Improving the modelling of irradiation-induced brain activation for in vivo PET verification of proton therapy. Issue 1 (July 2018)

• Record Type: Journal Article
• Authors: Bauer, Julia; Chen, Wenjing; Nischwitz, Sebastian; Liebl, Jakob; Rieken, Stefan; Welzel, Thomas; Debus, Juergen; Parodi, Katia
• Is Part Of: Radiotherapy and oncology. Volume 128:Issue 1(2018)
• Page Start: 101
• Page End: 108
• Publication Date: 2018-07
• Subjects: Proton therapy -- PET verification -- In vivo verification -- Monte Carlo simulation -- Washout model; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2018.01.016
• Languages: English
• ISSNs: 0167-8140

Abstract

Abstract: Background and purposes: A reliable Monte Carlo prediction of proton-induced brain tissue activation used for comparison to particle therapy positron-emission-tomography (PT-PET) measurements is crucial for in vivo treatment verification. Major limitations of current approaches to overcome include the CT-based patient model and the description of activity washout due to tissue perfusion. Material and methods: Two approaches were studied to improve the activity prediction for brain irradiation: (i) a refined patient model using tissue classification based on MR information and (ii) a PT-PET data-driven refinement of washout model parameters. Improvements of the activity predictions compared to post-treatment PT-PET measurements were assessed in terms of activity profile similarity for six patients treated with a single or two almost parallel fields delivered by active proton beam scanning. Results: The refined patient model yields a generally higher similarity for most of the patients, except in highly pathological areas leading to tissue misclassification. Using washout model parameters deduced from clinical patient data could considerably improve the activity profile similarity for all patients. Conclusions: Current methods used to predict proton-induced brain tissue activation can be improved with MR-based tissue classification and data-driven washout parameters, thus providing a more reliable basis for PT-PET verification.