Application of texture analysis to DaTscan images for enhanced assessment of progression in Parkinson’s disease

Objectives Dopamine transporter (DAT) SPECT imaging is increasingly utilized for diagnostic purposes in suspected parkinsonian syndromes. Our objective was to enable additional clinical utility of this modality, beyond standard diagnostic tasks, to tracking of progression in Parkinson’s disease (PD). Specifically, we investigated whether assessment of texture in radiotracer uptake enabled enhanced correlations with severity of motor and cognitive symptoms in PD.

Methods 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 n=116 subjects from the Parkinson’s Progressive Marker Initiative (PPMI) database, including 72 PD and 44 healthy controls (HC) (baseline scans with accompanying 3T MRI images, age < 70). 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 time of (ii) detection of symptoms (DD-sympt.) and (iii) diagnosis (DD-diag.), as well as (iv) the Montreal Cognitive Assessment (MoCA) score.

Results 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 ρ=-0.76, p-value<0.001). However, this became insignificant when applied to PD subjects only (ρ=-0.18, p-value=0.13), 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-sympt (p-values<0.01), (ii) DD-diag. (p-values<0.001), and (iv) MoCA (p-values<0.01), while no correlations were observed for conventional analysis (p-values=0.89, 0.14, 0.52 and 0.85, respectively).

Conclusions 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 symptomatology and progression. $$graphic_87EF1F68-967B-47A4-AB44-823D22387A9B$$

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