In this project supported by the NIBIB Trailblazer award, we are investigating whether the energy attribute of scattered photons acquired by SPECT systems can be used to perform transmission-less attenuation compensation in myocardial perfusion SPECT. Conventional methods for attenuation compensation require an independent attenuation-map measurement using a transmission scan, e.g. CT scan. This leads to several issues such as increased scanning costs, radiation dose, hardware complexity, and potentially inaccurate diagnosis due to misalignment between SPECT and CT. Thus, a transmission-less attenuation compensation method would be highly significant. Our studies demonstrate that scattered photons acquired in list-mode format contain information to estimate the estimate the attenuation distribution. We then developed a physics and deep-learning-based transmission-less attenuation compensation method that only uses the SPECT emission data. Further, we developed methods that use the energy attribute of scattered photons to estimate the activity map. This provides an opportunity to improve the effective sensitivity of SPECT systems.
Z. Yu, M. A. Rahman, R. Laforest, T. H. Schindler, A. K. Jha. “A physics and learning-based transmission-less attenuation compensation method for SPECT” (link to proceedings and presentation)
A. K. Jha, E. Clarkson, M. A. Kupinski, H. H. Barrett. “Joint reconstruction of activity and attenuation map using LM SPECT emission data”, Proc. SPIE 8668 Med. Imag., 86681W, 2013 (link)