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Radiomics and molecular analysis: Bridging the gap for predicting hepatocellular carcinoma prognosis

Year: 2024

Type: editorial

Abstract: This editorial examines a recent study that used radiomics based on computed tomography (CT) to predict the expression of the fibroblast-related gene enhancer of zeste homolog 2 (EZH2 ) and its correlation with the survival of patients with hepatocellular carcinoma (HCC). By integrating radiomics with molecular analysis, the study presented a strategy for accurately predicting the expression of EZH2 from CT scans. The findings demonstrated a strong link between the radiomics model, EZH2 expression, and patient prognosis. This noninvasive approach provides valuable insights into the therapeutic management of HCC.

Source: World Journal of Clinical Cases

DOI: 10.12998/wjcc.v13.i4.98550

Authors: Chun-Han Cheng, Wen-Rui Hao, Tzu-Hurng Cheng

Institutions: Linkou Chang Gung Memorial Hospital, Ministry of Health and Welfare, Taipei Medical University-Shuang Ho Hospital, Taipei Medical University, China Medical University

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4404304122

Cites: 8

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Related to: 10