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Background: The tumor histological grade is closely related to the prognosis of patients with endometrial cancer (EC). Multiparametric MRI, including diffusion-weighted imaging (DWI), provides information about the cellular density that may be useful to differentiate between benign and malignant uterine lesions. However, correlations between apparent diffusion coefficient (ADC) values and histopathological grading in endometrial cancer remain controversial. Material and methods: We retrospectively evaluated 92 patients with endometrial cancers, including both endometrioid adenocarcinomas (64) and non-endometrioid adenocarcinomas (28). All patients underwent DWI procedures, and mean ADC values were calculated in a region of interest. These values were then correlated with the tumor grading offered by the histopathological examination, which was considered the gold standard. In this way, the patients were divided into three groups (G1, G2, and G3). The ADC values were then compared to the results offered by the biopsy to see if the DWI sequence and ADC map could replace this procedure. We also compared the mean ADC values to the myometrial invasion (50%) and lymphovascular space invasion. Results: We have divided the ADC values into three categories corresponding to three grades: >0.850 × 10−3 mm2/s (ADC1), 0.730–0.849 × 10−3 mm2/s (ADC2) and <0.730 × 10−3 mm2/s (ADC3). The diagnostic accuracy of the ADC value was 85.71% for ADC1, 75.76% for ADC2, and 91.66% for ADC3. In 77 cases out of 92, the category in which they were placed using the ADC value corresponded to the result offered by the histopathological exam with an accuracy of 83.69%. For only 56.52% of patients, the biopsy result included the grading system. For each grading category, the mean ADC value showed better results than the biopsy; for G1 patients, the mean ADC value had an accuracy of 85.71% compared to 66.66% in the biopsy, G2 had 75.76% compared to 68.42%, and G3 had 91.66 compared to 75%. For both deep myometrial invasion and lymphovascular space invasion, there is a close, inversely proportional correlation with the mean ADC value. Conclusions: Mean endometrial tumor ADC on MR-DWI is inversely related to the histological grade, deep myometrial invasion and lymphovascular space invasion. Using this method, the patients could be better divided into risk categories for personalized treatment. [ABSTRACT FROM AUTHOR]

Simple Summary: Sentinel lymph node (SLN) mapping has been introduced to endometrial cancer treatment as an alternative to lymph node dissection for lymph node staging. Lymphovascular space invasion (LVSI) is a known prognostic risk factor in endometrial cancer and is associated with lymph node metastasis and worse outcomes. This study shows that LVSI is an independent predictor of recurrence in node-negative endometrial cancer patients with SLN mapping alone. The negative predictive value of sentinel lymph node mapping is significantly lower in LVSI-positive endometrial cancer patients. Due to these findings, importance should be attached to LVSI in early-stage endometrial cancer patients with negative SLN mapping, and adjuvant therapy should be discussed more thoroughly in these cases. Background: SLN mapping has emerged as a standard of care in endometrial cancer due to its high sensitivity and significant reduction in morbidity. Although lymphovascular space invasion (LVSI) is a known risk factor for lymph node metastasis and recurrence, evidence on the reliability of SLN mapping in LVSI-positive patients is scarce. The aim of this study was to determine the impact of LVSI on the diagnostic performance of SLN mapping. Methods: This retrospective cohort study included patients with endometrial cancer who underwent primary surgical treatment at the Bern University Hospital, Switzerland, between 2012 and 2022. Results: LVSI was present in 22% of patients and was significantly associated with lymph node metastasis (p < 0.001) and recurrence (p < 0.001). In node-negative patients with only SLN mapping performed, LVSI was an independent predictor of recurrence during multivariable Cox regression analysis (p = 0.036). The negative predictive value of SLN mapping was 91.5% and was significantly lower in tumors with LVSI (75.0%) compared to LVSI-negative tumors (95.6%, p = 0.004). Conclusion: The presence of LVSI was significantly associated with worse oncological outcomes. LVSI was an independent predictor of recurrence in node-negative patients with only SLN mapping performed. Furthermore, the negative predictive value of SLN mapping was significantly lower in LVSI-positive tumors. [ABSTRACT FROM AUTHOR]

Lymphovascular space invasion (LVSI) is the presence of tumor emboli in the endothelial-lined space at the tumor body's invasive edge. LVSI is one of three Sedlis criteria components—a prognostic tool for early cervical cancer (CC)—essential for indicating poor prognosis, such as lymph node metastasis, distant metastasis, or shorter survival rate. Despite its clinical significance, an in-depth comprehension of the molecular mechanisms or immune dynamics underlying LVSI in CC remains elusive. Therefore, this study investigated tumor-immune microenvironment (TIME) dynamics of the LVSI-positive group in CC. RNA sequencing included formalin-fixed paraffin-embedded (FFPE) slides from 21 CC patients, and differentially expressed genes (DEGs) were analyzed. Functional analysis and immune deconvolution revealed aberrantly enriched PI3K/Akt pathway activation and a heterogenic immune composition with a low abundance of regulatory T cells (Treg) between LVSI-positive and LVSI-absent groups. These findings improve the comprehension of LSVI TIME and immune mechanisms, benefiting targeted LVSI therapy for CC. [ABSTRACT FROM AUTHOR]

Simple Summary: Cervical cancer remains a major public health concern despite available screening and vaccination. Early-stage disease is frequently treated with radical surgery that has greater operative complications and results in a loss of fertility. Cervical cancer is most frequently diagnosed in pre-menopausal women, making fertility preservation a frequent concern. Additionally, in early-stage disease, there is mounting evidence that radical surgery is not necessary to achieve optimal oncologic outcomes. Using less radical surgical techniques improves patient surgical recovery, avoids long-term complications of surgery, and allows women to retain their fertility if they desire. This editorial presents the data for conservative management of early-stage cervical cancer. Cervical cancer remains a significant public health concern within the United States and across the world. Cervical cancer is most frequently diagnosed in women between the ages of 35 and 44 and therefore affects a younger patient population than many other cancers. The management of early-stage disease has frequently utilized radical hysterectomy with the associated increased surgical morbidity, without clear evidence of any benefits. In stage IA disease, there are retrospective pathologic data supporting the safety of conservative surgery and lymphadenectomy over radical hysterectomy. There are also emerging prospective studies supporting conservative management. This editorial presents the evidence for conservative management of stage IA cervical cancer by reviewing the existing retrospective studies as well as the ongoing prospective studies. [ABSTRACT FROM AUTHOR]

Simple Summary: In patients with early-stage endometrioid endometrial cancer, the presence of lymph vascular space involvement (LVSI) correlates with nodal metastases, shorter disease-free survival and overall survival. However, the effect of LVSI on recurrence patterns of these patients has been poorly studied, and the optimal adjuvant treatment remains unclear. Additionally, positive LVSI is indicative for nodal assessment, however, this parameter is usually not Known until a final pathology report. The main aim of our study was to analyze oncological outcomes and patterns of recurrence of these patients according to LVSI status, as well as to determine preoperative predictors of positive LVSI. We confirmed in a large multi-institutional cohort of patients (3546 participants), that positive LVSI is an independent prognostic factor for distant recurrences (HR 2.37) but not for local recurrence. In addition, deep myometrial invasion, high-grade tumors, cervical stroma invasion, and tumor diameter ≥ 2 cm are independent predictors of positive LVSI. The main aim is to compare oncological outcomes and patterns of recurrence of patients with early-stage endometrioid endometrial cancer according to lymphovascular space invasion (LVSI) status. The secondary objective is to determine preoperative predictors of LVSI. We performed a multicenter retrospective cohort study. A total of 3546 women diagnosed with postoperative early-stage (FIGO I-II, 2009) endometrioid endometrial cancer were included. Co-primary endpoints were disease-free survival (DFS), overall survival (OS), and pattern of recurrence. Cox proportional hazard models were used for time-to-event analysis. Univariate and multivariate logistical regression models were employed. Positive LVSI was identified in 528 patients (14.6%) and was an independent prognostic factor for DFS (HR 1.8), OS (HR 2.1) and distant recurrences (HR 2.37). Distant recurrences were more frequent in patients with positive LVSI (78.2% vs. 61.3%, p < 0.01). Deep myometrial invasion (OR 3.04), high-grade tumors (OR 2.54), cervical stroma invasion (OR 2.01), and tumor diameter ≥ 2 cm (OR 2.03) were independent predictors of LVSI. In conclusion, in these patients, LVSI is an independent risk factor for shorter DFS and OS, and distant recurrence, but not for local recurrence. Deep myometrial invasion, cervical stroma invasion, high-grade tumors, and a tumor diameter ≥ 2 cm are independent predictors of LVSI. [ABSTRACT FROM AUTHOR]

Simple Summary: Deep myometrial infiltration, clinical risk score, histological type, and lymphovascular space invasion are important clinical variables that have significant management implications for endometrial cancer patients. Determination of these factors using pure T2-weighted MRI is time-consuming, and the accuracy of this relies on the experience of the clinicians. Combining clinical information and radiomic features from MRI, we developed machine learning classification models to predict these clinical variables. Based on a training dataset, an automatic selection classification model with an optimized hyperparameters method was adopted to find the optimal classifiers. The accuracy of the model predictions was evaluated using an independent external testing dataset. The results suggest that an integrated model (combining clinical and radiomic features) achieved a reasonable accuracy for endometrial cancer clinical variable prediction. The application of these models in clinical practice could potentially lead to cost reductions and personalized treatment. Purpose: To predict deep myometrial infiltration (DMI), clinical risk category, histological type, and lymphovascular space invasion (LVSI) in women with endometrial cancer using machine learning classification methods based on clinical and image signatures from T2-weighted MR images. Methods: A training dataset containing 413 patients and an independent testing dataset consisting of 82 cases were employed in this retrospective study. Manual segmentation of the whole tumor volume on sagittal T2-weighted MRI was performed. Clinical and radiomic features were extracted to predict: (i) DMI of endometrial cancer patients, (ii) endometrial cancer clinical high-risk level, (iii) histological subtype of tumor, and (iv) presence of LVSI. A classification model with different automatically selected hyperparameter values was created. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, F1 score, average recall, and average precision were calculated to evaluate different models. Results: Based on the independent external testing dataset, the AUCs for DMI, high-risk endometrial cancer, endometrial histological type, and LVSI classification were 0.79, 0.82, 0.91, and 0.85, respectively. The corresponding 95% confidence intervals (CI) of the AUCs were [0.69, 0.89], [0.75, 0.91], [0.83, 0.97], and [0.77, 0.93], respectively. Conclusion: It is possible to classify endometrial cancer DMI, risk, histology type, and LVSI using different machine learning methods. [ABSTRACT FROM AUTHOR]

Background: SLN mapping has emerged as a standard of care in endometrial cancer due to its high sensitivity and significant reduction in morbidity. Although lymphovascular space invasion (LVSI) is a known risk factor for lymph node metastasis and recurrence, evidence on the reliability of SLN mapping in LVSI-positive patients is scarce. The aim of this study was to determine the impact of LVSI on the diagnostic performance of SLN mapping., Methods: This retrospective cohort study included patients with endometrial cancer who underwent primary surgical treatment at the Bern University Hospital, Switzerland, between 2012 and 2022., Results: LVSI was present in 22% of patients and was significantly associated with lymph node metastasis ( p < 0.001) and recurrence ( p < 0.001). In node-negative patients with only SLN mapping performed, LVSI was an independent predictor of recurrence during multivariable Cox regression analysis ( p = 0.036). The negative predictive value of SLN mapping was 91.5% and was significantly lower in tumors with LVSI (75.0%) compared to LVSI-negative tumors (95.6%, p = 0.004)., Conclusion: The presence of LVSI was significantly associated with worse oncological outcomes. LVSI was an independent predictor of recurrence in node-negative patients with only SLN mapping performed. Furthermore, the negative predictive value of SLN mapping was significantly lower in LVSI-positive tumors.

Objective: This study assessed the predictive value of the metabolic risk score (MRS) for lymphovascular space invasion (LVSI) in endometrial cancer (EC) patients., Methods: We included 1076 patients who were diagnosed with EC between January 2006 and December 2020 in Peking University People's Hospital. All patients were randomly divided into the training and validation cohorts in a ratio of 2:1. Data on clinicopathological indicators were collected. Univariable and multivariable logistic regression analysis was used to define candidate factors for LVSI. A backward stepwise selection was then used to select variables for inclusion in a nomogram. The performance of the nomogram was evaluated by discrimination, calibration, and clinical usefulness., Results: Independent predictors of LVSI included differentiation grades (G2: OR = 1.800, 95% CI: 1.050-3.070, p = 0.032) (G3: OR = 3.49, 95% CI: 1.870-6.520, p < 0.001), histology (OR = 2.723, 95% CI: 1.370-5.415, p = 0.004), MI (OR = 4.286, 95% CI: 2.663-6.896, p < 0.001), and MRS (OR = 1.124, 95% CI: 1.067-1.185, p < 0.001) in the training cohort. A nomogram was established to predict a patient's probability of developing LVSI based on these factors. The ROC curve analysis showed that an MRS-based nomogram significantly improved the efficiency of diagnosing LVSI compared with the nomogram based on clinicopathological factors ( p = 0.0376 and p = 0.0386 in the training and validation cohort, respectively). Subsequently, the calibration plot showed a favorable consistency in both groups. Moreover, we conducted a decision curve analysis, showing the great clinical benefit obtained from the application of our nomogram. However, our study faced several limitations. Further external validation and a larger sample size are needed in future studies., Conclusion: MRS-based nomograms are useful for predicting LVSI in patients with EC and may facilitate better clinical decision-making.

Simple Summary: Lymph node involvement is one of the major prognosis factors for early-stage cervical cancer. Improvement in preoperative identification of node-positive patients may lead to a more accurate triage to primary chemoradiation for these patients instead of radical surgery followed by adjuvant radiotherapy, given the increased morbidity of combined treatment. Several studies have well established risk factors for node involvement, but they are based on final pathologic examination of radical hysterectomy specimens and are usually extrapolated for preoperative risk assessment. Among these risk factors, tumor size, lymphovascular space invasion (LVSI) and depth of stromal invasion might be assessed in conization specimens. Our findings suggest that patients with depth of stromal invasion lower than 10 mm and no LVSI in conization specimens had lower risk of micro- and macrometastatic SLN. In this subpopulation, full node dissection may be questionable in case of SLN unilateral detection. Background: The prognosis of patients with cervical cancer is significantly worsened in case of lymph node involvement. The goal of this study was to determine whether pathologic features in conization specimens can predict the sentinel lymph node (SLN) status in early-stage cervical cancer. Methods: An ancillary analysis of two prospective multicentric database on SLN biopsy for cervical cancer (SENTICOL I and II) was carried out. Patients with IA to IB2 2018 FIGO stage, who underwent preoperative conization before SLN biopsy were included. Results: Between January 2005 and July 2012, 161 patients from 25 French centers fulfilled the inclusion criteria. Macrometastases, micrometastases and Isolated tumor cells (ITCs) were found in 4 (2.5%), 6 (3.7%) and 5 (3.1%) patients respectively. Compared to negative SLN patients, patients with micrometastatic and macrometastatic SLN were more likely to have lymphovascular space invasion (LVSI) (60% vs. 29.5%, p = 0.04) and deep stromal invasion (DSI) ≥ 10 mm (50% vs. 17.8%, p = 0.04). Among the 93 patients with DSI < 10 mm and absence of LVSI on conization specimens, three patients (3.2%) had ITCs and only one (1.1%) had micrometastases. Conclusions: Patients with DSI < 10 mm and no LVSI in conization specimens had lower risk of micro- and macrometastatic SLN. In this subpopulation, full node dissection may be questionable in case of SLN unilateral detection. [ABSTRACT FROM AUTHOR]

Simple Summary: The purpose of modifying a tumor staging system is to incorporate already well-established prognostic factors, allowing one to stratify cases and leading to tailored treatment approaches. Although lymphovascular space invasion (LVSI) has been described as an independent risk-factor of recurrence in early-stage cervical cancer and defined intermediate and high-risk cervical cancer according to the ESGO (European Society of Gynaecological Oncology) guidelines, this factor remains controversial and was not included in the last revised 2018 International Federation of Gynecology and Obstetrics (FIGO) classification. The aim of the present study was to determine whether LVSI has an impact on the prognosis of IB1 patients according to 2018 FIGO classification through two French prospective multicentric cohorts. Our results highlighted that LVSI was associated with a significantly decreased 5-year DFS in IB1 2018 FIGO stage compared to negative LVSI. Particular attention should be paid to LVSI status in early-stage cervical cancer for a more precise risk assessment and we suggest that LVSI may be considered in the new 2018 FIGO classification. Background: The aim of this study was to assess the prognostic impact of Lymphovascular space invasion (LVSI) in IB1 stage of the revised 2018 International Federation of Gynecology and Obstetrics (FIGO) classification for cervical cancer. Methods: A secondary analysis of two French prospective multicentric trials on Sentinel Lymph node biopsy for cervical cancer was performed. Patients with 2009 FIGO IB1 stage who underwent radical surgery between January 2005 and July 2012 from 28 French expert centers were included. The stage was modified retrospectively according to the new 2018 FIGO staging system. Results: According to the 2009 FIGO classification, 246 patients had IB1 disease stage and fulfilled the inclusion criteria. The median follow-up was 48 months (4–127). Twenty patients (8.1%) experienced a recurrence, and the 5-year Disease Free Survival (DFS) was 90.0%. Compared to 2018 IB1 staged patients, new IB2 had significantly decreased 5-year DFS, 78.6% vs. 92.9%, p = 0.006 whereas IIIC patients had similar 5-year DFS (91.7%, p = 0.95). In the subgroup of patients with FIGO 2018 IB1 stage, the presence of LVSI was associated with a significant decrease in DFS (82.5% vs. 95.8%, p = 0.04). Conclusions: LVSI is associated with decreased 5-year DFS in IB1 2018 FIGO stage and LVSI status should be considered in early-stage cervical cancer for a more precise risk assessment. [ABSTRACT FROM AUTHOR]