title: Algorithm and simulation for real-time positron emission based tumor tracking using a linear fiducial marker.
abstract: The effectiveness of radiotherapy in cancer treatment remains significantly limited by the accuracy of tumor dose delivery. The ideal solution lies in real-time localization of patient tumors during therapy; one such method is by tracking implanted low-activity positron emitters using two pairs of orthogonally placed gamma-ray detectors. Prior studies have examined multiple point sources, which have potential patient complications during implantation. A linear source geometry is proposed as a less invasive alternative, with potential higher-precision tracking. A source localization algorithm has been devised using cost-function minimization of the source position estimate relative to annihilation gamma coincidence lines. The algorithm was tested via Monte Carlo simulation methods using a Geant4 application for emission tomography (GATE) package for a source of length of 2.00 cm and width of 0.1 mm. The midpoint of the linear marker was located within submillimeter accuracy at 200 coincidence events and the orientation of the source determined with less than 5 degrees (0.087 rad) angular deviation at 300 events. At an optimal event count of 700, tracking had mean midpoint error of 0.48 +/- 0.26 mm and mean angular deviation of 0.041 +/- 0.023 rad (1.4 degrees +/- 0.8 degree). The source and tracking algorithm may prove effective for future clinical implementation in radiotherapy treatment.
authors: Department of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada.
authors: Nathan W
authors: NW
authors: Churchill
authors: Marc
authors: M
authors: Chamberland
authors: Tong
authors: T
authors: Xu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003199:Computer Systems; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016014:Linear Models; D008954:Models, Biological; D009068:Movement; D009369:Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity