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arXiv Computer Vision By Jun Cheng, Yuanyuan Kong, Qing Huang, Xiaotong Tan, Licong Dong, Yulong Han, Wufeng Xue, Ruobing Huang, Dong Ni, Qi Yang, Jie Yu, Ping Liang

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma by Integrating Multimodal Ultrasound and Clinical Data: A Multicenter Study

Read the original on arXiv Computer Vision →

The study developed a multimodal ultrasound and clinical data model to predict microvascular invasion (MVI) preoperatively in hepatocellular carcinoma (HCC). Using data from 489 patients across eight centers, the model combined B-mode ultrasound, color Doppler flow imaging, dynamic contrast-enhanced ultrasound, and clinical information, achieving an AUC of 0.8953 in external validation. Dynamic contrast-enhanced ultrasound contributed the most predictive power, while other modalities and clinical data added complementary value.

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