AIMC Topic: Endometrial Neoplasms

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Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts.

The Lancet. Digital health
BACKGROUND: Endometrial cancer can be molecularly classified into POLE, mismatch repair deficient (MMRd), p53 abnormal (p53abn), and no specific molecular profile (NSMP) subgroups. We aimed to develop an interpretable deep learning pipeline for whole...

Robot-assisted modified radical hysterectomy with removal of lymphatic vessel using indocyanine green: A new method.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The sentinel lymph node (SLN) procedures using indocyanine green (ICG) have recently been performed worldwide. The aim of this study was to emphasise the safety of robot-assisted modified radical hysterectomy (RAMRH) with removal of the l...

Predicting recurrence and recurrence-free survival in high-grade endometrial cancer using machine learning.

Journal of surgical oncology
OBJECTIVE: To develop machine-learning models to predict recurrence and time-to-recurrence in high-grade endometrial cancer (HGEC) following surgery and tailored adjuvant treatment.

The efficacy of deep learning models in the diagnosis of endometrial cancer using MRI: a comparison with radiologists.

BMC medical imaging
PURPOSE: To compare the diagnostic performance of deep learning models using convolutional neural networks (CNN) with that of radiologists in diagnosing endometrial cancer and to verify suitable imaging conditions.

Robot-assisted versus laparoscopic minimally invasive surgery for the treatment of stage I endometrial cancer.

Gynecologic oncology
OBJECTIVE: Recent reports in both cervical and endometrial cancer suggest that minimally invasive surgery (MIS) had an unanticipated negative impact on long-term clinical outcomes, including recurrence and death. Given increasing use of robotic surge...

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

Contrast media & molecular imaging
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. . 80 patients...

The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.

Journal of applied clinical medical physics
PURPOSE: To develop a 3D-Unet dose prediction model to predict the three-dimensional dose distribution of volumetric modulated arc therapy (VMAT) for cervical cancer and test the dose prediction performance of the model in endometrial cancer to explo...

"Long-term outcome in endometrial cancer patients after robot-assisted laparoscopic surgery with sentinel lymph node mapping".

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVE: Sentinel Lymph Node (SLN) mapping is increasingly used as an alternative to lymphadenectomy in endometrial cancer. There is, however, limited data regarding the clinical outcome and survival after SLN mapping. The aim of the study was to d...

A radiogenomics application for prognostic profiling of endometrial cancer.

Communications biology
Prognostication is critical for accurate diagnosis and tailored treatment in endometrial cancer (EC). We employed radiogenomics to integrate preoperative magnetic resonance imaging (MRI, n = 487 patients) with histologic-, transcriptomic- and molecul...

Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

Gynecologic oncology
BACKGROUND: Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic va...