Distal edge determination precision for a multi-slat prompt-gamma camera: A comprehensive simulation and optimization of the detection system

Morozov, A.; Simoes, Hugo; Crespo, Paulo

doi:10.1016/j.ejmp.2021.03.028

Cited by 3 publications

(1 citation statement)

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“…Compared to 1D systems, detector efficiency associated with 2D systems is reduced by one to two orders of magnitude and ranges between 10 −5 to 10 −6 prompt gammas per proton (Table 1). 15,40,41 While the lower count statistics of these systems may perplex individual spot placement, their use in the clinic is valuable for in‐situ integral dose verification which can highlight the discrepancies between TPS and delivered dose that are simply not considered in routine patient‐specific QA that is commonly measured in homogeneous water phantoms. Further improvements in detector efficiencies beyond the values listed in Table 1 can prove useful for applications of such systems for individual spot placement verification.…”

Section: Introductionmentioning

confidence: 99%

Design and performance evaluation of a slit‐slat camera for 2D prompt gamma imaging in proton therapy monitoring: A Monte Carlo simulation study

et al. 2023

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Purpose We investigated the design of a prompt gamma camera for real‐time dose delivery verification and the partial mitigation of range uncertainties. Methods A slit slat (SS) camera was optimized using the trade‐off between the signal‐to‐noise ratio and spatial resolution. Then, using the GATE Monte Carlo package, the camera performances were estimated by means of target shifts, beam position quantification, changing the camera distance from the beam, and air cavity inserting. A homogeneous PMMA phantom and the air gaps induced PMMA phantom were used. The air gaps ranged from 5 mm to 30 mm by 5 mm increments were positioned in the middle of the beam range. To reduce the simulation time, phase space scoring was used. The batch method with five realizations was used for stochastic error calculations. Results The system's detection efficiency was 1.1×10−4PGsEmitted0.33emPGs(1.8×10−5$1.1 \times {10}^{-4}\frac{{\rm PGs}}{{\rm Emitted}\ {\rm PGs}}\ (1.8 \times {10}^{-5}$ PGs/proton) for a 10 × 20 cm2 detector (source‐to‐collimator distance = 15.0 cm). Axial and transaxial resolutions were 23 mm and 18 mm, respectively. The SS camera estimated the range as 69.0 ± 3.4 (relative stochastic error 1‐sigma is 5%) and 67.6 ± 1.8 mm (2.6%) for the real range of 67.0 mm for 107 and 108 protons of 100 MeV, respectively. Considering 160 MeV, these values are 155.5 ± 3.1 (2%) and 152.2 ± 2.0 mm (1.3%) for the real range of 152.0 mm for 107 and 108 protons, respectively. Considering phantom shift, for a 100 MeV beam, the precision of the quantification (1‐sigma) in the axial and lateral phantom shift estimation is 2.6 mm and 1 mm, respectively. Accordingly, the axial and lateral quantification precisions were 1.3 mm and 1 mm for a 160 MeV beam, respectively. Furthermore, the quantification of an air gap formulated as gapdet=0.98×gapreal${{\rm gap}}_{det}=0.98 \times {{\rm gap}}_{{\rm real}}$, where gapdet${{\rm gap}}_{det}$ and gapreal are the estimated and real air gap, respectively. The precision of the air gap quantification is 1.6 mm (1 sigma). Moreover, 2D PG images show the trajectory of the proton beam through the phantom. Conclusion The proposed slit‐slat imaging systems can potentially provide a real‐time, in‐vivo, and non‐invasive treatment monitoring method for proton therapy.

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Section: Introductionmentioning

confidence: 99%

Design and performance evaluation of a slit‐slat camera for 2D prompt gamma imaging in proton therapy monitoring: A Monte Carlo simulation study

et al. 2023

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Development of focusing multi-knife-edge camera for proton beam range verification: A Monte Carlo study

Chiang,

Wang,

Liu

et al. 2024

Radiation Physics and Chemistry

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Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential

et al. 2023

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Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρs) within patients. Currently, the ρs distribution in a patient is derived from a single- energy CT (SECT) scan acquired for treatment planning by converting CT number (μHU) of each voxel to ρs using a Hounsfield look-up table (HLUT), also known as the CT calibration curve. μHU and ρs share a linear relationship with electron density but fundamentally differ in additional physical properties, such as photon attenuation cross section or effective atomic number and stopping number or mean excitation energy, respectively. Due to this degeneracy, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) for ρs prediction has been shown to be effective in reducing the uncertainty in ρs estimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy of ρs estimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: 1) a comprehensive review of the existing DECT/MECT methods for ρs estimation with their respective strengths and weaknesses; 2) a general review of uncertainties associated with DECT/MECT methods; 3) a general review of different aspects related to clinical implementation of DECT/MECT methods; 4) other potential advanced DECT/MECT applications beyond ρs estimation.

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Distal edge determination precision for a multi-slat prompt-gamma camera: A comprehensive simulation and optimization of the detection system

Cited by 3 publications

References 36 publications

Design and performance evaluation of a slit‐slat camera for 2D prompt gamma imaging in proton therapy monitoring: A Monte Carlo simulation study

Design and performance evaluation of a slit‐slat camera for 2D prompt gamma imaging in proton therapy monitoring: A Monte Carlo simulation study

Development of focusing multi-knife-edge camera for proton beam range verification: A Monte Carlo study

Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential

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