Automated brain volumetric program measuring regional brain atrophy in diagnosis of mild cognitive impairment and Alzheimer’s disease dementia

• Published in: Brain imaging and behavior Vol. 16; no. 5; pp. 2086 - 2096
• Main Authors: Ryu, Dong-Woo, Hong, Yun Jeong, Cho, Jung Hee, Kwak, Kichang, Lee, Jong-Min, Shim, Yong S, Youn, Young Chul, Yang, Dong Won
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.10.2022; Springer Nature B.V
• Subjects: Accuracy; Alzheimer's disease; Atrophy; Automation; Biomedical and Life Sciences; Biomedicine; Brain; Cerebellum; Cerebrospinal fluid; Cognitive ability; Dementia; Dementia disorders; Diagnosis; Diagnostic systems; Impairment; Medical diagnosis; Neurodegenerative diseases; Neuropsychology; Neuroradiology; Neurosciences; Original Research; Performance evaluation; Prediction models; Psychiatry; Regional development; Reliability; Computer-assisted image processing; Alzheimer’s disease; Magnetic resonance imaging; Cognitive dysfunction; Dementia
• ISSN: 1931-7557; 1931-7565
• DOI: 10.1007/s11682-022-00678-x

A quantitative analysis of brain volume can assist in the diagnosis of Alzheimer’s disease (AD) which is ususally accompanied by brain atrophy. With an automated analysis program Quick Brain Volumetry (QBraVo) developed for volumetric measurements, we measured regional volumes and ratios to evaluate their performance in discriminating AD dementia (ADD) and mild cognitive impairment (MCI) patients from normal controls (NC). Validation of QBraVo was based on intra-rater and inter-rater reliability with a manual measurement. The regional volumes and ratios to total intracranial volume (TIV) and to total brain volume (TBV) or total cerebrospinal fluid volume (TCV) were compared among subjects. The regional volume to total cerebellar volume ratio named Standardized Atrophy Volume Ratio (SAVR) was calculated to compare brain atrophy. Diagnostic performances to distinguish among NC, MCI, and ADD were compared between MMSE, SAVR, and the predictive model. In total, 56 NCs, 44 MCI, and 45 ADD patients were enrolled. The average run time of QBraVo was 5 min 36 seconds. Intra-rater reliability was 0.999. Inter-rater reliability was high for TBV, TCV, and TIV (R = 0.97, 0.89 and 0.93, respectively). The medial temporal SAVR showed the highest performance for discriminating ADD from NC (AUC = 0.808, diagnostic accuracy = 80.2%). The predictive model using both MMSE and medial temporal SAVR improved the diagnostic performance for MCI in NC (AUC = 0.844, diagnostic accuracy = 79%). Our results demonstrated QBraVo is a fast and accurate method to measure brain volume. The regional volume calculated as SAVR could help to diagnose ADD and MCI and increase diagnostic accuracy for MCI.