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

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 (18)F-flutemetamo...

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Autores principales: Imabayashi, Etsuko, Tamamura, Naoyuki, Yamaguchi, Yuzuho, Kamitaka, Yuto, Sakata, Muneyuki, Ishii, Kenji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515054/
https://www.ncbi.nlm.nih.gov/pubmed/35821311
http://dx.doi.org/10.1007/s12149-022-01769-x
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author Imabayashi, Etsuko
Tamamura, Naoyuki
Yamaguchi, Yuzuho
Kamitaka, Yuto
Sakata, Muneyuki
Ishii, Kenji
author_facet Imabayashi, Etsuko
Tamamura, Naoyuki
Yamaguchi, Yuzuho
Kamitaka, Yuto
Sakata, Muneyuki
Ishii, Kenji
author_sort Imabayashi, Etsuko
collection PubMed
description 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 (18)F-flutemetamol PET images without anatomical images. METHODS: Overall, 136 cases of patients administered (18)F-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. (18)F-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 (R(2) = 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 (18)F-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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12149-022-01769-x.
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spelling pubmed-95150542022-09-29 Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease Imabayashi, Etsuko Tamamura, Naoyuki Yamaguchi, Yuzuho Kamitaka, Yuto Sakata, Muneyuki Ishii, Kenji Ann Nucl Med Original Article 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 (18)F-flutemetamol PET images without anatomical images. METHODS: Overall, 136 cases of patients administered (18)F-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. (18)F-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 (R(2) = 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 (18)F-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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12149-022-01769-x. Springer Nature Singapore 2022-07-11 2022 /pmc/articles/PMC9515054/ /pubmed/35821311 http://dx.doi.org/10.1007/s12149-022-01769-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Imabayashi, Etsuko
Tamamura, Naoyuki
Yamaguchi, Yuzuho
Kamitaka, Yuto
Sakata, Muneyuki
Ishii, Kenji
Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title_full Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title_fullStr Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title_full_unstemmed Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title_short Automated semi-quantitative amyloid PET analysis technique without MR images for Alzheimer’s disease
title_sort automated semi-quantitative amyloid pet analysis technique without mr images for alzheimer’s disease
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9515054/
https://www.ncbi.nlm.nih.gov/pubmed/35821311
http://dx.doi.org/10.1007/s12149-022-01769-x
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