| Literature DB >> 30090663 |
Daichi Sone1,2, Etsuko Imabayashi2, Norihide Maikusa2, Masayo Ogawa2, Noriko Sato3, Hiroshi Matsuda2.
Abstract
Voxel-based specific regional analysis system for Alzheimer's disease (VSRAD) software is widely used in clinical practice in Alzheimer's disease (AD). The existing VSRAD is based on the normal database with 1.5-tesla MRI scans (VSRAD-1.5T), and its utility for patients have undergone 3-tesla MRI is still controversial. We recruited 19 patients with early AD and 28 healthy controls who had undergone 3-tesla MRI scans at our institute (Cohort 1). We also used the 3-tesla MRI data of 30 patients with early AD and 13 healthy controls from the Japanese Alzheimer's Disease Neuroimaging Initiative (Cohort 2). We also created a new VSRAD based on 65 normal subjects' 3-tesla MRI scans (VSRAD-3T), and compared the detectability of AD between VSRAD-1.5T and VSRAD-3T, using receiver operating characteristic curve and area under the curve (AUC) analyses. As a result, there were no significant differences in the detectability of AD between VSRAD-3T and VSRAD-1.5T, except for the whole white matter atrophy score, which showed significantly better AUC in VSRAD-3T than in VSRAD-1.5T in both Cohort 1 (p=0.04) and 2 (p<0.01). Generally, there were better diagnostic values in Cohort 2 than in Cohort 1. The optimal cutoff values varied but were generally lower than in the previously published data. In conclusion, for patients with 3-tesla MRI, the detectability of early AD by the existing VSRAD was not different from that by the new VSRAD based on 3-tesla database. We should exercise caution when using the existing VSRAD for 3-tesla white matter analyses or for setting cutoff values.Entities:
Keywords: 3-tesla MRI; Alzheimer’s disease; VSRAD; voxel-based morphometry
Year: 2018 PMID: 30090663 PMCID: PMC6065286 DOI: 10.14336/AD.2017.0818
Source DB: PubMed Journal: Aging Dis ISSN: 2152-5250 Impact factor: 6.745
The demographics of Cohorts 1 and 2 and the normal databases for this study.
| Cohort 1 - Our Institute | Cohort 2 - J-ADNI | Normal Databases | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| Early AD | Controls | Early AD | Controls | VSRAD-3T | VSRAD-1.5T | |
| Age (mean ± SD) | 69.8 ± 8.6 | 66.9 ± 7.9 | 74.2 ± 6.8 | 68.2 ± 6.0 | 70.3 ± 8.6 | 70.4 ± 7.8 |
| Age (range) | 53-81 | 54-86 | 61-83 | 61-80 | 54-85 | 54-86 |
| Gender (M:F) | 6:13 | 15:13 | 12:18 | 6:7 | 30:35 | 37:43 |
| Global CDR (range) | 0.5-1.0 | 0 | 0.5-1.0 | 0 | N/A | N/A |
| MMSE (mean ± SD) | 21.9 ± 4.5 | 29.3 ± 1.0 | 24.8 ± 2.5 | 29.8 ± 0.6 | N/A | 29.1 ± 1.2 |
(Matsuda et al. AJNR Am J Neuroradiol. 2012)
AUC values for differentiation of early AD from healthy controls using both VSRADs of ROC analysis
| Cohort 1 - Our Institute
| Cohort 2 - J-ADNI
| |||||
|---|---|---|---|---|---|---|
| VSRAD-3T | VSRAD-1.5T | p-value | VSRAD-3T | VSRAD-1.5T | p-value | |
| Severity | 0.818 | 0.813 | 0.76 | 0.933 | 0.931 | 0.76 |
| Extent | 0.855 | 0.820 | 0.24 | 0.918 | 0.933 | 0.35 |
| Ratio | 0.847 | 0.806 | 0.22 | 0.903 | 0.918 | 0.30 |
| Maximum | 0.814 | 0.792 | 0.44 | 0.928 | 0.938 | 0.45 |
| Whole GM | 0.745 | 0.772 | 0.63 | 0.862 | 0.797 | 0.12 |
| Whole WM | 0.723 | 0.564 | 0.04* | 0.865 | 0.662 | <0.01* |
AUC: area under the curve, ROC: receiver operating characteristic, GM: gray matter, WM: white matter.
Figure 1.The beeswarm plots and diagnostic values at the optimal cutoff for each score on both VSRADs in Cohort 1.
Figure 2.The beeswarm plots and diagnostic values at the optimal cutoff for each score on both VSRADs in Cohort 2.