A role for biological optimization within the current treatment planning paradigm
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Updated: Jun 18, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
Published on: February 6, 2019
1Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710, USA. shiva.das@duke.edu
Purpose:
Biological optimization using complication probability models in intensity modulated radiotherapy (IMRT) planning has tremendous potential for reducing radiation-induced toxicity. Nevertheless, biological optimization is almost never clinically utilized, probably because of clinician confidence in, and familiarity with, physical dose-volume constraints. The method proposed here incorporates biological optimization after dose-volume constrained optimization so as to improve the dose distribution without detrimentally affecting the important reductions achieved by dose-volume optimization (DVO).
Methods:
Following DVO, the clinician/planner first identifies "fixed points" on the target and organ-at-risk (OAR) dose-volume histograms. These points represent important DVO plan qualities that are not to be violated within a specified tolerance. Biological optimization then maximally reduces a biological metric (illustrated with equivalent uniform dose (EUD) in this work) while keeping the fixed dose-volume points within tolerance limits, as follows. Incremental fluence adjustments are computed and applied to incrementally reduce the OAR EUDs while approximately maintaining the fixed points. This process of incremental fluence adjustment is iterated until the fixed points exceed tolerance. At this juncture, remedial fluence adjustments are computed and iteratively applied to bring the fixed points back within tolerance, without increasing OAR EUDs. This process of EUD reduction followed by fixed-point correction is repeated until no further EUD reduction is possible. The method is demonstrated in the context of a prostate cancer case and olfactory neuroblastoma case. The efficacy of EUD reduction after DVO is evaluated by comparison to an optimizer with purely biological (EUD) OAR objectives.
Results:
For both cases, EUD reduction after DVO additionally reduced doses, especially high doses, to normal organs. For the prostate case, bladder/rectum EUDs were reduced (after DVO) by 5.0%/3.9%, and highest doses were reduced by 4.6%/7.8%. The optimization with purely biological OAR objectives achieved bladder/rectal EUDs that were 7.4%/3.1% lower than from DVO, but only reduced highest doses by 1.4%/0.7%. In the olfactory neuroblastoma case, the target was closely surrounded by the eyes, optic nerves, chiasm, and brainstem. In one of the scenarios studied, the eyes, optic nerves, and chiasm were targeted for EUD reduction after DVO. EUD to the left eye, right eye, left optic nerve, right optic nerve, and chiasm were reduced by 7.0%, 5.7%, 4.7%, 4.1%, and 0.6%, respectively, and highest doses were reduced by 16.5%, 11.0%, 5.1%, 3.8%, and 1.5%, respectively. The optimization with purely biological OAR objectives was less effective for the eyes and optics nerves. EUDs for the left eye/right eye/left optic nerve/right optic nerve/chiasm were lower than that from DVO by 0.4%/2.7%/4.0%/2.8%/15.6% and highest doses were lower by 4.6%/1.4%/2.4%/6.4%/7.1% (but purely biological optimization was better overall for the OARs not targeted for EUD reduction).
Conclusions:
Incorporating biological optimization after dose-volume constrained optimization can further reduce biological metrics, while preserving the important dose reductions achieved by dose-volume constrained optimization. Thus, biological optimization may be accommodated within the framework of current IMRT planning clinical expectations.
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