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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...

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Autores principales: Presotto, Luca, Iaccarino, Leonardo, Sala, Arianna, Vanoli, Emilia G., Muscio, Cristina, Nigri, Anna, Bruzzone, Maria Grazia, Tagliavini, Fabrizio, Gianolli, Luigi, Perani, Daniela, Bettinardi, Valentino
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
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.
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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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