Intratumoral heterogeneity of CT enhancement for component prediction and prognostic significance in combined hepatocellular carcinoma‑cholangiocarcinoma.

Abstract

Objectives: To construct a combined nomogram using CT enhancement ratio-based habitat imaging and radiological features in predicting the main component of combined hepatocellular carcinoma‑cholangiocarcinoma (cHCC-CCA), and to assess its ability for stratifying the prognosis.

Materials and methods: Patients with pathologically diagnosed cHCC-CCA who underwent contrast-enhanced CT examinations were retrospectively included and randomized into the training and validation cohorts. Tumors were grouped into high hepatocellular carcinoma (HCC) component (high-HCC%) and low-HCC component (low-HCC%) according to pathology. Voxels of tumor from early enhancement ratio and late enhancement ratio maps were clustered into different habitats through the k-means algorithm. The volume fractions of different habitats were quantified. Logistic regression analyses were utilized to identify independent predictors for high-HCC%, construct prediction models, and visualize them as a nomogram. The predictive performance was assessed by receiver operating characteristic analysis. Survival analysis was conducted using the Kaplan-Meier method.

Results: 165 patients were finally included, and 78 (47.27%) patients were grouped as high-HCC%. Four tumor habitats were determined. The fraction of habitat 1 (f₁) was significantly higher, while the fraction of habitat 4 (f₄) was significantly lower in the high-HCC% group than in the low-HCC% group. Tumor capsule, corona enhancement, delayed enhancement, f₁, and f₄ were used to construct the combined nomogram with AUCs of 0.927 and 0.923 in training and validation cohorts, respectively. The combined nomogram predicted-high-HCC% exhibited better prognoses than the predicted-low-HCC% groups in terms of recurrence-free survival and overall survival.

Conclusion: Enhancement-based CT habitat imaging exhibited potential for predicting the main component cHCC-CCA, and provided a tool for prognosis stratification.

Key points: Question The component of combined hepatocellular-cholangiocarcinoma (cHCC-CCA) significantly affected the prognosis, but there is no effective method for predicting the main component of cHCC-CCA. Findings The combined nomogram integrated habitat parameters and radiological features can predict the main component of cHCC-CCA and help stratify the prognosis after hepatectomy. Clinical relevance The habitat-based combined nomogram offers an effective tool for personalized and appropriate treatment in cHCC-CCA patients.