Radiomics in the diagnosis and treatment of hepatocellular carcinoma_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

GULIZAINA Hapaer ¹ , CHE Feng ¹ , LI Qian ¹ , WEI Yi ¹ , HUANG Zixing ¹ ,  SONG Bin ^1,2

1. Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Department of Radiology, Sanya People’s Hospital, Sanya 572000, P. R. China;

Corresponding author：

SONG Bin, Email: songlab_radiology@163.com

Keywords：

hepatocellular carcinoma; radiomics; diagnosis and treatment

DOI：

10.7507/1007-9424.202409073

Video：

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Objective To summarize the progress of radiomics in the diagnosis and treatment of hepatocellular carcinoma and discuss its future direction, limitations and challenges. Method We retrieve the literature related to radiomics in the diagnosis and treatment of hepatocellular carcinoma and make an review. Results Traditional hepatocellular carcinoma imaging examination, diagnosis and differential diagnosis had certain limitations. Radiomics as an emerging technology, it helped extract tissue biological information that could not be detected by the naked eye from high-throughput quantitative images and transform into high-dimensional qualitative quantitative data, and either alone or in combination with other clinical and molecular data such as demographics, histology, genomics or proteomics or other clinical and molecular data to solve clinical problems such as hepatocellular carcinoma diagnosis and differential diagnosis, staging and grading, therapeutic regimen development and predicting prognosis and survival after therapy, etc. At present, there were still several problems to be solved in radiomics, such as insufficient interpretability of the combined artificial intelligence-medical imaging approach, lack of uniform standards and lack of external validation, etc. Conclusions The study of radiomics in the diagnosis and treatment of hepatocellular carcinoma has been deepened and expanded to different degrees with great potential and application prospects. Radiomics brings greater benefits to the diagnosis, treatment and management of hepatocellular carcinoma patients, provides a new direction for optimizing medical decision-making and promoting the development of precision medicine. However, there are still some deficiencies and challenges to overcome in the radiomics technology and methods, which require extensive validation and optimization through further clinical trials.

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6. Yao S, Ye Z, Wei Y, et al. Radiomics in hepatocellular carcinoma: a state-of-the-art review. World J Gastrointest Oncol, 2021, 13(11): 1599-1615.
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8. Hricak H. Oncologic imaging: a guiding hand of personalized cancer care. Radiology, 2011, 259(3): 633-640.
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41. Wu C, Du X, Zhang Y, et al. Five machine learning-based radiomics models for preoperative prediction of histological grade in hepatocellular carcinoma. J Cancer Res Clin Oncol, 2023, 149(16): 15103-15112.
42. Yan Y, Si Z, Chun C, et al. Multiphase MRI-based radiomics for predicting histological grade of hepatocellular carcinoma. J Magn Reson Imaging, 2024, 60(5): 2117-2127.
43. Ameli S, Venkatesh BA, Shaghaghi M, et al. Role of MRI-derived radiomics features in determining degree of tumor differentiation of hepatocellular carcinoma. Diagnostics (Basel), 2022, 12(10): 2386.
44. Brancato V, Garbino N, Salvatore M, et al. MRI-based radiomic features help identify lesions and predict histopathological grade of hepatocellular carcinoma. Diagnostics (Basel), 2022, 12(5): 1085.
45. Li C, Xu J, Liu Y, et al. Kupffer phase radiomics signature in sonazoid-enhanced ultrasound is an independent and effective predictor of the pathologic grade of hepatocellular carcinoma. J Oncol, 2022, 2022: 6123242.
46. 王恺悌, 巴登才仁·安蕊, 丛赟, 等. 肝细胞癌微血管侵犯术后早期复发的研究进展. 中国普外基础与临床杂志, 2024, 31(11): 1399-1405.
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