Imaging simulation of "Scratch-PET": an intraoperative PET with a hand-held detector

• Published in: 2023 IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD) p. 1
• Main Authors: Ishikawa, T., Iwao, Y., Akamatsu, G., Takyu, S., Tashima, H., Okamoto, T., Yamaya, T., Haneishi, H.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04.11.2023
• Subjects: Geometry; Phantoms; Semiconductor detectors; Semiconductor device measurement; Sensitivity; Surgery; Visualization
• ISSN: 2577-0829
• DOI: 10.1109/NSSMICRTSD49126.2023.10338607

In cancer surgery, excessive resection of biological tissues leads to the functional loss of the organ and the increase of physical burden for patients. However, it is difficult to identify precise resection regions intraoperatively. PET is often used for cancer diagnosis, but its intraoperative use has been prevented; massive equipment like a detector ring may interfere with the surgical process. Therefore, we aimed at developing an intraoperative PET system with a hand-held probe-type detector, called "Scratch-PET." The system allows the surgeon to scan a target region using a hand-held detector. PET images appear like on a scratch card. In this work, we proposed an image reconstruction framework to achieve real-time image reconstruction even under the condition that the geometry changes by moving a hand-held detector. We used GPU-based list-mode time-of-flight (TOF) row-action maximum likelihood algorithm (RAMLA) reconstruction, and the reconstructed image is displayed every 10 s. We also implemented a fast calculation method for the global sensitivity image that is required in the Scratch-PET image reconstruction. We demonstrated the feasibility of the proposed method through computer simulation. We modeled the small geometry of Scratch-PET and simulated a 2 min measurement of a tumor phantom with a practical activity concentration. The tumor phantom consisted of the elliptical background and four spherical sources of 10, 8, 6 and 4 mm diameter, each with 1:8 contrast. As a result, we were able to visualize a spherical source of 6mm diameter. Our proposed image reconstruction framework ran without delay, which supported the feasibility of the Scratch-PET concept.