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Integrative MR Imaging Interpretation in Cognitive Impairment with Alzheimer's Disease, Small Vessel Disease, and Glymphatic Function-Related MR Parameters.
You, Sung-Hye; Kim, Byungjun; Kim, InSeong; Yang, Kyung-Sook; Kim, Kyung Min; Kim, Bo Kyu; Shin, Jae Ho.
Afiliación
  • You SH; Department of Radiology, Anam Hospital, Korea University College of Medicine, Korea (S.-H.Y., B.K., K.M.K., B.K.K., J.H.S.).
  • Kim B; Department of Radiology, Anam Hospital, Korea University College of Medicine, Korea (S.-H.Y., B.K., K.M.K., B.K.K., J.H.S.). Electronic address: bj1492.kim@gmail.com.
  • Kim I; Siemens Healthineers, Seoul, Korea (I.K.).
  • Yang KS; Department of Biostatistics, Korea University College of Medicine, Seoul, Korea (K.-S.Y.).
  • Kim KM; Department of Radiology, Anam Hospital, Korea University College of Medicine, Korea (S.-H.Y., B.K., K.M.K., B.K.K., J.H.S.).
  • Kim BK; Department of Radiology, Anam Hospital, Korea University College of Medicine, Korea (S.-H.Y., B.K., K.M.K., B.K.K., J.H.S.).
  • Shin JH; Department of Radiology, Anam Hospital, Korea University College of Medicine, Korea (S.-H.Y., B.K., K.M.K., B.K.K., J.H.S.).
Acad Radiol ; 2024 Sep 17.
Article en En | MEDLINE | ID: mdl-39294052
ABSTRACT
RATIONALE AND

OBJECTIVES:

The role of MR imaging in patients with cognitive impairment is to evaluate each component of Alzheimer's disease (AD), small vessel disease (SVD), and glymphatic function. We want to validate the diagnostic performance of the comprehensive interpretation of these parameters to predict the cognitive impairment stage. MATERIALS AND 

METHODS:

This retrospective single-center study included 359 patients with cognitive impairment who had undergone MRI (FLAIR, T2WI, 3D-T1WI, susceptibility-weighted imaging, and diffusion tensor imaging [DTI]) and a neuropsychological screening battery between January 2020 and July 2022. Each AD and SVD-related MR parameter was visually evaluated, and DTI analysis along the perivascular space (ALPS) index was calculated. Volumetry analysis was performed using Neurophet AQUA AI-based software. Using logistic regression analysis, four types of models were developed and compared by adding the components in the following order (1) clinical factors and AD, (2) SVD, (3) glymphatic function-related MR parameters, and (4) volumetric data. Chi-square automatic interaction detection algorithm was used to develop diagnostic tree analysis (DTA) model to predict late-stage cognitive impairment.

RESULTS:

APOE4 status, years of education, medial temporal lobe atrophy score, Fazekas scale score, DTI-ALPS index, and white matter hyperintensity were significant predictors of late-stage cognitive impairment. The performance of the prediction model increased from Model 1 to Model 4 (AUC 0.880, 0.899, 0.914, and 0.945, respectively). The overall accuracy of the DTA model was 87.47%.

CONCLUSION:

Integrative brain MRI assessments in patients with cognitive impairment, AD, SVD, and glymphatic function-related MR parameters, improve the prediction of late-stage cognitive impairment.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Acad Radiol Asunto de la revista: RADIOLOGIA Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos