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Correlation Between Platelet Count in Patients with Hepatocellular Carcinoma and LI-RADS Criteria Based on Abdominal CT Scan Examinations at Dr. Soetomo Regional General Hospital, Surabaya

Research output: Contribution to journalArticlepeer-review

Abstract

Hepatocellular carcinoma (HCC) is a primary liver malignancy with high mortality rates, while the Liver Imaging Reporting and Data System (LI-RADS) is used to determine the probability of HCC based on radiological imaging characteristics. Platelets are known to play a role in tumor progression, but their relationship with LI-RADS classification remains unclear. This study aims to determine the relationship between platelet count and LI-RADS classification in HCC patients. This study is a retrospective observational analytical study of 56 HCC patients who underwent abdominal CT-scan examination at Dr. Soetomo General Hospital Surabaya from January to December 2023. LI-RADS classification was determined based on multiphasic CT-scan, while platelet data were obtained from blood tests performed at most 10 days before or after radiological examination. Relationship analysis was performed using Spearman correlation test. The results showed that the majority of subjects were male (83.9%) with a mean age of 52.25 ± 9.92 years. Most patients were categorized as LI-RADS 5 (87.5%) and had normal platelet counts (85.7%). Correlation test showed no significant relationship between platelet count and LI-RADS classification (p = 0.269), and no meaningful relationship was found between platelets and main LI-RADS features such as arterial phase hyperenhancement, washout, and enhancing capsule (p > 0.05). The conclusion of this study shows that platelet count does not correlate with LI-RADS classification in HCC patients and therefore cannot be used as a predictive indicator of HCC probability level based on radiological imaging, and further research is needed considering confounding factors such as liver function, portal hypertension, and cytokine profile.

Original languageEnglish
Pages (from-to)639-648
Number of pages10
JournalInternational Journal of Drug Delivery Technology
Volume16
Issue number1
DOIs
Publication statusPublished - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Hepatocellular carcinoma
  • LI-RADS
  • abdominal CT-scan
  • liver imaging
  • platelets

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