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01 · ABSTRACT

Abstract

Hepatocellular Carcinoma (HCC) is a growing global health burden with high incidence and mortality rates. Despite advances in surgical techniques and perioperative care, outcomes after surgical treatment have not improved over the past three decades. Molecular imaging is an emerging field that enables researchers to study diseases at the molecular and cellular levels, enabling the detection of elevated serum α-fetoprotein (AFP) and abnormal expressions of various HCC-specific and nonspecific cell surface antigens and intracellular targets. Molecular imaging techniques detect liver lesions at the molecular and cellular level, allowing early detection and accurate staging of HCC. Positron emission tomography (PET) imaging offers greater sensitivity and specificity, while hepatobiliary-specific radiotracers with SPECT imaging provide insights into benign and malignant lesion differentiation. Radiomics and artificial intelligence are vital in deciphering molecular imaging data, with machine learning algorithms boosting diagnostic gains and predicting treatment response. Theranostics, a state-of-the-art application, provides diagnostic and therapeutic leverage following a single imaging agent. By understanding tumor biology in real time, radiopharmaceuticals can be transformed into personalized radiotherapies, enabling clinicians to make science-driven decisions throughout the illness. Future directions include developing novel radiotracers and integrating AI into clinical decision-making. Collaboration between academic researchers, clinicians, and industry colleagues is crucial to converting exciting advances into improved clinical outcomes for HCC patients.

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02 · PUBLICATION RECORD

Article details

JournalMedical Research Archives
IssueVol 12 No 3 (2024): March issue, Vol.12, Issue 3
SectionResearch Articles
Published26 March 2024
DOI10.18103/mra.v12i3.5212
ISSN2375-1924
03 · RIGHTS & REUSE

Rights & reuse

This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.

Authors & affiliations

FG

Farshid Gheisari

Ionizing and Non-ionizing Radiation Protection Research Center (INIRPRC), Shiraz University of Medical Sciences, Shiraz, Iran

RV

Reza Vali

Diagnostic Imaging, Nuclear Medicine Division, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada

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