ArticleRadiology and oncology2026
Prediction of Ki-67 expression in hepatocellular carcinoma: a dual-center study based on T2-weighted imaging habitat analysis.
Article in Radiology and oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundLimited research has applied habitat imaging to evaluate the association between T2-weighted magnetic resonance imaging (T2WI-MRI) features and Ki-67 expression in hepatocellular carcinoma HCC). This study aimed to link T2WI habitat-derived parameters to Ki-67 status and aggressiveness in HCC. PATIENTS AND
methodsThis dual-center retrospective study, enrolled patients with pathologically confirmed HCC undergoing preoperative MRI (2020-2024). Using Ki-67 index cutoff (20%). Tumor habitat partitioning was performed using k-means clustering (k = 5), followed by extraction of both habitat-specific radiomic features and conventional whole-tumor features. Feature selection was conducted using least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation. Three predictive models were constructed with the ExtraTrees algorithm: a habitat model, a radiomics model, and a clinical model. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), DeLong test, and decision curve analysis (DCA).
resultsT2WI-based habitat imaging enables a noninvasive assessment of intratumoral heterogeneity, significantly improving the prediction of Ki-67 expression status in HCC. This approach may provide a promising imaging biomarker for molecular subtyping and support personalized preoperative treatment strategies.
conclusionsT2WI habitat imaging enables improved Ki-67 prediction, supporting informed therapeutic decisions in HCC.
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