A novel approach for proton therapy pencil beam scanning patient specific quality assurance using an integrated detector system and 3D dose reconstruction
Новый подход к обеспечению качества сканирования тонким пучком при протонной терапии для конкретного пациента с использованием интегрированной детекторной системы и трёхмерной реконструкции дозы
2025-12-08
SCID: 54.1/np8xb2bk
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3D dose reconstructionCMOS pixel sensorMonte Carlo dose reconstructionTransmission Calorimeter (TC)gamma pass rate (2%/2mm)integrated detector systempencil beam scanning (PBS) patient-specific quality assurancescintillator range telescopespot-by-spot beam parameter verificationspread out Bragg Peak (SOBP)
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Abstract (AI)
Purpose Current proton beam therapy patient-specific quality assurance (PSQA) methods rely on time-intensive phantom measurements or machine-reported parameters without independent verification. This work presents an integrated detector system for phantom-less Pencil Beam Scanning (PBS) PSQA, providing independent spot-by-spot measurements of all critical beam parameters and 3D dose reconstruction. Methods The integrated detector combines three separate systems: a scintillator range telescope for range and energy measurement; a CMOS pixel sensor for spot position and size verification; and a Transmission Calorimeter (TC) for beam intensity measurements. Measured parameters feed Monte Carlo simulations to reconstruct 3D dose distributions for comparison with treatment planning predictions. Validation was performed at UCLH using single spot position spread out Bragg Peak (SOBP) and 5×5×10 spot box field configurations. Results Energy values obtained from range measurements showed strong correlation with DICOM values ( R 2 > 0.998) with an accuracy of between 2.17 mm and 1.23 mm for different beam deliveries. CMOS pixel sensor measurements succeeded for single spot fields but experienced saturation at higher intensities and incomplete coverage for the larger box field. The TC demonstrated excellent dose linearity ( R 2 = 1.000). Monte Carlo reconstructions agreed well with reference simulations for longitudinal profiles, though lateral reconstructions proved challenging with 77% gamma pass rates (2%/2mm) for the box field. Discussion This proof-of-concept demonstrates feasibility of independent beam parameter verification for PBS PSQA while maintaining patient geometry. The approach offers advantages over current methods but requires resolution of energy calibration offsets and detector limitations before clinical implementation. Future work will address these challenges and expand validation to clinical treatment plans.
Key Findings
1
An integrated detector system combining a scintillator range telescope, CMOS pixel sensor, and Transmission Calorimeter enables phantom-less PBS patient-specific QA with spot-by-spot beam parameter measurements.
2
CMOS pixel sensor successfully measured spot position and size for single-spot fields but saturated at higher intensities and had incomplete coverage for larger 5×5×10 box fields.
3
Monte Carlo 3D dose reconstructions agreed well with reference simulations longitudinally, but lateral reconstructions were limited, yielding 77% gamma pass rate (2%/2 mm) for the box field.
4
Range measurements strongly correlate with DICOM energy values (R2 > 0.998) with accuracy between 2.17 mm and 1.23 mm across different deliveries.
5
The proof-of-concept shows feasibility of independent, patient-geometry-preserving PBS PSQA but requires resolution of energy calibration offsets and detector limitations before clinical use.
6
Transmission Calorimeter demonstrated excellent dose linearity (R2 = 1.000) for beam intensity measurements.
Research Object
Integrated detector system for phantom-less pencil beam scanning (PBS) patient-specific quality assurance combining a scintillator range telescope, CMOS pixel sensor, and Transmission Calorimeter
Research Subject
Independent spot-by-spot verification of PBS beam parameters (range/energy, spot position and size, intensity) and Monte Carlo-based 3D dose reconstruction for patient-specific QA compared to treatment-planning predictions
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2025-12-08
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