Role of preoperative magnetic resonance imaging and histological assessment in identifying patients with a low risk of endometrial cancer: a Korean Gynecologic Oncology Group ancillary study

Prediction of final pathology depending on preoperative myometrial invasion and grade assessment in low-risk endometrial cancer patients: A Korean Gynecologic Oncology Group ancillary study

OBJECTIVES

Fertility-sparing treatment (FST) might be considered an option for reproductive patients with low-risk endometrial cancer (EC). On the other hand, the matching rates between preoperative assessment and postoperative pathology in low-risk EC patients are not high enough. We aimed to predict the postoperative pathology depending on preoperative myometrial invasion (MI) and grade in low-risk EC patients to help extend the current criteria for FST.

METHODS/MATERIALS

This ancillary study (KGOG 2015S) of Korean Gynecologic Oncology Group 2015, a prospective, multicenter study included patients with no MI or MI <1/2 on preoperative MRI and endometrioid adenocarcinoma and grade 1 or 2 on endometrial biopsy. Among the eligible patients, Groups 1-4 were defined with no MI and grade 1, no MI and grade 2, MI <1/2 and grade 1, and MI <1/2 and grade 2, respectively. New prediction models using machine learning were developed.

RESULTS

Among 251 eligible patients, Groups 1-4 included 106, 41, 74, and 30 patients, respectively. The new prediction models showed superior prediction values to those from conventional analysis. In the new prediction models, the best NPV, sensitivity, and AUC of preoperative each group to predict postoperative each group were as follows: 87.2%, 71.6%, and 0.732 (Group 1); 97.6%, 78.6%, and 0.656 (Group 2); 71.3%, 78.6% and 0.588 (Group 3); 91.8%, 64.9%, and 0.676% (Group 4).

CONCLUSIONS

In low-risk EC patients, the prediction of postoperative pathology was ineffective, but the new prediction models provided a better prediction.

Preoperative risk stratification in women with endometrial cancer: A comparison of contrast-enhanced MR imaging and diffusion-weighted MR imaging

PURPOSE

To compare CE MRI and DWI in the risk stratification of women with endometrial cancer for lymph node metastasis.

METHOD

Two readers independently assessed the degree of myometrial invasion on two separate occasions in a retrospective cohort of 84 women with endometrial cancers: once with CE MRI and standard anatomic sequences and another time with DWI and standard anatomic sequences. Participants were stratified according to their risk of lymph node metastasis following the European Society for Medical Oncology guidelines. The rate of lymph node metastasis was compared between the risk stratification groups obtained using CE MRI or DWI by generalized estimating equations.

RESULTS

In the low-risk group, the rate of lymph node metastasis was 1.9% (1/53) when using CE MRI and 1.9% (1/54) when using DWI for reader 1, and 3.8% (2/52) when using CE MRI and 1.9% (1/52) when using DWI for reader 2. The rate of lymph node metastasis in the high-risk group was 25.8% (8/31) when using CE MRI and 26.7% (8/30) when using DWI for reader 1, and 21.9% (7/32) when using CE MRI and 25.0% (8/32) when using DWI for reader 2. There was no significant difference between CE MRI and DWI in the rate of lymph node metastasis according to the risk stratification (p > .05 in both low- and high-risk groups for both readers).

CONCLUSION

DWI might be a comparable alternative to CE MRI in the preoperative risk stratification of women with endometrial cancer for lymph node metastasis.

Preoperative MRI and immunohistochemical examination for the prediction of high-risk endometrial cancer

Background

Magnetic resonance imaging (MRI) and immunohistochemical (IHC) examination provides useful information for the risk stratification of endometrial cancer (EC). However, the use of the combination of MRI and IHC for the prediction of high-risk EC is controversial. The aim of this study was to evaluate the value of preoperative MRI and IHC examination in prediction of patients with high-risk EC.

Methods

This retrospective case-control study was conducted from January 1, 2018 to May 1, 2021 at two hospitals. A primary cohort (n=102) comprised patients with histologically confirmed EC in one hospital between January 1, 2018 and May 31, 2020. An additional external cohort (n=35) comprising patients with histologically confirmed EC in a different hospital from January 1, 2020 to May 1, 2021 was included for validation. Imaging features including tumor size, tumor margin, relative T2 value, tumor signal intensity on diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), T2-weighted imaging (T2WI) were determined from preoperative MRI images. IHC markers including ER, PR, p53 and Ki67 were determined through IHC staining of preoperative curettage specimen. Patients were divided into high-risk and low-intermediate- risk group based on the final histological results. Differences between categorical and numerical variables were assessed using chi-square test and independent-sample t-test, respectively. Multivariate binary logistic regression analyses were used for construction of the prediction model A fusion prediction model was constructed by combining MRI features and IHC markers. The predictive performance of the model was then validated using the external cohort.

Results

Imaging and IHC markers were significantly associated with risk ranks. Model 1 based on MRI features showed an area under the curve (AUC) of 0.822 [95% confidence interval (CI), 0.741-0.903] whereas Model 2 based on IHC markers showed an AUC of 0.894 (95% CI, 0.829-0.960). Notably, model 3 integrating independent MRI and IHC risk factors demonstrated good calibration and high differentiation ability with an AUC of 0.958 (95% CI, 0.923-0.993), and showed good discrimination with an AUC of 0.84 (95% CI, 0.677-0.942) using the external validation set.

Conclusions

This study proposes a comprehensive predictive model comprising MRI and IHC features as a powerful tool for preoperative risk stratification to assist in clinical decision-making for EC patients.

Assessment of Preoperative Endometrial Histopathological Sampling as a Predictor of Final Surgical Pathology in Endometrial Cancer

OBJECTIVE

 To evaluate the agreement between the histopathological diagnoses of preoperative endometrial samples and surgical specimens and correlate the agreement between the diagnoses with the impact on surgical management and the survival of patients with endometrial adenocarcinomas.

METHODS

 Sixty-two patients treated for endometrial cancer at a university hospital from 2002 to 2011 were retrospectively evaluated. The histopathological findings of preoperative endometrial samples and of surgical specimens were analyzed. The patients were subjected to hysterectomy as well as adjuvant treatment, if necessary, and clinical follow-up, according to the institutional protocol. Lesions were classified as endometrioid tumor (type 1) grades 1, 2, or 3 or non-endometrioid carcinoma (type 2).

RESULTS

 The agreement between the histopathological diagnoses based on preoperative endometrial samples and surgical specimens was fair (Kappa: 0.40; p < 0.001). However, the agreement was very significant for tumor type and grade, in which a higher concordance occurred at a higher grade. The percentage of patients with lymph nodes affected was 19.2%. Although most patients presenting with disease remission or cure were in the early stages (90.5%), there were no significant differences between those patients who had a misdiagnosis (11/16; 68.8%) and those who had a correct diagnosis (25/33; 75.8%) based on preoperative endometrial sampling (p = 0.605).

CONCLUSION

 Our findings corroborate the literature and confirm the under staging of preoperative endometrial samples based on histopathological assessment, especially for lower grade endometrial tumors. We suggest that the preoperative diagnosis should be complemented with other methods to better plan the surgical management strategy.

Predictive Value of Kanagawa Cancer Center Scoring System for Lymph Node Metastasis and Need for Lymphadenectomy in Patients With Endometrial Cancer: A Validation Study

OBJECTIVES

The objective of this study was to determine the predictive value of Kanagawa Cancer Center (KCC) scoring system for lymph node metastasis and need for lymphadenectomy in patients with endometrial cancer.

METHODS

This cross-sectional study was conducted during a 2-year period in a gynecologic oncology referral center in Southern Iran. We included a total number of 94 patients with endometrial cancer. Preoperative assessment included tumor volume, myometrium invasion, histology, and CA125. The KCC was calculated for all the patients. All the patients underwent total abdominal hysterectomy and bilateral salpingo-oophorectomy along with dissection of pelvic and para-aortic lymph nodes. The histopathology of the dissected lymph nodes was considered as criterion standard, and the predictive value of KCC was evaluated accordingly.

RESULTS

The mean ± SD age of the patients was 56.8 ± 10.2 years. Overall, 26 patients (27.7%) tested positive for lymph node involvement. The sensitivity, specificity, positive predictive value, and negative predictive value of KCC for lymph node involvement was found to be 35.3%, 100%, 100%, and 64.7%, respectively. Overall, the predictive value according to the area under the curve measured by receiver operating characteristic curve was found to be 0.890 (0.823-0.956) indicative of moderate accuracy. Lymph node involvement was associated with higher Federation of Gynecology and Obstetrics stage (P < 0.001), higher tumor volume (P = 0.003), higher histological subtype (P < 0.001), positive CA125 (P < 0.001), and higher KCC score (P < 0.001).

CONCLUSIONS

The KCC scoring system has a moderate accuracy for predicting the lymph node involvement in patients with endometrial cancer.