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Abstract #0717

Multi-region Radiomics-based Prediction of Microvascular Invasion in Hepatocellular Carcinoma Using Multi-sequence MRI

Feng Chen1, Shishi Luo1, Mengying Dong1, Weiyuan Huang1, Yuting Liao2, Xiao Yu2, and Yongzhou Xu2
1Hainan General Hospital (Hainan Affiliated Hospital of Hainan Medical University), Haikou, China, 2Philips Healthcare, Guangzhou, China

Synopsis

Keywords: Liver, Cancer

Motivation: Identifying MVI before surgery is crucial to optimizing treatment strategies and predicting prognosis.

Goal(s): To develop a multi-region radiomics-based predictive model using multi-sequence MRI to assess MVI in HCC.

Approach: Three Models (Tumor, Tumor-Expand5, Tumor-Expand10) were constructed and evaluated.

Results: The Tumor-Expand5 model, with the best predictive accuracy, demonstrates its effectiveness. The research explores the advantages of 5mm VOI expansion for MVI diagnosis over the 10mm VOI expansion, providing valuable insights. Despite limitations, this study offers a preoperative tool to predict MVI in HCC, enhancing clinical decision-making.

Impact: Predicting Microvascular Invasion (MVI) in HCC through multi-region radiomics-based MRI advances precision medicine and treatment optimization. The Tumor-Expand5 model's superior diagnostic performance demonstrates the potential to enhance clinical decision-making.

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