Hepatocellular carcinoma imaging: Exploring traditional techniques and emerging innovations for early intervention

Abstract

Hepatocellular carcinoma (HCC) continues to be a diagnostic and therapeutic challenge for healthcare systems around the world in addition to being a significant contributor to oncologic mortality. To improve the standard of life and the survival of patients, early diagnosis of the condition and subsequent appropriate treatment are essential. Hepatocellular carcinoma (HCC) observation, early detection, diagnosis, and follow-up all depend heavily on imaging modalities. They provide valuable information about the characteristics of HCC nodules, aiding in non-invasive diagnosis and staging. Imaging has evolved beyond simply confirming a suspected diagnosis in the management of hepatocellular carcinoma (HCC). Several traditional imaging modalities, including PET/CT, MRI, MR elastography, ultrasound (US), and endoscopy, along with next-generation imaging modalities such as photoacoustic imaging, and Cerenkov luminescence with the utilization of contrasting agents further enhance their diagnostic capabilities in HCC. The selection of the most appropriate imaging modality and contrasting agent depends on various factors, including the clinical scenario, patient characteristics, and availability of resources. In addition to these advancements, artificial intelligence (AI) has developed as a valuable tool in radiology for the management of HCC. In this review, we highlighted the most important imaging techniques for managing patients with a high risk of HCC.

Keywords

• Hepatocellular carcinoma
• Oncological imaging
• Ultrasound
• Diagnosis
• Artificial intelligence