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Published in: Annals of Nuclear Medicine 10/2022

Open Access 11-07-2022 | Alzheimer's Disease | Original Article

Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease

Authors: Etsuko Imabayashi, Naoyuki Tamamura, Yuzuho Yamaguchi, Yuto Kamitaka, Muneyuki Sakata, Kenji Ishii

Published in: Annals of Nuclear Medicine | Issue 10/2022

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Abstract

Objective

Although beta-amyloid (Aβ) positron emission tomography (PET) images are interpreted visually as positive or negative, approximately 10% are judged as equivocal in Alzheimer’s disease. Therefore, we aimed to develop an automated semi-quantitative analysis technique using 18F-flutemetamol PET images without anatomical images.

Methods

Overall, 136 cases of patients administered 18F-flutemetamol were enrolled. Of 136 cases, five PET images each with the highest and lowest values of standardized uptake value ratio (SUVr) of cerebral cortex-to-pons were used to create positive and negative templates. Using these templates, PET images of the remaining 126 cases were standardized, and SUVr images were produced with the pons as a reference region. The mean of SUVr values in the volume of interest delineated on the cerebral cortex was compared to those in the CortexID Suite (GE Healthcare). Furthermore, centiloid (CL) values were calculated for the 126 cases using data from the Centiloid Project (http://​www.​gaain.​org/​centiloid-project) and both templates. 18F-flutemetamol-PET was interpreted visually as positive/negative based on Aβ deposition in the cortex. However, the criterion "equivocal" was added for cases with focal or mild Aβ accumulation that were difficult to categorize. Optimal cutoff values of SUVr and CL maximizing sensitivity and specificity for Aβ detection were determined by receiver operating characteristic (ROC) analysis using the visual evaluation as a standard of truth.

Results

SUVr calculated by our method and CortexID were highly correlated (R2 = 0.9657). The 126 PET images comprised 84 negative and 42 positive cases of Aβ deposition by visual evaluation, of which 11 and 10 were classified as equivocal, respectively. ROC analyses determined the optimal cutoff values, sensitivity, and specificity for SUVr as 0.544, 89.3%, and 92.9%, respectively, and for CL as 12.400, 94.0%, and 92.9%, respectively. Both semi-quantitative analyses showed that 12 and 9 of the 21 equivocal cases were negative and positive, respectively, under the optimal cutoff values.

Conclusions

This semi-quantitative analysis technique using 18F-flutemetamol-PET calculated SUVr and CL automatically without anatomical images. Moreover, it objectively and homogeneously interpreted positive or negative Aβ burden in the brain as a supplemental tool for the visual reading of equivocal cases in routine clinical practice.
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Metadata
Title
Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
Authors
Etsuko Imabayashi
Naoyuki Tamamura
Yuzuho Yamaguchi
Yuto Kamitaka
Muneyuki Sakata
Kenji Ishii
Publication date
11-07-2022
Publisher
Springer Nature Singapore
Published in
Annals of Nuclear Medicine / Issue 10/2022
Print ISSN: 0914-7187
Electronic ISSN: 1864-6433
DOI
https://doi.org/10.1007/s12149-022-01769-x

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