@article {Asma488, author = {Evren Asma and Ravindra Manjeshwar}, title = {SPECT acquisition protocol design for local performance optimization}, volume = {52}, number = {supplement 1}, pages = {488--488}, year = {2011}, publisher = {Society of Nuclear Medicine}, abstract = {488 Objectives Our goal is to design data-driven, adaptive acquisition protocols for rotating SPECT systems in order to optimize local quantitation or detection performance around a region-of-interest (ROI). Methods Our two-step approach consists of a scout scan followed by the constrained optimization of a rapidly computable local metric over the acquisition parameters. The parameters are typically scan times at each view but can also include collimator types and dimensions. The scout scan is used for the determination of the regions-of-interest, estimation of the Fisher Information Matrix and the estimation of the lesion profile for detection tasks. Local metric examples are lesion-to-background contrast ratio for quantitation and numerical observer signal-to-noise ratios for detection. Rapidly computable theoretical expressions proportional to these metrics allow them to be optimized numerically. Optimization constraints are fixed total scan time and minimum per-view scan times equal to that spent during the scout scan. This latter constraint ensures that each view is represented and that the scout scan becomes part of the final dataset. Any scan time allocation scheme can be used to initialize the optimization and inexact optimization is acceptable provided the metric is significantly improved. Results Simulated clinical SPECT scans of cylindrical phantoms and NCAT phantoms with inserted tumors showed that at the optimal smoothing level, our approach is capable of improving local SNR approx. 70\% over a uniform scan and approx. 60\% over sensitivity-weighted scan time allocations. It achieves this goal by significantly reducing noise (34-37\% reduction) at slightly improved (approx. 10\%) contrast. Theoretically predicted SNR improvements varied between 15-72\% depending on the level of image smoothing. These predictions were matched or exceeded in the NCAT simulations. Conclusions Local imaging performance can be significantly improved by modulating the scan times at each view. This comes at the expense of highly directional noise correlations around the ROI. Research Support GE Healthcar}, issn = {0161-5505}, URL = {https://jnm.snmjournals.org/content/52/supplement_1/488}, eprint = {https://jnm.snmjournals.org/content}, journal = {Journal of Nuclear Medicine} }