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Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

ABSTRACT: PURPOSE:Knowledge-based planning (KBP) techniques have been reported to improve plan quality, efficiency, and consistency in radiation therapy. However, plan complexity and deliverability have not been addressed previously for treatment plans guided by an established in-house KBP system. The purpose of this work was to assess dosimetric, mechanical, and delivery properties of plans designed with a common KBP method for prostate cases treated via volumetric modulated arc therapy (VMAT). METHODS:Thirty-one prostate patients previously treated with VMAT were replanned with an in-house KBP method based on the overlap volume histogram. VMAT plan complexities of the KBP plans and the reference clinical plans were quantified via monitor units, modulation complexity scores, the edge metric, and average leaf motion per degree of gantry rotation. Each set of plans was delivered to the same diode array and agreement between computed and measured dose distributions was evaluated using the gamma index. Varying percent dose-difference (1-3%) and distance-to-agreement (1 mm to 3 mm) thresholds were assessed for gamma analyses. RESULTS:Knowledge-based planning (KBP) plans achieved average reductions of 6.4 Gy (P < 0.001) and 8.2 Gy (P < 0.001) in mean bladder and rectum dose compared to reference plans, while maintaining clinically acceptable target dose. However, KBP plans were significantly more complex than reference plans in each evaluated metric (P < 0.001). KBP plans also showed significant reductions (P < 0.05) in gamma passing rates at each evaluated criterion compared to reference plans. CONCLUSIONS:While KBP plans had significantly reduced bladder and rectum dose, they were significantly more complex and had significantly worse quality assurance outcomes than reference plans. These results suggest caution should be taken when implementing an in-house KBP technique.

SUBMITTER: Wall PDH

PROVIDER: S-EPMC6964749 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

Wall Phillip D H PDH Fontenot Jonas D JD

Journal of applied clinical medical physics 20191209 1

<h4>Purpose</h4>Knowledge-based planning (KBP) techniques have been reported to improve plan quality, efficiency, and consistency in radiation therapy. However, plan complexity and deliverability have not been addressed previously for treatment plans guided by an established in-house KBP system. The purpose of this work was to assess dosimetric, mechanical, and delivery properties of plans designed with a common KBP method for prostate cases treated via volumetric modulated arc therapy (VMAT).<h ...[more]

PMID: 31816175

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Project description:BackgroundThe newest release of the Eclipse (Varian) treatment planning system (TPS) includes an optimizing engine for Elekta volumetric-modulated arc therapy (VMAT) planning. The purpose of this study was to evaluate this new algorithm and to compare it to intensity-modulated radiation therapy (IMRT) for various disease sites by creating single- and double-arc VMAT plans.MethodsA total of 162 plans were evaluated in this study, including 38 endometrial, 57 head and neck, 12 brain, 10 breast and 45 prostate cancer cases. The real-life IMRT plans were developed during routine clinical cases using the TPS Eclipse. VMAT plans were generated using a preclinical version of Eclipse with tumor-region-specific optimizing templates without interference of the operator: with one full arc (1A) and with two full arcs (2A), and with partial arcs for breast and prostate with hip implant cases. All plans were evaluated based on target coverage, homogeneity and conformity. The organs at risk (OARs) were analyzed according to plan objectives, such as the mean and maximum doses. If one or more objectives were exceeded, the plan was considered clinically unacceptable, and a second VMAT plan was created by adapting the optimization penalties once.ResultsCompared to IMRT, single- and double-arc VMAT plans showed comparable or better results concerning the target coverage: the maximum dose in the target for 1A is the same as that for IMRT; for 2A, an average reduction of 1.3% over all plans was observed. The conformity showed a statistically significant improvement for both 1A (+3%) and 2A (+6%). The mean total body dose was statistically significant lower for the considered arc techniques (IMRT: 16.0 Gy, VMAT: 15.3 Gy, p < 0.001). However, the sparing of OARs shows individual behavior that depends strongly on the different tumor regions. A clear difference is found in the number of monitor units (MUs) per plan: VMAT shows a reduction of 31%.ConclusionThese findings demonstrate that based on optimizing templates with minimal interaction of the operator, the Eclipse TPS is able to achieve a plan quality for the Elekta VMAT delivery technique that is comparable to that of fixed-field IMRT. Plans with two arcs show better dose distributions than plans with one arc.

Project description:BackgroundTo investigate the feasibility of a knowledge-based automated intensity-modulated radiation therapy (IMRT) planning technique for locally advanced nasopharyngeal carcinoma (NPC) radiotherapy.MethodsOne hundred forty NPC patients treated with definitive radiation therapy with the step-and-shoot IMRT techniques were retrospectively selected and separated into a knowledge library (n = 115) and a test library (n = 25). For each patient in the knowledge library, the overlap volume histogram (OVH), target volume histogram (TVH) and dose objectives were extracted from the manually generated plan. 5-fold cross validation was performed to divide the patients in the knowledge library into 5 groups before validating one group by using the other 4 groups to train each neural network (NN) machine learning models. For patients in the test library, their OVH and TVH were then used by the trained models to predict a corresponding set of mean dose objectives, which were subsequently used to generate automated plans (APs) in Pinnacle planning system via an in-house developed automated scripting system. All APs were obtained after a single step of optimization. Manual plans (MPs) for the test patients were generated by an experienced medical physicist strictly following the established clinical protocols. The qualities of the APs and MPs were evaluated by an attending radiation oncologist. The dosimetric parameters for planning target volume (PTV) coverage and the organs-at-risk (OAR) sparing were also quantitatively measured and compared using Mann-Whitney U test and Bonferroni correction.ResultsAPs and MPs had the same rating for more than 80% of the patients (19 out of 25) in the test group. Both AP and MP achieved PTV coverage criteria for no less than 80% of the patients. For each OAR, the number of APs achieving its criterion was similar to that in the MPs. The AP approach improved planning efficiency by greatly reducing the planning duration to about 17% of the MP (9.85 ± 1.13 min vs. 57.10 ± 6.35 min).ConclusionA robust and effective knowledge-based IMRT treatment planning technique for locally advanced NPC is developed. Patient specific dose objectives can be predicted by trained NN models based on the individual's OVH and clinical TVH goals. The automated planning scripts can use these dose objectives to efficiently generate APs with largely shortened planning time. These APs had comparable dosimetric qualities when compared to our clinic's manual plans.

Dataset Information

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

Publications

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge-based VMAT planning technique.

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