Multi-Ethnic Norms for Volumes of Subcortical and Lobar Brain Structures Measured by Neuro I: Ethnicity May Improve the Diagnosis of Alzheimer’s Disease¹

Article type: Research Article

Authors: Choi, Yu Yong^{a; b} | Lee, Jang Jae^a | te Nijenhuis, Jan^a | Choi, Kyu Yeong^a | Park, Jongseong^c | Ok, Jongmyoung^c | Choo, IL Han^d | Kim, Hoowon^{a; e} | Song, Min-Kyung^b | Choi, Seong-Min^{b; f} | Cho, Soo Hyun^{b; f} | Chae, Youngshik^g | Kim, Byeong C.^{b; f; *} | Lee, Kun Ho^{a; c; g; h; *}

Affiliations: [a] Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea | [b] Department of Neurology, Chonnam National University Hospital, Gwangju, Republic of Korea | [c] Neurozen Inc., Seoul, Republic of Korea | [d] Department of Neuropsychiatry, Chosun University School of Medicine and Hospital, Gwangju, Republic of Korea | [e] Department of Neurology, Chosun University School of Medicine and Hospital, Gwangju, Republic of Korea | [f] Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea | [g] Korea Brain Research Institute, Daegu, Republic of Korea | [h] Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea

Correspondence: [*] Byeong C. Kim, Department of Neurology, Chonnam National University Hospital, Gwangju 61469, Republic of Korea. E-mail: [email protected] and Kun Ho Lee, a Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Republic of Korea. E-mail: [email protected].

Note: [1] Some of the Caucasian data were from the ADNI project launched in 2003 as a public-private partnership, led by Principal Investigator Michael W. Weiner (see http://www.adni-info.org/ for up-to-date information).

Abstract: Background:We previously demonstrated the validity of a regression model that included ethnicity as a novel predictor for predicting normative brain volumes in old age. The model was optimized using brain volumes measured with a standard tool FreeSurfer. Objective:Here we further verified the prediction model using newly estimated brain volumes from Neuro I, a quantitative brain analysis system developed for Korean populations. Methods:Lobar and subcortical volumes were estimated from MRI images of 1,629 normal Korean and 786 Caucasian subjects (age range 59–89) and were predicted in linear regression from ethnicity, age, sex, intracranial volume, magnetic field strength, and scanner manufacturers. Results:In the regression model predicting the new volumes, ethnicity was again a substantial predictor in most regions. Additionally, the model-based z-scores of regions were calculated for 428 AD patients and the matched controls, and then employed for diagnostic classification. When the AD classifier adopted the z-scores adjusted for ethnicity, the diagnostic accuracy has noticeably improved (AUC = 0.85, ΔAUC = + 0.04, D = 4.10, p <  0.001). Conclusions:Our results suggest that the prediction model remains robust across different measurement tool, and ethnicity significantly contributes to the establishment of norms for brain volumes and the development of a diagnostic system for neurodegenerative diseases.

Keywords: Alzheimer’s disease, brain aging, ethnic difference, magnetic resonance imaging, norm

DOI: 10.3233/JAD-231182

Journal: Journal of Alzheimer's Disease, vol. Pre-press, no. Pre-press, pp. 1-18, 2024