Monte Carlo Simulation of High Energy Photon Imaging

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DESCRIPTION (provided by applicant): The broad long-term objective of this work is to substantially improve imaging, quantification and dosimetry of high-energy single-photon emitters imaged with gamma cameras. A specific long-term objective is to verify the hypothesis of a highly significant correlation between tumor regression and calculated tumor radiation absorbed dose in two radionuclide therapies 1) 1-131 anti-B1 radioimmunotherapy (RIT), and 2) 1-131 metaiodobenzylguanidine (MIBG) therapy. At our institution, a phase II 1-131 labeled anti-B1 RIT trial for follicular lymphoma, showed a 97% response rate and a 63% complete response rate. The success of 1-131 RIT and MIBG therapy has renewed interest in 1-131 imaging for accurate internal dose estimates. During the previous period a Monte Carlo code for modeling single-photon imaging of I-131 was optimized and validated. Simulation studies demonstrated the current limitations to accurate I-131 activity quantification using single photon computed tomography (SPECT). The focus for the next period will be on using Monte Carlo to develop highly patient-specific methods that will significantly improve the two main steps in tumor/organ dosimetry: activity quantification and absorbed dose calculation. The patient-specific methods will be implemented by integrating information from SPECT and co-registered CT. Specifically we propose to implement 1) patient-specific partial volume correction; 2) a Monte Carlo based forward projector, which includes patient-specific scatter; 3) 3-D patient-specific dose estimation. In addition, we will continue evaluation of a 3D OSEM reconstruction, which includes detector response and we will generate data for a multi-center evaluation of conjugate-view activity quantification methods. The work will culminate with phantom studies that establish the optimum methods for 1-131 SPECT quantification and dose estimation and with the application of the methods to existing RIT patient data to possibly reveal a statistically significant relationship between dose and tumor volume reduction. In addition, we will attempt to correlate newly available parameters from the 3-D dosimetry, such as dose non-uniformity and minimum dose, with tumor volume reduction. A strong dose-response relationship has not yet been demonstrated in any 1-131 RIT clinical study possibly due to poor dose estimation. Here we propose to combine and expand many tools to significantly improve the estimate and make advances towards individualized treatment planning.