Program Information
Should We Accumulate the Biological Effect Instead of Dose?
N Niebuhr123*, C Hentschke123 , R Floca123 , K Kraus123 , M Alber234 , A Pfaffenberger123 , (1) German Cancer Research Center (DKFZ), Heidelberg, Germany, (2) Heidelberg Institute for Radiation Oncology (HIRO), Heidelberg, Germany, (3) National Center for Radiation Research in Oncology (NCRO), Heidelberg, Germany (4) Heidelberg University Hospital, Heidelberg, Germany
Presentations
TU-C1-GePD-JT-3 (Tuesday, August 1, 2017) 9:30 AM - 10:00 AM Room: Joint Imaging-Therapy ePoster Theater
Purpose: Daily imaging of patients undergoing radiotherapy treatment facilitates the accumulation of delivered doses. Yet, estimating the biological effect (i.e. cell survival fraction) from the total accumulated dose introduces a systematic mathematical error since the biological impact of fractional dose variations is neglected by averaging. We investigate implications of the consistent use of the linear quadratic model (LQM) in the prediction of the local biological effect based on accumulated dose compared with the fractional effect prediction.
Methods: Two strategies are compared: S1 – dose accumulation followed by local survival estimation using the LQM. S2 – accumulation of the local biological effect from fraction doses. In a theoretical analysis, the difference between both approaches is compared for varying mean doses, dose variations, and α/β-assignment. An automated workflow using the software AVID and RTToolbox is implemented to compare both strategies on 3D patient data.
Results: From application of Jensen’s inequality it follows that S1 ≥ S2 for all voxels. Thus the standard accumulation method leads to an overestimation of the survival S1 compared with S2. Analysis shows that the overestimation is strongest for small α/β and fractional mean doses around 1-2 Gy. For amplitudes in dose variations up to 100% between fractions observable in gradient regions, the overestimation is up to 8% for S1=0.32. The difference is increased for hypofractionation scenarios. First simulations in pelvic cancer patient data agree with the theoretical results.
Conclusion: The results from this theoretical investigation suggest that the systematic overestimation of S1 compared with S2 is important for certain organ sensitivities and fractionation schemes. Pursuing the proposed approach might lead to adjustments in predicted tissue response models which are currently based on dose accumulation. The approach is being tested in patient data of various anatomical sites and fractionation schemes with a special focus on hypofractionation.
Funding Support, Disclosures, and Conflict of Interest: This work was partially funded by the Federal Ministry of Education and Research of Germany (BMBF), Grant No. 01|B13001 (SPARTA)
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