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The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study

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dc.contributor.author김진성-
dc.contributor.author이주한-
dc.date.accessioned2025-02-03T09:23:39Z-
dc.date.available2025-02-03T09:23:39Z-
dc.date.issued2024-11-
dc.identifier.issn1743-9191-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/202426-
dc.description.abstractBackground: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed to investigate the prognostic value of preoperative kidney cortex volume in predicting the loss of kidney function in elderly donors, by developing an artificial intelligence (AI)-based model for precise kidney volume measurement and applying it to living kidney donors. Materials and methods: A multicenter retrospective cohort study using data from living donors who underwent donor nephrectomy between January 2010 and December 2020 was conducted. An AI segmentation model was developed and validated to measure kidney cortex volume from pre-donation computer tomographic (CT) images. The association between measured preoperative kidney volumes and post-nephrectomy renal function was analyzed through a generalized additive model. Results: A total of 1074 living kidney donors were included in the study. Validation of the developed kidney cortex volume model showed a Dice similarity coefficient of 0.97 and a Hausdorff distance of 0.76 mm. The measured cortex volumes exhibited an age-related decrease, which correlated with declining kidney function. Elderly donors showed greater decreases in estimated glomerular filtration rates (eGFR) post-donation compared to young donors ( P =0.041). Larger preoperative remnant kidney cortex volume was associated with significantly less decline of eGFR post-donation than those with smaller preoperative remnant kidney cortex volume ( P <0.001). Conclusion: This study highlights the critical role of preoperative kidney cortex volume in the donor assessment process, particularly for elderly donors. The fully automated model for measuring kidney cortex volume provides a valuable tool for predicting post-donation renal function and holds promise for enhancing donor evaluation and safety. Trial registration: ClinicalTrials.gov NCT06216795.-
dc.description.statementOfResponsibilityopen-
dc.formatapplication/pdf-
dc.languageEnglish-
dc.publisherElsevier-
dc.relation.isPartOfINTERNATIONAL JOURNAL OF SURGERY-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.subject.MESHAdult-
dc.subject.MESHAge Factors-
dc.subject.MESHAged-
dc.subject.MESHArtificial Intelligence*-
dc.subject.MESHCohort Studies-
dc.subject.MESHFemale-
dc.subject.MESHGlomerular Filtration Rate / physiology-
dc.subject.MESHHumans-
dc.subject.MESHKidney Transplantation*-
dc.subject.MESHKidney* / diagnostic imaging-
dc.subject.MESHKidney* / physiology-
dc.subject.MESHKidney* / physiopathology-
dc.subject.MESHLiving Donors*-
dc.subject.MESHMale-
dc.subject.MESHMiddle Aged-
dc.subject.MESHNephrectomy* / adverse effects-
dc.subject.MESHNephrectomy* / methods-
dc.subject.MESHOrgan Size-
dc.subject.MESHPreoperative Period-
dc.subject.MESHRetrospective Studies-
dc.subject.MESHTomography, X-Ray Computed-
dc.titleThe role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Radiation Oncology (방사선종양학교실)-
dc.contributor.googleauthorEun-Ah Jo-
dc.contributor.googleauthorJuhan Lee-
dc.contributor.googleauthorSeonggong Moon-
dc.contributor.googleauthorJin Sung Kim-
dc.contributor.googleauthorAhram Han-
dc.contributor.googleauthorJongwon Ha-
dc.contributor.googleauthorYong Chul Kim-
dc.contributor.googleauthorSangil Min-
dc.identifier.doi10.1097/JS9.0000000000002030-
dc.contributor.localIdA04548-
dc.relation.journalcodeJ01162-
dc.identifier.eissn1743-9159-
dc.identifier.pmid39116451-
dc.contributor.alternativeNameKim, Jinsung-
dc.contributor.affiliatedAuthor김진성-
dc.citation.volume110-
dc.citation.number11-
dc.citation.startPage7169-
dc.citation.endPage7176-
dc.identifier.bibliographicCitationINTERNATIONAL JOURNAL OF SURGERY, Vol.110(11) : 7169-7176, 2024-11-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiation Oncology (방사선종양학교실) > 1. Journal Papers

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