Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction

TL;DR

This paper introduces a training-aware conformal prediction method to efficiently triage IMRT plans, reducing QA workload while maintaining high accuracy in clinical decision-making.

Contribution

It develops a novel conformal risk control approach that integrates clinical thresholds and risk functions, enhancing IMRT QA efficiency.

Findings

Significantly reduces the number of plans requiring measurement.

Achieves high sensitivity and specificity in plan triage.

Validates the effectiveness of conformal prediction in clinical QA.

Abstract

Measurement quality assurance (QA) practices play a key role in the safe use of Intensity Modulated Radiation Therapies (IMRT) for cancer treatment. These practices have reduced measurement-based IMRT QA failure below 1%. However, these practices are time and labor intensive which can lead to delays in patient care. In this study, we examine how conformal prediction methodologies can be used to robustly triage plans. We propose a new training-aware conformal risk control method by combining the benefit of conformal risk control and conformal training. We incorporate the decision making thresholds based on the gamma passing rate, along with the risk functions used in clinical evaluation, into the design of the risk control framework. Our method achieves high sensitivity and specificity and significantly reduces the number of plans needing measurement without generating a huge confidence interval. Our results demonstrate the validity and applicability of conformal prediction methods for improving efficiency and reducing the workload of the IMRT QA process.