ArticleJournal of imaging2022
Quantitative Analysis of Liver Disease Using MRI-Based Radiomic Features of the Liver and Spleen.
Article in Journal of imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Radiomics-Based Assessment of Portal Hypertension Severity and Risk Stratification of Cirrhotic Patients Using Routine CT Scans.Liver international : official journal of the International Association for the Study of the Liver · 2026Article
- Preliminary quantitative assessment of liver and spleen MR imaging and elastography in clinically significant portal hypertension.Scientific reports · 2026Article
- Prediction of hepatic functional reserve using a gadoxetic acid-enhanced MRI-derived 'Severity Index'.BMC medical imaging · 2025Article
- Radiomic-enhanced multimodal ultrasound for early detection of acute kidney injury secondary to renal vein thrombosis: a preclinical diagnostic modeling study.Renal failure · 2025Article
- Predicting Chronic Liver Disease Severity by Liver and Splenic Extracellular Volume Fraction Derived from spectral-CT.Current medical imaging · 2025Article
- Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis.World journal of gastroenterology · 2024Article
- Radiomics Applications in Spleen Imaging: A Systematic Review and Methodological Quality Assessment.Diagnostics (Basel, Switzerland) · 2023Review
- Impact of Emerging Deep Learning-Based MR Image Reconstruction Algorithms on Abdominal MRI Radiomic Features.Journal of computer assisted tomographyArticle
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundRadiomics extracts quantitative image features to identify biomarkers for characterizing disease. Our aim was to characterize the ability of radiomic features extracted from magnetic resonance (MR) imaging of the liver and spleen to detect cirrhosis by comparing features from patients with cirrhosis to those without cirrhosis.
methodsThis retrospective study compared MR-derived radiomic features between patients with cirrhosis undergoing hepatocellular carcinoma screening and patients without cirrhosis undergoing intraductal papillary mucinous neoplasm surveillance between 2015 and 2018 using the same imaging protocol. Secondary analyses stratified the cirrhosis cohort by liver disease severity using clinical compensation/decompensation and Model for End-Stage Liver Disease (MELD).
resultsOf 167 patients, 90 had cirrhosis with 68.9% compensated and median MELD 8. Combined liver and spleen radiomic features generated an AUC 0.94 for detecting cirrhosis, with shape and texture components contributing more than size. Discrimination of cirrhosis remained high after stratification by liver disease severity.
conclusionsMR-based liver and spleen radiomic features had high accuracy in identifying cirrhosis, after stratification by clinical compensation/decompensation and MELD. Shape and texture features performed better than size features. These findings will inform radiomic-based applications for cirrhosis diagnosis and severity.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.