Promising Outcomes of Original Grant:
We hypothesized in the original funded grant that evaluation of texture and variability, beyond conventional averaging of voxel (element of space) intensities within a region of interest in dopamine transporter (DAT) SPECT (brain imaging technique) images, could provide improved correlations with clinical measures, such as the unified Parkinson's disease (PD) rating scale score or cognitive score. Our results supported this hypothesis, thus motivating the application of such texture analysis framework for improved tracking of progression in PD.
Objectives for Supplemental Investigation:
In the present work, we build on past efforts by further developing and implementing texture analysis to positron emission tomography (brain imaging technique) data
(AV-133) within the Parkinson's Progression Markers Initiative dataset, applying texture metrics this to longitudinal data to truly assess ability to track progression of disease on an individualized basis and analyzing genomic variability within the population to link to features extracted from the images. These studies are a natural extension of our past work, which focused on cross-sectional baseline SPECT images.
Importance of This Research for the Development of a New PD Therapy:
The successful completion of this study could have important clinical implications. Enhanced sensitivity to small neuroanatomic changes is expected to provide novel insights into the relationship between changes in dopamine and PD symptoms, while extending the clinical usefulness of imaging techniques. In addition to aiding in the identification of early disease, these techniques, if successful, will be applied to images from individuals at increased risk of PD in an attempt to discern patterns that might be involved in disease development and to assess the impact of novel disease-modifying therapies.