Radiomics and molecular analysis: Bridging the gap for predicting hepatocellular carcinoma prognosis
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 (<i>EZH2</i>) 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 <i>EZH2</i> from CT scans. The findings demonstrated a strong link between the radiomics model, <i>EZH2</i> expression, and patient prognosis. This noninvasive approach provides valuable insights into the therapeutic management of HCC.
Authors
- Chun‐Han Cheng (ORCID: https://orcid.org/0000-0002-7262-861X)
- Wen‐Rui Hao (ORCID: https://orcid.org/0000-0001-6067-1306)
- Tzu-Hurng Cheng
Institutions
- Taipei Medical University (TW)
Publication Details
- Journal
- World Journal of Clinical Cases
- Published
- 2024-11-13
- DOI
- https://doi.org/10.12998/wjcc.v13.i4.98550
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00