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Real-time marker-less tumor tracking with TOF PET: in silico feasibility study.

Xinyi ChengDongxu YangYuncheng ZhongYiping Shao
Published in: Physics in medicine and biology (2022)
Purpose. Although positron emission tomography (PET) can provide a functional image of static tumors for RT guidance, it's conventionally very challenging for PET to track a moving tumor in real-time with a multiple frame/s sampling rate. In this study, we developed a novel method to enable PET based three-dimension (3D) real-time marker-less tumor tracking (RMTT) and demonstrated its feasibility with a simulation study. Methods. For each line-of-response (LOR) acquired, its positron-electron annihilation position is calculated based on the time difference between the two gamma interactions detected by the TOF PET detectors. The accumulation of these annihilation positions from data acquired within a single sampling frame forms a coarsely measured 3D distribution of positron-emitter radiotracer uptakes of the lung tumor and other organs and tissues (background). With clinically relevant tumor size and sufficient differential radiotracer uptake concentrations between the tumor and background, the high-uptake tumor can be differentiated from the surrounding low-uptake background in the measured distribution of radiotracer uptakes. With a volume-of-interest (VOI) that closely encloses the tumor, the count-weighted centroid of the annihilation positions within the VOI can be calculated as the tumor position. All these data processes can be conducted online. The feasibility of the new method was investigated with a simulated cardiac-torso digital phantom and stationary dual-panel TOF PET detectors to track a 28 mm diameter lung tumor with a 4:1 tumor-to-background 18 FDG activity concentration ratio. Results. The initial study shows TOF PET based RMTT can achieve <2.0 mm tumor tracking accuracy with 5 frame s -1 sampling rate under the simulated conditions. In comparison, using reconstructed PET images to track a similar size tumor would require >30 s acquisition time to achieve the same tracking accuracy. Conclusion. With the demonstrated feasibility, the new method may enable TOF PET based RMTT for practical RT applications.
Keyphrases
  • positron emission tomography
  • computed tomography
  • pet imaging
  • pet ct
  • ms ms
  • mass spectrometry
  • heart failure
  • deep learning
  • gene expression
  • social media
  • machine learning
  • molecular dynamics simulations