Quantifying Systematic RBE-Weighted Dose Uncertainty Arising from Multiple Variable RBE Models in Organ at Risk.

PURPOSE: Relative biological effectiveness (RBE) uncertainties have been a concern for treatment planning in proton therapy, particularly for treatment sites that are near organs at risk (OARs). In such a clinical situation, the utilization of variable RBE models is preferred over constant RBE model of 1.1. The problem, however, lies in the exact choice of RBE model, especially when current RBE models are plagued with a host of uncertainties. This paper aims to determine the influence of RBE models on treatment planning, specifically to improve the understanding of the influence of the RBE models with regard to the passing and failing of treatment plans. This can be achieved by studying the RBE-weighted dose uncertainties across RBE models for OARs in cases where the target volume overlaps the OARs. Multi-field optimization (MFO) and single-field optimization (SFO) plans were compared in order to recommend which technique was more effective in eliminating the variations between RBE models. METHODS: Fifteen brain tumor patients were selected based on their profile where their target volume overlaps with both the brain stem and the optic chiasm. In this study, 6 RBE models were analyzed to determine the RBE-weighted dose uncertainties. Both MFO and SFO planning techniques were adopted for the treatment planning of each patient. RBE-weighted dose uncertainties in the OARs are calculated assuming ( α ß ) x of 3 Gy and 8 Gy. Statistical analysis was used to ascertain the differences in RBE-weighted dose uncertainties between MFO and SFO planning. Additionally, further investigation of the linear energy transfer (LET) distribution was conducted to determine the relationship between LET distribution and RBE-weighted dose uncertainties. RESULTS: The results showed no strong indication on which planning technique would be the best for achieving treatment planning constraints. MFO and SFO showed significant differences (P <.05) in the RBE-weighted dose uncertainties in the OAR. In both clinical target volume (CTV)-brain stem and CTV-chiasm overlap region, 10 of 15 patients showed a lower median RBE-weighted dose uncertainty in MFO planning compared with SFO planning. In the LET analysis, 8 patients (optic chiasm) and 13 patients (brain stem) showed a lower mean LET in MFO planning compared with SFO planning. It was also observed that lesser RBE-weighted dose uncertainties were present with MFO planning compared with SFO planning technique. CONCLUSIONS: Calculations of the RBE-weighted dose uncertainties based on 6 RBE models and 2 different ( α ß ) x revealed that MFO planning is a better option as opposed to SFO planning for cases of overlapping brain tumor with OARs in eliminating RBE-weighted dose uncertainties. Incorporation of RBE models failed to dictate the passing or failing of a treatment plan. To eliminate RBE-weighted dose uncertainties in OARs, the MFO planning technique is recommended for brain tumor when CTV and OARs overlap.

Use of a constrained hierarchical optimization dataset enhances knowledge-based planning as a quality assurance tool for prostate bed irradiation.

PURPOSE: To investigate whether building a knowledge-based planning (KBP) model with prostate bed plans constructed from constrained hierarchical optimization (CHO) would result in more efficient model construction with more consistent output than a model built using plans from a traditional, trial-and-error-based optimization (TEO) technique. METHODS: Three KBP models were constructed from plans from subsets of 58 post-prostatectomy patients treated with intensity-modulated radiation therapy. TEO54 was built from 54 TEO plans, selected to represent typical clinical variations in target and organ-at-risk sizes and shapes. CHO30 and TEO30 were built from the same 30 patients populated with CHO and TEO plans, respectively. The three models were each applied to a new set of 18 patient scans and dose-volume histogram estimates (DVHEs) were generated for rectal and bladder walls and compared for each patient. RESULTS: CHO30 resulted in a significantly tighter range in DVHEs (P < 0.01) for both the rectal and bladder walls compared with either of the TEO models, indicating less uncertainty in the dose estimation. Plans resulting from KBP optimization using each model were very similar. CONCLUSION: Populating a KBP model with CHO data resulted in a high quality model. Since CHO plans can be generated automatically offline in a process that necessitates little to no user interaction, a CHO-KBP model can quickly adapt to changes in plan evaluation criteria or planning techniques without the need to wait to accrue sufficient numbers of clinical TEO plans. This may facilitate the use of KBP approaches for initial or ongoing quality assurance procedures and plan quality audits.

Split-VMAT technique to control the expiratory breath-hold time in liver stereotactic body radiation therapy.

PURPOSE: In this study, we demonstrate the feasibility of using split-arcs in volumetric modulated arc therapy (VMAT), tailored for expiratory breath-hold in stereotactic body radiation therapy (SBRT) for liver tumors. We compare it with three-dimensional conformal radiation therapy (3D-CRT) and continuous-VMAT, for ten randomly selected hepatocellular carcinoma cases. METHODS: Four coplanar and four non-coplanar beams were used for the 3D-CRT plans. A pair of partial arcs, chosen using a back-and-forth rotating motion, were used for the continuous-VMAT plans. Split-VMAT plans were created using the same arc range as the continuous-VMAT plans, but were split into smaller arcs (<90°), to simulate an expiratory breath hold of <15s. The dose distribution, treatment delivery efficiency, and patient specific quality assurance of the split-VMAT, were verified to ensure that the outcomes were equal, or better than, those for 3D-CRT and continuous-VMAT. The prescription was 48Gy/4 fractions, to 95% of the PTV, using 10MV FFF X-ray beams. RESULTS: The mean dose of the liver-GTV was lower in the split-VMAT compared with that of 3D-CRT. Split-VMAT was more conformal compared with 3D-CRT. The total treatment time for split-VMAT was shorter than that of 3D-CRT. Similar dosimetric indices were observed for split-VMAT and continuous-VMAT. All VMAT plans passed the gamma acceptance test. CONCLUSIONS: Split-VMAT designed to accommodate an expiratory breath-hold period of 15s is a feasible and efficient use of liver SBRT, because it does not compromise the quality of the plan, when compared with 3D-CRT or continuous-VMAT.