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Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy

J Schuemann

J Schuemann*, D Giantsoudi , C Grassberger , H Paganetti, Massachusetts General Hospital, Boston, MA


SU-E-T-135 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

To estimate the clinical relevance of approximations made in analytical dose calculation methods (ADCs) used for treatment planning on tumor coverage and tumor control probability (TCP) in proton therapy.

We compared dose distributions planned with ADC to delivered dose distributions (as determined by TOPAS Monte Carlo (MC) simulations). We investigated 10 patients per site for 5 treatment sites (head-and-neck, lung, breast, prostate, liver). We evaluated differences between the two dose distributions analyzing dosimetric indices based on the dose-volume-histograms, the γ-index and the TCP. The normal tissue complication probability (NTCP) was estimated for the bladder and anterior rectum for the prostate patients.

We find that the target doses are overestimated by the ADC by 1-2% on average for all patients considered. All dosimetric indices (the mean dose, D95, D50 and D02, the dose values covering 95%, 50% and 2% of the target volume, respectively) are predicted within 5% of the delivered dose. A γ-index with a 3%/3mm criteria had a passing rate for target volumes above 96% for all patients. The TCP predicted by the two algorithms was up to 2%, 2.5%, 6%, 6.5%, and 11% for liver and breast, prostate, head-and-neck and lung patients, respectively. Differences in NTCP for anterior-rectum and bladder for prostate patients were less than 3%.

We show that ADC provide adequate dose distributions for most patients, however, they can result in underdosage of the target by as much as 5%. The TCP was found to be up to 11% lower than predicted. Advanced dose-calculation methods like MC simulations may be necessary in proton therapy to ensure target coverage for heterogeneous patient geometries, in clinical trials comparing proton therapy to conventional radiotherapy to avoid biases due to systematic discrepancies in calculated dose distributions, and, if tighter range margins are considered.

Funding Support, Disclosures, and Conflict of Interest: Fully funded by NIH grants.

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