Radiomics Analysis Based on Preoperative Multiparametric MRI for Prediction of TACE Refractoriness in Hepatocellular Carcinoma
Motivation: Parts of HCC respond poorly to TACE, and its efficacy declines as the number of procedures increases in the clinical practice, which is called TACE refractoriness. Goal(s): To develop and validate a preoperative multiparametric MRI-based radiomics model to predict TACE refractoriness in HCC. Approach: Radiomics feature selection was performed using PCC and RFE, and SVM was used to construct radiomic models based on each sequence and their combination, clinical-radiological model based on selected clinical-radiological predictor and combined model. Results: The combined model exhibited excellent predictive performance. The multi-phase radiomics signature performed better in predicting TACE refractoriness compared to the best single-phase radiomics signature. Impact: The preoperative multiparametric MRI radiomics analysis can predict TACE refractoriness in hepatocellular carcinoma, which may provide better guidance for decision-making regarding further TACE treatment and optimize the mode of treatment and patient management, ultimately resulting in patient survival benefits.
Authors
- Yan Qin Tan (ORCID: https://orcid.org/0000-0002-7529-9807)
- Wenji Xu (ORCID: https://orcid.org/0000-0002-3057-8589)
- Hui Zhang (ORCID: https://orcid.org/0000-0002-1523-2651)
Publication Details
- 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
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/3655
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00