An uncertainty-incorporated method for fast beam angle selection in intensity-modulated proton therapy.

Aim: We propose a novel metric called ψ - score to rank the Intensity Modulated Proton Therapy (IMPT) beams in the order of their optimality and robustness. The beams ranked based on this metric were accordingly chosen for IMPT optimization. The objective of this work is to study the effectiveness of the proposed method in various clinical cases. Methods and Materials: We have used Pinnacle TPS (Philips Medical System V 16.2) for performing the optimization. To validate our approach, we have applied it in four clinical cases: Lung, Pancreas, Prostate+Node and Prostate. Basically, for all clinical cases, four set of plans were created using Multi field optimization (MFO) and Robust Optimization (RO) with same clinical objectives, namely (1) Conventional angle plan without Robust Optimization (CA Plan), (2) Suitable angle Plan without Robust Optimization (SA Plan), (3) Conventional angle plan with Robust Optimization (CA-RO Plan), (4) Suitable angle Plan with Robust Optimization (SA-RO Plan). Initial plan was generated with 20 equiangular beams starting from the gantry angle of 0°. In the corresponding SA Plan and SA-RO Plan, the beam angles were obtained using the guidance provided by ψ - score. Results: All CA plans were compared against the SA plans in terms of Dose distribution, Dose volume histogram (DVH) and percentage of dose difference. The results obtained from the clinical cases indicate that the plan quality is considerably improved without significantly compromising the robustness when the beam angles are optimized using the proposed method. It takes approximately 10-15 min to find the suitable beam angles without Robust Optimization (RO), while it takes approximately 20-30 min to find the suitable beam angles with RO. However, the inclusion of RO in BAO did not result in a change in the final beam angles for anatomies other than lung. Conclusion: The results obtained in different anatomic sites demonstrate the usefulness of our approach in improving the plan quality by determining optimal beam angles in IMPT.

A Novel Method for Improving VMAT Plan Quality and Deliverability.

BACKGROUND: A new VMAT method called "Augmented Arc" (or simply Aug Arc) is proposed. The aim of this study is to demonstrate the validity of the proposed method in different clinical cases. Basically, Aug Arc refers to the portion(s) of the VMAT arc that is augmented with an additional arc to improve the plan quality. The Aug Arc portions in the Arc is determined using an objective function-based scoring method called "ψ - score". METHODS: To validate our approach, we have applied it in four clinical cases: Lung, Abdomen, Gynecologic (Gyn) and Pancreas. Basically, for Lung and Pancreas cases, four sets of plans were created, which are: (1) Single arc plan (S Arc), (2) Double arc plan (D Arc), (3) Partial Arc plan without Aug Arc (P Arc) and (4) Partial plan with Aug Arc (P+Aug Arc). For Abdomen and Gyn cases, three sets of plans were created, which are: (1) Single arc plan (S Arc), (2) Double arc plan (D Arc) and (3) Single Arc with Aug Arc (S+Aug Arc). To compute the "ψ - score", an initial optimization was performed by using full Arc with 4-degree gantry spacing. Subsequently, Aug Arc portions were identified using the ψ - score plot in the single arc and partial arc scenarios. RESULTS: The study finds that the proposed method is useful to improve the plan quality and plan deliverability for both centrically and non-centrically located tumors in terms of reducing the OAR dose, monitor units, beam on time and low dose volume without compromising the target coverage. CONCLUSION: The results indicate that the proposed approach could strike a balance between full double arc and single arc or partial arc in such a way that the planner can find a sweet spot of delivery parameters that result in optimal plan quality.

Evaluation of plan quality improvements in PlanIQ-guided Autoplanning.

AIM: Philips recently integrated PlanIQ with Autoplan® in Pinnacle3 TPS (V16.2). The objective of the present work is to quantitatively demonstrate how this integration improves the plan quality. BACKGROUND: Pinnacle3 Autoplan® is the tool that generates the treatment plans with clinically acceptable plan quality with less manual intervention. In the recent past, a new tool called PlanIQ (Sun Nuclear Corp.) was introduced for a priori estimation of the best possible sparing of an organ at risk (OAR) for a given patient anatomy. Philips has recently integrated PlanIQ tool with Autoplan® for a seamless and efficient planning workflow. MATERIALS AND METHODS: We have performed this evaluation in Pinnacle3 TPS (V.16.2) for the VMAT treatment technique. All plans were created using Varian True beam machine with the dual arc technique. Basically, we created two sets of VMAT plans using 6 MV photons. In the first set of VMAT plans (AP_RTOG), we used OAR goals from either RTOG guidelines to perform optimization using Autoplan®. Subsequently, we exported the same dataset to the PlanIQ system to perform feasibility analysis on the OAR goals. These newly obtained OAR goals from PlanIQ were used to generate the other set of plans (AP_PlanIQ plans). We compared the dosimetric results from these two sets of plans in five cases, such as brain, head & neck, lung, abdomen and prostate. RESULTS: We compared the dosimetric results for AP_RTOG and AP_PlanIQ plans. We used RTOG guidelines to evaluate the plans and observed that while both sets of plans were meeting the RTOG guidelines in terms of OAR sparing, the AP_PlanIQ plans were significantly better in terms of OAR sparing as compared to AP_RTOG plans without any compromise in the target coverage. CONCLUSION: The results indicate that, although Autoplan helps achieve the user-defined goals without much manual intervention, the plan quality (OAR sparing) can be significantly improved without taking many iterative steps when PlanIQ suggested clinical goals are used in the Autoplan-based optimization. ADVANCES IN KNOWLEDGE: At present, there are no published material available about the efficacy of the integration of PlanIQ with Autoplanning®. In the present work, our objective is to evaluate the improvements in plan quality resulting from this integration.