AD Resemblance Atrophy Index as a Diagnostic Biomarker for Alzheimer’s Disease: A Retrospective Clinical and Biological Validation

Article type: Research Article

Authors: Mai, Yingren^{a; 1} | Yu, Qun^{a; 1} | Zhu, Feiqi^{b; 1} | Luo, Yishan^c | Liao, Wang^a | Zhao, Lei^c | Xu, Chunyan^b | Fang, Wenli^a | Ruan, Yuting^a | Cao, Zhiyu^a | Lei, Ming^a | Au, Lisa^d | Mok, Vincent C.T.^{c; d} | Shi, Lin^{c; e; *} | Liu, Jun^{a; f; g; *}

Affiliations: [a] Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China | [b] Cognitive Impairment Ward of Neurology Department, The Third Affiliated Hospital of Shenzhen University Medical College, Shenzhen, China | [c] BrainNow Research Institute, Shenzhen, China | [d] Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong SAR, China | [e] Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China | [f] Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China | [g] Laboratory of RNA and Major Diseases of Brain and Heart, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, China

Correspondence: [*] Correspondence to: Lin Shi, Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China. E-mail: shilin@cuhk.edu.hk. Jun Liu, Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, No. 107 Yanjiang West Road, Guangzhou, Guangdong, P.R. China. E-mail: liujun6@mail.sysu.edu.cn.

Note: [1] These authors contributed equally to this work.

Abstract: Background:Magnetic resonance imaging (MRI) provides objective information about brain structural atrophy in patients with Alzheimer’s disease (AD). This multi-structural atrophic information, when integrated as a single differential index, has the potential to further elevate the accuracy of AD identification from normal control (NC) compared to the conventional structure volumetric index. Objective:We herein investigated the performance of such an MRI-derived AD index, AD-Resemblance Atrophy Index (AD-RAI), as a neuroimaging biomarker in clinical scenario. Method:Fifty AD patients (19 with the Amyloid, Tau, Neurodegeneration (ATN) results assessed in cerebrospinal fluid) and 50 age- and gender-matched NC (19 with ATN results assessed using positron emission tomography) were recruited in this study. MRI-based imaging biomarkers, i.e., AD-RAI, were quantified using AccuBrain®. The accuracy, sensitivity, specificity, and area under the ROC curve (AUC) of these MRI-based imaging biomarkers were evaluated with the diagnosis result according to clinical criteria for all subjects and ATN biological markers for the subgroup. Results:In the whole groups of AD and NC subjects, the accuracy of AD-RAI was 91%, sensitivity and specificity were 88% and 96%, respectively, and the AUC was 92%. In the subgroup of 19 AD and 19 NC with ATN results, AD-RAI results matched completely with ATN classification. AD-RAI outperforms the volume of any single brain structure measured. Conclusion:The finding supports the hypothesis that MRI-derived composite AD-RAI is a more accurate imaging biomarker than individual brain structure volumetry in the identification of AD from NC in the clinical scenario.

Keywords: AD-Resemblance atrophy index, Alzheimer’s disease, ATN biological markers, automated brain volumetry, magnetic resonance imaging

DOI: 10.3233/JAD-201033

Journal: Journal of Alzheimer's Disease, vol. 79, no. 3, pp. 1023-1032, 2021