This work ͑i͒ proposes a probabilistic treatment planning framework, termed coverage optimized planning ͑COP͒, based on dose coverage histogram ͑DCH͒ criteria; ͑ii͒ describes a concrete proofof-concept implementation of COP within the PINNACLE treatment planning system; and ͑iii͒ for a set of 28 prostate anatomies, compares COP plans generated with this implementation to traditional PTV-based plans generated with planning criteria approximating those in the high dose arm of the Radiation Therapy Oncology Group 0126 protocol. Let D v denote the dose delivered to fractional volume v of a structure. In conventional intensity modulated radiation therapy planning, D v has a unique value derived from the static ͑planned͒ dose distribution. In the presence of geometric uncertainties ͑e.g., setup errors͒ D v assumes a range of values. The DCH is the complementary cumulative distribution function of D v . DCHs are similar to dose volume histograms ͑DVHs͒. Whereas a DVH plots volume v versus dose D, a DCH plots coverage probability Q versus D. For a given patient, Q is the probability ͑i.e., percentage of geometric uncertainties͒ for which the realized value of D v exceeds D. PTV-based treatment plans can be converted to COP plans by replacing DVH optimization criteria with corresponding DCH criteria. In this approach, PTVs and planning organ at risk volumes are discarded, and DCH criteria are instead applied directly to clinical target volumes ͑CTVs͒ or organs at risk ͑OARs͒. Plans are optimized using a similar strategy as for DVH criteria. The specific implementation is described. COP was found to produce better plans than standard PTV-based plans, in the following sense. While target OAR dose tradeoff curves were equivalent to those for PTV-based plans, COP plans were able to exploit slack in OAR doses, i.e., cases where OAR doses were below their optimization limits, to increase target coverage. Specifically, because COP plans were not constrained by a predefined PTV, they were able to provide wider dosimetric margins around the CTV, by pushing OAR doses up to, but not beyond, their optimization limits. COP plans demonstrated improved target coverage when averaged over all 28 prostate anatomies, indicating that the COP approach can provide benefits for many patients. However, the degree to which slack OAR doses can be exploited to increase target coverage will vary according to the individual patient anatomy. The proof-of-concept COP implementation investigated here utilized a probabilistic DCH criteria only for the CTV minimum dose criterion. All other optimization criteria were conventional DVH criteria. In a mature COP implementation, all optimization criteria will be DCH criteria, enabling direct planning control over probabilistic dose distributions. Further research is necessary to determine the benefits of COP planning, in terms of tumor control probability and/or normal tissue complication probabilities.

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Purpose: To evaluate the dose‐mapping error (DME) inherent to conventional dose‐mapping algorithms as a function of dose‐matrix resolution. Methods: As DME has been reported to be greatest where dose‐gradients overlap tissue‐density gradients, non‐clinical 66 Gy IMRT plans were generated for 11 lung patients with the target edge defined as the maximum 3D density gradient on the 0% (end of inhale) breathing phase. Post‐optimization, Beams were copied to 9 breathing phases. Monte Carlo dose computed (with 2*2*2 mm3 resolution) on all 10 breathing phases was deformably mapped to phase 0% using the Monte Carlo energy‐transfer method with congruent mass‐mapping (EMCM); an externally implemented tri‐linear interpolation method with voxel sub‐division; Pinnacle's internal (tri‐linear) method; and a post‐processing energy‐mass voxel‐warping method (dTransform). All methods used the same base displacement‐vector‐field (or it's pseudo‐inverse as appropriate) for the dose mapping. Mapping was also performed at 4*4*4 mm3 by merging adjacent dose voxels. Results: Using EMCM as the reference standard, no clinically significant (>1 Gy) DMEs were found for the mean lung dose (MLD), lung V20Gy, or esophagus dose‐volume indices, although MLD and V20Gy were statistically different (2*2*2 mm3). Pinnacle‐to‐EMCM target D98% DMEs of 4.4 and 1.2 Gy were observed (2*2*2 mm3). However dTransform, which like EMCM conserves integral dose, had DME >1 Gy for one case. The root mean square RMS of the DME for the tri‐linear‐to‐ EMCM methods was lower for the smaller voxel volume for the tumor 4D‐D98%, lung V20Gy, and cord D1%. Conclusion: When tissue gradients overlap with dose gradients, organs‐at‐risk DME was statistically significant but not clinically significant. Target‐D98%‐DME was deemed clinically significant for 2/11 patients (2*2*2 mm3). Since tri‐linear RMS‐DME between EMCM and tri‐linear was reduced at 2*2*2 mm3, use of this resolution is recommended for dose mapping. Interpolative dose methods are sufficiently accurate for the majority of cases. J.V. Siebers receives funding support from Varian Medical Systems.

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