Evidence map›Paper›PMID 42081100›Full record

ArticleAbdominal radiology (New York)2026

Hepatobiliary phase radiomics for identifying subclinical liver dysfunction in compensated chronic liver disease: development and external validation.

Fatih Işık, Serdar Sipahioğlu, Muhammed Emre Işıktaş, Muhammed Halid Yener, Mehmet Alperen Tezcan, Nurullah Dag, Hakan Dursun, Fatih Alper

Abstract readValidation Study
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Article in Abdominal radiology (New York), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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8 authors.

Fatih IşıkDepartment of Radiology, Erzurum Regional Training and Research Hospital, Erzurum, Turkey. drfatih.isik@icloud.com.
Serdar SipahioğluDepartment of Radiology, Ankara Dışkapı Yıldırım Beyazıt Training and Research Hospital, Ankara, Turkey.
Muhammed Emre IşıktaşDepartment of Radiology, Faculty of Medicine, Atatürk University, Erzurum, Turkey.
Muhammed Halid YenerDepartment of Radiology, Faculty of Medicine, Atatürk University, Erzurum, Turkey.
Mehmet Alperen TezcanDepartment of Radiology, Faculty of Medicine, Balikesir University, Balikesir, Turkey.
Nurullah DagDepartment of Radiology, Faculty of Medicine, Inonu University, Malatya, Turkey.
Hakan DursunDepartment of Gastroenterology, Faculty of Medicine, Atatürk University, Erzurum, Turkey.
Fatih AlperDepartment of Radiology, Faculty of Medicine, Atatürk University, Erzurum, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo develop and externally validate a radiomics model derived from gadoxetic acid-enhanced hepatobiliary phase (HBP) MRI for detecting subclinical liver dysfunction in patients with compensated chronic liver disease (CLD).

methodsIn this retrospective study, patients were included based on Child-Pugh Class A status and absence of clinical decompensation. Subclinical liver dysfunction was defined using a composite reference standard integrating ALBI score ( > - 2.60), MELD-Na ≥ 10, and FIB-4 ≥ 2.67. Whole-liver radiomic features were extracted from HBP images. Feature selection and model development were performed using Boruta and class-weighted logistic regression within a nested cross-validation framework.

resultsA total of 138 individuals (90 patients with subclinical liver dysfunction and 48 controls) were analyzed. Six radiomic features were selected for model development. In the internal test cohort (n = 21), the model achieved a ROC-AUC of 0.86 [95% CI: 0.66-1.00] with an accuracy of 0.81 [95% CI: 0.62-0.95]. In the external validation cohort (n = 26), the model achieved a ROC-AUC of 0.89 [95% CI: 0.73-0.99] and an accuracy of 0.77 [95% CI: 0.58-0.92] using a fixed decision threshold. Both first-order and texture-based features were represented among the selected predictors.

conclusionHBP-derived radiomics demonstrates potential as a noninvasive biomarker for identifying subclinical liver dysfunction in compensated CLD patients. While the results are promising, the relatively small validation cohorts warrant cautious interpretation, and further validation in larger multicenter populations is required to confirm robustness and generalizability.

Indexed as

Liver DiseasesMagnetic Resonance ImagingRadiomicsAgedChronic DiseaseContrast MediaFemaleGadolinium DTPAHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesContrast MediaGadolinium DTPAgadolinium ethoxybenzyl DTPAComputer-assistedContrast mediaImage processingLiverLiver diseasesLiver function testsMagnetic resonance imaging

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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.