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Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification
The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantificatio...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072675/ https://www.ncbi.nlm.nih.gov/pubmed/30094164 http://dx.doi.org/10.1016/j.nicl.2018.07.013 |
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author | Presotto, Luca Iaccarino, Leonardo Sala, Arianna Vanoli, Emilia G. Muscio, Cristina Nigri, Anna Bruzzone, Maria Grazia Tagliavini, Fabrizio Gianolli, Luigi Perani, Daniela Bettinardi, Valentino |
author_facet | Presotto, Luca Iaccarino, Leonardo Sala, Arianna Vanoli, Emilia G. Muscio, Cristina Nigri, Anna Bruzzone, Maria Grazia Tagliavini, Fabrizio Gianolli, Luigi Perani, Daniela Bettinardi, Valentino |
author_sort | Presotto, Luca |
collection | PubMed |
description | The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT ((18)F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global (18)F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVr(CT,) SUVr(MRI)) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVr(CT) and SUVr(MRI) global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis. |
format | Online Article Text |
id | pubmed-6072675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-60726752018-08-09 Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification Presotto, Luca Iaccarino, Leonardo Sala, Arianna Vanoli, Emilia G. Muscio, Cristina Nigri, Anna Bruzzone, Maria Grazia Tagliavini, Fabrizio Gianolli, Luigi Perani, Daniela Bettinardi, Valentino Neuroimage Clin Regular Article The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT ((18)F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global (18)F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVr(CT,) SUVr(MRI)) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVr(CT) and SUVr(MRI) global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis. Elsevier 2018-07-19 /pmc/articles/PMC6072675/ /pubmed/30094164 http://dx.doi.org/10.1016/j.nicl.2018.07.013 Text en © 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Regular Article Presotto, Luca Iaccarino, Leonardo Sala, Arianna Vanoli, Emilia G. Muscio, Cristina Nigri, Anna Bruzzone, Maria Grazia Tagliavini, Fabrizio Gianolli, Luigi Perani, Daniela Bettinardi, Valentino Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title | Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title_full | Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title_fullStr | Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title_full_unstemmed | Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title_short | Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification |
title_sort | low-dose ct for the spatial normalization of pet images: a validation procedure for amyloid-pet semi-quantification |
topic | Regular Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6072675/ https://www.ncbi.nlm.nih.gov/pubmed/30094164 http://dx.doi.org/10.1016/j.nicl.2018.07.013 |
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