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Correlation of HbA1c levels with CT-based body composition biomarkers in diabetes mellitus and metabolic syndrome.
Warner, Joshua D; Blake, Glen M; Garrett, John W; Lee, Matthew H; Nelson, Leslie W; Summers, Ronald M; Pickhardt, Perry J.
Afiliación
  • Warner JD; The Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Blake GM; School of Biomedical Engineering and Imaging Sciences, King's College London, St Thomas' Hospital, London, SE1 7EH, UK.
  • Garrett JW; The Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Lee MH; The Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Nelson LW; The Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
  • Summers RM; Imaging Biomarkers and Computer-Aided Diagnosis Laboratory, Radiology and Imaging Sciences, National Institutes of Health Clinical Center, Bethesda, MD, USA.
  • Pickhardt PJ; The Departments of Radiology and Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA. ppickhardt2@uwhealth.org.
Sci Rep ; 14(1): 21875, 2024 09 19.
Article en En | MEDLINE | ID: mdl-39300115
ABSTRACT
Diabetes mellitus and metabolic syndrome are closely linked with visceral body composition, but clinical assessment is limited to external measurements and laboratory values including hemoglobin A1c (HbA1c). Modern deep learning and AI algorithms allow automated extraction of biomarkers for organ size, density, and body composition from routine computed tomography (CT) exams. Comparing visceral CT biomarkers across groups with differing glycemic control revealed significant, progressive CT biomarker changes with increasing HbA1c. For example, in the unenhanced female cohort, mean changes between normal and poorly-controlled diabetes showed 53% increase in visceral adipose tissue area, 22% increase in kidney volume, 24% increase in liver volume, 6% decrease in liver density (hepatic steatosis), 16% increase in skeletal muscle area, and 21% decrease in skeletal muscle density (myosteatosis) (all p < 0.001). The multisystem changes of metabolic syndrome can be objectively and retrospectively measured using automated CT biomarkers, with implications for diabetes, metabolic syndrome, and GLP-1 agonists.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Composición Corporal / Hemoglobina Glucada / Biomarcadores / Tomografía Computarizada por Rayos X / Síndrome Metabólico Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Composición Corporal / Hemoglobina Glucada / Biomarcadores / Tomografía Computarizada por Rayos X / Síndrome Metabólico Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido