Cargando…

Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments

Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and co...

Descripción completa

Detalles Bibliográficos
Autores principales: Rahmim, Arman, Salimpour, Yousef, Jain, Saurabh, Blinder, Stephan A.L., Klyuzhin, Ivan S., Smith, Gwenn S., Mari, Zoltan, Sossi, Vesna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5153560/
https://www.ncbi.nlm.nih.gov/pubmed/27995072
http://dx.doi.org/10.1016/j.nicl.2016.02.012
_version_ 1782474715373240320
author Rahmim, Arman
Salimpour, Yousef
Jain, Saurabh
Blinder, Stephan A.L.
Klyuzhin, Ivan S.
Smith, Gwenn S.
Mari, Zoltan
Sossi, Vesna
author_facet Rahmim, Arman
Salimpour, Yousef
Jain, Saurabh
Blinder, Stephan A.L.
Klyuzhin, Ivan S.
Smith, Gwenn S.
Mari, Zoltan
Sossi, Vesna
author_sort Rahmim, Arman
collection PubMed
description Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression.
format Online
Article
Text
id pubmed-5153560
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-51535602016-12-19 Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments Rahmim, Arman Salimpour, Yousef Jain, Saurabh Blinder, Stephan A.L. Klyuzhin, Ivan S. Smith, Gwenn S. Mari, Zoltan Sossi, Vesna Neuroimage Clin Article Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected Parkinsonian syndromes. We performed a cross-sectional study to investigate whether assessment of texture in DAT SPECT radiotracer uptake enables enhanced correlations with severity of motor and cognitive symptoms in Parkinson's disease (PD), with the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. Quantitative analysis in routine DAT SPECT imaging, if performed at all, has been restricted to assessment of mean regional uptake. We applied a framework wherein textural features were extracted from the images. Notably, the framework did not require registration to a common template, and worked in the subject-native space. Image analysis included registration of SPECT images onto corresponding MRI images, automatic region-of-interest (ROI) extraction on the MRI images, followed by computation of Haralick texture features. We analyzed 141 subjects from the Parkinson's Progressive Marker Initiative (PPMI) database, including 85 PD and 56 healthy controls (HC) (baseline scans with accompanying 3 T MRI images). We performed univariate and multivariate regression analyses between the quantitative metrics and different clinical measures, namely (i) the UPDRS (part III - motor) score, disease duration as measured from (ii) time of diagnosis (DD-diag.) and (iii) time of appearance of symptoms (DD-sympt.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score. For conventional mean uptake analysis in the putamen, we showed significant correlations with clinical measures only when both HC and PD were included (Pearson correlation r = − 0.74, p-value < 0.001). However, this was not significant when applied to PD subjects only (r = − 0.19, p-value = 0.084), and no such correlations were observed in the caudate. By contrast, for the PD subjects, significant correlations were observed in the caudate when including texture metrics, with (i) UPDRS (p-values < 0.01), (ii) DD-diag. (p-values < 0.001), (iii) DD-sympt (p-values < 0.05), and (iv) MoCA (p-values < 0.01), while no correlations were observed for conventional analysis (p-values = 0.94, 0.34, 0.88 and 0.96, respectively). Our results demonstrated the ability to capture valuable information using advanced texture metrics from striatal DAT SPECT, enabling significant correlations of striatal DAT binding with clinical, motor and cognitive outcomes, and suggesting that textural features hold potential as biomarkers of PD severity and progression. Elsevier 2016-02-23 /pmc/articles/PMC5153560/ /pubmed/27995072 http://dx.doi.org/10.1016/j.nicl.2016.02.012 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rahmim, Arman
Salimpour, Yousef
Jain, Saurabh
Blinder, Stephan A.L.
Klyuzhin, Ivan S.
Smith, Gwenn S.
Mari, Zoltan
Sossi, Vesna
Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title_full Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title_fullStr Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title_full_unstemmed Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title_short Application of texture analysis to DAT SPECT imaging: Relationship to clinical assessments
title_sort application of texture analysis to dat spect imaging: relationship to clinical assessments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5153560/
https://www.ncbi.nlm.nih.gov/pubmed/27995072
http://dx.doi.org/10.1016/j.nicl.2016.02.012
work_keys_str_mv AT rahmimarman applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT salimpouryousef applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT jainsaurabh applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT blinderstephanal applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT klyuzhinivans applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT smithgwenns applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT marizoltan applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments
AT sossivesna applicationoftextureanalysistodatspectimagingrelationshiptoclinicalassessments