JOURNAL ARTICLE

Habitats based multiparametric magnetic resonance imaging radiomics model for prediction of endometrial cancer molecular subtypes.

Wentao JinHe ZhangHaiming LiGuofu ZhangWentao LiTianping Wang

Year: 2024 Journal:   Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition

Abstract

Motivation: Endometrial cancer (EC) is a highly heterogeneous cancer comprising of both histological and molecular subtypes. The p53abn subtype is associated with a poor prognosis particularly. Goal(s): We aimed to develop habitats based multiparametric MRI radiomics model for the prediction of EC molecular subtype and evaluated the performance. Approach: Our study is a dual-center retrospective research. Results: Our habitats model demonstrated good performance in both internal and external validations. It exhibited higher efficacy compared to radiomics and clinical models. Impact: Using a non-invasive modality method to trigger these subtypes of EC as early as possible will aid clinicians to establish individual treatment. This research also marks the first use of habitat analysis in the study of EC.

Keywords:
Radiomics Magnetic resonance imaging Endometrial cancer Cancer Nuclear magnetic resonance Medicine Radiology Physics Internal medicine

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Topics

Radiomics and Machine Learning in Medical Imaging
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging

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