Design of a compact proton beam energy modulator for imaging
Name
ProtonBeamPaper_final_preprint.pdf
Size
2.76 MB
Format
Adobe PDF
Checksum (MD5)
904fbcba80ca0a516b1acfb9bb2592cd
Author(s)
Aggarwal, Neerja
Cavuto, Matthew L.
Li, Melissa
Rodman, Nathaniel H.
Slocum, Alexander H
Jee, Kyung-Wook
Lu, Hsiao-Ming
Date Issued
March 2020
Journal
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Publisher
Elsevier BV
Citation
Aggarwal, Neerja et al. "Design of a compact proton beam energy modulator for imaging." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 955 (March 2020): 163269 © 2019 Elsevier B.V.
Version
Author's final manuscript
Abstract
Proton beam therapy is the current state of the art for irradiation of cancerous tumors near vital organs. Proton imaging is a new technology that images tumors with the same particle interaction as proton therapy, promising more accurate treatment preparation compared to traditional computerized tomography scans. A specific proton imaging technique in development at Massachusetts General Hospital requires an energy modulator that can fit inside the gantry nozzle. This work presents the design of a compact proton beam energy modulator required for such imaging applications. A combination of steel and lead wedges was used to create a balanced modulation wheel, with an axis of rotation perpendicular to the incident beam. The mechanical design also allows interchangeable disks and precise position control. The modulator design was verified by testing on a proton beam line. The final device achieved a wide range of energy modulation (21 cm water-equivalent thickness) while maintaining a constant exiting beam angular spread meeting device requirements. This compact design facilitates proton imaging to be practically incorporated into future gantry systems, which will advance proton treatment for tumors near vital organs.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.nima.2019.163269
