Yuma Tsubaki1, Takayoshi Kitamura2, Natsumi Shimokawa1, Go Akamatsu3, Masayuki Sasaki4. 1. Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan. 2. Department of Health Sciences, School of Medicine, Kyushu University, Fukuoka, Japan; and. 3. National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba, Japan. 4. Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; msasaki@hs.med.kyushu-u.ac.jp.
Abstract
Amyloid PET noninvasively visualizes amyloid-β accumulation in the brain. Visual binary reading is the standard method for interpreting amyloid PET, whereas objective quantitative evaluation is required in research and clinical trials. Anatomic standardization is important for quantitative analysis, and various standard templates are used for this purpose. To address the large differences in radioactivity distribution between amyloid-positive and amyloid-negative participants, an adaptive-template method has been proposed for the anatomic standardization of amyloid PET. In this study, we investigated the difference between the adaptive-template method and the single-template methods (use of a positive or a negative template) in amyloid PET quantitative evaluation, focusing on the accuracy in diagnosing Alzheimer's disease (AD). Methods: In total, 166 participants (58 healthy controls [HCs], 62 patients with mild cognitive impairment [MCI], and 46 patients with AD) who underwent 11C-Pittsburgh compound B (11C-PiB) PET through the Japanese Alzheimer's Disease Neuroimaging Initiative study were examined. For the anatomic standardization of 11C-PiB PET images, we applied 3 methods: a positive-template-based method, a negative-template-based method, and an adaptive-template-based method. The positive template was created by averaging the PET images for 4 patients with AD and 7 patients with MCI. Conversely, the negative template was created by averaging the PET images for 8 HCs. In the adaptive-template-based method, either of the templates was used on the basis of the similarity (normalized cross-correlation [NCC]) between the individual standardized image and the corresponding template. An empiric PiB-prone region of interest was used to evaluate specific regions where amyloid-β accumulates. The reference region was the cerebellar cortex, and the evaluated regions were the posterior cingulate gyrus and precuneus and the frontal, lateral temporal, lateral parietal, and occipital lobes. The mean cortical SUV ratio (mcSUVR) was calculated for quantitative evaluation. Results: The NCCs of single-template-based methods (the positive template or negative template) showed a significant difference among the HC, MCI, and AD groups (P < 0.05), whereas the NCC of the adaptive-template-based method did not (P > 0.05). The mcSUVR exhibited significant differences among the HC, MCI, and AD groups with all methods (P < 0.05). The mcSUVR area under the curve by receiver operating characteristic analysis between the positive group (MCI and AD) and the HC group did not significantly differ among templates. With regard to diagnostic accuracy based on mcSUVR, the sensitivity of the negative-template-based and adaptive-template-based methods was superior to that of the positive-template-based method (P < 0.05); however, there was no significant difference in specificity between them. Conclusion: In quantitative evaluation of AD by amyloid PET, the adaptive-template-based anatomic standardization method had greater diagnostic accuracy than the single-template-based methods.
Amyloid PET noninvasively visualizes amyloid-β accumulation in the brain. Visual binary reading is the standard method for interpreting amyloid PET, whereas objective quantitative evaluation is required in research and clinical trials. Anatomic standardization is important for quantitative analysis, and various standard templates are used for this purpose. To address the large differences in radioactivity distribution between amyloid-positive and amyloid-negative participants, an adaptive-template method has been proposed for the anatomic standardization of amyloid PET. In this study, we investigated the difference between the adaptive-template method and the single-template methods (use of a positive or a negative template) in amyloid PET quantitative evaluation, focusing on the accuracy in diagnosing Alzheimer's disease (AD). Methods: In total, 166 participants (58 healthy controls [HCs], 62 patients with mild cognitive impairment [MCI], and 46 patients with AD) who underwent 11C-Pittsburgh compound B (11C-PiB) PET through the Japanese Alzheimer's Disease Neuroimaging Initiative study were examined. For the anatomic standardization of 11C-PiB PET images, we applied 3 methods: a positive-template-based method, a negative-template-based method, and an adaptive-template-based method. The positive template was created by averaging the PET images for 4 patients with AD and 7 patients with MCI. Conversely, the negative template was created by averaging the PET images for 8 HCs. In the adaptive-template-based method, either of the templates was used on the basis of the similarity (normalized cross-correlation [NCC]) between the individual standardized image and the corresponding template. An empiric PiB-prone region of interest was used to evaluate specific regions where amyloid-β accumulates. The reference region was the cerebellar cortex, and the evaluated regions were the posterior cingulate gyrus and precuneus and the frontal, lateral temporal, lateral parietal, and occipital lobes. The mean cortical SUV ratio (mcSUVR) was calculated for quantitative evaluation. Results: The NCCs of single-template-based methods (the positive template or negative template) showed a significant difference among the HC, MCI, and AD groups (P < 0.05), whereas the NCC of the adaptive-template-based method did not (P > 0.05). The mcSUVR exhibited significant differences among the HC, MCI, and AD groups with all methods (P < 0.05). The mcSUVR area under the curve by receiver operating characteristic analysis between the positive group (MCI and AD) and the HC group did not significantly differ among templates. With regard to diagnostic accuracy based on mcSUVR, the sensitivity of the negative-template-based and adaptive-template-based methods was superior to that of the positive-template-based method (P < 0.05); however, there was no significant difference in specificity between them. Conclusion: In quantitative evaluation of AD by amyloid PET, the adaptive-template-based anatomic standardization method had greater diagnostic accuracy than the single-template-based methods.
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