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 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.

Scanning rats on the high resolution research tomograph (HRRT): a comparison study with a dedicated micro-PET.

PURPOSE: The Siemens ECAT high resolution research tomograph (HRRT) is a dedicated human brain PET camera with a 6% absolute sensitivity and a (2.3 mm)(3) spatial resolution, improving to (1.8 mm)(3) when point spread function (PSF) modeling algorithms are used. These values are very close to those of dedicated small animal PET cameras such as the Siemens microPET FOCUS 120 (F120). The larger axial and transaxial field of view of the HRRT compared to the F120 allows, in principle, for simultaneous imaging of several rodents thus potentially reducing scanning costs and time. This study investigates the feasibility of using the HRRT for quantitative small animal brain studies. METHODS: We compare, in terms of magnitude, reproducibility, and asymmetry, the nondisplaceable tissue input binding potentials (BP(ND)) in the striata obtained from [(11)C]methylphenidate scans of the same rats imaged on both the F120 and the HRRT. The animal studies are complemented by a phantom study aimed at investigating noise properties relevant to the size of typical regions of interest used in rat brain image analysis. RESULTS: (i) The BP(ND) values obtained from HRRT data are lower than those obtained on the F120 by 38% when PSF modeling is not used, while they are 7% higher with PSF modeling. (ii) The within animal reproducibility on the HRRT is 18% without PSF modeling, worse than the 6% reproducibility on the F120, and is even further degraded to a value of 27% with the use of PSF modeling. (iii) The asymmetry between the left and right striatum in healthy rats worsens from 4.7% in the F120 images to 7.8% in the HRRT images reconstructed without PSF modeling, and is even worse with a value of 14.8% when PSF modeling is used. (iv) Overshooting artifacts and clumpiness in the noise structure of the HRRT images reconstructed with PSF modeling are clearly visible. CONCLUSIONS: The spatial resolution achieved on the HRRT without the use of resolution recovery techniques is not sufficient to allow for reliable quantitative small animal brain imaging. While PSF modeling in the reconstruction of the HRRT images in principle improves the resolution close to the level of the F120, it also introduces small scale nonuniformity artifacts and overshooting artifacts which preclude reliable quantitative small animal brain imaging on the HRRT.