Yingren Mai1, Qun Yu1, Feiqi Zhu2, Yishan Luo3, Wang Liao1, Lei Zhao3, Chunyan Xu2, Wenli Fang1, Yuting Ruan1, Zhiyu Cao1, Ming Lei1, Lisa Au4, Vincent C T Mok3,4, Lin Shi3,5, Jun Liu1,6,7. 1. Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 2. Cognitive Impairment Ward of Neurology Department, The Third Affiliated Hospital of Shenzhen University Medical College, Shenzhen, China. 3. BrainNow Research Institute, Shenzhen, China. 4. 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. 5. Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong SAR, China. 6. Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China. 7. Laboratory of RNA and Major Diseases of Brain and Heart, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, China.
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.
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.
Authors: Panteleimon Giannakopoulos; Marie-Louise Montandon; François R Herrmann; Dennis Hedderich; Christian Gaser; Elias Kellner; Cristelle Rodriguez; Sven Haller Journal: Eur Radiol Date: 2022-04-29 Impact factor: 5.315
Authors: Yingren Mai; Zhiyu Cao; Jiaxin Xu; Qun Yu; Shaoqing Yang; Jingyi Tang; Lei Zhao; Wenli Fang; Yishan Luo; Ming Lei; Vincent C T Mok; Lin Shi; Wang Liao; Jun Liu Journal: Front Aging Neurosci Date: 2022-04-28 Impact factor: 5.702
Authors: Qiling He; Lin Shi; Yishan Luo; Chao Wan; Ian B Malone; Vincent C T Mok; James H Cole; Melis Anatürk Journal: Front Aging Neurosci Date: 2022-08-05 Impact factor: 5.702