Figure 2 shows the results of the visual evaluation in relation to clinical diagnosis. Among subjects with NC, 44 subjects (75.9%) were amyloid PET–negative and 14 subjects (24.1%) showed either positive or equivocal result. Among patients with MCI, 21 patients (33.9%) were negative, and 41 patients (66.1%) were either positive or equivocal. finally, in patients with AD, three patients (6.5%) were negative and 43 patients (93.5%) were either positive or equivocal. When MCI and AD were considered to be a disease, the sensitivity was 78%, the specificity was 76%, and the accuracy was 77% (Table 2).
Table 2
Comparison of the diagnostic accuracy for differentiation
| Sensitivity | Specificity | Accuracy |
Visual evaluation | 78% (84/108) | 76% (44/58) | 77% (128/166) |
mcSUVR | 77% (83/108) | 79% (46/58) | 78% (129/166) |
maxSUVR | 79% (85/108) | 79% (46/58) | 79% (131/166) |
Not significant |
mcSUVR, Mean cortical standardized uptake value ratio; maxSUVR, maximum SUVR. |
Figure 3 shows the relationship between regional visual interpretation and regional SUVR in each region. When the visual point of regional uptake was high, the SUVR was also high. Spearman’s rank correlation coefficient was significant (ρ = 0.86; p < 0.05). Significant correlations were also observed in the precuneus/posterior cingulate (ρ = 0.87; p < 0.05), the frontal lobe (ρ = 0.87; p < 0.05), the lateral temporal lobe (ρ = 0.86; p < 0.05), and the lateral parietal lobe (ρ = 0.85; p < 0.05).
The relationship between visual and quantitative evaluation by patient group is shown in Fig. 4. The cut-off value for differentiating between visually negative and both positive and equivocal results was calculated by ROC analysis. Cutoff values were 1.41 for mcSUVR and 1.59 for maxSUVR. Concordant results between visual and quantitative evaluation were obtained as 157 of 166 cases (94.6%) for mcSUVR and 158 of 166 cases (95.2%) for maxSUVR. In 98 subjects with visually positive or equivocal findings, seven subjects were negative using mcSUVR, and six subjects were negative using maxSUVR. Among 68 subjects with visually negative results, one subject was positive using mcSUVR, and no subjects were positive using maxSUVR. The mcSUVR values of negative, equivocal, and positive outcomes were 1.25 ± 0.11, 1.39 ± 0.20, and 2.17 ± 0.34, respectively. The difference in mcSUVR among visual classifications was significant (p < 0.05). Separately, the maxSUVR values of negative, equivocal, and positive results were 1.35 ± 0.13, 1.56 ± 0.21, and 2.48 ± 0.41, respectively (p < 0.05).
The comparison of diagnostic accuracy between visual and quantitative evaluation is shown in Table 2. The sensitivity, specificity, and accuracy when using visual evaluation were 78%, 76%, and 77%, respectively. Additionally, they were 77%, 79%, and 78% using mcSUVR and were 79%, 79%, and 79% using maxSUVR, respectively. In comparison with visual evaluation, one true-positive subject decreased, and two true negative subjects increased using mcSUVR. Further, by using maxSUVR, one true-positive subject increased and two true negative subjects increased. Ultimately, the diagnostic accuracy of quantitative evaluation was almost equal to that of visual evaluation. The clinical diagnosis by maxSUVR tended to be a little higher than that when using visual evaluation and mcSUVR, though the difference was not statistically significant.