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Statistical limitations in proton imaging

Collins-Fekete, Charles-Antoine, Dikaios, Nikolaos, Royle, Gary and Evans, Philip Statistical limitations in proton imaging Physics in Medicine and Biology.

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Collins-Fekete+et+al_2020_Phys._Med._Biol._10.1088_1361-6560_ab7972.pdf - Accepted version Manuscript

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Abstract

Proton imaging is a promising technology for proton radiotherapy as it can be used for: 1) direct sampling of the tissue stopping power, 2) input information for multi-modality RSP reconstruction, 3) gold-standard calibration against concurrent techniques, 4) tracking motion and 5) pre-treatment positioning. However, no end-to-end characterization of the image quality (signal-to-noise ratio and spatial resolution, blurring uncertainty) against the dose has been done. This work aims to establish a model relating these characteristics and to describe their relationship with proton energy and object size. The imaging noise originates from two processes: the Coulomb scattering with the nucleus, producing a path deviation, and the energy loss straggling with electrons. The noise is found to increases with thickness crossed and, independently, decreases with decreasing energy. The scattering noise is dominant around high-gradient edge whereas the straggling noise is maximal in homogeneous regions. Image quality metrics are found to behave oppositely against energy: lower energy minimizes both the noise and the spatial resolution, with the optimal energy choice depending on the application and location in the imaged object. In conclusion, the model presented will help define an optimal usage of proton imaging to reach the promised application of this technology and establish a fair comparison with other imaging

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Collins-Fekete, Charles-Antoine
Dikaios, Nikolaosn.dikaios@surrey.ac.uk
Royle, Gary
Evans, Philipp.evans@surrey.ac.uk
Funders : EPSRC
Grant Title : EPSRC Grant
Depositing User : James Marshall
Date Deposited : 26 Feb 2020 16:59
Last Modified : 26 Feb 2020 16:59
URI: http://epubs.surrey.ac.uk/id/eprint/853837

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