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Advanced CT techniques for assessing hepatocellular carcinoma.

Yuko Nakamura1, Toru Higaki2, Yukiko Honda2

  • 1Diagnostic Radiology, Hiroshima University, 1-2-3 Kasumi, Minami-ku, Hiroshima, 734-8551, Japan. yukon@hiroshima-u.ac.jp.

La Radiologia Medica
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Summary

Advanced imaging techniques like dual-energy CT, perfusion CT, and AI offer improved evaluation for hepatocellular carcinoma (HCC) compared to conventional methods. These methods enhance liver tumor characterization, treatment response assessment, and survival prediction in HCC patients.

Keywords:
Artificial intelligenceDual-energy CTHepatocellular carcinomaPerfusion CTTomography, X-ray computed

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Area of Science:

  • Radiology and Oncological Imaging
  • Medical Diagnostics

Background:

  • Hepatocellular carcinoma (HCC) is a globally prevalent cancer, frequently evaluated using hepatic dynamic CT.
  • Conventional CT methods have limitations in precise characterization and response assessment.
  • Advanced imaging modalities are being investigated to improve HCC evaluation.

Purpose of the Study:

  • To review the advantages and disadvantages of conventional hepatic dynamic CT for HCC.
  • To discuss the principles, applications, and limitations of dual-energy CT and perfusion CT in HCC.
  • To explore the utility of artificial intelligence (AI) in diagnosing HCC.

Main Methods:

  • Review of conventional hepatic dynamic CT imaging.
  • Discussion of dual-energy CT and perfusion CT principles and clinical applications.
  • Analysis of AI-based methods for HCC diagnosis.

Main Results:

  • Conventional hepatic dynamic CT has limitations in evaluating HCC.
  • Dual-energy CT and perfusion CT offer precise characterization and quantification for HCC.
  • AI-based methods show promise for HCC diagnosis and management.

Conclusions:

  • Advanced CT techniques, including dual-energy CT, perfusion CT, and AI, provide superior insights into HCC compared to conventional methods.
  • These technologies aid in accurate tumor characterization, treatment response evaluation, and survival prediction.
  • Further integration of AI holds significant potential for improving HCC diagnosis and patient outcomes.