Evidence map›Paper›PMID 41276640›Full record

ArticleAbdominal radiology (New York)2026

Segmental fECV measurement using PCD-CT as an early predictor of liver function decline in chronic liver disease.

Takashi Ohtani, Masato Shimada, Kouki Takahashi, Sayuri Hakoda, Yukihiro Tomita, Kiyotaka Takeuchi, Satomi Kanai, Tasuku Wakabayashi, Ayaki Kitano, Kenji Takata and 2 more

Abstract read
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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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Takashi OhtaniRadiological Center, University of Fukui Hospital, Fukui, Japan. ohtanita@u-fukui.ac.jp.
Masato ShimadaRadiological Center, University of Fukui Hospital, Fukui, Japan.
Kouki TakahashiRadiological Center, University of Fukui Hospital, Fukui, Japan.
Sayuri HakodaDepartment of Radiology, University of Fukui, Fukui, Japan.
Yukihiro TomitaDepartment of Radiology, University of Fukui, Fukui, Japan.
Kiyotaka TakeuchiDepartment of Radiology, University of Fukui, Fukui, Japan.
Satomi KanaiDepartment of Radiology, University of Fukui, Fukui, Japan.
Tasuku WakabayashiDepartment of Radiology, University of Fukui, Fukui, Japan.
Ayaki KitanoDepartment of Radiology, University of Fukui, Fukui, Japan.
Kenji TakataDepartment of Radiology, University of Fukui, Fukui, Japan.
Toshiki TateishiRadiological Center, University of Fukui Hospital, Fukui, Japan.
Tetsuya TsujikawaDepartment of Radiology, University of Fukui, Fukui, Japan. awaji@u-fukui.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of this study was to investigate the utility of segmental hepatic extracellular volume fractions (fECV) calculated using a photon-counting detector CT (PCD-CT) for predicting liver function decline, as reflected by the modified albumin-bilirubin (mALBI) grade in chronic liver disease (CLD). MATERIALS AND

methodsA total of 146 patients with CLD underwent PCD-CT of the liver, including 3-minute equilibrium phase imaging. Iodine densities of the aorta and liver segments (S2-S8), based on Couinaud's classification, were measured to calculate fECV. The diagnostic accuracy of segmental fECV for predicting early liver function decline was assessed using mALBI grade as the functional reference standard, with receiver operating characteristic (ROC) analysis.

resultsFor mALBI grades 1, 2b, and 3, no significant differences in fECV were found among segments. For mALBI grade 2a, fECV values were significantly larger in S4 and S5 compared to S2, S3, S6, and S7 (p < 0.05), and the fECV in S8 was significantly larger than in S7 (p < 0.05). The fECV values in S6 and S7 significantly increased with higher mALBI grade, while other segments showed less pronounced increases. ROC analysis revealed that fECV in S4, S5, and S8 demonstrated sensitivities, specificities, and accuracies of approximately 90% for predicting early liver function decline (distinguishing mALBI grade 1 from grades 2a or above).

conclusionSegmental fECV measurement using PCD-CT offers preliminary insights into liver function. Increased fECV in the medial (S4) and anterior (S5, S8) segments showed potential as an early indicator of functional decline, while fECV in the posterior segments (S6, S7) suggested utility in disease staging. As a proof-of-concept study, these findings require further validation before this approach can be adopted in clinical practice.

Indexed as

Liver DiseasesTomography, X-Ray ComputedAdultAgedAged, 80 and overChronic DiseaseContrast MediaFemaleHumansLiverLiver Function TestsMaleMiddle AgedPredictive Value of TestsRetrospective StudiesContrast MediaCLDfECVPCD-CT

Identifiers

PMID41276640
PMCPMC13109207

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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.