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CT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma

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dc.contributor.authorHeo, Subin-
dc.contributor.authorJeong, Boryeong-
dc.contributor.authorLee, Seung Soo-
dc.contributor.authorKim, Minju-
dc.contributor.authorJang, Hyeon Ji-
dc.contributor.authorChoi, Se Jin-
dc.contributor.authorKim, Kang Mo-
dc.contributor.authorHa, Tae-Yong-
dc.contributor.authorJung, Dong-Hwan-
dc.contributor.author정보령-
dc.date.accessioned2025-11-17T04:49:34Z-
dc.date.available2025-11-17T04:49:34Z-
dc.date.created2025-07-22-
dc.date.issued2025-08-
dc.identifier.issn0938-7994-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/208874-
dc.description.abstractBackgroundWhile the CT-based method of detecting clinically significant portal hypertension (CSPH) emerged as a noninvasive alternative for evaluating CSPH, its predictive ability for post-hepatectomy outcomes is unknown. Therefore, this study aimed to evaluate the impact of CT-based CSPH on outcomes following hepatectomy for hepatocellular carcinoma (HCC).MethodsThis retrospective single-center study included patients with advanced chronic liver disease (ACLD) who underwent hepatectomy for very early or early-stage HCC between January 2017 and December 2018. CSPH was assessed using CT-based criteria, which included splenomegaly determined by deep learning-based spleen volume measurements with personalized reference thresholds, and the presence of gastroesophageal varices (GEV), spontaneous portosystemic shunt or ascites. Logistic regression and competing risk analyses were used to identify factors associated with severe post-hepatectomy liver failure (PHLF), hepatic decompensation, and liver-related death or transplantation. The predictive performance of existing models for PHLF was compared using both CT-based and conventional CSPH criteria (endoscopic GEV or splenomegaly with thrombocytopenia).ResultsAmong 593 patients (460 men; mean age 57.9 +/- 9.3 years), 41 (6.9%) developed severe PHLF. The median follow-up period was 62 months. CT-based CSPH independently predicted severe PHLF (OR 7.672 [95% CI 3.209-18.346]), hepatic decompensation (subdistribution hazard ratio (sHR) 4.518 [1.868-10.929]), and liver-related death or transplantation (sHR 2.756 [1.315-5.773]). When integrated into existing models, CT-based CSPH outperformed conventional CSPH in predicting severe PHLF (AUC 0.724 vs. 0.694 for EASL algorithm (p = 0.036) and 0.854 vs. 0.830 for Wang's model (p = 0.011)).ConclusionsCT-based CSPH is a strong predictor of poor post-hepatectomy outcomes in HCC patients with ACLD, offering a noninvasive surgical risk assessment tool.Key PointsQuestionCan CT-based detection of clinically significant portal hypertension (CSPH) serve as a noninvasive predictor of post-hepatectomy outcomes in hepatocellular carcinoma (HCC) patients?FindingsCT-based CSPH independently predicted severe post-hepatectomy liver failure, hepatic decompensation, and liver-related death or transplantation, outperforming conventional CSPH criteria in predictive performance.Clinical relevanceCT-based CSPH offers a noninvasive and effective tool for surgical risk assessment in HCC patients, potentially improving the selection of candidates for hepatectomy and optimizing patient outcomes.Key PointsQuestionCan CT-based detection of clinically significant portal hypertension (CSPH) serve as a noninvasive predictor of post-hepatectomy outcomes in hepatocellular carcinoma (HCC) patients?FindingsCT-based CSPH independently predicted severe post-hepatectomy liver failure, hepatic decompensation, and liver-related death or transplantation, outperforming conventional CSPH criteria in predictive performance.Clinical relevanceCT-based CSPH offers a noninvasive and effective tool for surgical risk assessment in HCC patients, potentially improving the selection of candidates for hepatectomy and optimizing patient outcomes. Key PointsQuestionCan CT-based detection of clinically significant portal hypertension (CSPH) serve as a noninvasive predictor of post-hepatectomy outcomes in hepatocellular carcinoma (HCC) patients?FindingsCT-based CSPH independently predicted severe post-hepatectomy liver failure, hepatic decompensation, and liver-related death or transplantation, outperforming conventional CSPH criteria in predictive performance.Clinical relevanceCT-based CSPH offers a noninvasive and effective tool for surgical risk assessment in HCC patients, potentially improving the selection of candidates for hepatectomy and optimizing patient outcomes.-
dc.languageEnglish-
dc.publisherSpringer International-
dc.relation.isPartOfEUROPEAN RADIOLOGY-
dc.relation.isPartOfEUROPEAN RADIOLOGY-
dc.subject.MESHAged-
dc.subject.MESHCarcinoma, Hepatocellular* / complications-
dc.subject.MESHCarcinoma, Hepatocellular* / diagnostic imaging-
dc.subject.MESHCarcinoma, Hepatocellular* / surgery-
dc.subject.MESHFemale-
dc.subject.MESHHepatectomy*-
dc.subject.MESHHumans-
dc.subject.MESHHypertension, Portal* / complications-
dc.subject.MESHHypertension, Portal* / diagnostic imaging-
dc.subject.MESHLiver Neoplasms* / complications-
dc.subject.MESHLiver Neoplasms* / diagnostic imaging-
dc.subject.MESHLiver Neoplasms* / surgery-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPostoperative Complications* / diagnostic imaging-
dc.subject.MESHPredictive Value of Tests-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHTomography, X-Ray Computed* / methods-
dc.subject.MESHTreatment Outcome-
dc.titleCT-based detection of clinically significant portal hypertension predicts post-hepatectomy outcomes in hepatocellular carcinoma-
dc.typeArticle-
dc.contributor.googleauthorHeo, Subin-
dc.contributor.googleauthorJeong, Boryeong-
dc.contributor.googleauthorLee, Seung Soo-
dc.contributor.googleauthorKim, Minju-
dc.contributor.googleauthorJang, Hyeon Ji-
dc.contributor.googleauthorChoi, Se Jin-
dc.contributor.googleauthorKim, Kang Mo-
dc.contributor.googleauthorHa, Tae-Yong-
dc.contributor.googleauthorJung, Dong-Hwan-
dc.identifier.doi10.1007/s00330-025-11411-9-
dc.relation.journalcodeJ00851-
dc.identifier.eissn1432-1084-
dc.identifier.pmid39953152-
dc.identifier.urlhttps://link.springer.com/article/10.1007/s00330-025-11411-9-
dc.subject.keywordLiver failure-
dc.subject.keywordHepatectomy-
dc.subject.keywordComputed tomography-
dc.subject.keywordPortal hypertension-
dc.subject.keywordDeep learning-
dc.contributor.affiliatedAuthorJeong, Boryeong-
dc.identifier.scopusid2-s2.0-85218822126-
dc.identifier.wosid001420954900001-
dc.citation.volume35-
dc.citation.number8-
dc.citation.startPage4980-
dc.citation.endPage4992-
dc.identifier.bibliographicCitationEUROPEAN RADIOLOGY, Vol.35(8) : 4980-4992, 2025-08-
dc.identifier.rimsid88005-
dc.type.rimsART-
dc.description.journalClass1-
dc.description.journalClass1-
dc.subject.keywordAuthorLiver failure-
dc.subject.keywordAuthorHepatectomy-
dc.subject.keywordAuthorComputed tomography-
dc.subject.keywordAuthorPortal hypertension-
dc.subject.keywordAuthorDeep learning-
dc.subject.keywordPlusVENOUS-PRESSURE GRADIENT-
dc.subject.keywordPlusLIVER-
dc.subject.keywordPlusMANAGEMENT-
dc.subject.keywordPlusCIRRHOSIS-
dc.subject.keywordPlusRESECTION-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryRadiology, Nuclear Medicine & Medical Imaging-
dc.relation.journalResearchAreaRadiology, Nuclear Medicine & Medical Imaging-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers

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