Comprehensive clinical implementation, workflow, and FMEA of bespoke silicone bolus cast from 3D printed molds using open-source resources

利用开源资源,对基于 3D 打印模具的定制硅胶推注液进行全面的临床实施、工作流程和失效模式及影响分析 (FMEA)。

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Abstract

BACKGROUND: Bolus materials have been used for decades in radiotherapy. Most frequently, these materials are utilized to bring dose closer to the skin surface to cover superficial targets optimally. While cavity filling, such as nasal cavities, is desirable, traditional commercial bolus is lacking, requiring other solutions. Recently, investigators have worked on utilizing 3D printing technology, including commercially available solutions, which can overcome some challenges with traditional bolus. PURPOSE: To utilize failure modes and effects analysis (FMEA) to successfully implement a comprehensive 3D printed bolus solution to replace commercial bolus in our clinic using a series of open-source (or free) software products. METHODS: 3D printed molds for bespoke bolus were created by exporting the DICOM structures of the bolus designed in the treatment planning system and manipulated to create a multipart mold for 3D printing. A silicone (Ecoflex 00-30) mixture is poured into the mold and cured to form the bolus. Molds for sheet bolus of five thicknesses were also created. A comprehensive FMEA was performed to guide workflow adjustments and QA steps. RESULTS: The process map identified 39 and 30 distinct steps for the bespoke and flat sheet bolus workflows, respectively. The corresponding FMEA highlighted 119 and 86 failure modes, with 69 shared between the processes. Misunderstanding of plan intent was a potential cause for most of the highest-scoring failure modes, indicating that physics and dosimetry involvement early in the process is paramount. CONCLUSION: FMEA informed the design and implementation of QA steps to guarantee a safe and high-quality comprehensive implementation of silicone bolus from 3D printed molds. This approach allows for greater adaptability not afforded by traditional bolus, as well as potential dissemination to other clinics due to the open-source nature of the workflow.

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