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Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern

BACKGROUND: Alzheimer’s disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP’s perf...

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Autores principales: Štokelj, Eva, Tomše, Petra, Tomanič, Tadej, Dhawan, Vijay, Eidelberg, David, Trošt, Maja, Simončič, Urban
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209378/
https://www.ncbi.nlm.nih.gov/pubmed/37222957
http://dx.doi.org/10.1186/s13550-023-01001-5
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author Štokelj, Eva
Tomše, Petra
Tomanič, Tadej
Dhawan, Vijay
Eidelberg, David
Trošt, Maja
Simončič, Urban
author_facet Štokelj, Eva
Tomše, Petra
Tomanič, Tadej
Dhawan, Vijay
Eidelberg, David
Trošt, Maja
Simončič, Urban
author_sort Štokelj, Eva
collection PubMed
description BACKGROUND: Alzheimer’s disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP’s performance need to be clarified. METHODS: 240 2-[(18)F]fluoro-2-deoxy-d-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions. RESULTS: ADRP’s performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP’s diagnostic performance only marginally in the range from 8 to 15 mm. ADRP’s performance stayed optimal even when applied to validation images of resolution differing from the identification images. CONCLUSIONS: While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP’s diagnostic performance. ADRP’s performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones.
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spelling pubmed-102093782023-05-26 Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern Štokelj, Eva Tomše, Petra Tomanič, Tadej Dhawan, Vijay Eidelberg, David Trošt, Maja Simončič, Urban EJNMMI Res Original Research BACKGROUND: Alzheimer’s disease-related pattern (ADRP) is a metabolic brain biomarker of Alzheimer’s disease (AD). While ADRP is being introduced into research, the effect of the size of the identification cohort and the effect of the resolution of identification and validation images on ADRP’s performance need to be clarified. METHODS: 240 2-[(18)F]fluoro-2-deoxy-d-glucose positron emission tomography images [120 AD/120 cognitive normals (CN)] were selected from the Alzheimer's disease neuroimaging initiative database. A total of 200 images (100 AD/100 CN) were used to identify different versions of ADRP using a scaled subprofile model/principal component analysis. For this purpose, five identification groups were randomly selected 25 times. The identification groups differed in the number of images (20 AD/20 CN, 30 AD/30 CN, 40 AD/40 CN, 60 AD/60 CN, and 80 AD/80 CN) and image resolutions (6, 8, 10, 12, 15 and 20 mm). A total of 750 ADRPs were identified and validated through the area under the curve (AUC) values on the remaining 20 AD/20 CN with six different image resolutions. RESULTS: ADRP’s performance for the differentiation between AD patients and CN demonstrated only a marginal average AUC increase, when the number of subjects in the identification group increases (AUC increase for about 0.03 from 20 AD/20 CN to 80 AD/80 CN). However, the average of the lowest five AUC values increased with the increasing number of participants (AUC increase for about 0.07 from 20 AD/20 CN to 30 AD/30 CN and for an additional 0.02 from 30 AD/30 CN to 40 AD/40 CN). The resolution of the identification images affects ADRP’s diagnostic performance only marginally in the range from 8 to 15 mm. ADRP’s performance stayed optimal even when applied to validation images of resolution differing from the identification images. CONCLUSIONS: While small (20 AD/20 CN images) identification cohorts may be adequate in a favorable selection of cases, larger cohorts (at least 30 AD/30 CN images) shall be preferred to overcome possible/random biological differences and improve ADRP’s diagnostic performance. ADRP’s performance stays stable even when applied to the validation images with a resolution different than the resolution of the identification ones. Springer Berlin Heidelberg 2023-05-24 /pmc/articles/PMC10209378/ /pubmed/37222957 http://dx.doi.org/10.1186/s13550-023-01001-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 Research
Štokelj, Eva
Tomše, Petra
Tomanič, Tadej
Dhawan, Vijay
Eidelberg, David
Trošt, Maja
Simončič, Urban
Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title_full Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title_fullStr Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title_full_unstemmed Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title_short Effect of the identification group size and image resolution on the diagnostic performance of metabolic Alzheimer’s disease-related pattern
title_sort effect of the identification group size and image resolution on the diagnostic performance of metabolic alzheimer’s disease-related pattern
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209378/
https://www.ncbi.nlm.nih.gov/pubmed/37222957
http://dx.doi.org/10.1186/s13550-023-01001-5
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