Radiomics in hepatocellular carcinoma: A state-of-the-art review
Shan Yao, Ye Zheng, Yi Wei, Hanyu Jiang, Bin Song
Abstract
Hepatocellular carcinoma (HCC) is the most common cancer and the second major contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide invisible high-dimensional quantitative and mineable data derived from routine-acquired images, has enormous potential for HCC management from diagnosis to prognosis as well as providing contributions to the rapidly developing deep learning methodology. This article aims to review the radiomics approach and its current state-of-the-art clinical application scenario in HCC. The limitations, challenges, and thoughts on future directions are also summarized.
Topics & Concepts
RadiomicsMedicineHepatocellular carcinomaIntensive care medicineMedical physicsRadiologyInternal medicineRadiomics and Machine Learning in Medical ImagingHepatocellular Carcinoma Treatment and PrognosisRenal cell carcinoma treatment