An empirical method for splitting arcs in VMAT.

PURPOSE: We present a new approach to determine the optimal arc split for VMAT beams which is an extension of our recently published algorithm for selecting optimal beam angles in Intensity Modulated Radiation Therapy (IMRT) MATERIAL AND METHODS: The proposed approach uses an objective function based scoring method called "ψ - score" to determine optimal arc splitting strategy. To validate our approach, we applied it in different clinical cases: Abdomen-Para aortic node, Lung, Pancreas and Prostate. Basically, for all clinical cases, two set of plans were created, namely VMAT plan and VMAT_S plan using Pinnacle3 (V16.2, Philips Medical Systems (Cleveland), Inc.). In the VMAT plans, full arc (360°) with 4-degree gantry spacing was used during optimization to compute the "ψ - score". Subsequently the avoidable arc portions were identified and removed using the ψ - score plot followed by the final optimization (VMAT_S). RESULTS: Equivalent or better OAR sparing, and similar target coverage were achieved in VMAT_S plans compared to VMAT plans. VMAT_S reduced the number of control points and monitor units by 24.2% and 12.9% respectively. On the average, beam on time was reduced by 21.9% and low dose volume (5 Gy isodose volume) to healthy tissues was reduced by 4.9% in VMAT_S compared to VMAT plans. CONCLUSION: The results demonstrated that the proposed method is useful for reducing the monitor units, beam on time and low dose volume without significantly compromising plan quality and most useful for non-centrically located targets.

Objective function based ranking method for selection of optimal beam angles in IMRT.

We propose a novel method for the selection of optimal beam angles in Intensity Modulated Radiation Therapy (IMRT). The proposed approach uses an objective function based metric called "target-to-critical organ objective function ratio" to find out the optimal gantry angles. The beams are ranked based on this metric and are accordingly chosen for IMRT optimization. We have used the Pinnacle TPS (Philips Medical System V 16.2) for performing the IMRT optimization. In order to validate our approach, we have applied it in four clinical cases: Head and Neck, Lung, Abdomen and Prostate. Basically, for all clinical cases, two set of plans were created with same clinical objectives, namely Equal angle plan (EA Plan) and Suitable angle Plan (SA Plan). In the EA plans, the beam angles were placed in an equiangular manner starting from the gantry angle of 0°. In the corresponding SA plans, the beam angles were decided using the guidance provided by the algorithm. The reduction in OAR mean dose and max dose obtained in SA plans is about 3 to 16% and 3 to 15% respectively depending upon the treatment site while obtaining equal target coverage as compared to their EA counterparts. It takes approximately 15-25 min to find the optimal beam angles. The results obtained from the clinical cases indicate that the plan quality is considerably improved when the beam angles are optimized using the proposed method.

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.

An empirical method for automatic determination of maximum number of segments in DMPO-based IMRT for Head and Neck cases.

AIM: An empirical scheme called "anatomy-guided segment counting (AGSC)" is proposed for automatic selection of maximum number of segments (NOS) for direct machine parameter optimization (DMPO). BACKGROUND: Direct machine parameter optimization (DMPO) requires the user to define the maximum number of segments (NOS) in order to proceed with an optimization process. Till date there is no established approach to arrive at an optimal and case-specific maximum NOS in DMPO, and this step is largely left to the planner's experience. MATERIALS AND METHODS: The AGSC scheme basically uses the Beam's-eye views (BEVs) and other planning parameters to decide on appropriate number of segments for the beam. The proposed algorithm was tested in eight H&N cases. We used Auto Plan feature available in Pinnacle3 (version 9.10.0) for driving the DMPO optimization. RESULTS: There is about 13% reduction in the composite objective value in AGSC plans as compared to the plans employing 6 NOS per beam and 10% increase in the composite objective value in AGSC plans as compared to the plans employing 8 NOS per beam. On the delivery efficiency front, there is about 10% increase in NOS in AGSC plans as compared to the plans employing 6 NOS per beam specification. Similarly, there is about 19% reduction in NOS in AGSC plans as compared to the plans employing 8 NOS per beam specification. CONCLUSION: The study demonstrates that the AGSC method allows specifying appropriate number of segments into the DMPO module accounting for the complexity of a given case.

Determination of optimal number of beams in direct machine parameter optimization-based intensity modulated radiotherapy for head and neck cases.

This paper aims to introduce an algorithm called "sensitivity-based beam number selection (SBBNS)" for fully automated and case-specific determination of an optimal number of equispaced beams in intensity-modulated radiotherapy (IMRT). We tested the algorithm in five head and neck cases of varying complexity. We used direct machine parameter optimization method coupled with Auto Plan feature available in Pinnacle TPS (Version 9.10.0) for optimization. The Pearson correlation test shows a correlation of 0.88 between predicted and actual optimal number of beams, which indicates that SBBNS method is capable of predicting optimal number of beams for head and neck cases with reasonable accuracy. The major advantage of the algorithm is that it intrinsically takes into account various case- and machine-specific factors for the determination of optimal number. The study demonstrates that the algorithm can be effectively applied to IMRT scenarios to determine case specific and optimal number of beams for head and neck cases.

Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy.

This study aims to evaluate the performance of a new algorithm for optimization of beam weights in anatomy-based intensity modulated radiotherapy (IMRT). The algorithm uses a numerical technique called Gaussian-Elimination that derives the optimum beam weights in an exact or non-iterative way. The distinct feature of the algorithm is that it takes only fraction of a second to optimize the beam weights, irrespective of the complexity of the given case. The algorithm has been implemented using MATLAB with a Graphical User Interface (GUI) option for convenient specification of dose constraints and penalties to different structures. We have tested the numerical and clinical capabilities of the proposed algorithm in several patient cases in comparison with KonRad((R)) inverse planning system. The comparative analysis shows that the algorithm can generate anatomy-based IMRT plans with about 50% reduction in number of MUs and 60% reduction in number of apertures, while producing dose distribution comparable to that of beamlet-based IMRT plans. Hence, it is clearly evident from the study that the proposed algorithm can be effectively used for clinical applications.