Assessment of a CT-based radiomics model for predicting hepatocellular carcinoma grade
https://doi.org/10.16931/1995-5464.2025-4-44-51
Abstract
Aim. To assess the effectiveness and feasibility of CT radiomics-based machine-learning models for hepatocellular carcinoma diagnosis.
Materials and Methods. The study included 42 patients with pathologically confirmed hepatocellular carcinoma. All patients underwent surgery or received medical advice between January 2013 and December 2022. Machinelearning algorithms were used to evaluate texture analysis data from preoperative CT scans.
Results. In comparative analysis, the AdaBoost model outperformed standard statistical methods in identifying Grade 3 hepatocellular carcinoma. Sensitivity was higher by 15.4%, specificity by 3.1%, and diagnostic accuracy by 15.31%.
Conclusion. The use of machine-learning based radiomics is a promising noninvasive method for evaluating the histological hepatocellular carcinoma grade. The obtained results may be applied in a variety of clinical and research contexts.
About the Authors
L. A. Sannikova
A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation
Russian Federation
Russian Federation
Lyudmila A. Sannikova – Resident Physician at the Department of Radiology and Magnetic Resonance Imaging
27, Bol'shaya Serpukhovskaia str., Moscow, 117997
A. A. Ustalov
A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation
Russian Federation
Russian Federation
Andrey A. Ustalov – Junior Researcher at the Department of Radiology and Magnetic Resonance Imaging
27, Bol'shaya Serpukhovskaia str., Moscow, 117997
S. A. Shmeleva
A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation
Russian Federation
Russian Federation
Sofiia A. Shmeleva – Resident Physician at the Department of Radiology and Magnetic Resonance Imaging
27, Bol'shaya Serpukhovskaia str., Moscow, 117997
M. Yu. Shantarevich
A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation
Russian Federation
Russian Federation
Mariia Yu. Shantarevich – Cand. of Sci. (Med.), Radiologist at the Department of Radiology
27, Bol'shaya Serpukhovskaia str., Moscow, 117997
E. V. Kondratyev
A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation
Russian Federation
Russian Federation
Evgeny V. Kondratyev – Cand. of Sci. (Med.), Head of the Radiology Department
27, Bol'shaya Serpukhovskaia str., Moscow, 117997
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For citations:
Sannikova L.A., Ustalov A.A., Shmeleva S.A., Shantarevich M.Yu., Kondratyev E.V. Assessment of a CT-based radiomics model for predicting hepatocellular carcinoma grade. Annaly khirurgicheskoy gepatologii = Annals of HPB Surgery. 2025;30(4):44-51. (In Russ.) https://doi.org/10.16931/1995-5464.2025-4-44-51
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