Literature DB >> 26520750

Comparison of organ-at-risk sparing and plan robustness for spot-scanning proton therapy and volumetric modulated arc photon therapy in head-and-neck cancer.

Danique L J Barten1, Jim P Tol1, Max Dahele1, Ben J Slotman1, Wilko F A R Verbakel1.   

Abstract

PURPOSE: Proton radiotherapy for head-and-neck cancer (HNC) aims to improve organ-at-risk (OAR) sparing over photon radiotherapy. However, it may be less robust for setup and range uncertainties. The authors investigated OAR sparing and plan robustness for spot-scanning proton planning techniques and compared these with volumetric modulated arc therapy (VMAT) photon plans.
METHODS: Ten HNC patients were replanned using two arc VMAT (RapidArc) and spot-scanning proton techniques. OARs to be spared included the contra- and ipsilateral parotid and submandibular glands and individual swallowing muscles. Proton plans were made using Multifield Optimization (MFO, using three, five, and seven fields) and Single-field Optimization (SFO, using three fields). OAR sparing was evaluated using mean dose to composite salivary glands (CompSal) and composite swallowing muscles (CompSwal). Plan robustness was determined for setup and range uncertainties (±3 mm for setup, ±3% HU) evaluating V95% and V107% for clinical target volumes.
RESULTS: Averaged over all patients CompSal/CompSwal mean doses were lower for the three-field MFO plans (14.6/16.4 Gy) compared to the three-field SFO plans (20.0/23.7 Gy) and VMAT plans (23.0/25.3 Gy). Using more than three fields resulted in differences in OAR sparing of less than 1.5 Gy between plans. SFO plans were significantly more robust than MFO plans. VMAT plans were the most robust.
CONCLUSIONS: MFO plans had improved OAR sparing but were less robust than SFO and VMAT plans, while SFO plans were more robust than MFO plans but resulted in less OAR sparing. Robustness of the MFO plans did not increase with more fields.

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Year:  2015        PMID: 26520750     DOI: 10.1118/1.4933245

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  13 in total

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10.  Can knowledge-based DVH predictions be used for automated, individualized quality assurance of radiotherapy treatment plans?

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