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Abstract #4287

Radiomic features Based on Multi-sequence MRI Predict Immunohistochemical Biomarkers of Endometrial Cancer

Liting Shen1, Xiaojun Chen2,3, Xue Wang1, Lu Han4, and Peng Wu4
1The Second Affiliated Hospital and Yuying Children′s Hospital of Wenzhou Medical University, Wenzhou, China, 2Affiliated Jinhua hospital, Jinhua, China, 3Zhejiang University School of Medicine, Jinhua, China, 4Philips Healthcare, Shanghai, China

Synopsis

Keywords: Pelvis, Radiomics

Motivation: A non-invasive, precise, and efficient preoperative evaluation method is crucial for the prognosis of patients with EC.

Goal(s): The aim of this study was to construct MRI-based radiomics models to predict immunohistochemical biomarkers and assess the relationship between radiomic features and the Ki-67 proliferation rate in EC.

Approach: The receiver operating characteristic (ROC) curves were analyzed to evaluate the performance of the radiomics models.

Results: Both single sequence and multi-sequence models demonstrated good diagnostic performance, although the diagnostic performance of multi-sequence models outperformed the single sequence models.

Impact: MRI-based radiomic features are promising predictors of immunohistochemistry and prognosis in EC.

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Keywords