Dataset Information

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations.

ABSTRACT:

Purpose

To quantitatively evaluate through automated simulations the clinical significance of potential high-dose rate (HDR) prostate brachytherapy (HDRPB) physics errors selected from our internal failure-modes and effect analysis (FMEA).

Methods and materials

A list of failure modes was compiled and scored independently by 8 brachytherapy physicists on a one-to-ten scale for severity (S), occurrence (O), and detectability (D), with risk priority number (RPN) = SxOxD. Variability of RPNs across observers (standard deviation/average) was calculated. Six idealized HDRPB plans were generated, and error simulations were performed: single (N = 1722) and systematic (N = 126) catheter shifts (craniocaudal; -1cm:1 cm); single catheter digitization errors (tip and connector needle-tips displaced independently in random directions; 0.1 cm:0.5 cm; N = 44,318); and swaps (two catheters swapped during digitization or connection; N = 528). The deviations due to each error in prostate D90%, urethra D20%, and rectum D1cm³ were analyzed using two thresholds: 5-20% (possible clinical impact) and >20% (potentially reportable events).

Results

Twenty-nine relevant failure modes were described. Overall, RPNs ranged from 6 to 108 (average ± 1 standard deviation, 46 ± 23), with responder variability ranging from 19% to 184% (average 75% ± 30%). Potentially reportable events were observed in the simulations for systematic shifts >0.4 cm for prostate and digitization errors >0.3 cm for the urethra and >0.4 cm for rectum. Possible clinical impact was observed for catheter swaps (all organs), systematic shifts >0.2 cm for prostate and >0.4 cm for rectum, and digitization errors >0.2 cm for prostate and >0.1 cm for urethra and rectum.

Conclusions

A high variability in RPN scores was observed. Systematic simulations can provide insight in the severity scoring of multiple failure modes, supplementing typical FMEA approaches.

SUBMITTER: Nunez DA

PROVIDER: S-EPMC9283911 | biostudies-literature | 2021 Sep-Oct

REPOSITORIES: biostudies-literature

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Publications

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations.

Nunez David Aramburu DA Trager Michael M Beaudry Joel J Cohen Gilad N GN Dauer Lawrence T LT Gorovets Daniel D Hassan Rezaeian Nima N Kollmeier Marisa A MA Leong Brian B McCann Patrick P Williamson Matthew M Zelefsky Michael J MJ Damato Antonio L AL

Brachytherapy 20210627 5

<h4>Purpose</h4>To quantitatively evaluate through automated simulations the clinical significance of potential high-dose rate (HDR) prostate brachytherapy (HDRPB) physics errors selected from our internal failure-modes and effect analysis (FMEA).<h4>Methods and materials</h4>A list of failure modes was compiled and scored independently by 8 brachytherapy physicists on a one-to-ten scale for severity (S), occurrence (O), and detectability (D), with risk priority number (RPN) = SxOxD. Variability ...[more]

PMID: 34193362

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Project description:PurposeBi-objective simultaneous optimization of catheter positions and dwell times for high-dose-rate (HDR) prostate brachytherapy, based directly on dose-volume indices, has shown promising results. However, optimization with the state-of-the-art evolutionary algorithm MO-RV-GOMEA so far required several hours of runtime, and resulting catheter positions were not always clinically feasible. The aim of this study is to extend the optimization model and apply GPU parallelization to achieve clinically acceptable computation times. The resulting optimization procedure is compared with a previously introduced method based solely on geometric criteria, the adapted Centroidal Voronoi Tessellations (CVT) algorithm.MethodsBi-objective simultaneous optimization was performed with a GPU-parallelized version of MO-RV-GOMEA. This optimization of catheter positions and dwell times was retrospectively applied to the data of 26 patients previously treated with HDR prostate brachytherapy for 8-16 catheters (steps of 2). Optimization of catheter positions using CVT was performed in seconds, after which optimization of only the dwell times using MO-RV-GOMEA was performed in 1 min.ResultsSimultaneous optimization of catheter positions and dwell times using MO-RV-GOMEA was performed in 5 min. For 16 down to 8 catheters (steps of 2), MO-RV-GOMEA found plans satisfying the planning-aims for 20, 20, 18, 14, and 11 out of the 26 patients, respectively. CVT achieved this for 19, 17, 13, 9, and 2 patients, respectively. The P-value for the difference between MO-RV-GOMEA and CVT was 0.023 for 16 catheters, 0.005 for 14 catheters, and <0.001 for 12, 10, and 8 catheters.ConclusionsWith bi-objective simultaneous optimization on a GPU, high-quality catheter positions can now be obtained within 5 min, which is clinically acceptable, but slower than CVT. For 16 catheters, the difference between MO-RV-GOMEA and CVT is clinically irrelevant. For 14 catheters and less, MO-RV-GOMEA outperforms CVT in finding plans satisfying all planning-aims.

Project description:PurposeImage-guided high-dose-rate (HDR) prostate brachytherapy is a safe and effective treatment option for prostate cancer patients; however, some patients still experience acute and late genitourinary (GU) toxicity. Studies have shown that urethral dose is associated with the incidence and severity of GU toxicity. Therefore, a technique that can further spare the urethra while ensuring adequate target coverage is highly desirable. Intensity modulated brachytherapy (IMBT) designs, such as rotating shield brachytherapy (RSBT), offer ideal dosimetry theoretically but are challenging to implement clinically due to the need for high precision in moving the treatment delivery mechanisms synchronized with the source loading. In this study, we propose a novel relatively easy-to-implement solution based on the direction modulated brachytherapy (DMBT) design concept, which does not involve moving parts and works effectively with the ubiquitous 192Ir source.Materials and methodsThe popular Varian VS2000 (VS) and GammaMedPlus (GMP) 192Ir sources, with outer diameters of 0.6 mm and 0.9 mm, respectively, were simulated using the GEANT4 Monte Carlo (MC) simulation code. The novel DMBT needle concept consists of a 14-gauge nitinol needle, which houses a platinum shield inside. A single groove, consistent with the outer diameter of each source, was incorporated inside the platinum shield to accommodate the HDR source. The maximum thickness of the shield was 1.1 mm (0.8 mm) for the VS (GMP) source. To evaluate the effectiveness of the DMBT needle concept in reducing urethral dose, 6 patient cases were studied and DMBT plans were created by replacing two needles close to the urethra with the DMBT needles. The dosimetric comparisons between the DMBT and reference clinical plans were done by assessing the dose-volume histogram (DVH) planning criteria for the target coverage and organs-at-risk.ResultsThe MC results showed that the use of the novel DMBT needle design with the VS source (GMP source) could reduce the dose by 49.6% (39.2%) at 1 cm from the needle behind the platinum shield, as compared to the unshielded side. Additionally, when using the same DVH planning criteria as the original plan, the DMBT plan with the VS (GMP) source reduced the maximum urethral dose by 10.3% ± 5.6% (8.1% ± 5.0%) and 17.7% ± 14.2% (16.6% ± 13.3%) for 0 mm and 2 mm margins, respectively, while maintaining equivalent V90% and D100 target coverage.ConclusionThe novel DMBT technique offers a promising clinically implementable solution for sparing urethra, particularly in pre-apical region, without compromising the target coverage or increasing treatment time.

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Dataset Information

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations.

Purpose

Methods and materials

Results

Conclusions

Publications

Quantifying clinical severity of physics errors in high-dose rate prostate brachytherapy using simulations.

Similar Datasets

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