Modelling SPECT auto-contouring acquisitions for (177)Lu & (131)I molecular radiotherapy using new developments in Geant4/GATE
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AbstractPurpose Monte Carlo modelling of SPECT imaging in Molecular Radiotherapy can improve activity quantification. Until now, SPECT modelling with GATE only considered circular orbit (CO) acquisitions. This cannot reproduce auto-contour acquisitions, where the detector head moves close to the patient to improve image resolution. The aim of this work is to develop and validate an auto-contouring step-and-shoot acquisition mode for GATE SPECT modelling. Methods 177Lu and 131I SPECT experimental acquisitions performed on a Siemens Symbia T2 and GE Discovery 670 gamma camera, respectively, were modelled. SPECT projections were obtained for a cylindrical Jaszczak phantom and a lung and spine phantom. Detector head parameters (radial positions and acquisition angles) were extracted from the experimental projections to model the non-circular orbit (NCO) detector motion. The gamma camera model was validated against the experimental projections obtained with the cylindrical Jaszczak (177Lu) and lung and spine phantom (131I). Then, 177Lu and 131I CO and NCO SPECT projections were simulated to validate the impact of explicit NCO modelling on simulated projections. Results Experimental and simulated SPECT images were compared using the gamma index, and were in good agreement with gamma index passing rate (GIPR) and gammaavg of 96.27%, 0.242 (177Lu) and 92.89%, 0.36 (131I). Then, simulated 177Lu and 131I CO and NCO SPECT projections were compared. The GIPR, gammaavg between the two gamma camera motions was 99.85%, 0.108 for 177Lu and 75.58%, 0.6 for 131I. Conclusion This work thereby justifies the need for auto-contouring modelling for isotopes with high septal penetration.
CitationKayal G, Chauvin M, Mora-Ramirez E, Clayton N, Vergara-Gil A, Tran-Gia J, et al. Modelling SPECT auto-contouring acquisitions for 177Lu & 131I molecular radiotherapy using new developments in Geant4/GATE. Vol. 96, Physica Medica. Elsevier BV; 2022. p. 101–13.
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