Application of multimodal fusion technology in early recurrence prediction and pathological analysis of
Li-Hong Huang1, Yi-Jing Fang2, Xiao-Jun Zheng1
1Department of Radiology, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi Zhuang Autonomous Region, China.
Background:
Early recurrence is an important factor affecting the prognosis of hepatocellular carcinoma (HCC), but its preoperative prediction remains challenging.
Aim:
To explore the value of a multimodal interpretable fusion model combining computed tomography (CT) habitat imaging (HI), radiomics, and clinical features in predicting early recurrence of HCC and analyze its correlation with pathological indicators.
Methods:
The 191 HCC patients were categorized into early recurrence and non-early recurrence groups based on postoperative follow-up outcomes, and randomly divided into training and testing sets in a 7:3 ratio. Based on CT arterial phase and clinical data, the habitat model, radiomics model, clinical model, and fusion model were constructed and compared for their predictive ability in early recurrence of HCC. For the optimal model, SHapley Additive exPlanations (SHAP) analysis was performed to evaluate the contribution of different features in the model, and the correlation between HI and radiomics features with tumor microvascular invasion (MVI), Ki67 expression, GPC-3 expression, and pathological grading was analyzed.
Results:
The fusion model demonstrated the best performance in predicting early recurrence of HCC, achieving the area under the curve of 0.933 on the validation set. The decision curve analysis curve indicated that the fusion model yielded the highest clinical net benefit. SHAP analysis provided valuable insights into explaining the fusion model's prediction of early HCC recurrence. Correlation analysis revealed significant associations between certain radiomics and Habitat features and pathological indicators such as MVI and Ki-67 expression in HCC.
Conclusion:
An interpretable fusion model integrating clinical, radiomic, and habitat features can assist clinicians in identifying early postoperative recurrence of HCC, offering significant potential for prognosis prediction and clinical management.
