# A prospective hazard analysis of real‐time adaptive helical tomotherapy

## TL;DR

This study uses a new safety analysis method to evaluate real-time adaptive radiation therapy systems, identifying risks and proposing ways to improve safety.

## Contribution

The paper demonstrates the application of System Theoretic Process Analysis (STPA) to real-time adaptive helical tomotherapy for the first time.

## Key findings

- A control structure model with 12 sub-systems and 21 control actions identified 108 unsafe control actions and 595 causal scenarios.
- Sixty-one causal scenarios were selected for mitigation strategies, including improved documentation and parameter testing.
- The study provides a transferable example of STPA application in radiation therapy safety assessments.

## Abstract

Following the release in 2016 of the report of the American Association of Physicists in Medicine Task Group 100, there has been growing interest in the use of prospective hazard analysis in radiation therapy. System Theoretic Process Analysis (STPA) is an emerging technique in this domain that is particularly suited to processes that involve time sensitive collaboration, decision‐making and/or automation.

The goal of this research was to use STPA to evaluate existing processes and procedures with an aim to identify improvements, gaps or unforeseen risks stemming from implementing real‐time adaptive treatment on a helical tomotherapy platform.

The Radixact treatment delivery system (Accuray Inc., Sunnyvale, CA, USA), an evolution of the Tomotherapy platform, incorporates upgrades such as the Synchrony system for real‐time motion monitoring and treatment adaptation. In collaboration with a team from the radiation oncology department of a large public hospital, a prospective hazard analysis focused on the real‐time adaptive capabilities of the Radixact Synchrony system was conducted using STPA. The system boundaries were defined and a control structure model comprising sub‐systems and control actions was developed. Unsafe control actions were identified and broad‐based causal scenarios were generated. The causal scenarios that were novel, specific to Synchrony or challenging to mitigate were selected for further analysis regarding impacts and potential causes, following which mitigation strategies were proposed, taking into consideration the hierarchy of controls.

A control structure model encompassing the entire patient journey was developed, incorporating all the hardware and software components and human decision makers. The model consisted of 12 sub‐systems and 21 control actions, resulting in 108 unsafe control actions and 595 causal scenarios. Sixty‐one causal scenarios were selected for further analysis, for which mitigation strategies were proposed based on the hierarchy of controls. These included the development of better reference documentation, the systematic testing of the sensitivity of tracking performance to changes in tracking parameters, guidance around setting and documenting tracking parameters, and documentation review.

STPA was effectively used to assess the Radixact Synchrony system's real‐time adaptive radiation therapy capabilities, providing insight into how the system could become unsafe throughout the patient journey. While focused on Radixact Synchrony and real‐time adaptive radiation therapy, this study offers a transferable example of STPA application, from analysis initialization to mitigation, that can inform other safety assessments in radiation therapy.