was constructed by combining radiomic features with clinical features, with a pooled c-index of 0.907 (95%CI: 0.886-0.928) in the training set and 0.823 (95%CI: 0.757-0.890) in the validation set, and good sensitivity and specificity. The c-index of the machine learning model constructed based on clinical features alone was not inferior to that based on radiomic features only. In addition, logistic regression was found to be the main modeling method and has ideal predictive performance with different categories of modeling variables.

Conclusion

Although the model based on radiomic features combined with clinical features has the best predictive efficiency, there is no recognized specification for the application of radiomics at present. In addition, the logistic regression constructed by clinical features shows good sensitivity and specificity. In this context, large-sample studies covering different races are warranted to develop predictive nomograms based on clinical features, which can be widely applied in clinical practice.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42023420774.

Diagnostic Performance of Preoperative Imaging in Endometrial Cancer

BACKGROUND

Endometrial cancer is one of the most common gynecological malignancies. Because the findings mentioned in radiogram interpretation reports issued by diagnostic radiologists influence treatment strategies, we aimed to evaluate the diagnostic accuracy of preoperative computed tomography (CT) and magnetic resonance imaging (MRI) interpretation results in clinically relevant settings.

METHODS

The clinical records of patients diagnosed with endometrial cancer treated at Tohoku University Hospital from January 2012 to December 2021 were reviewed. The preoperative and pathologically estimated cancer stages were compared based on the results mentioned in the radiogram interpretation report.

RESULTS

The preoperative and postoperative cancer stages were concordant in 70.0% of the patients. By contrast, the cancer stage was underdiagnosed and overdiagnosed in 21.7% and 8.2% of the patients, respectively. The sensitivities of MRI for deep myometrial invasion, cervical stromal invasion, vaginal invasion, and adnexal metastasis were 65.1%, 58.2%, 33.3%, and 18.4%, respectively. The sensitivity and specificity for pelvic lymph node metastasis using a combination of CT and MRI were 40.9% and 98.4%, respectively. Those for para-aortic lymph node metastases using CT were 37.0% and 99.5%, respectively.

CONCLUSIONS

The low sensitivity observed in this study clarified the limitations of preoperative diagnostic performance in current clinical practice.

Transvaginal ultrasound versus magnetic resonance imaging for preoperative assessment of myometrial infiltration in patients with low-grade endometrioid endometrial cancer: A systematic review and head-to-head meta-analysis

PURPOSE

We aimed to compare the diagnostic performance of magnetic resonance imaging (MRI) and transvaginal ultrasound (TVS) for detecting myometrial invasion (MI) in patients with low-grade endometrioid endometrial carcinoma.

METHODS

A comprehensive search of MEDLINE (Pubmed), Web of Science, Embase and Scopus (from January 1990 to December 2022) was performed for articles comparing TVS and MRI in the evaluation of myometrial infiltration in low-grade (grade 1 or 2) endometrioid endometrial carcinoma in the same group of patients. We used QUADAS-2 tool for assessing the risk of bias of studies.

RESULTS

We found 104 citations in our extensive research. Four articles were ultimately included in the meta-analysis, after excluding 100 reports. All articles were considered low risk of bias in most of the domains assessed in QUADAS-2. We observed that pooled sensitivity and specificity for detecting deep MI were 65% (95% confidence interval [CI] = 54%-75%) and 85% (95% CI = 79%-89%) for MRI, and 71% (95% CI = 63%-78%) and 76% (95% CI = 67%-83%) for TVS, respectively. No statistical differences were found between both imaging techniques (p > 0.05). We observed low heterogeneity for sensitivity and high for specificity regarding TVS; and moderate for both sensitivity and specificity in case of MRI.

CONCLUSIONS

The diagnostic performance of TVS and MRI for the evaluation of deep MI in women with low-grade endometrioid endometrial cancer is similar. However, further research is needed as the number of studies is scanty.

Analysis of correlation of pre-therapeutic assessment and the final diagnosis in endometrial cancer: role of tumor volume in the magnetic resonance imaging

Objective

To evaluate whether the introduction of tumor volume as new parameter in the MRI assessment could improve both concordance between preoperative and postoperative staging, and the identification of histological findings.

Methods

A retrospective observational study with 127 patients with endometrial cancer (EC) identified between 2016 and 2021 at the Juan Ramon Jimenez University Hospital, Huelva (Spain) was carried out. Tumor volume was measured in three ways. Analyses of Receiver Operating Characteristic (ROC) curve and the area under the curve (AUC) were performed.

Results

Although preoperative MRI had an 89.6% and 66.7% sensitivity for the detection of deep mucosal invasion and cervical stroma infiltration, preoperative assessment had an intraclass correlation coefficient of 0.517, underestimating tumor final stage in 12.6% of cases, with a poor agreement between preoperative MRI and postoperative staging (κ=0.082) and low sensitivity (14.3%) for serosa infiltration. The cut-off values for all three volume parameters had good/excellent AUC (0.73-0.85), with high sensitivity (70-83%) and specificity (64-84%) values for all histopathological variables. Excellent/good agreement was found all volume parameters for the identification of deep myometrial invasion (0.71), cervical stroma infiltration (0.80), serosa infiltration (0.81), and lymph node metastases (0.81).

Conclusion

Tumor volume measurements have good predictive capacity to detect histopathological findings that affect final tumor staging and might play a crucial role in the preoperative assessment of patients with endometrial cancer in the future.

Female sexual function evaluation and intraoperative vaginal reconstruction in bladder cancer

RC significantly negatively impacts sexual function (SF) in both men and women. While significant research resources have been allocated to examine the deleterious effects of post prostatectomy erectile dysfunction, little attention has been directed towards female sexual function and organ preservation post cystectomy. These academic shortcomings often result in poor provider awareness and inadequate preoperative assessment. As such, it is crucial for all providers involved in female RC care to understand the necessary and available tools for preoperative evaluation, in addition to the anatomic and reconstructive techniques. This review aims to summarize the current preoperative evaluation and available tools of SF assessment and describe in detail the varying operative techniques in the preservation or restoration of SF in women after RC. The review explores the intricacies of preoperative evaluation tools, and intraoperative techniques for organ- and nerve-sparing during radical cystectomy in females. Particular emphasis on vaginal reconstruction after partial or complete resection is provided, including split-thickness skin (STF) graft vaginoplasy, pedicled flaps, myocutaneous flaps and use of bowel segments. In conclusion, this narrative review highlights the importance of understanding anatomic considerations and nerve-sparing strategies in promoting postoperative SF and quality of life. Furthermore, the review describes the advantages and limitations of each organ- and nerve-sparing technique and their impact on sexual function and overall well-being.

Preoperative Assessment of Cervical Involvement in Endometrial Cancer by Transvaginal Ultrasound and Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

OBJECTIVE

 To compare the diagnostic accuracy of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) for detecting cervical infiltration by endometrial carcinoma using meta-analysis assessment.

METHODS

 An extensive search of papers comparing TVS and MRI for assessing cervical infiltration in endometrial cancer in the same set of patients was performed in Medline (Pubmed), Web of Science, and the Cochrane Database. Quality was assessed using QUADAS-2 tool (Quality Assessment of Diagnostic Accuracy Studies-2). Quantitative meta-analysis was performed.

RESULTS

 Our extended search identified 12 articles that used both techniques in the same set of patients and were included in the meta-analysis. The risk of bias for most studies was high for patient selection and index tests in QUADAS-2. Overall, the pooled estimated sensitivity and specificity for diagnosing cervical infiltration in women with endometrial cancer were identical for both techniques [69 % (95 % CI, 51 %-82 %) and 93 % (95 % CI, 90 %-95 %) for TVS, and 69 % (95 % CI, 57 %-79 %) and 91 % (95 % CI, 90 %-95 %) for MRI, respectively]. No statistical differences were found when comparing both methods. Heterogeneity was high for sensitivity and moderate for specificity when analyzing TVS and moderate for both sensitivity and specificity in the case of MRI.

CONCLUSION

 TVS and MRI showed very similar diagnostic performance for diagnosing cervical involvement in women with endometrial cancer.

Diagnostic accuracy of MRI for evaluating myometrial invasion in endometrial cancer: a comparison of MUSE-DWI, rFOV-DWI, and DCE-MRI

OBJECTIVES

To compare the image quality of high-resolution diffusion-weighted imaging (DWI) using multiplexed sensitivity encoding (MUSE) versus reduced field-of-view (rFOV) techniques in endometrial cancer (EC) and to compare the diagnostic performance of these techniques with that of dynamic contrast-enhanced (DCE) MRI for assessing myometrial invasion of EC.

METHODS

MUSE-DWI and rFOV-DWI were obtained preoperatively in 58 women with EC. Three radiologists assessed the image quality of MUSE-DWI and rFOV-DWI. For 55 women who underwent DCE-MRI, the same radiologists assessed the superficial and deep myometrial invasion using MUSE-DWI, rFOV-DWI, and DCE-MRI. Qualitative scores were compared using the Wilcoxon signed-rank test. Receiver operating characteristic analysis was performed to compare the diagnostic performance.

RESULTS

Artifacts, sharpness, lesion conspicuity, and overall quality were significantly better with MUSE-DWI than with rFOV-DWI (p < 0.05). The area under the curve (AUC) of MUSE-DWI, rFOV-DWI, and DCE-MRI for the assessment of myometrial invasion were not significantly different except for significantly higher AUC of MUSE-DWI than that of DCE-MRI for superficial myometrial invasion (0.76 for MUSE-DWI and 0.64 for DCE-MRI, p = 0.049) and for deep myometrial invasion (0.92 for MUSE-DWI and 0.80 for DCE-MRI, p = 0.022) in one observer, and that of rFOV-DWI for deep myometrial invasion in another observer (0.96 for MUSE-DWI and 0.89 for rFOV-MRI, p = 0.048).

CONCLUSION

MUSE-DWI exhibits better image quality than rFOV-DWI. MUSE-DWI and rFOV-DWI shows almost equivalent diagnostic performance compared to DCE-MRI for assessing superficial and deep myometrial invasion in EC although MUSE-DWI may be helpful for some radiologists.

Endometrial Cancer Staging: Is There Value in ADC?

PURPOSE

To assess the ability of apparent diffusion coefficient (ADC) measurements in predicting the histological grade of endometrial cancer. A secondary goal was to assess the agreement between MRI and surgical staging as an accurate measurement.

METHODS

Patients with endometrial cancers diagnosed between 2018-2020 and having received both MRI and surgical staging were retrospectively enrolled. Patients were characterized according to histology, tumor size, FIGO stage (MRI and surgical stage), and functional MRI parameters (DCE and DWI/ADC). Statistical analysis was performed to determine if an association could be identified between ADC variables and histology grade. Secondarily, we assessed the degree of agreement between the MRI and surgical stages according to the FIGO classification.

RESULTS

The cohort included 45 women with endometrial cancer. Quantitative analysis of ADC variables did not find a statistically significant association with histological tumor grades. DCE showed higher sensitivity than DWI/ADC in the assessment of myometrial invasion (85.00% versus 65.00%) with the same specificity (80.00%). A good agreement between MRI and histopathology for the FIGO stage was found (kappa of 0.72, p < 0.01). Differences in staging between MRI and surgery were detected in eight cases, which could not be justified by the interval between MRI and surgery.

CONCLUSIONS

ADC values were not useful for predicting endometrial cancer grade, despite the good agreement between MRI interpretation and histopathology of endometrial cancer staging at our center.

ESGO/ESHRE/ESGE Guidelines for the fertility-sparing treatment of patients with endometrial carcinoma

Background: The standard surgical treatment of endometrial carcinoma (EC) consisting of total hysterectomy with bilateral salpingo-oophorectomy drastically affects the quality of life of patients and creates a challenge for clinicians. Recent evidence-based guidelines of the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy & Oncology (ESTRO) and the European Society of Pathology (ESP) provide comprehensive guidelines on all relevant issues of diagnosis and treatment in EC in a multidisciplinary setting. While also addressing work-up for fertility preservation treatments and the management and follow-up for fertility preservation, it was considered relevant to further extend the guidance on fertility sparing treatment. Objectives: To define recommendations for fertility-sparing treatment of patients with endometrial carcinoma. Materials and Methods: ESGO/ESHRE/ESGE nominated an international multidisciplinary development group consisting of practicing clinicians and researchers who have demonstrated leadership and expertise in the care and research of EC (11 experts across Europe). To ensure that the guidelines are evidence-based, the literature published since 2016, identified from a systematic search was reviewed and critically appraised. In the absence of any clear scientific evidence, judgment was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 95 independent international practitioners in cancer care delivery and patient representatives. Results: The multidisciplinary development group formulated 48 recommendations for fertility-sparing treatment of patients with endometrial carcinoma in four sections: patient selection, tumour clinicopathological characteristics, treatment and special issues. Conclusions: These recommendations provide guidance to professionals caring for women with endometrial carcinoma, including but not limited to professionals in the field of gynaecological oncology, onco-fertility, reproductive surgery, endoscopy, conservative surgery, and histopathology, and will help towards a holistic and multidisciplinary approach for this challenging clinical scenario. What is new? A collaboration was set up between the ESGO, ESHRE and ESGE, aiming to develop clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing treatment in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.

ESGO/ESHRE/ESGE Guidelines for the fertility-sparing treatment of patients with endometrial carcinoma. Hum Reprod Open 2023;2023:hoac057. [PMID: 36756380 PMCID: PMC9900425 DOI: 10.1093/hropen/hoac057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

STUDY QUESTION

How should fertility-sparing treatment of patients with endometrial carcinoma be performed?

SUMMARY ANSWER

Forty-eight recommendations were formulated on fertility-sparing treatment of patients with endometrial carcinoma.

WHAT IS KNOWN ALREADY

The standard surgical treatment of endometrial carcinoma consisting of total hysterectomy with bilateral salpingo-oophorectomy drastically affects the quality of life of patients and creates a challenge for clinicians. Recent evidence-based guidelines of the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy & Oncology (ESTRO) and the European Society of Pathology (ESP) provide comprehensive guidelines on all relevant issues of diagnosis and treatment in endometrial carcinoma in a multidisciplinary setting. While addressing also work-up for fertility preservation treatments and the management and follow-up for fertility preservation, it was considered relevant to further extend the guidance on fertility-sparing treatment.

STUDY DESIGN SIZE DURATION

A collaboration was set up between the ESGO, the European Society of Human Reproduction and Embryology (ESHRE) and the European Society for Gynaecological Endoscopy (ESGE), aiming to develop clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing treatment in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.

PARTICIPANTS/MATERIALS SETTING METHODS

ESGO/ESHRE/ESGE nominated an international multidisciplinary development group consisting of practising clinicians and researchers who have demonstrated leadership and expertise in the care and research of endometrial carcinoma (11 experts across Europe). To ensure that the guidelines are evidence-based, the literature published since 2016, identified from a systematic search was reviewed and critically appraised. In the absence of any clear scientific evidence, judgement was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 95 independent international practitioners in cancer care delivery and patient representatives.

MAIN RESULTS AND THE ROLE OF CHANCE

The multidisciplinary development group formulated 48 recommendations in four sections; patient selection, tumour clinicopathological characteristics, treatment and special issues.

LIMITATIONS REASONS FOR CAUTION

Of the 48 recommendations, none could be based on level I evidence and only 16 could be based on level II evidence, implicating that 66% of the recommendations are supported only by observational data, professional experience and consensus of the development group.

WIDER IMPLICATIONS OF THE FINDINGS

These recommendations provide guidance to professionals caring for women with endometrial carcinoma, including but not limited to professionals in the field of gynaecological oncology, onco-fertility, reproductive surgery, endoscopy, conservative surgery and histopathology, and will help towards a holistic and multidisciplinary approach for this challenging clinical scenario.

STUDY FUNDING/COMPETING INTERESTS

All costs relating to the development process were covered from ESGO, ESHRE and ESGE funds. There was no external funding of the development process or manuscript production. G.S. has reported grants from MSD Italia S.r.l., advisory boards for Storz, Bayer, Astrazeneca, Metronic, TESARO Bio Italy S.r.l and Johnson & Johnson, and honoraria for lectures from Clovis Oncology Italy S.r.l. M.G. has reported advisory boards for Gedeon Richter and Merck. The other authors have reported no conflicts of interest.

DISCLAIMER

This document represents the views of ESHRE, ESGO and ESGE which are the result of consensus between the relevant stakeholders and where relevant based on the scientific evidence available at the time of preparation. The recommendations should be used for informational and educational purposes. They should not be interpreted as setting a standard of care, or be deemed inclusive of all proper methods of care nor exclusive of other methods of care reasonably directed to obtaining the same results. They do not replace the need for application of clinical judgement to each individual presentation, nor variations based on locality and facility type.

ESGO/ESHRE/ESGE Guidelines for the fertility-sparing treatment of patients with endometrial carcinoma

The standard surgical treatment of endometrial carcinoma, consisting of total hysterectomy with bilateral salpingo-oophorectomy, drastically affects the quality of life of patients and creates a challenge for clinicians. Recent evidence-based guidelines of the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) provide comprehensive information on all relevant issues of diagnosis and treatment in endometrial carcinoma in a multidisciplinary setting. While addressing also work-up for fertility preservation treatments and the management and follow-up for fertility preservation, it was considered relevant to further extend the guidance on fertility-sparing treatment.A collaboration was set up between the ESGO, the European Society of Human Reproduction and Embryology (ESHRE), and the European Society for Gynaecological Endoscopy (ESGE), aiming to develop clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing treatment (patient selection, tumor clinicopathological characteristics, treatment, special issues) in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.ESGO/ESHRE/ESGE nominated an international multidisciplinary development group consisting of practicing clinicians and researchers who have demonstrated leadership and expertise in the care and research of endometrial carcinoma (11 experts from across Europe). To ensure that the guidelines are evidence-based, the literature published since 2016, identified by a systematic search, was reviewed and critically appraised. In the absence of any clear scientific evidence, judgment was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 95 independent international practitioners in cancer care delivery and patient representatives.

ESGO/ESHRE/ESGE Guidelines for the fertility-sparing treatment of patients with endometrial carcinoma

Background

The standard surgical treatment of endometrial carcinoma (EC) consisting of total hysterectomy with bilateral salpingo-oophorectomy drastically affects the quality of life of patients and creates a challenge for clinicians. Recent evidence-based guidelines of the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy & Oncology (ESTRO) and the European Society of Pathology (ESP) provide comprehensive guidelines on all relevant issues of diagnosis and treatment in EC in a multidisciplinary setting. While also addressing work-up for fertility preservation treatments and the management and follow-up for fertility preservation, it was considered relevant to further extend the guidance on fertility sparing treatment.

Objectives

To define recommendations for fertility-sparing treatment of patients with endometrial carcinoma.

Materials and Methods

ESGO/ESHRE/ESGE nominated an international multidisciplinary development group consisting of practicing clinicians and researchers who have demonstrated leadership and expertise in the care and research of EC (11 experts across Europe). To ensure that the guidelines are evidence-based, the literature published since 2016, identified from a systematic search was reviewed and critically appraised. In the absence of any clear scientific evidence, judgment was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 95 independent international practitioners in cancer care delivery and patient representatives.

Results

The multidisciplinary development group formulated 48 recommendations for fertility-sparing treatment of patients with endometrial carcinoma in four sections: patient selection, tumour clinicopathological characteristics, treatment and special issues.

Conclusions

These recommendations provide guidance to professionals caring for women with endometrial carcinoma, including but not limited to professionals in the field of gynaecological oncology, onco-fertility, reproductive surgery, endoscopy, conservative surgery, and histopathology, and will help towards a holistic and multidisciplinary approach for this challenging clinical scenario. What is new? A collaboration was set up between the ESGO, ESHRE and ESGE, aiming to develop clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing treatment in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.

Uterine Neoplasms, Version 1.2023, NCCN Clinical Practice Guidelines in Oncology

Adenocarcinoma of the endometrium (also known as endometrial cancer, or more broadly as uterine cancer or carcinoma of the uterine corpus) is the most common malignancy of the female genital tract in the United States. It is estimated that 65,950 new uterine cancer cases will have occurred in 2022, with 12,550 deaths resulting from the disease. Endometrial carcinoma includes pure endometrioid cancer and carcinomas with high-risk endometrial histology (including uterine serous carcinoma, clear cell carcinoma, carcinosarcoma [also known as malignant mixed Müllerian tumor], and undifferentiated/dedifferentiated carcinoma). Stromal or mesenchymal sarcomas are uncommon subtypes accounting for approximately 3% of all uterine cancers. This selection from the NCCN Guidelines for Uterine Neoplasms focuses on the diagnosis, staging, and management of pure endometrioid carcinoma. The complete version of the NCCN Guidelines for Uterine Neoplasms is available online at NCCN.org.

Fertility Preservation in Endometrial Cancer-Treatment and Molecular Aspects

Endometrial cancer is one of the most common gynecological malignancies worldwide; incidences are rising, with 417,367 new cases registered in 2020. Of these, the proportion of women that are of reproductive age is around 4-14% and the number is increasing. Thus, in addition to oncological therapy and safety, the preservation of fertility plays a central role in therapeutic strategies. Molecular genetic patient data provide a robust supplementary benefit that improves primary risk assessment and can help design personalized treatment options to curtail over- and undertreatment and contribute to fertility preserving strategies. The aim of our review is to provide an overview of the latest significant recommendations in the diagnosis and therapy of endometrial cancer during reproductive age. In this paper the most recent groundbreaking molecular discoveries in endometrial cancer are highlighted and discussed as an opportunity to enhance the prognostic and therapy options in this special patient collective.

Accuracy of transvaginal ultrasound versus MRI in the PreOperative Diagnostics of low-grade Endometrial Cancer (PODEC) study: a prospective multicentre study

AIM

To investigate if the diagnostic accuracy of transvaginal ultrasound (TVUS) performed by gynaecologists is sufficient for preoperative assessment of low-grade endometrial cancer (EC) compared to magnetic resonance imaging (MRI).

MATERIALS AND METHODS

MRI and TVUS performed by gynaecologists were assessed at the participating centres. The MRI examinations were interpreted by two radiologists at the tertiary centre. Deep myometrial and cervical stroma invasion were visually assessed and compared to postoperative histopathology.

RESULTS

Two hundred and fifty-nine patients were included. There was a statistically significant difference in specificity assessing deep myometrial invasion between MRI and TVUS (MRI 0.88, TVUS 0.68). There was no difference in sensitivity (MRI 0.73, TVUS 0.68). When assessing cervical stroma infiltration, MRI had a higher specificity (MRI 0.96, TVUS 0.90), but there was no difference in sensitivity (MRI 0.41, TVUS 0.32).

CONCLUSION

MRI has higher specificity than TVUS performed by gynaecologists for assessing deep MI and CSI in low-grade EC, but similar sensitivities. The use of TVUS as a first-line test, rather than MRI, may be supported by this study in centres where access to MRI may be limited.

The value of magnetic resonance imaging-based tumor shape features for assessing microsatellite instability status in endometrial cancer

BACKGROUND

Microsatellite instability (MSI) status can be used for the classification and risk stratification of endometrial cancer (EC). This study aimed to investigate whether magnetic resonance imaging (MRI)-based tumor shape features can help assess MSI status in EC before surgery.

METHODS

The medical records of 88 EC patients with MSI status were retrospectively reviewed. Quantitative and subjective shape features based on MRI were used to assess MSI status. Variables were compared using the Student's t-test, χ² test, or Wilcoxon rank-sum test where appropriate. Univariate and multivariate analyses were performed by the logistic regression model. The area under the curve (AUC) was used to estimate the discrimination performance of variables.

RESULTS

There were 23 patients with MSI, and 65 patients with microsatellite stability (MSS) in this study. Eccentricity and shape type showed significant differences between MSI and MSS (P=0.039 and P=0.033, respectively). The AUC values of eccentricity, shape type, and the combination of 2 features for assessing MSI were 0.662 [95% confidence interval (CI): 0.554-0.770], 0.627 (95% CI: 0.512-0.743), and 0.727 (95% CI: 0.613-0.842), respectively. Considering the International Federation of Gynecology and Obstetrics (FIGO) staging, eccentricity maintained a significant difference in stages I-II (P=0.039), while there was no statistical difference in stages III-IV (P=0.601).

CONCLUSIONS

It is possible that MRI-based tumor shape features, including eccentricity and shape type, could be promising markers for assessing MSI status. The features may aid in the preliminary screening of EC patients with MSI.

Different multiparametric MRI-based radiomics models for differentiating stage IA endometrial cancer from benign endometrial lesions: A multicenter study

Purpose

The aim of this study was to evaluate the value of different multiparametric MRI-based radiomics models in differentiating stage IA endometrial cancer (EC) from benign endometrial lesions.

Methods

The data of patients with endometrial lesions from two centers were collected. The radiomics features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) map, and late contrast-enhanced T1-weighted imaging (LCE-T1WI). After data dimension reduction and feature selection, nine machine learning algorithms were conducted to determine which was the optimal radiomics model for differential diagnosis. The univariate analyses and logistic regression (LR) were performed to reduce valueless clinical parameters and to develop the clinical model. A nomogram using the radscores combined with clinical parameters was developed. Two integrated models were obtained respectively by the ensemble strategy and stacking algorithm based on the clinical model and optimal radiomics model. The area under the curve (AUC), clinical decisive curve (CDC), net reclassification index (NRI), and integrated discrimination index (IDI) were used to evaluate the performance and clinical benefits of the models.

Results

A total of 371 patients were incorporated. The LR model was the optimal radiomics model with the highest average AUC (0.854) and accuracy (0.802) in the internal and external validation groups (AUC = 0.910 and 0.798, respectively), and outperformed the clinical model (AUC = 0.739 and 0.592, respectively) or the radiologist (AUC = 0.768 and 0.628, respectively). The nomogram (AUC = 0.917 and 0.802, respectively) achieved better discrimination performance than the optimal radiomics model in two validation groups. The stacking model (AUC = 0.915) and ensemble model (AUC = 0.918) had a similar performance compared with the nomogram in the internal validation group, whereas the AUCs of the stacking model (AUC = 0.792) and ensemble model (AUC = 0.794) were lower than those of the nomogram and radiomics model in the external validation group. According to the CDC, NRI, and IDI, the optimal radiomics model, nomogram, stacking model, and ensemble model achieved good net benefits.

Conclusions

Multiparametric MRI-based radiomics models can non-invasively differentiate stage IA EC from benign endometrial lesions, and LR is the best machine learning algorithm. The nomogram presents excellent and stable diagnostic efficiency.

Preliminary Application of Magnetization Transfer Imaging in the Study of Normal Uterus and Uterine Lesions

Purpose

The aim of this study is to evaluate the utility of magnetization transfer (MT) imaging in the study of normal uterus and common uterine lesions.

Methods

This prospective study enrolled 160 consecutive patients with suspected uterine lesions. MT ratio (MTR) map was obtained by pelvic MT imaging on a 3.0T MRI scanner. Patients confirmed by pathology were divided into microscopic lesion group and lesion group, according to whether the maximum diameter of the lesion was less than 5 mm. After evaluating and eliminating patients with poor image quality by a three-point Likert scale, MTR values of lesions and normal endometrium, myometrium, and cervix were independently measured on the MTR map by two radiologists. Inter-reader agreement was evaluated. MTR values were compared among different uterine lesions and normal uterine structures using the Mann–Whitney U test with Bonferroni correction. Receiver operating characteristic curve was performed. The correlations between age and MTR values were explored by Pearson correlation analyses.

Results

A total of 96 patients with 121 uterine lesions in the lesion group and 41 patients in the microscopic lesion group were measured. The MTR values among normal endometrium, myometrium, and cervix were statistical significant differences (P < 0.05). There were significant differences between endometrial cancer and normal endometrium and between cervical cancer and normal cervix (both P ≤ 0.001). Area under the curve (AUC) for diagnosing endometrial and cervical cancer were 0.73 and 0.86. Myometrial lesions had significantly higher MTR values than endometrial lesions and cervical cancer (both P < 0.001), and the AUC for differentiating myometrial lesions from them were 0.89 and 0.94. MTR values of endometrial cancer were significantly higher than those of cervical cancer (P = 0.02). There was a critical correlation between age and MTR values in endometrial cancer (r = 0.81, P = 0.04).

Conclusions

MTR values showed significant differences among normal uterine structures. It was valuable for diagnosing and differentiating uterine cancer. MTR values could differentiate myometrial lesions from endometrial or cervical lesions.

Development and Validation of Multiparametric MRI-based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer

Background Stratifying high-risk histopathologic features in endometrial carcinoma is important for treatment planning. Radiomics analysis at preoperative MRI holds potential to identify high-risk phenotypes. Purpose To evaluate the performance of multiparametric MRI three-dimensional radiomics-based machine learning models for differentiating low- from high-risk histopathologic markers-deep myometrial invasion (MI), lymphovascular space invasion (LVSI), and high-grade status-and advanced-stage endometrial carcinoma. Materials and Methods This dual-center retrospective study included women with histologically proven endometrial carcinoma who underwent 1.5-T MRI before hysterectomy between January 2011 and July 2015. Exclusion criteria were tumor diameter less than 1 cm, missing MRI sequences or histopathology reports, neoadjuvant therapy, and malignant neoplasms other than endometrial carcinoma. Three-dimensional radiomics features were extracted after tumor segmentation at MRI (T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI). Predictive features were selected in the training set with use of random forest (RF) models for each end point, and trained RF models were applied to the external test set. Five board-certified radiologists conducted MRI-based staging and deep MI assessment in the training set. Areas under the receiver operating characteristic curve (AUCs) were reported with balanced accuracies, and radiologists' readings were compared with radiomics with use of McNemar tests. Results In total, 157 women were included: 94 at the first institution (training set; mean age, 66 years ± 11 [SD]) and 63 at the second institution (test set; 67 years ± 12). RF models dichotomizing deep MI, LVSI, high grade, and International Federation of Gynecology and Obstetrics (FIGO) stage led to AUCs of 0.81 (95% CI: 0.68, 0.88), 0.80 (95% CI: 0.67, 0.93), 0.74 (95% CI: 0.61, 0.86), and 0.84 (95% CI: 0.72, 0.92), respectively, in the test set. In the training set, radiomics provided increased performance compared with radiologists' readings for identifying deep MI (balanced accuracy, 86% vs 79%; P = .03), while no evidence of a difference was observed in performance for advanced FIGO stage (80% vs 78%; P = .27). Conclusion Three-dimensional radiomics can stratify patients by using preoperative MRI according to high-risk histopathologic end points in endometrial carcinoma and provide nonsignificantly different or higher performance than radiologists in identifying advanced stage and deep myometrial invasion, respectively. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kido and Nishio in this issue.

Development and Validation of an MRI-based Radiomics Nomogram for Assessing Deep Myometrial Invasion in Early Stage Endometrial Adenocarcinoma

RATIONALE AND OBJECTIVES

To establish a radiomics nomogram for detecting deep myometrial invasion (DMI) in early stage endometrioid adenocarcinoma (EAC).

MATERIALS AND METHODS

A total of 266 patients with stage I EAC were divided into training (n = 185) and test groups (n = 81). Logistic regression were used to identify clinical predictors. Radiomics features were extracted and selected from multiparameter MR images. The important clinical factors and radiomics features were integrated into a nomogram. A receiver operating characteristic curve was used to evaluate the nomogram. Two radiologists evaluated MR images with or without the help of the nomogram to detect DMI. The clinical benefit of using the nomogram was evaluated by decision curve analysis (DCA) and by calculating net reclassification index (NRI) and integrated discrimination index (IDI).

RESULTS

Age and CA125 were independent clinical predictors. The area under the curves of the clinical parameters, radiomics signature and nomogram in evaluating DMI were 0.744, 0.869 and 0.883, respectively. The accuracies of the two radiologists increased from 79.0% and 80.2% to 90.1% and 92.5% when they used the nomogram. The NRI of the two radiologists were 0.262 and 0.318, and the IDI were 0.322 and 0.405. According to DCA, the nomogram showed a higher net benefit than the radiomics signature or unaided radiologists. Cross-validation showed the outcome of radiomics analysis may not be influenced by changes in field strength.

CONCLUSION

The radiomics nomogram based on radiomics features and clinical factors can help radiologists evaluate DMI and improve their accuracy in predicting DMI in early stage EAC.

MRI-based radiomics nomogram for the preoperative prediction of deep myometrial invasion of FIGO I stage endometrial carcinoma

BACKGROUND

Endometrial carcinoma (EC) is one of the most common gynecological malignancies with an increasing incidence, and an accurate preoperative diagnosis of deep myometrial invasion (DMI) is crucial for personalized treatment.

OBJECTIVE

To determine the predictive value of an MRI-based radiomics nomogram for the presence of DMI in FIGO I stage EC.

METHODS

We retrospectively collected 163 patients with pathologically confirmed stage I EC from two centers and divided all samples into a training group (center 1) and a validation group (center 2). Clinical and routine imaging indicators were analyzed by logistical regression to construct a conventional diagnostic model (M1). Radiomics features extracted from the axial T2-weighted (T2W) and axial contrast-enhanced T1-weighted (CE-T1W) images were treated with the intraclass correlation coefficient, Mann-Whitney U test, least absolute shrinkage and selection operator (LASSO), and logistic regression analysis with Akaike information criterion (AIC) to build a combined radiomics signature (M2). A nomogram (M3) was constructed by M1 and M2. Calibration and decision curves were drawn to evaluate the nomogram in the training and validation cohorts. The diagnostic performance of each indicator and model was evaluated by the area under the receiver operating characteristic curve (AUC).

RESULT

The four most significant radiomics features were finally selected from the CE-T1W MRI. For the diagnosis of DMI, the AUC_T /AUC_V of M1 was 0.798/0.738, the AUC_T /AUC_V of M2 was 0.880/0.852, and the AUC_T /AUC_V of M3 was 0.936/0.871 in the training and validation groups, respectively. The calibration curves showed that M3 was in good agreement with the ideal values. The decision curve analysis suggested potential clinical application values of the nomogram.

CONCLUSION

A nomogram based on MRI radiomics and clinical imaging indicators can improve the diagnosis of DMI in patients with FIGO I stage EC. This article is protected by copyright. All rights reserved.

Radiomics Nomogram in Assisting Lymphadenectomy Decisions by Predicting Lymph Node Metastasis in Early-Stage Endometrial Cancer

Background

Lymph node metastasis (LNM) is an important risk factor affecting treatment strategy and prognosis for endometrial cancer (EC) patients. A radiomics nomogram was established in assisting lymphadenectomy decisions preoperatively by predicting LNM status in early-stage EC patients.

Methods

A total of 707 retrospective clinical early-stage EC patients were enrolled and randomly divided into a training cohort and a test cohort. Radiomics features were extracted from MR imaging. Three models were built, including a guideline-recommended clinical model (grade 1-2 endometrioid tumors by dilatation and curettage and less than 50% myometrial invasion on MRI without cervical infiltration), a radiomics model (selected radiomics features), and a radiomics nomogram model (combing the selected radiomics features, myometrial invasion on MRI, and cancer antigen 125). The predictive performance of the three models was assessed by the area under the receiver operating characteristic (ROC) curves (AUC). The clinical decision curves, net reclassification index (NRI), and total integrated discrimination index (IDI) based on the total included patients to assess the clinical benefit of the clinical model and the radiomics nomogram were calculated.

Results

The predictive ability of the clinical model, the radiomics model, and the radiomics nomogram between LNM and non-LNM were 0.66 [95% CI: 0.55-0.77], 0.82 [95% CI: 0.74-0.90], and 0.85 [95% CI: 0.77-0.93] in the training cohort, and 0.67 [95% CI: 0.56-0.78], 0.81 [95% CI: 0.72-0.90], and 0.83 [95% CI: 0.74-0.92] in the test cohort, respectively. The decision curve analysis, NRI (1.06 [95% CI: 0.81-1.32]), and IDI (0.05 [95% CI: 0.03-0.07]) demonstrated the clinical usefulness of the radiomics nomogram.

Conclusions

The predictive radiomics nomogram could be conveniently used for individualized prediction of LNM and assisting lymphadenectomy decisions in early-stage EC patients.

Evaluation and Monitoring of Endometrial Cancer Based on Magnetic Resonance Imaging Features of Deep Learning

This study was aimed to compare and analyze the magnetic resonance imaging (MRI) manifestations and surgical pathological results of endometrial cancer (EC) and to explore the clinical research of MRI in the diagnosis and staging of EC. Methods. 80 patients with EC admitted to the hospital were selected as the research objects. The ResNet network was used to optimize the network. When the depth was added, the accuracy of the model was improved, the network parameters were iteratively updated, and the damage function of the minimized network was obtained. The recognition efficiency of MRI images was analyzed using three network modes: shallow CNN network, Res-Net network, and optimized network. The images of EC patients were analyzed, and a quantitative and timed MRI was achieved using simulated datasets in deep learning neural networks, which provided the basis for the formulation of single-scan MRI parameters. All patients underwent preoperative MRI examination using coronal and sagittal T1WI and T2WI imaging. The results showed that the accuracy and specificity of T2 weighted imaging and enhanced scanning in MRI were 88.75% and 95%, respectively. Sensitivity was 87.5%, negative predictive value was 93.75%, and positive predictive value was 86.25%. By MRI examination, 80 cases of EC in patients with stage I diagnosis were 72 cases, accounting for 90%, with endometrial thickening and uneven enhancement. In conclusion, the MRI manifestations of EC are diversified, and MRI has a high value for the staging of EC. MRI examination is conducive to improving diagnostic accuracy.

Efficacy of transvaginal ultrasound versus magnetic resonance imaging for preoperative assessment of myometrial invasion in patients with endometrioid endometrial cancer: a prospective comparative study

Background

We compared the accuracy of preoperative transvaginal ultrasound (TVUS) versus magnetic resonance imaging (MRI) for the assessment of myometrial invasion (MI) in patients with endometrial cancer (EC), while definitive histopathological diagnosis served as a reference method.

Patients and methods

Study performed at a single tertiary centre from 2019 to 2021, included women with a histopathological proven EC, hospitalized for scheduled surgery. TVUS and MRI were performed prior to surgical staging for assessment MI, which was estimated using two objective TVUS methods (Gordon’s and Karlsson’s) and MRI. Patients were divided into two groups, after surgery and histopathological assessment of MI: superficial (≤ 50%) and deep (> 50%).

Results

Sixty patients were eligible for the study. According to the reference method, there were 34 (56.7%) cases in the study with MI < 50%, and 26 (43.3%) with MI > 50%. Both objective TVUS methods and MRI showed no statistical significant differences in overall diagnostic performance for the preoperative assessment of MI. The concordance coefficient between both TVUS methods, MRI and histopathology was statistically significant (p < 0.001). Gordon’s method calculating MI reached a positive predictive value (PPV) of 83%, negative predictive value (NPV) of 83%, 77% sensitivity, 88% specificity, and 83% overall accuracy. Karlsson’s method reached PPV of 82%, NPV of 79%, 69% sensitivity, 88% specificity, and 80% overall accuracy. Accordingly, MRI calculating MI reached PPV of 83%, NPV of 97%, 97% sensitivity, 85% specificity, and 90% overall accuracy.

Conclusions

We found that objective TVUS assessment of myometrial invasion was performed with a diagnostic accuracy comparable to that of MRI in women with endometrial cancer.

Diagnostic performance of transvaginal ultrasound and magnetic resonance imaging for preoperative evaluation of low-grade endometrioid endometrial carcinoma: prospective comparative study

OBJECTIVE

To compare the diagnostic performance of transvaginal ultrasound (TVS) and magnetic resonance imaging (MRI) in the prediction of deep myometrial invasion (DMI) and cervical stromal invasion (CSI) in patients with low-grade (Grade 1 or 2) endometrioid endometrial cancer (EEC).

METHODS

This was a prospective study including all patients with low-grade EEC diagnosed between October 2013 and July 2018 at the Vall d'Hebron Hospital in Barcelona, Spain. Preoperative staging was performed using TVS and MRI, followed by surgical staging. Final histology was considered as the reference standard. Sensitivity, specificity, likelihood ratios and diagnostic accuracy were calculated for both imaging techniques in the prediction of DMI and CSI, and the agreement index was calculated for both techniques. The STARD 2015 guidelines were followed.

RESULTS

A total of 131 patients with low-grade EEC were included consecutively. Sensitivity was higher for TVS than for MRI both for the prediction of DMI (69% (95% CI, 53-82%) vs 51% (95% CI, 36-66%), respectively) and CSI (43% (95% CI, 27-61%) vs 24% (95% CI, 12-41%), respectively). Specificity was similar for TVS and MRI in the prediction of DMI (87% (95% CI, 78-93%) vs 91% (95% CI, 82-96%)) and equal in the prediction of CSI (97% (95% CI, 91-99%) for both). The agreement index between TVS and MRI was 0.84 (95% CI, 0.76-0.90) for DMI and 0.92 (95% CI, 0.85-0.96) for CSI.

CONCLUSIONS

The diagnostic performance of TVS is similar to that of MRI for the prediction of DMI and CSI in low-grade EEC, and TVS can play a role as a first-line imaging technique in the preoperative evaluation of low-grade EEC. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Preoperative prediction of high-risk endometrial cancer by expert and non-expert transvaginal ultrasonography, magnetic resonance imaging, and endometrial histology

OBJECTIVE

To identify women with high-risk endometrial cancers using expert and non-expert transvaginal ultrasonography (TVS) and MRI.

STUDY DESIGN

Myometrial involvement was prospectively evaluated in patients with atypical hyperplasia or endometrial cancer on ultrasound by non-experts at first visit (non-expert-TVS: n = 266) and experts (expert-TVS: n = 188) at second visit. MRI (n = 175) was performed when high-risk cancer was suspected on non-expert-TVS. Preoperatively, high-risk cancer was defined as myometrial involvement ≥50 %, or preoperative unfavorable tumor histology (grade 3 endometrioid, non-endometrioid tumors, or tumor in cervical biopsies) obtained by endometrial sampling or hysteroscopic biopsies. Preoperative evaluations were compared with final histopathology obtained at surgery, high-risk cancer being defined as unfavorable tumor histology or patients with FIGO stage ≥1b.

RESULTS

Preoperative unfavorable tumor histology was seen in 64 women and correctly identified 63 of 128 high-risk cancers. Preoperative diagnosis of unfavorable tumor histology or myometrial involvement ≥50 %, i.e. judged high-risk, had an area under the curve (AUC), sensitivity, and specificity of 79.5 %, 93.8 %, 65.2 % on non-expert-TVS; 85.5 %, 84.4 %, 86.5 % on expert-TVS, and 85.4 %, 89.6 %, 81.2 % on MRI. AUC values were not significantly different between MRI and expert-TVS, but lower on non-expert-TVS (p < 0.02). However, sensitivity was highest on non-expert-TVS, where a low cutpoint for myometrial involvement was used (included potentially deep and difficult evaluations) in contrast to an exact cutpoint of myometrial involvement ≥50 % used on expert-TVS and MRI. The highest AUC, 88.6 %, was seen when MRI was performed in patients with myometrial involvement ≥50 %, determined on non-expert TVS. Sensitivity was reduced to 85.9 %, while specificity increased to 91.3 %. Thus, MRI was needed for risk classification in only 104 (39 %) patients.

CONCLUSION

Diagnostically, expert-TVS and MRI were comparable and superior to non-expert-TVS. However, non-expert-TVS classified all patients with unclear myometrial involvement ≥50 %, and thereby only misdiagnosed 6.2 % of high-risk cases. Non-expert-TVS combined with MRI when myometrial involvement was ≥50 % on non-expert-TVS was a simple and effective method comparable with expert imaging to identify low- and high-risk cancer and select patients for SLND. Addition of MRI to the diagnostic regimen was needed in only 39 % of our patients.

Predictive value of T2-weighted imaging and dynamic contrast-enhanced MRI for assessing cervical invasion in patients with endometrial cancer: a meta-analysis

PURPOSE

To obtain the diagnostic accuracy of T2-weighted imaging (T2WI), and dynamic contrast-enhanced MRI (DCE-MRI) in the preoperative assessment of cervical invasion in patients with endometrial cancer (EC).

METHODS

Databases including PubMed, Embase, Cochrane Library, Web of Science, and Clinical Trials were searched for relevant articles published from January 2000 to August 2020. Pooled estimation data were obtained by statistical analysis.

RESULTS

In total, 24 articles were included. For assessing cervical invasion of EC, the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) for T2WI were 0.70 (0.61-0.77), 0.92 (0.89-0.94), 8.7 (6.5-11.6), 0.33 (0.25-0.43), 26 (17-41), and 0.92 (0.89-0.94), respectively. For DCE-MRI, the pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.75 (0.60-0.85), 0.95 (0.89-0.98), 14.7 (6.6-32.9), 0.27 (0.16-0.44), 55 (18-165), and 0.92 (0.89-0.94), respectively; for T2WI combined with DCE-MRI, they were 0.58 (0.41-0.73), 0.98 (0.95-0.99), 28.1 (12.8-62.1), 0.43 (0.30-0.63), 65 (29-146), and 0.94 (0.91-0.96), respectively.

CONCLUSIONS

DCE-MRI demonstrated higher diagnostic performance than T2WI in the prediction of cervical invasion in patients with EC. T2WI combined with DCE-MRI improved the pooled specificity, PLR, DOR, and AUC compared to T2WI alone or DCE-MRI alone.

MRI to assess deep myometrial invasion in patients with endometrial cancer:A multi-reader study to evaluate the diagnostic role of different sequences

OBJECTIVE

The identification of deep myometrial invasion (DMI) represents a fundamental aspect in patients with endometrial cancer (EC) for accurate disease staging. It can be detected on MRI using T2-weighted (T2-w), diffusion weighted (DWI) and dynamic contrast enhanced sequences (DCE). Aim of the study was to perform a multi-reader evaluation of such sequences to identify the most accurate and its reliability for the best protocol.

METHODS

In this multicenter retrospective study, MRI were independently evaluated by 4 radiologists (2 senior and 2 novice) with a sequence-based approach to identify DMI. The performance of the entire protocol was also evaluated. A comparison between the different sequences assessed by the same reader was performed using receiver operating curve and post-hoc analysis. Intraclass Correlation Coefficient (ICC) was used to assess inter- and intra-observer variability.

RESULTS

A total of 92 patients were included. The performance of the readers did not show significant differences among DWI, DCE and the entire protocol. For only one senior radiologist, who reached the highest diagnostic accuracy with the entire protocol (82,6 %), both DWI (p = 0,0197) and entire protocol (p = 0,0039) were found significantly superior to T2-w. The highest inter-observer agreement was obtained with the entire protocol by expert readers (ICC = 0,77).

CONCLUSIONS

For the detection of DMI, the performances of DWI and DCE alone and that of a complete protocol do not significantly differ, even though the latter ensures the highest reliability particularly for expert readers. In cases in which T2-w and DWI are consistent, an unenhanced protocol could be proposed.

Diagnostic Accuracy of MRI for Detecting Cervical Invasion in Patients with Endometrial Carcinoma: A Meta-Analysis

Objectives: To evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in the preoperative assessment of cervical invasion and to analyse the influence of different imaging protocols in patients with endometrial carcinoma.

Methods: An extensive search of articles about MRI for assessing cervical invasion in patients with endometrial carcinoma was performed on PubMed, Embase, Web of Science, Cochrane Library, and Clinical Trials from January 2000 to July 2020. Two reviewers independently evaluated the methodological quality of each study by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Diagnostic accuracy results and additional useful information were extracted. The pooled estimation data was obtained by statistical analysis.

Results: A total of 42 eligible studies were included in the meta-analysis. Significant evidence of heterogeneity was found for detecting cervical invasion (I² = 74.1%, P = 0.00 for sensitivity and I² = 56.2%, P = 0.00 for specificity). The pooled sensitivity and specificity of MRI were 0.58 and 0.95 respectively. The use of higher field strength (3.0 T) demonstrated higher pooled sensitivity (0.74). Using diffusion weighted imaging (DWI) alone presented higher pooled sensitivity (0.86) than using other sequences. The studies that used dynamic contrast-enhanced MRI (DCE-MRI) alone showed higher sensitivity (0.80) and specificity (0.96) than those that used T2-weighted imaging (T2WI) alone.

Conclusions: MRI shows high specificity for detecting cervical infiltration in endometrial carcinoma. Using DWI or a 3.0-T device may improve the pooled sensitivity. DCE-MRI demonstrates higher pooled sensitivity and specificity than T2WI.

Evaluation of Pre-Therapeutic Assessment in Endometrial Cancer Staging

OBJECTIVE

The aim of this retrospective cohort study is to evaluate the concordance between the preoperative MRI and histology data with the final histopathological examination.

METHOD

This is a retrospective observational study of 183 patients operated for endometrioid cancer between January 2009 and December 2019 in the surgical oncology department of the Lorraine Cancer Institute (ICL) in Vandœuvre-lès-Nancy. The patients included are all women operated on for endometrioid-type endometrial cancer over this period. The exclusion criteria are patients for whom the pre-therapy check-up does not include pelvic MRI and those who have not had first-line surgery. The final anatomopathological results were compared with preoperative imaging data and with endometrial biopsy data.

RESULTS

For the myometrial infiltration, the sensitivity of MRI was of 37% and the specificity of 54%. To detect nodal metastases, the sensitivity of MRI was of 21% and the specificity of 93%. We observed an under estimation of the FIGO classification (p = 0.001) with the MRI in 42.7% of cases (n = 76) and an overestimation in 24.2% of cases (n = 43). There was a concordance in 33.1% of cases (n = 59). We had a poor agreement between the MRI and final histopathological examination with an adjusted kappa (κ) of 0.12 [95% IC (0.02; 0.24)]. There was a moderate concordance on the grade between the pretherapeutic biopsy and the final histopathological examination on excised tissue with an adjusted kappa of 0.52 [95% IC 0.42-0.62)]. Endometrial biopsy underestimated the tumor grade in 28.9% of cases (n = 50) (p < 0.001), overestimated the tumor grade in 6.9% of cases (n = 12) and we observed a concordance in 64.2% of cases (n = 111).

CONCLUSION

The pre-operative assessment of endometrial cancer is inconsistent with the results obtained on final histopathological examination. A study with a systematic review should be done to assess the performance of MRI, only in expert centers, in order to consider a a specific care management for endometrial cancer patients: patients who have had an MRI in an outpatient center should have their imaging systematically reviewed, with the possibility of a new examination in case of incomplete sequences, by expert radiologists, and discussed in multidisciplinary concertation meeting in expert centers, before any therapeutic decision. The sentinel node biopsy must be used for low and intermediate risk endometrial cancer.

Endometrial cancer-is our knowledge changing?

In developed countries, endometrial cancer (EC) is the most frequent gynecologic malignancy in postmenopausal women. At the same time, EC has become one of the most common cancers in numerous developing countries, probably influenced by global epidemic of obesity. The majority of patients have low-grade endometrioid cancer with a high 5-year survival rate, but with high-risk EC, the survival rates are still rather low. However, despite intensive research in last decades, our knowledge of the mechanisms, risk factors, diagnosis and treatment have not significantly improved. The standard treatment of all types of EC is still a traditional combination of surgery, irradiation and/or chemotherapy, despite the fact that each of these options is not without having some negative side effects. Despite the fact that on the molecular level, EC is relatively well-studied, but the efforts to transform these findings into either diagnosis or therapies of EC remain elusive. In addition, some research into risk factors involved in the development or progression of EC seems to be more a fishing expedition than a well thought-out approach. The purpose of this review is to summarize the most recent developments in the search for biomarkers and prognostic markers and to discuss the progress in EC treatment.

Radiologists with MRI-based radiomics aids to predict the pelvic lymph node metastasis in endometrial cancer: a multicenter study

OBJECTIVE

To construct a MRI radiomics model and help radiologists to improve the assessments of pelvic lymph node metastasis (PLNM) in endometrial cancer (EC) preoperatively.

METHODS

During January 2014 and May 2019, 622 EC patients (age 56.6 ± 8.8 years; range 27-85 years) from five different centers (A to E) were divided into training set, validation set 1 (351 cases from center A), and validation set 2 (271 cases from centers B-E). The radiomics features were extracted basing on T2WI, DWI, ADC, and CE-T1WI images, and most related radiomics features were selected using the random forest classifier to build a radiomics model. The ROC curve was used to evaluate the performance of training set and validation sets, radiologists based on MRI findings alone, and with the aid of the radiomics model. The clinical decisive curve (CDC), net reclassification index (NRI), and total integrated discrimination index (IDI) were used to assess the clinical benefit of using the radiomics model.

RESULTS

The AUC values were 0.935 for the training set, 0.909 and 0.885 for validation sets 1 and 2, 0.623 and 0.643 for the radiologists 1 and 2 alone, and 0.814 and 0.842 for the radiomics-aided radiologists 1 and 2, respectively. The AUC, CDC, NRI, and IDI showed higher diagnostic performance and clinical net benefits for the radiomics-aided radiologists than for the radiologists alone.

CONCLUSIONS

The MRI-based radiomics model could be used to assess the status of pelvic lymph node and help radiologists improve their performance in predicting PLNM in EC.

KEY POINTS

• A total of 358 radiomics features were extracted. The 37 most important features were selected using the random forest classifier. • The reclassification measures of discrimination confirmed that the radiomics-aided radiologists performed better than the radiologists alone, with an NRI of 1.26 and an IDI of 0.21 for radiologist 1 and an NRI of 1.37 and an IDI of 0.24 for radiologist 2.