Texture and shape analysis on high and low spatial resolution emission images

Texture and shape analysis applied to positron emission tomography (PET) or single photon emission computed tomography (SPECT) imaging is a technique based on the characterization of the spatial distribution of a radio tracer using texture and shape descriptors. It has been shown in recent studies to provide functional disease related information. Applied to high resolution PET images of patients suffering from Parkinson´s disease (PD), a good correlation has been found between 3D moment invariants (3DMI) which are shape metrics and Parkinson´s disease severity. Given the wide availability of SPECT cameras in clinical environments, could texture and shape analysis provide comparable results on lower resolution images to those obtained with state-of-the-art PET cameras? The aim of the present study is to investigate the applicability and robustness of the texture and shape analysis in the specific context of images displaying localized spatial distribution of the tracer with disease induced spatial abnormalities. Applicability and robustness of the method was tested against: i) the choice of the texture and shape descriptors, ii) the image spatial resolution, iii) the image noise level and iv) the definition of the region of interest (ROI). Methods: a magnetic resonance imaging (MRI) scan to provide anatomical information for ROIs placement and a high resolution PET scan providing a dynamic sequence of [¹¹C]dihydrotetrabenazine (DTBZ) images were acquired for 13 PD patients and 6 healthy controls. To simulate the lower spatial resolutions, the reconstructed PET images were smoothed with a 3D Gaussian filter with a full width at half maximum (FWHM) ranging from 2 mm to 20 mm. As an evaluation criterion, Spearman´s correlation was calculated between texture and shape metrics and disease severity assessed either by the unified Parkinson´s disease rating scale (UPDRS) scores or by the disease duration. Results and conclusion: this study has shown that texture and shape analysis can provide relevant disease related information when applied to images of tracers displaying a localized spatial distribution with disease dependent heterogeneity and/or shape characteristics. In the specific case of Parkinson´s disease imaged with the PET tracer [¹¹C]DTBZ, we have shown that the MEAN intensity metric and the 3D moment invariant metrics are strongly correlated with disease severity and that the strength of the correlation persisted on images ranging from the highest spatial resolutions achievable by state-of-the-art PET cameras to the lowest resolutions achievable by any modern clinical SPECT camera.