A method for acquiring random range uncertainty probability distributions in proton therapy.

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Holloway, SM 
Holloway, MD 
Thomas, SJ 

In treatment planning we depend upon accurate knowledge of geometric and range uncertainties. If the uncertainty model is inaccurate then the plan will produce under-dosing of the target and/or overdosing of OAR. We aim to provide a method for which centre and site-specific population range uncertainty due to inter-fraction motion can be quantified to improve the uncertainty model in proton treatment planning. Daily volumetric MVCT data from previously treated radiotherapy patients has been used to investigate inter-fraction changes to water equivalent path-length (WEPL). Daily image-guidance scans were carried out for each patient and corrected for changes in CTV position (using rigid transformations). An effective depth algorithm was used to determine residual range changes, after corrections had been applied, throughout the treatment by comparing WEPL within the CTV at each fraction for several beam angles. As a proof of principle this method was used to quantify uncertainties for inter-fraction range changes for a sample of head and neck patients of [Formula: see text] mm, [Formula: see text] mm and overall [Formula: see text] mm. For prostate [Formula: see text] mm, [Formula: see text] mm and overall [Formula: see text] mm. The choice of beam angle for head and neck did not affect the inter-fraction range error significantly; however this was not the same for prostate. Greater range changes were seen using a lateral beam compared to an anterior beam for prostate due to relative motion of the prostate and femoral heads. A method has been developed to quantify population range changes due to inter-fraction motion that can be adapted for the clinic. The results of this work highlight the importance of robust planning and analysis in proton therapy. Such information could be used in robust optimisation algorithms or treatment plan robustness analysis. Such knowledge will aid in establishing beam start conditions at planning and for establishing adaptive planning protocols.

Algorithms, Head and Neck Neoplasms, Humans, Male, Movement, Organs at Risk, Prostatic Neoplasms, Proton Therapy, Radiotherapy Dosage, Radiotherapy Planning, Computer-Assisted, Uncertainty
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Phys Med Biol
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IOP Publishing
This work was funded by a Medical Research Council Studentship to the University of Cambridge (G1000384). Dr S. Holloway is currently supported by a Cancer Research UK Centres Network Accelerator Award Grant (A21993) to the ART-NET consortium.