The effect of myometrial invasion on prognostic factors and survival analysis in endometrial carcinoma

The Utility of Apparent Water Diffusion Coefficient Maps for Evaluating the Presence of Myometrial Invasion in Patients with Endometrial Cancer

PURPOSE

To assess the utility of apparent diffusion coefficient maps (ADC) for diagnosing myometrial invasion (MI) in endometrial cancer (EC).

METHODS

This retrospective study included 164 patients (mean age, 56 years; range, 25-89 years) who underwent preoperative MRI for EC with <1/2 MI or no MI between April 2016 and July 2023. Five sequences were evaluated: T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), ADC, dynamic contrast-enhanced T1-weighted imaging (DCE-T1WI), and contrast-enhanced T1WI (CE-T1WI). Three experienced radiologists independently assessed the sequences for MI. For ADC, MI was determined if the endometrial-myometrial junction-tumor boundary had disappeared. Additionally, the assessment of MI was performed using the combination of T2WI, DWI, and ADC, as well as T2WI, DCE-T1WI, and CE-T1WI. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) for the presence of MI were calculated and compared between the sequences and combinations. Inter-reader agreement was assessed using kappa (κ) statistics.

RESULTS

The sensitivity of ADC was significantly higher than T2WI (P < 0.001) and DCE-T1WI (P = 0.018) for one reader and significantly higher than CE-T1WI (P = 0.045 and 0.043) for two readers. The specificity of ADC was significantly lower than T2WI (P = 0.015 and < 0.001) and CE-T1WI (P = 0.031 and 0.01) for two readers and significantly lower than DCE-T1WI (P = 0.031) for one reader. The AUC of ADC was significantly higher than T2WI (P = 0.048) and DCE-T1WI (P = 0.049) for one reader. The combination including ADC showed higher positive predictive value for all three readers compared to any sequence or combination including contrast enhancement. Additionally, ADC demonstrated the highest agreement rates.

CONCLUSION

ADC had high sensitivity for MI and the highest agreement rate among all sequences. Thus, this sequence, combined with other sequences, can be crucial for a comprehensive evaluation of MI.

Impact of adjuvant treatments and risk factors on survival in 2023 FIGO stage IIB endometrial cancer patients: Turkish Gynecologic Oncology Group Study

OBJECTIVE

The aim of this study was to investigate the impact of adjuvant treatments, factors influencing recurrence, and survival data in patients with 2023 International Federation of Gynecology and Obstetrics (FIGO) stage IIB endometrial cancer.

METHODS

A retrospective analysis was conducted on patients with endometrial cancer who underwent surgery between 2005 and 2022 at seven different centers in Turkey. Demographic, clinicopathological, and survival data were collected and analyzed.

RESULTS

Among 7323 patients, 565 (7.7%) were classified as 2023 FIGO stage IIB based on pathological results. Of 565 patients, 214 were followed without receiving adjuvant treatment, while 335 (95.4%) received adjuvant radiotherapy, and 16 (4.6%) received radiotherapy and chemotherapy. The locoregional recurrence rate was higher in patients with a tumor size >4 cm (p=0.038) and myometrial invasion >50% (p=0.045). In patients with distant metastasis, the recurrence rate was lower in those with myometrial invasion <50% compared with myometrial invasion ≥50% (p=0.031). The impact of adjuvant treatment on endometrial cancer patients revealed no significant differences for both disease free survival (p=0.85) and overall survival (p=0.54). Subgroup analyses showed that in patients with deep myometrial invasion, adjuvant treatment was associated with a significant increase in overall survival (p=0.044), but there was no effect on disease-free survival (p=0.12).

CONCLUSIONS

Patients with stage IIB endometrial cancer with myometrial invasion ≥50% were more likely to have locoregional and distant metastases. Adjuvant radiotherapy or chemoradiotherapy did not demonstrate an overall survival benefit in these patients.

Integrating proteomics and explainable artificial intelligence: a comprehensive analysis of protein biomarkers for endometrial cancer diagnosis and prognosis

Endometrial cancer, which is the most common gynaecological cancer in women after breast, colorectal and lung cancer, can be diagnosed at an early stage. The first aim of this study is to classify age, tumor grade, myometrial invasion and tumor size, which play an important role in the diagnosis and prognosis of endometrial cancer, with machine learning methods combined with explainable artificial intelligence. 20 endometrial cancer patients proteomic data obtained from tumor biopsies taken from different regions of EC tissue were used. The data obtained were then classified according to age, tumor size, tumor grade and myometrial invasion. Then, by using three different machine learning methods, explainable artificial intelligence was applied to the model that best classifies these groups and possible protein biomarkers that can be used in endometrial prognosis were evaluated. The optimal model for age classification was XGBoost with AUC (98.8%), for tumor grade classification was XGBoost with AUC (98.6%), for myometrial invasion classification was LightGBM with AUC (95.1%), and finally for tumor size classification was XGBoost with AUC (94.8%). By combining the optimal models and the SHAP approach, possible protein biomarkers and their expressions were obtained for classification. Finally, EWRS1 protein was found to be common in three groups (age, myometrial invasion, tumor size). This article's findings indicate that models have been developed that can accurately classify factors including age, tumor grade, and myometrial invasion all of which are critical for determining the prognosis of endometrial cancer as well as potential protein biomarkers associated with these factors. Furthermore, we were able to provide an analysis of how the quantities of the proteins suggested as biomarkers varied throughout the classes by combining the SHAP values with these ideal models.

Enhancing Preoperative Assessment of Endometrial Cancer: The Role of Diffusion-Weighted Magnetic Resonance Imaging in Evaluating Myometrial Invasion

BACKGROUND

Endometrial cancer (EC) is the most common gynecological malignancy. Accurate preoperative staging is essential for guiding treatment. The depth of myometrial invasion is a key prognostic factor. This prospective study aimed to evaluate the added benefit of diffusion-weighted imaging (DWI) compared to T2-weighted imaging (T2WI) and dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative assessment of myometrial invasion in EC.

AIM AND OBJECTIVES

The aim of this prospective study was to evaluate the added benefit of DWI in the preoperative assessment of myometrial invasion in EC, in comparison with T2WI and DCE-MRI. The objectives were to assess the imaging characteristics of endometrial carcinoma on T2WI, DCE, and DW MR, to assess the depth of myometrial invasion and overall stage in EC patients, to compare the diagnostic performance of DCE-MRI with that of DW-MRI combined with T2WI, to describe how MR imaging findings can be combined with tumor histologic features and grading to guide treatment planning, and to evaluate the pitfalls and limitations of DCE and DW MR in the assessment of EC.

MATERIALS AND METHODS

Thirty-one patients with histologically confirmed EC underwent preoperative pelvic MRI on a 1.5T scanner. T2WI, DWI (b-values 0, 1000 s/mm2), and DCE-MRI were performed. Two radiologists independently assessed myometrial invasion on T2WI, T2WI + DWI, and T2WI + DCE-MRI. Histopathology after hysterectomy was the reference standard. Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each MRI protocol, with separate analyses for superficial (<50%) and deep (≥50%) myometrial invasions.

RESULTS

The accuracy for assessing superficial invasion was 61.3% for T2WI, 87.1% for T2WI + DWI, and 87.1% for T2WI + DCE-MRI. For deep invasion, accuracy was 64.5% for T2WI, 90.3% for T2WI + DWI, and 90.3% for T2WI + DCE-MRI. Sensitivity, specificity, PPV, and NPV for T2WI + DWI and T2WI + DCE-MRI were high and comparable (88.9-91.7%) for both superficial and deep invasions. T2WI had markedly lower sensitivity and specificity. The differences between T2WI and the functional MRI protocols were statistically significant (p < 0.01).

CONCLUSION

DWI and DCE-MRI significantly improve the diagnostic performance of MRI for the preoperative assessment of myometrial invasion depth in EC compared to T2WI alone. DWI + T2WI and DCE-MRI + T2WI demonstrate comparable high accuracy. DWI may be preferable since it is faster and avoids contrast administration.

Association of Lymphovascular Space Invasion (LVSI) with Histological Tumor Grade and Myometrial Invasion in Endometrial Carcinoma: A Review Study

Endometrial carcinoma is one of the most frequent gynecological cancers in developed countries. Lymphovascular space invasion (LVSI), histological grade, and myometrial invasion (MMI) are important prognostic factors of endometrial carcinoma. LVSI is considered an independent poor prognostic factor in endometrial carcinoma. Based on the importance of LVSI, this study aimed to discuss the association of LVSI with tumor grade and MMI. A search of PubMed, EMBASE, Web of Science, Scopus, Google Scholar, and Cochrane Library was carried out to collect related studies. Consequently, most studies showed that LVSI is significantly associated with higher histologic grade and deep MMI.

Diagnostic value of T2 and diffusion-weighted imaging (DWI) in local staging of endometrial cancer

BACKGROUND

Endometrial cancer (EC) is the eighth most prevalent cancer globally. T2-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) help anatomical localization and local staging of lesions. The present study was performed to assess the diagnostic value of the simultaneous use of T2 and DWI techniques in EC evaluation.

METHODS

Seventy-eight histopathological-proven EC cases were included in this study. Patients were assessed using a complete MRI exam, including T2 and DWI. The myometrial invasion, cervical, serosal or adnexal, vaginal or parametrial, and pelvic lymph node involvements and accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated in each sequence distinctly and was compared with the pathology findings and full standard protocol using post-contrast multiphasic contrast-enhanced series.

RESULTS

Deep myometrial invasion in EC cases was detected in 38.5% by T2-DWI and 37.2% by pathology. The pathology diagnosed cervical, serosal, and vaginal involvements and pelvic lymph node metastases in 20.5%, 7.7%, 6.4% and 11.5% of cases respectively, while the numbers for T2-DWI were 26.9%, 7.7%, 7.7%, and 15.4%, respectively. The accuracy, sensitivity, specificity, PPV, and NPV of T2-DWI in the diagnosis of myometrial invasion were 93.5%, 93.1%, 93.8%, 90%, and 93.8%, respectively. A slightly higher Kappa coefficient of DWI (0.973) in the diagnosis of myometrial invasion was identified compared to T2 (0.946). The T2-DWI technique had a 52.6% intraclass correlation coefficient in the diagnosis of IA stage.

CONCLUSION

The simultaneous consideration of T2 and DWI technique may signify a noninvasive, rapid, safe, and accurate approach for precisely assessing myometrial invasion and EC staging. Elimination of intravenous contrast material result in prevention of contrast related side effects beside significant cost reduction for health care systems and patients with a comparable result to contrast enhanced MRI.

Ovarian metastasis risk factors in endometrial carcinoma: A systematic review and meta-analysis

OBJECTIVE

To investigate the incidence of ovarian metastasis in endometrial carcinoma (EC) and analyze its risk factors and provide a theoretical basis for whether retention of the ovary in patients with EC.

METHODS

A systematic search using synonyms of 'ovarian cancer' and 'metastasis' was conducted in PubMed, Cochrane database, Embase, Google Scholar, and WOS database. Meta-analysis was performed on 7 included studies, comprising 4281 clinical-stage I-IV EC patients. Studies were assessed using the Newcastle-Ottawa Scale (NOS) criteria. Odds risks (OR) and 95% confidence intervals (CI) were calculated using an inverse variance weighted random-effects model.

RESULTS

The ovarian metastasis risk of EC was significantly higher for patients with myometrial invasion >1/2 (OR = 18.19, 95% CI 5.34 to 61.96 compared to myometrial invasion ≤1/2), any pelvic lymph node invasion (PLNI) (OR = 5.41, 95% CI 2.60-10.97 compared to without PLNI), G3 pathological grade (OR = 2.66, 95%CI 1.35-5.24 compared to G1-G2), non-endometrioid pathological type (OR = 6.46, 95% CI 3.25 to 12.83 compared to endometrioid), lymphatic vascular space invasion (LVSI) (OR = 6.46, 95% CI 3.25 to 12.83 compare to without LVSI), age >45 (OR = 2.01, 95% CI 0.29 to 14.11 compared to age ≤45), and cervical invasion (OR = 4.12, 95% CI 1.87 to 9.08 compared to without cervical invasion).

CONCLUSION

About 4.95% of EC patients develop ovarian metastasis. Age >45, myometrial invasion >1/2, cervical invasion, PLNI, pathological type, G3 pathological grade, and LVSI were the high-risk factors for ovarian metastasis of EC. Ovarian preservation should be carefully selected for patients with EC, and preoperative and intraoperative evaluations should be entirely performed.

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.

NCD epidemic and sexual reproductive health issues in the infectious disease world

Nil.