Josh W.H. Lindsay , Simon J.P. Meara , Matthew Clarke , Matthew Lowe , David Lines , Marianne C. Aznar , Marcel van Herk
{"title":"Cone-beam computed tomography reconstruction for a commercial proton beam therapy system","authors":"Josh W.H. Lindsay , Simon J.P. Meara , Matthew Clarke , Matthew Lowe , David Lines , Marianne C. Aznar , Marcel van Herk","doi":"10.1016/j.phro.2025.100745","DOIUrl":null,"url":null,"abstract":"<div><h3>Background & Purpose:</h3><div>Cone-beam computed tomography (CBCT) images are used in image-guided radiotherapy to track anatomical changes throughout treatment and to set up patients to ensure accurate delivery of therapeutic radiation at each treatment session. An offline method of CBCT reconstruction workflow, operating on 2D projection images and specific to the imaging system in question, is needed for many image optimisation studies. Here we present a methodology to reconstruct CBCT images from these data for a commercial proton beam therapy machine, accounting for the variation in exposure and beam hardening from filtration due to gantry rotation during CBCT acquisition.</div></div><div><h3>Materials & Methods:</h3><div>Projection data of solid water phantoms were acquired to model bow-tie filter motion and beam hardening effects. Projection data and system CBCT reconstructions of a Catphan504 phantom were acquired for validation of the method, as well as a retrospectively accessed patient image. The presented workflow was assessed against the clinical reconstructions using uniformity, signal-to-noise-ratio, and contrast-to-noise-ratio measured in the phantom images.</div></div><div><h3>Results:</h3><div>The offline workflow eliminated crescent artefacts due to variable exposure and beam hardening in phantom and patient images. Signal-to-noise and contrast-to-noise ratios were similar compared to system reconstructions, although with slight differences thought to be due to interplay effects in the bow-tie filter.</div></div><div><h3>Conclusion:</h3><div>A workflow was developed to emulate the CBCT reconstruction process for a commercial proton therapy machine, providing a useful tool for optimised acquisition parameters and novel reconstruction processes using this system.</div></div>","PeriodicalId":36850,"journal":{"name":"Physics and Imaging in Radiation Oncology","volume":"34 ","pages":"Article 100745"},"PeriodicalIF":3.4000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics and Imaging in Radiation Oncology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405631625000508","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background & Purpose:
Cone-beam computed tomography (CBCT) images are used in image-guided radiotherapy to track anatomical changes throughout treatment and to set up patients to ensure accurate delivery of therapeutic radiation at each treatment session. An offline method of CBCT reconstruction workflow, operating on 2D projection images and specific to the imaging system in question, is needed for many image optimisation studies. Here we present a methodology to reconstruct CBCT images from these data for a commercial proton beam therapy machine, accounting for the variation in exposure and beam hardening from filtration due to gantry rotation during CBCT acquisition.
Materials & Methods:
Projection data of solid water phantoms were acquired to model bow-tie filter motion and beam hardening effects. Projection data and system CBCT reconstructions of a Catphan504 phantom were acquired for validation of the method, as well as a retrospectively accessed patient image. The presented workflow was assessed against the clinical reconstructions using uniformity, signal-to-noise-ratio, and contrast-to-noise-ratio measured in the phantom images.
Results:
The offline workflow eliminated crescent artefacts due to variable exposure and beam hardening in phantom and patient images. Signal-to-noise and contrast-to-noise ratios were similar compared to system reconstructions, although with slight differences thought to be due to interplay effects in the bow-tie filter.
Conclusion:
A workflow was developed to emulate the CBCT reconstruction process for a commercial proton therapy machine, providing a useful tool for optimised acquisition parameters and novel reconstruction processes using this system.