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Safety‐oriented design of in‐house software for new techniques: A case study using a model‐based 4 DCT protocol
Author(s) -
O'Connell Dylan,
Thomas David H.,
Lewis John H.,
Hasse Katelyn,
Santhanam Anand,
Lamb James M.,
Cao Minsong,
Tenn Stephen,
Agazaryan Nzhde,
Lee Percy P.,
Low Daniel A.
Publication year - 2019
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13386
Subject(s) - computer science , workflow , quality assurance , protocol (science) , software , reliability engineering , software engineering , engineering , medicine , operations management , external quality assessment , alternative medicine , pathology , database , programming language
Purpose In‐house software is commonly employed to implement new imaging and therapy techniques before commercial solutions are available. Risk analysis methods, as detailed in the TG ‐100 report of the American Association of Physicists in Medicine, provide a framework for quality management of processes but offer little guidance on software design. In this work, we examine a novel model‐based four‐dimensional computed tomography (4 DCT ) protocol using the TG ‐100 approach and describe two additional methods for promoting safety of the associated in‐house software. Methods To implement a previously published model‐based 4 DCT protocol, in‐house software was necessary for tasks such as synchronizing a respiratory signal to computed tomography images, deformable image registration ( DIR ), model parameter fitting, and interfacing with a treatment planning system. A process map was generated detailing the workflow. Failure modes and effects analysis ( FMEA ) was performed to identify critical steps and guide quality interventions. Software system safety was addressed through writing “use cases,” narratives that characterize the behavior of the software, for all major operations to elicit safety requirements. Safety requirements were codified using the easy approach to requirements syntax ( EARS ) to ensure testability and eliminate ambiguity. Results Sixty‐one failure modes were identified and assigned risk priority numbers using FMEA . Resultant quality management interventions include integration of a comprehensive reporting and logging system into the software, mandating daily and monthly equipment quality assurance procedures, and a checklist to be completed at image acquisition. Use cases and resulting safety requirements informed the design of needed in‐house software as well as a suite of tests performed during the image generation process. Conclusions TG ‐100 methods were used to construct a process‐level quality management program for a 4 DCT imaging protocol. Two supplemental tools from the field of requirements engineering facilitated elicitation and codification of safety requirements that informed the design and testing of in‐house software necessary to implement the protocol. These general tools can be applied to promote safety when in‐house software is needed to bring new techniques to the clinic.