Related Experiment Video For Computed tomography
Updated: Jan 28, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
Dynamic Computed Tomography Perfusion Imaging: Complementary Diagnostic Tool in Hepatocellular Carcinoma Assessment
Davide Ippolito1, Anna Pecorelli1, Giulia Querques1
1University of Milano-Bicocca, Milan, Italy; Department of Diagnostic Radiology, San Gerardo Hospital, Via Pergolesi 33 - 20900 Monza, Italy.
Abstract:
Early diagnosis of HCC is of paramount importance in order to enable the application of curative treatments. Among these, radiofrequency ablation (RFA) is actually considered the most effective ablative therapy for early stage hepatocellular carcinoma (HCC) not suitable for surgery. On the other hand, transarterial chemoembolization (TACE) represents the standard of care for intermediate stage HCC and compensated liver function. Finally, sorafenib, an oral antiangiogenic targeted drug, is the only approved systemic therapy for advanced HCC with vascular invasion, extrahepatic spread, and well-preserved liver function. Beside traditional radiological techniques, new functional imaging tools have been introduced in order to provide not only morphological information but also quantitative functional data. In this review, we analyze perfusion-CT (pCT) from a technical point of view, describing the main different mathematical analytical models for the quantification of tissue perfusion from acquired CT raw data, the most commonly acquired perfusion parameters, and the technical parameters required to perform a standard pCT examination. Moreover, a systematic review of the literature was performed to assess the role of pCT as an emerging imaging biomarker for HCC diagnosis, response evaluation to RFA, TACE, and sorafenib, and we examine its challenges in HCC management.
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