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

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Abstract

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.

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Availability of data and material

The data used for the analyses is available on request.

Code availability

The software that we made for the brain volume analysis is available on request from the corresponding author.

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Funding

This study was supported by a grant from the Ministry of Health and Welfare (HI18C0530) and by the Health Fellowship Foundation.

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Authors and Affiliations

  1. Department of Neurology, College of Medicine, The Catholic University of Korea, 222, Banpo-daero, Seocho-gu, Seoul, 06591, Republic of Korea

    Dong-Woo Ryu, Yun Jeong Hong, Jung Hee Cho, Yong S Shim & Dong Won Yang

  2. Department of Biomedical Engineering, Hanyang University, Seoul, Republic of Korea

    Kichang Kwak & Jong-Min Lee

  3. Department of Neurology, Chung-Ang University Hospital, Seoul, Republic of Korea

    Young Chul Youn

Authors
  1. Dong-Woo Ryu
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  2. Yun Jeong Hong
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  3. Jung Hee Cho
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  4. Kichang Kwak
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  5. Jong-Min Lee
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  6. Yong S Shim
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  7. Young Chul Youn
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  8. Dong Won Yang
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Contributions

DW Ryu: Conceptualization; Methodology; Validation; Formal analysis; Data curation, Writing—original draft preparation, review and editing; Approval of final manuscript, YJ Hong: Formal analysis; Data curation; Approval of final manuscript, JH Cho: Software; Formal analysis; Approval of final manuscript, KC Kwak: Software; Validation; Approval of final manuscript, JM Lee: Software; Approval of final manuscript, YS Shim: Formal analysis; Data curation; Approval of final manuscript, YC Youn: Formal analysis; Data curation; Approval of final manuscript, DW Yang: Conceptualization; Methodology; Software; Validation; Data curation; Writing—original draft preparation, review and editing; Approval of final manuscript.

Corresponding author

Correspondence to Dong Won Yang.

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The study protocol was approved by the institutional review board and the ethical standard committee at our institution.

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The ethics board determined that participant consent was not required for the retrospective observations.

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All the authors aggressed with the publication of this article.

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Authors had confirmed that there is no conflict of interest to disclose.

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Ryu, DW., Hong, Y.J., Cho, J.H. et al. Automated brain volumetric program measuring regional brain atrophy in diagnosis of mild cognitive impairment and Alzheimer’s disease dementia. Brain Imaging and Behavior 16, 2086–2096 (2022). https://doi.org/10.1007/s11682-022-00678-x

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  • DOI: https://doi.org/10.1007/s11682-022-00678-x

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