Comprehensive Dosimetric Verification and Positional Sensitivity Analysis in Brachytherapy: A Unified ESAPI Tool for HDR and LDR Treatments

TL;DR

This study introduces a versatile ESAPI-based software tool for brachytherapy QA, enabling independent dose calculations, automating protocols, and analyzing positional uncertainties in HDR and LDR treatments to improve clinical safety.

Contribution

The paper presents a novel, integrated ESAPI tool that automates brachytherapy QA, performs dose calculations, and conducts sensitivity analysis for both HDR and LDR treatments, enhancing workflow and safety.

Findings

Systematic displacements cause greater dosimetric deviations than stochastic movements.

Smaller prostate volumes are more sensitive to positional errors.

Point source models overestimate bladder dose compared to line source models.

Abstract

This study presents the development and validation of an independent software tool based on the Varian Eclipse Scripting API (ESAPI) for multi-modal brachytherapy Quality Assurance (QA). The tool addresses GEC-ESTRO HDR protocols and LDR positional uncertainty analysis. Engineered in C#, the application interfaces with BrachyVision, Vitesse, and Variseed, enabling independent TG-43 dose calculations -- comparing point and line source models -- integrated with EQD2-based radiobiological summation. In HDR cervical cancer, the tool successfully automated EMBRACE II protocol reporting, streamlining clinical workflows by combining dosimetric QA with predictive and prospective planning. For LDR prostate treatments, a stochastic simulation module quantified the impact of systematic (rigid-body) versus random seed displacements on target coverage ($D_{90\%}$) and Organs at Risk (OAR) safety ($D_{0.1cc}$). Sensitivity analysis in LDR prostate implants was benchmarked using two clinical cases (prostate volumes 31 cc and 71.3 cc). LDR simulations revealed that systematic displacements ($\pm$ 2 mm) yielded significantly higher dosimetric deviations than stochastic movements. In the 31 cc case, systematic shifts resulted in a rectal ($D_{0.1cc}$) standard deviation (SD) of 24.3 Gy, whereas random displacements reduced this to 12.4 Gy. In the 71.3 cc case, random displacements resulted in a rectal $D_{0.1cc}$ SD of 7.6 Gy, confirming that smaller volumes exhibit heightened sensitivity to errors. Technical analysis demonstrated that the point source model overestimated bladder $D_{10\%}$ by 8% relative to the line source model. Our findings confirm that systematic rigid-body shifts represent a greater clinical risk for OAR toxicity than stochastic migration. Integrating predictive sensitivity analysis into the clinical workflow significantly enhances patient safety through robust plan verification.