@article {Shenkov291, author = {Nikolay Shenkov and Ivan Klyuzhin and Sima Fotouhi and Esmaeil Davoodi-Bojd and Hamid Soltanian-Zadeh and Arman Rahmim and Vesna Sossi}, title = {A metric to quantify DaTSCAN tracer uptake in subjects with Parkinson{\textquoteright}s disease computed without MRI-based regions of interest}, volume = {58}, number = {supplement 1}, pages = {291--291}, year = {2017}, publisher = {Society of Nuclear Medicine}, abstract = {291Objectives: Several image metrics can be used to quantify DaTSCAN binding from SPECT scans of subjects with Parkinson{\textquoteright}s disease (PD). These metrics are typically calculated on regions of interest (ROIs) that require either coregistration with MR structural images or manual placement. We propose a new approach comprised of a new metric, sum intensity (SI), evaluated over a bounding box (BB) that is automatically placed on SPECT images, thus eliminating the need of MR images or manual ROI placement. We compute the correlation of the SI values with UPDRS motor score of PD subjects. This correlation is compared with the ones obtained (i) by the same metric evaluated over MRI-defined ROIs and (ii) by the commonly used putamen binding ratio (PBR) evaluated over manually placed ROIs, as used in the standard analysis of the Parkinson{\textquoteright}s Progression Markers Initiative (PPMI) DaTSCAN data.Methods: We compute all image metrics on DaTSCAN SPECT images of 76 PD subjects from the PPMI database. SI is computed on the voxels in the more- and less-affected side of the striatum separately. SI is defined as the sum of all voxel intensities in the region that have normalized intensity larger than 2, where 1 is the reference region (occipital cortex) intensity. The following metrics are calculated: (1) SI using a BB ROI, (2) SI using a putamen MRI ROI and (3) putamen binding ratio (PBR) using manual ROI selection. For the SI-BB calculation all SPECT scans are registered to an average healthy control SPECT template. The box-shaped ROI is automatically fitted by finding the region in the image with the highest tracer activity. The box size is (84 x 52 x 24) mm^3 and it encloses the entire striatum (panel A in the figure). For the SI - MRI ROI calculation, each SPECT image is coregistered with the corresponding MR structural image. Automatic segmentation of the MR scan is used to obtain the MR-based striatum ROIs used for the metric calculation. The PBRs were obtained from the PPMI database. These metrics are calculated on manually-placed ROIs from the 8 slices with highest activity of the striatal region. The PBR is the ratio between the average tracer binding in the putamen and that in the occipital cortex. For each subject the motor scores from all clinical exams within 1 year of the imaging date are averaged to reduce clinical exam variability.Results: Scatterplots of each image metric and motor scores are shown in panel B in the figure. The SI metric achieves stronger correlation with motor score when computed on the BB ROI (Spearman rho = -0.41 for SI-BB and rho = -0.27 for SI-MRI). The SI-BB metric performs very similarly to the PBR which uses manually placed ROIs (rho = -0.43). The strongest correlation across all metrics is found when regressing imaging data from each side against the contralateral motor score components (less affected side + common) and (more affected side + common). Averaging the motor scores of each subject from clinical examinations over a pre-determined time period increases the correlation between them and imaging data by 10-15\%, indicating an intrinsic noise in the clinical assessments.Conclusion: The new SI metric computed on BB ROI performs very similarly to the reference PBR metric, in terms of correlation with motor score. The SI-BB metric might significantly simplify the quantification of SPECT DaTSCAN binding in patients with PD, since it is automatically computed and does not require anatomical guidance provided by MR images. Using averages from multiple UPDRS score assessments may be very beneficial when comparing imaging to clinical disease progression outcomes.}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/58/supplement_1/291}, eprint = {https://jnm.snmjournals.org/content}, journal = {Journal of Nuclear Medicine} }