Coverage-based treatment planning: optimizing the IMRT PTV to meet a CTV coverage criterion.
This work demonstrates an iterative approach-referred to as coverage-based treatment planning-designed to produce treatment plans that ensure target coverage for a specified percentage of setup errors. In this approach the clinical target volume to planning target volume (CTV-to-PTV) margin is iteratively adjusted until the specified CTV coverage is achieved. The advantage of this approach is that it automatically compensates for the dosimetric margin around the CTV, i.e., the extra margin that is created when the dose distribution extends beyond the PTV. When applied to 27 prostate plans, this approach reduced the average CTV-to-PTV margin from 5 to 2.8 mm. This reduction in PTV size produced a corresponding decrease in the volume of normal tissue receiving high dose. The total volume of tissue receiving > or =65 Gy was reduced on average by 19.3% or about 48 cc. Individual reductions varied from 8.7% to 28.6%. The volume of bladder receiving > or =60 Gy was reduced on average by 5.6% (reductions for individuals varied from 1.7% to 10.6%), and the volume of periprostatic rectum receiving > or =65 Gy was reduced on average by 4.9% (reductions for individuals varied from 0.9% to 12.3%). The iterative method proposed here represents a step toward a probabilistic treatment planning algorithm which can generate dose distributions (i.e., treated volumes) that closely approximate a specified level of coverage in the presence of geometric uncertainties. The general principles of coverage-based treatment planning are applicable to arbitrary treatment sites and delivery techniques. Importantly, observed deviations between coverage implied by specified CTV-to-PTV margins and coverage achieved by a given treatment plan imply a generic need to perform coverage probability analysis on a per-plan basis to ensure that the desired level of coverage is achieved.
Gordon
J J
JJ
Department of Radiation Oncology, Virginia Commonwealth University, P.O. Box 980058, Richmond, Virginia 23298, USA. jgordon@mcvh-vcu.edu
Siebers
J V
JV
D000465:Algorithms; D055592:Biophysical Phenomena; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000473:pathology / Q000532:radiotherapy; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods* / Q000706:statistics & numerical data