Modeling prompt gamma (PG) emission, detection and imaging in real patient anatomy using a novel Compton camera for dose verification in proton therapy

Objective. Prompt gamma (PG) imaging is a promising modality for proton dose verification. Currently, there is a lack of effective tools to investigate the entire PG imaging process in patient anatomy, from PG emission to camera detection and image reconstruction, to evaluate and optimize its efficacy for dose verification in proton therapy. Approach. To address this gap, we developed a Monte-Carlo package, POLARIS J Monte Carlo (PJ-MC), that simulates the entire PG emission and imaging workflow in patient anatomy. We utilized Geant4 classes and G4-ancillary tools, employing the DCMTK external tool with G4PhantomParameterisation to convert patient CT data into voxelized geometries. Proton beams were modeled based on medical physics commissioning data. A novel two-stage POLARIS-J3 Compton-Camera was simulated under the patient couch for recording total, double, and triple scattered PG signals. Proton maximum range calculations from the PJ-MC are compared with dose calculations from a clinical treatment planning system. The detected PG signals data in the simulation were used to reconstruct PG images using Kernel- Weighted-Back-Projection algorithm. Main results. Analysis of gamma energy distribution showed a decay pattern with clear emission lines from nuclear reactions involving oxygen, carbon, nitrogen, and calcium. Neutron-induced reactions contribute significantly less-by an order of magnitude-compared to proton-induced reactions in various tissues. Mean absolute percentage error analysis showed that PG range verification was more stable when considering the range at 80 or 50 of Dₘₐₓ, as opposed to the range at the Dₘₐₓ, where energy gating slightly improves accuracy but may reduce localization due to photon loss. Results showed that patient anatomy can impact the location of hot spot in the PG images, affecting its accuracy for localizing Bragg peak. Significance. In summary, our simulation package provides additional insights into PG emission and imaging in patient anatomy and serves as a robust tool for evaluating and optimizing PG imaging, enhancing its precision for dose verification in proton therapy.

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Publication Details

Journal
Maryland Shared Open Access Repository (USMAI Consortium)
Published
2025-06-10
DOI
https://doi.org/10.13016/m26ytk-dtgb
Primary Topic
Radiation Therapy and Dosimetry
Type
article
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article

Modeling prompt gamma (PG) emission, detection and imaging in real patient anatomy using a novel Compton camera for dose verification in proton therapy

Matthias K. Gobbert, V R Sharma, Ehsan Shakeri, J C Polf et al.
Maryland Shared Open Access Repository (USMAI Consortium)
Radiation Therapy and Dosimetry
article

Modeling prompt gamma (PG) emission, detection and imaging in real patient anatomy using a novel Compton camera for dose verification in proton therapy

Matthias K. Gobbert, V R Sharma, Ehsan Shakeri, J C Polf, Z Jiang, S W Peterson, S Mossahebi, A Chalise, L Ren
article en

Abstract

Objective. Prompt gamma (PG) imaging is a promising modality for proton dose verification. Currently, there is a lack of effective tools to investigate the entire PG imaging process in patient anatomy, from PG emission to camera detection and image reconstruction, to evaluate and optimize its efficacy for dose verification in proton therapy. Approach. To address this gap, we developed a Monte-Carlo package, POLARIS J Monte Carlo (PJ-MC), that simulates the entire PG emission and imaging workflow in patient anatomy. We utilized Geant4 classes and G4-ancillary tools, employing the DCMTK external tool with G4PhantomParameterisation to convert patient CT data into voxelized geometries. Proton beams were modeled based on medical physics commissioning data. A novel two-stage POLARIS-J3 Compton-Camera was simulated under the patient couch for recording total, double, and triple scattered PG signals. Proton maximum range calculations from the PJ-MC are compared with dose calculations from a clinical treatment planning system. The detected PG signals data in the simulation were used to reconstruct PG images using Kernel- Weighted-Back-Projection algorithm. Main results. Analysis of gamma energy distribution showed a decay pattern with clear emission lines from nuclear reactions involving oxygen, carbon, nitrogen, and calcium. Neutron-induced reactions contribute significantly less-by an order of magnitude-compared to proton-induced reactions in various tissues. Mean absolute percentage error analysis showed that PG range verification was more stable when considering the range at 80 or 50 of Dₘₐₓ, as opposed to the range at the Dₘₐₓ, where energy gating slightly improves accuracy but may reduce localization due to photon loss. Results showed that patient anatomy can impact the location of hot spot in the PG images, affecting its accuracy for localizing Bragg peak. Significance. In summary, our simulation package provides additional insights into PG emission and imaging in patient anatomy and serves as a robust tool for evaluating and optimizing PG imaging, enhancing its precision for dose verification in proton therapy.

Maryland Shared Open Access Repository (USMAI Consortium)
Openalex Percentile: Top 23%
Radiation Therapy and Dosimetry
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