Feasibility of a unified approach to intensity-modulated radiation therapy and volume-modulated arc therapy optimization and delivery

Technical Note: A fast inverse direct aperture optimization algorithm for volumetric-modulated arc therapy

PURPOSE

In a recent article, our group proposed a fast direct aperture optimization (DAO) algorithm for fixed-gantry intensity-modulated radiation therapy (IMRT) called fast inverse direct aperture optimization (FIDAO). When tested on fixed-gantry IMRT plans, we observed up to a 200-fold increase in the optimization speed. Compared to IMRT, rotational volumetric-modulated arc therapy (VMAT) is a much larger optimization problem and has many more delivery constraints. The purpose of this work is to extend and evaluate FIDAO for inverse planning of VMAT plans.

METHODS

A prototype FIDAO algorithm for VMAT treatment planning was developed in MATLAB using the open-source treatment planning toolkit matRad (v2.2 dev_VMAT build). VMAT treatment plans using one 360⁰ arc were generated on the AAPM TG-119 phantom, as well as sample clinical liver and prostate cases. The plans were created by first performing fluence map optimization on 28° equispaced beams, followed by aperture sequencing and arc sequencing with a gantry angular sampling rate of 4°. After arc sequencing, a copy of the plan underwent DAO using the prototype FIDAO algorithm, while another copy of the plan underwent DAO using matRad's DAO method, which served as the conventional algorithm.

RESULTS

Both algorithms achieved similar plan quality, although the FIDAO plans had considerably fewer hot spots in the unspecified normal tissue. The optimization time (number of iterations) for FIDAO and the conventional DAO algorithm, respectively, were: 65 s (245) vs 602 s (275) in the TG-119 phantom case; 25 s (85) vs 803 s (159) in the liver case; and 99 s (174) vs 754 s (149) in the prostate case.

CONCLUSIONS

This study demonstrated promising speed enhancements in using FIDAO for the direct aperture optimization of VMAT plans.

VMAT plus a few computer-optimized non-coplanar IMRT beams (VMAT+) tested for liver SBRT

PURPOSE

To propose a novel treatment approach, designated VMAT+, involving addition of <5 IMRT beams with computer-optimized non-coplanar orientations to VMAT, and evaluate it for liver Stereotactic Body Radiation Therapy (SBRT). VMAT+ is investigated as an alternative for (1) coplanar VMAT and (2) multi-beam non-coplanar treatment.

METHODS/MATERIALS

For fifteen patients with liver metastases, VMAT+ plans were compared with (1) dual-arc VMAT and (2) 25-beam, non-coplanar treatment with computer-optimized beam orientations (25-NCP). All plans were generated fully automatically for delivery of the highest feasible tumor Biologically Effective Dose (BED). OAR doses, intermediate-dose-spillage, dose-compactness, and measured delivery times were evaluated.

RESULTS

With VMAT+ the maximum achievable tumor BED was equal to that of 25-NCP. Conversely, VMAT resulted in a lower tumor BED in 5 patients. Compared to VMAT, VMAT+ yielded significant dose reductions in OARs. Intermediate-dose-spillage and dose-compactness were significantly improved by 9.8% and 17.3% (p≤0.002), respectively. Treatment times with VMAT+ were only enhanced by 4.1min on average, compared to VMAT (8.4min). Improvements in OAR sparing with 25-NCP, compared to VMAT+, were generally modest and/or statistically insignificant, while delivery times were on average 20.5min longer.

CONCLUSIONS

For liver SBRT, VMAT+ is equivalent to time-consuming treatment with 25 non-coplanar beams in terms of achievable tumor BED. Compared to VMAT, OAR sparing and intermediate-dose-spillage are significantly improved, with minor increase in delivery time.

Use of proximal operator graph solver for radiation therapy inverse treatment planning

PURPOSE

Most radiation therapy optimization problems can be formulated as an unconstrained problem and solved efficiently by quasi-Newton methods such as the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm. However, several next generation planning techniques such as total variation regularization- based optimization and MV+kV optimization, involve constrained or mixed-norm optimization, and cannot be solved by quasi-Newton methods. Using standard optimization algorithms on such problems often leads to prohibitively long optimization times and large memory requirements. This work investigates the use of a recently developed proximal operator graph solver (POGS) in solving such radiation therapy optimization problems.

METHODS

Radiation therapy inverse treatment planning was formulated as a graph form problem, and the proximal operators of POGS for quadratic optimization were derived. POGS was exploited for the first time to impose hard dose constraints along with soft constraints in the objective function. The solver was applied to several clinical treatment sites (TG119, liver, prostate, and head&neck), and the results were compared to the solutions obtained by other commercial and non-commercial optimizers.

RESULTS

For inverse planning optimization with nonnegativity box constraints on beamlet intensity, the speed of POGS can compete with that of LBFGSB in some situations. For constrained and mixed-norm optimization, POGS is about one or two orders of magnitude faster than the other solvers while requiring less computer memory.

CONCLUSIONS

POGS was used for solving inverse treatment planning problems involving constrained or mixed-norm formulation on several example sites. This approach was found to improve upon standard solvers in terms of computation speed and memory usage, and is capable of solving traditionally difficult problems, such as total variation regularization-based optimization and combined MV+kV optimization.

Application programming in C# environment with recorded user software interactions and its application in autopilot of VMAT/IMRT treatment planning

An autopilot scheme of volumetric‐modulated arc therapy (VMAT)/intensity‐modulated radiation therapy (IMRT) planning with the guidance of prior knowledge is established with recorded interactions between a planner and a commercial treatment planning system (TPS). Microsoft (MS) Visual Studio Coded UI is applied to record some common planner‐TPS interactions as subroutines. The TPS used in this study is a Windows‐based Eclipse system. The interactions of our application program with Eclipse TPS are realized through a series of subroutines obtained by prerecording the mouse clicks or keyboard strokes of a planner in operating the TPS. A strategy to autopilot Eclipse VMAT/IMRT plan selection process is developed as a specific example of the proposed “scripting” method. The autopiloted planning is navigated by a decision function constructed with a reference plan that has the same prescription and similar anatomy with the case at hand. The calculation proceeds by alternating between the Eclipse optimization and the outer‐loop optimization independent of the Eclipse. In the C# program, the dosimetric characteristics of a reference treatment plan are used to assess and modify the Eclipse planning parameters and to guide the search for a clinically sensible treatment plan. The approach is applied to plan a head and neck (HN) VMAT case and a prostate IMRT case. Our study demonstrated the feasibility of application programming method in C# environment with recorded interactions of planner‐TPS. The process mimics a planner's planning process and automatically provides clinically sensible treatment plans that would otherwise require a large amount of manual trial and error of a planner. The proposed technique enables us to harness a commercial TPS by application programming via the use of recorded human computer interactions and provides an effective tool to greatly facilitate the treatment planning process.

PACS number(s): 87.55.D‐, 87.55.kd, 87.55.de

An IMRT/VMAT Technique for Nonsmall Cell Lung Cancer

The study is to investigate a Hybrid IMRT/VMAT technique which combines intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) for the treatment of nonsmall cell lung cancer (NSCLC). Two partial arcs VMAT, 5-field IMRT, and hybrid plans were created for 15 patients with NSCLC. The hybrid plans were combination of 2 partial arcs VMAT and 5-field IMRT. The dose distribution of planning target volume (PTV) and organs at risk (OARs) for hybrid technique was compared with IMRT and VMAT. The monitor units (MUs) and treatment delivery time were also evaluated. Hybrid technique significantly improved the target conformity and homogeneity compared with IMRT and VMAT. The mean delivery time of IMRT, VMAT, and hybrid plans was 280 s, 114 s, and 327 s, respectively. The mean MUs needed for IMRT, VMAT, and hybrid plans were 933, 512, and 737, respectively. Hybrid technique reduced V5, V10, V30, and MLD of normal lung compared with VMAT and spared the OARs better with fewer MUs with the cost of a little higher V5, V10, and mean lung dose (MLD) of normal lung compared with IMRT. Hybrid IMRT/VMAT can be a viable radiotherapy technique with better plan quality.