Longitudinal follow-up of incidental renal calculi on computed tomography.

Deep learning Longitudinal follow-up Outcomes Renal calculi Volumetric measurements

Journal

Abdominal radiology (New York)
ISSN: 2366-0058
Titre abrégé: Abdom Radiol (NY)
Pays: United States
ID NLM: 101674571

Informations de publication

Date de publication:
31 Oct 2023
Historique:
received: 24 07 2023
accepted: 20 09 2023
revised: 19 09 2023
medline: 31 10 2023
pubmed: 31 10 2023
entrez: 31 10 2023
Statut: aheadofprint

Résumé

Measuring small kidney stones on CT is a time-consuming task often neglected. Volumetric assessment provides a better measure of size than linear dimensions. Our objective is to analyze the growth rate and prognosis of incidental kidney stones in asymptomatic patients on CT. This retrospective study included 4266 scans from 2030 asymptomatic patients who underwent two or more nonenhanced CT scans for colorectal screening between 2004 and 2016. The DL software identified and measured the volume, location, and attenuation of 883 stones. The corresponding scans were manually evaluated, and patients without follow-up were excluded. At each follow-up, the stones were categorized as new, growing, persistent, or resolved. Stone size (volume and diameter), attenuation, and location were correlated with the outcome and growth rates of the stones. The stone cohort comprised 407 scans from 189 (M: 124, F: 65, median age: 55.4 years) patients. The median number of stones per scan was 1 (IQR: [1, 2]). The median stone volume was 17.1 mm

Identifiants

pubmed: 37906271
doi: 10.1007/s00261-023-04075-w
pii: 10.1007/s00261-023-04075-w
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : Intramural NIH HHS
ID : Z01 CL040003
Pays : United States
Organisme : Intramural NIH HHS
ID : Z01 CL040004
Pays : United States

Informations de copyright

© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.

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Auteurs

Pritam Mukherjee (P)

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, Room 1C224D, 10 Center Drive, Bethesda, MD, 20892-1182, USA.

Sungwon Lee (S)

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, Room 1C224D, 10 Center Drive, Bethesda, MD, 20892-1182, USA.

Daniel C Elton (DC)

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, Room 1C224D, 10 Center Drive, Bethesda, MD, 20892-1182, USA.

Perry J Pickhardt (PJ)

Department of Radiology, School of Medicine & Public Health, The University of Wisconsin, Madison, WI, USA.

Ronald M Summers (RM)

Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Department of Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Building 10, Room 1C224D, 10 Center Drive, Bethesda, MD, 20892-1182, USA. rms@nih.gov.

Classifications MeSH