Abstract

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.

Highlights

  • Imaging of the dopaminergic system with SPECT has become widespread in Europe and has entered a new active phase in the US since⁎ Corresponding author at: JHOC Building Room 3245, 601 N

  • We focus on dopamine transporter (DAT) SPECT imaging, given its increasingly popular clinical usage

  • When both healthy controls (HC) and Parkinson's disease (PD) subjects were included in correlation analysis, conventional normalized mean uptake approach resulted in significant correlations with clinical measures

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Summary

Introduction

Imaging of the dopaminergic system with SPECT has become widespread in Europe and has entered a new active phase in the US since⁎ Corresponding author at: JHOC Building Room 3245, 601 N. Quantitative analysis may be more sensitive to detecting the early stages of disease and to better track disease progression Such an effort is consistent with the aim of the Parkinson's Progressive Marker Initiative (PPMI) (Parkinson Progression Marker, 2011) to identity biomarkers of PD progression, a critical step in the development of novel and enhanced treatments for PD. We perform a cross-sectional study to investigate whether use of advanced textural features enables enhanced correlations with clinical assessments. This is a step towards the long-term goal of enabling clinical utility of DAT SPECT imaging, beyond standard diagnostic tasks, to tracking of progression in PD. The present work includes assessment of both motor and non-motor symptoms, since it has been shown that a number of neuropsychiatric symptoms and cognitive disorders are more common in PD compared to the general population and contribute to the disability associated with the illness (de la Riva et al, 2014; Gustafsson et al, 2015)

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