Szczegóły publikacji
Opis bibliograficzny
Data acquisition system for radiation dose distribution monitoring in photon radiotherapy / Bartosz MINDUR, Tomasz FIUTOWSKI, Jakub HAJDUGA, Damian Kabat, Kamila KALECIŃSKA, Maciej KOPEĆ, Stefan KOPERNY, Dagmara KULIG, Bartłomiej ŁACH, Jakub MOROŃ, Bartłomiej RACHWAŁ, Wiktor Szewczyk, Piotr WIĄCEK, Tomasz SZUMLAK // Journal of Instrumentation [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 1748-0221. — 2025 — vol. 20 iss. 6 art. no. P06040, s. [2], 1-30. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 30, Abstr. — Publikacja dostępna online od: 2025-06-24
Autorzy (14)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 161897 |
|---|---|
| Data dodania do BaDAP | 2025-09-04 |
| Tekst źródłowy | URL |
| DOI | 10.1088/1748-0221/20/06/P06040 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Instrumentation |
Abstract
Recent advancements in photon radiation therapy have transformed cancer treatment planning through the integration of multimodal imaging and machine learning-enhanced simulation software. Despite these improvements, a critical challenge remains in verifying the actual radiation dose delivered to patients during treatment, as current systems rely solely on machine-level monitoring rather than direct patient-level measurement. To address this gap, we present a novel scintillator-based detection system designed for real-time dosimetry. One of the main components of the system is a high-precision data acquisition platform enabling adaptive measurement geometries tailored to specific procedural scenarios. At the core of the system lies a modular DAQ architecture based on slice, featuring a 64-channel photomultiplier, front-end electronics with carefully selected ASIC for signal processing, and FPGA-based module for communication synchronized via a precision timing backbone. The system achieves remarkable performance metrics, including sustained data throughput of nearly 8 Gbit s-1, sub-microsecond synchronization across all channels, and accurate response to variable light intensities. This platform may bridge the critical gap between treatment planning and real-time dose delivery verification. The system's reconfigurable design and reliability proven in controlled laser tests, position it as a promising solution for clinical implementation. Future work will focus on integration with the medical linear accelerators and the development of machine learning algorithms for real-time dose adaptation, ultimately enhancing treatment accuracy and patient safety in radiation oncology.
