Participants of this study were recruited from an on-going CU-SEEDS (The Chinese University of Hong Kong - Screening for Early AlzhEimer’s DiseaSe) study, which aimed to validate biomarkers (e.g. retinal imaging, brain MRI, plasma) for detection of AD. The study aimed to initially recruit 100 subjects (40 CU, 40 MCI, 20 mild AD with dementia) from the community and Cognitive Disorder Clinic of the Prince of Wales Hospital, Hong Kong SAR. Inclusion criteria were (1) Chinese ethnicity; (2) age between 50 to 80-year-old; and (3) a primary language of Cantonese. Exclusion criteria were (1) known diagnosis of non-AD dementia; (2) known history of stroke, parkinsonism, major psychiatric disease, or any significant neurological diseases (e.g. brain tumor); and/or (3) contraindication for MRI/PET. An experienced dementia specialist (L.W.C.A.) examined all potential subjects for eligibility of this study.
Syndromal staging of cognitive continuum
We defined CU and MCI according to the 2018 NIA-AA research framework (1). We used the Chinese Abbreviated Memory Inventory (CAMI) to define the presence of memory complaints(20). Subjects having one or more “Yes” to the 5 questions in CAMI were classified as having subjective memory complaints. We performed Hong Kong List Learning Test (HKLLT) (21) and the Hong Kong version of Montreal Cognitive Assessment (HK-MoCA) (22) for all subjects. We defined MCI as the presence of subjective memory complaints that represented a decline from baseline, objective memory impairment as defined by a z-score adjusted by age in Trial 4 (i.e. 10 min-delayed recall) of HKLLT of ≤-1 standard deviation (SD) (23), and the cognitive impairment has no major impact in daily function as defined by a clinical dementia rating scale (CDR) of ≤0.5. We defined CU as having a z-score adjusted by age in Trial 4 of HKLLT >-1SD and a CDR of 0. All participants provided written informed consent and this study was approved by the local ethics committee.
MRI was performed at Prince of Wales Hospital using a 3.0 Tesla scanner (Achieva TX; Philips Medical Systems, Best, Netherlands). The scanning protocol included a 3D T1-weighted MPRAGE sequence acquired at a resolution of 1.1mmx1.1mmx1.2mm which was used for visual assessment and volumetric analysis, as well as standard T2-weighted and FLAIR sequences to assess for other structural abnormalities including strategic infarcts and significant white matter hyperintensities.
We performed 11C- PIB and 18F-T807 PET/CT to quantify beta-amyloid and tau deposition, respectively at the Department of Nuclear Medicine & PET of Hong Kong Sanatorium & Hospital, Hong Kong SAR. All subjects received 11C-PIB intravenously and were scanned at 35 min post injection. Within one week, they underwent 18F-T807 PET/CT at 85 min post IV injection. 11C-PIB and 18F-T807 uptake were quantified by the “global cortical to cerebellum Standard Uptake Value ratio (SUVR)”. The calculation of SUVR included 13 target regions of interest contoured automatically: frontal gyrus, gyrus rectus, lateral temporal lobe, medial temporal lobe, posterior cingulate gyrus, precuneus, putamen, thalamus, superior parietal lobe, occipital lobe, head of the caudate, cerebellar vermis and brainstem.
We defined A+ if (1) increased 11C-PIB uptake was visually observed in regions known to have beta-amyloid deposits in patients with AD dementia, e.g. frontal lobe, parietal lobe, lateral temporal lobe, posterior cingulate, precuneus and/or caudate; and/or (2) global retention ≥1.42. We defined T+ if (1) increased 18F-T807 uptake was visually observed in regions known to have tau deposits in AD dementia, e.g. medial temporal lobe, inferior and middle temporal lobe, medial and lateral parietal lobe, occipital and frontal lobe (24); and/or (2) SUVR ≥1.14. CU and MCI subjects who had A+T+ were diagnosed as having preclinical and prodromal AD, respectively (1). All PET imaging data was interpreted by an experienced nuclear medicine specialist (E.Y.L.L.) who was blinded to subjects’ cognitive and structural imaging data.
Visual ratings of MTA
An experienced neuroradiologist (J.A.) rated MTA using Scheltens’s scale (25). 10 individuals were randomly selected and rated again by the same neuroradiologist to obtain intra-rater reliability. We took the average of the left and right MTA scores as the final MTA score. We used the cutoff of ≥ 1 to define prodromal AD (26). We also explored the performance using other pre-specified cutoffs (i.e. ≥1.5 (27, 28) and age-adjusted: 1.5 for <75-year-old, and 2 for ≥75-year-old (29)) which have been used for the diagnosis of AD at the dementia stage.
All the MRIs were processed using AccuBrain® IV 1.1 (BrainNow Medical Technology Company Ltd.) that performs brain structure and tissue segmentation and quantification using 3D T1-weighted MR image (30). We used the summation of the volume of both sides in milliliter (mL) as the final raw HV. Accubrain® also generated the hippocampal fraction (HF) (bilateral absolute HV/intracranial volume). AccuBrain® also generated AD-RAI to indicate the similarity in atrophy pattern between the subject’s brain and those with AD with dementia (ranging from 0 to 1.0).
We investigated the performance of AD-RAI in detecting subjects with A+T+ using an index of ≥ 0.5, as obtained from the derivation study that was found to be the optimal cutoff in differentiating between “converters” and “stable” using ADNI database(19). Note that in our derivation study, we did not obtain the optimal cutoffs of HV and HF in differentiating between “converters” and “stable”. In order to compare AD-RAI with conventional imaging measures (i.e. HV and HF) in detecting A+T+ subjects in the present validation study, we further generated receiving operating curve (ROC) among all subjects and among MCI and CU subgroups for the differentiation between “converters” and “stable” subjects. The derived optimal cutoffs were as follows: all subjects - HV: 6.44mL, HF: 0.42%, MCI subjects - HV: 6.07mL, HF: 0.41%, and CU subjects - HV: 6.64mL, HF: 0.44%. The performance metrics (sensitivity, specificity, positive predictive values, negative predictive values, accuracy) using the optimal cutoffs of AD-RAI, HV, and HF in differentiating converters and stable subjects from ADNI database can be found in supplemental material (Appendix I to III). We also compared pre-specified cutoffs (HV: 5.91mL, HF: 0.39%) used for the detection of AD with dementia (30). MRI of the 10 individuals who were randomly selected for evaluation of intra-rater reliability for visual MTA rating were processed again by AccuBrain® to test/re-test precision of the tool in generating HV, HF, and AD-RAI.
Continuous variables were presented as means (SD), whilst categorical variables were presented as numbers (percentage). The p-values representing the group difference were derived from independent-samples t-test. Intra-rater reliability was assessed with the weighted Cohen’s kappa test (31). Sensitivity and specificity with 95% confidence intervals (CI), positive and negative prediction values (PPV, NPV), and accuracy were employed to evaluate the performance of different measures in the identification of A+T+ subjects. We also explored the metrics of various imaging measures in the detection of A+ with or without T+ (i.e. Alzheimer’s continuum). Statistical analyses were performed using SPSS version 25.0 for IOS.