Speaker
Description
High spatial resolution is essential to successfully resolve small structures in the brain and to enable imaging of neurological pathways at the onset of diseases. A key challenge with ultra-high-resolution PET scanners is the significant degradation of resolution that occurs beyond the central area of the field-of-view (FOV). The Ultra-High-Resolution (UHR) Brain PET scanner was designed with short (12 mm) LYSO crystals to mitigate the parallax error off the FOV center, but at the expense of reduced sensitivity [1]. To address these limitations, the LabPET II based technology platform of the UHR was upgraded to implement depth-of-interaction (DOI) measurement using longer (15 mm) dual LGSO phoswich detectors in the Scanner Approaching in Vivo Autoradiographic Neuro Tomography (SAVANT). Simulation results indicate an estimated gain in sensitivity of 40%, while maintaining the resolution below 2 mm FWHM at the edge of the brain. For DOI determination, the crystal identification between slow (43-48 ns decay time) and fast (30-35 ns decay time) LGSO scintillators uses a model-based dual-threshold time-over-threshold (ToT) discrimination technique that is currently achieving better than 70% accuracy. The 6.5/8.5 mm length ratio of the top slow and bottom fast LGSO scintillators resulted from trade-offs between off-center spatial resolution degradation and balanced coincidence detection efficiency of the two crystal layers. We report the first experimental results obtained using the partially assembled scanner (182 mm axial extent), which demonstrate the improvement in resolution uniformity across the radial FOV achieved using this simple DOI discrimination scheme. Point source and phantom measurements taken at various radial positions within the FOV effectively demonstrate the gain in spatial resolution compared to non-DOI measurements, though not reaching the resolution predicted by simulation. It is anticipated that further refinement of the crystal identification process, potentially using AI, will yield the forecasted benefits from simulation. Preliminary results for imaging the human brain will be presented.
[1] E. Gaudin, M. Toussaint, C. Thibaudeau, M. Paille, R. Fontaine, and R. Lecomte, “Performance Simulation of an Ultrahigh Resolution Brain PET Scanner Using 1.2-mm Pixel Detectors,” IEEE Trans. Radiat. Plasma Med. Sci., vol. 3, no. 3, pp. 334–342, May 2019, doi: 10.1109/TRPMS.2018.2877511.
| Track | PSMR |
|---|---|
| Presentation type | Oral |