Improved accuracy of amyloid PET quantification with adaptive template-based anatomic standardization

Amyloid positron emission tomography (PET) noninvasively visualizes amyloid-β (Aβ) accumulation in the brain. Visual binary reading is the standard method for interpreting amyloid PET, while objective quantitative evaluation is required in research and clinical trials. Anatomical standardization is important for quantitative analysis, and various standard templates are used for this purpose. To address the large differences in the radioactivity distribution between amyloid-positive and amyloid-negative participants, an adaptive template method has been proposed for the anatomical 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\u27s disease (AD). A total of 166 participants (58 normal controls (NCs), 62 participants with mild cognitive impairment (MCI), and 46 patients with AD) who underwent [C] Pittsburgh Compound B PET (C-PiB) through the Japanese Alzheimer\u27s Disease Neuroimaging Initiative study were examined. For the anatomical standardization of C-PiB PET images, we applied three methods a positive template-based method, a negative template-based method, and adaptive template-based method. The positive template was created by averaged four patients with AD and seven patients with MCI PET images. Conversely, the negative template was created by averaged eight participants of NC PET images. 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. Empirical PiB-prone region-of-interest was used to evaluate specific regions where Aβ accumulates. The reference region was the cerebellar cortex, whereas the evaluated regions were the posterior cingulate gyrus and precuneus as well as the frontal, lateral temporal, lateral parietal, and occipital lobes. The mean cortical standardized uptake value ratio (mcSUVR) was calculated for quantitative evaluation. The NCCs of single template-based methods (the positive template or negative template) showed a significant difference between NC, MCI and AD ( 0.05). The mcSUVR exhibited significant differences between NC, MCI and AD in all methods ( < 0.05). The area under curve by receiver operating characteristic analysis between the positive group (MCI and AD) and NC was not significantly different in mcSUVR among all templates. With regard to diagnostic accuracy based on mcSUVR, the sensitivity of the negative and adaptive template-based methods was superior to that of the positive template-based method ( < 0.05); however, there was no significant difference in specificity between them. In the diagnostic accuracy for AD by amyloid PET quantitative evaluation, the adaptive template-based anatomical standardization method outperformed the single template-based methods

Development and evaluation of an automated quantification tool for amyloid PET images

Background: Quantitative evaluation of amyloid positron emission tomography(PET) with standardized uptake value ratio (SUVR) plays a key role in clinical studies of Alzheimer’s disease (AD). We have proposed a PET-only (MR-free) amyloid quantification method, although some commercial software packages are required. The aim of this study was to develop an automated quantification tool for amyloid PET without using commercial software.Methods: The quantification tool was created by combining four components: (1)anatomical standardization to positive and negative templates using NEUROSTAT stereo.exe; (2) similarity calculation between standardized images and respective templates based on normalized cross-correlation (selection of the image for SUVR measurement); (3) voxel value normalization by the mean value of reference regions (making an SUVR-scaled image); and (4) SUVR calculation based on pre-defined regions of interest (ROIs). We examined 166 subjects who underwent a [11C] Pittsburgh compound-B PET scan through the Japanese Alzheimer’s Disease Neuroimaging Initiative (J-ADNI) study. SUVRs in five ROIs (frontal lobe, temporal lobe, parietal lobe, occipital lobe, and posterior cingulate cortex and precuneus) were calculated with the cerebellar cortex as the reference region. The SUVRs obtained by our tool were compared with manual step-by-step processing and the conventional PMOD-based method (PMOD Technologies, Switzerland).Results: Compared with manual step-by-step processing, our developed automated quantification tool reduced processing time by 85%. The SUVRs obtained by the developed quantification tool were consistent with those obtained by manual processing. Compared with the conventional PMOD-based method, the developed quantification tool provided 1.5% lower SUVR values, on average. We determined that this bias is likely due to the difference in anatomical standardization methods.Conclusions: We developed an automated quantification tool for amyloid PETimages. Using this tool, SUVR values can be quickly measured without individual MRI and without commercial software. This quantification tool may be useful for clinical studies of AD