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Limiting treatment plan complexity by applying a novel commercial tool.

ABSTRACT: PURPOSE:A recently introduced commercial tool is tested to assess whether it is able to reduce the complexity of a treatment plan and improve deliverability without compromising overall quality. METHODS:Ten prostate and ten oropharynx plans of previously treated patients were reoptimized using the aperture shape controller (ASC) tool recently introduced in Eclipse TPS (Varian Medical Systems, Palo Alto, CA). The performance of ASC was assessed in terms of the overall plan quality using a plan quality metric, the reduction in plan complexity through the analysis of 14 of the most common plan complexity metrics, and the change in plan deliverability through 3D dosimetric measurements. Similarly, plans optimized limiting the total number of delivered monitor units was assessed and compared. The two strategies were also combined to assess their potential combination. RESULTS:The plans optimized by exploiting the ASC generally show a reduced number of total Monitor Units, a more constant gantry rotation and a MLC modulation characterized by larger and less complicated shapes with leaves traveling shorter overall lengths. CONCLUSIONS:This first experience suggests that the ASC is an effective tool to reduce the unnecessary complexity of a plan. This turns into an increased plan deliverability with no loss of plan quality.

SUBMITTER: Scaggion A

PROVIDER: S-EPMC7484888 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Limiting treatment plan complexity by applying a novel commercial tool.

Scaggion Alessandro A Fusella Marco M Agnello Giancarmelo G Bettinelli Andrea A Pivato Nicola N Roggio Antonella A Rossato Marco A MA Sepulcri Matteo M Paiusco Marta M

Journal of applied clinical medical physics 20200521 8

<h4>Purpose</h4>A recently introduced commercial tool is tested to assess whether it is able to reduce the complexity of a treatment plan and improve deliverability without compromising overall quality.<h4>Methods</h4>Ten prostate and ten oropharynx plans of previously treated patients were reoptimized using the aperture shape controller (ASC) tool recently introduced in Eclipse TPS (Varian Medical Systems, Palo Alto, CA). The performance of ASC was assessed in terms of the overall plan quality ...[more]

PMID: 32436656

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Project description:PurposeThe purpose of this study was to develop an auto-planning platform to be interfaced with a commercial treatment planning system (TPS). The main goal was to obtain robust and high-quality plans for different anatomic sites and various dosimetric requirements.MethodsMonaco (Elekta, St. Louis, US) was the TPS in this work. All input parameters for inverse planning could be defined in a plan template inside Monaco. A software tool called Robot Framework was used to launch auto-planning trials with updated plan templates. The template modifier external to Monaco was the major component of our auto-planning platform. For current implementation, it was a rule-based system that mimics the trial-and-error process of an experienced planner. A template was automatically updated by changing the optimization constraints based on dosimetric evaluation of the plan obtained in the previous trial, along with the data of the iterative optimization extracted from Monaco. Treatment plans generated by Monaco with all plan evaluation criteria satisfied were considered acceptable, and such plans would be saved for further evaluation by clinicians. The auto-planning platform was validated for 10 prostate and 10 head-and-neck cases in comparison with clinical plans generated by experienced planners.ResultsThe performance and robustness of our auto-planning platform was tested with clinical cases of prostate and head and neck treatment. For prostate cases, automatically generated plans had very similar plan quality with the clinical plans, and the bladder volume receiving 62.5 Gy, 50 Gy, and 40 Gy in auto-plans was reduced by 1%, 3%, and 5%, respectively. For head and neck cases, auto-plans had better conformity with reduced dose to the normal structures but slightly higher dose inhomogeneity in the target volume. Remarkably, the maximum dose in the spinal cord and brain stem was reduced by more than 3.5 Gy in auto-plans. Fluence map optimization only with less than 30 trials was adequate to generate acceptable plans, and subsequent optimization for final plans was completed by Monaco without further intervention. The plan quality was weakly dependent on the parameter selection in the initial template and the choices of the step sizes for changing the constraint values.ConclusionAn automated planning platform to interface with Monaco was developed, and our reported tests showed preliminary results for prostate and head and neck cases.

Project description:BackgroundBenzodiazepine receptor agonists (BZRAs) are often prescribed for long-term use. However, guidelines recommend limiting prescriptions to short-term use (< 4 weeks) to reduce the risk of adverse effects and dependence. A recent systematic review reported that brief interventions targeting long-term BZRA use in primary care (e.g., short consultations, written letters to patients) were effective in helping patients to discontinue BZRA medication. However, the complexity of these interventions has not been examined in detail. This study aimed to apply the intervention Complexity Assessment Tool for Systematic Reviews (iCAT_SR) to brief interventions targeting long-term BZRA use. METHODS: Two reviewers independently assessed the interventions using the six core iCAT_SR dimensions: organisational level/ category targeted, behaviour targeted, number of intervention components, degree of tailoring, skill level required by those delivering and receiving the intervention. The four optional iCAT_SR dimensions were applied where possible. A scoring system was using to calculate a complexity score for each intervention. Pearson's correlations were used to assess the relationship between intervention complexity and effect size, as well as the relationship between intervention complexity and number of component behaviour change techniques (BCTs). Inter-rater reliability was calculated using Cohen's Kappa coefficient.ResultsFour of the six core iCAT_SR dimensions were applied to the interventions with high inter-rater reliability (Cohen's Kappa = 0.916). Application of the four optional dimensions was prevented by a lack of detail in study reports. Intervention complexity scores ranged from 8 to 11 (median: 11). There was no relationship detected between intervention complexity and either intervention effect size or number of component BCTs.ConclusionsThis study adds to the literature on worked examples of the practical application of the iCAT_SR. The findings highlight how more detailed reporting of interventions is needed in order to optimise the application of iCAT_SR and its potential to differentiate between interventions across the full range of complexity dimensions. Further work is needed to establish the validity of applying a scoring system to iCAT_SR assessments.

Project description:PurposeTo assess the impact of the planner's experience and optimization algorithm on the plan quality and complexity of total marrow and lymphoid irradiation (TMLI) delivered by means of volumetric modulated arc therapy (VMAT) over 2010-2022 at our institute.MethodsEighty-two consecutive TMLI plans were considered. Three complexity indices were computed to characterize the plans in terms of leaf gap size, irregularity of beam apertures, and modulation complexity. Dosimetric points of the target volume (D2%) and organs at risk (OAR) (Dmean) were automatically extracted to combine them with plan complexity and obtain a global quality score (GQS). The analysis was stratified based on the different optimization algorithms used over the years, including a knowledge-based (KB) model. Patient-specific quality assurance (QA) using Portal Dosimetry was performed retrospectively, and the gamma agreement index (GAI) was investigated in conjunction with plan complexity.ResultsPlan complexity significantly reduced over the years (r = -0.50, p < 0.01). Significant differences in plan complexity and plan dosimetric quality among the different algorithms were observed. Moreover, the KB model allowed to achieve significantly better dosimetric results to the OARs. The plan quality remained similar or even improved during the years and when moving to a newer algorithm, with GQS increasing from 0.019 ± 0.002 to 0.025 ± 0.003 (p < 0.01). The significant correlation between GQS and time (r = 0.33, p = 0.01) indicated that the planner's experience was relevant to improve the plan quality of TMLI plans. Significant correlations between the GAI and the complexity metrics (r = -0.71, p < 0.01) were also found.ConclusionBoth the planner's experience and algorithm version are crucial to achieve an optimal plan quality in TMLI plans. Thus, the impact of the optimization algorithm should be carefully evaluated when a new algorithm is introduced and in system upgrades. Knowledge-based strategies can be useful to increase standardization and improve plan quality of TMLI treatments.

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Limiting treatment plan complexity by applying a novel commercial tool.

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Limiting treatment plan complexity by applying a novel commercial tool.

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