Supporting patient-specific quality assurance with fast Monte Carlo at CCB proton therapy center

Abstract

Purpose

Experimental patient-specific quality assurance (PSQA) in proton therapy is a labor-intensive process requiring physical access to treatment rooms, beam time, and significant human resources. With the increasing complexity of treatment plans and the implementation of adaptive therapy, the need for efficient alternatives is pressing. Simulation-based techniques are proposed as a replacement or enhancement for experimental ones. This study presents a data-driven approach to simulation-based PSQA criteria selection and validation.

Methods

The FRED Monte Carlo code was used to simulate PSQA for 293 patients (Gantry 1) and 296 patients (Gantry 2), divided into training and verification subsets. The training dataset guided criteria selection for simulation-based PSQA. The gamma index (GI) was analysed with criteria of 3 %/2 mm, 2 %/2 mm, 1.75 %/2 mm, 1.5 %/2 mm and 1.25 %/2 mm and compared to experimental PSQA through Spearman’s rank test. Both GI criteria and passing rate thresholds were tested to maximize consistency between experimental and simulation-based PSQA and to minimize the likelihood of false-positive errors. We validated the selected criterion on the verification subset.

Results

The analysis identified the 1.75 %/2 mm GI criterion with a 95 % passing rate as optimal. Validation on an independent verification dataset of 2816 planes showed high consistency between simulation-based and experimental PSQA: 97.5 % agreement for Gantry 1 and 98.6 % for Gantry 2. False positives were eliminated for Gantry 1 and reduced to 0.5 % for Gantry 2.

Conclusion

The proposed approach demonstrates its potential to streamline PSQA workflows, maintain clinical accuracy, and enable the integration of simulation-based PSQA into routine practice.