An in-silico quality assurance study of contouring target volumes in thoracic tumors within a cooperative group setting

在合作组环境下,对胸部肿瘤靶区勾画进行计算机模拟质量保证研究

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Abstract

INTRODUCTION: Target delineation variability is a significant technical impediment in multi-institutional trials which employ intensity modulated radiotherapy (IMRT), as there is a real potential for clinically meaningful variances that can impact the outcomes in clinical trials. The goal of this study is to determine the variability of target delineation among participants from different institutions as part of Southwest Oncology Group (SWOG) Radiotherapy Committee's multi-institutional in-silico quality assurance study in patients with Pancoast tumors as a "dry run" for trial implementation. METHODS: CT simulation scans were acquired from four patients with Pancoast tumor. Two patients had simulation 4D-CT and FDG-FDG PET-CT while two patients had 3D-CT and FDG-FDG PET-CT. Seventeen SWOG-affiliated physicians independently delineated target volumes defined as gross primary and nodal tumor volumes (GTV_P & GTV_N), clinical target volume (CTV), and planning target volume (PTV).Six board-certified thoracic radiation oncologists were designated as the 'Experts' for this study. Their delineations were used to create a simultaneous truth and performance level estimation (STAPLE) contours using ADMIRE software (Elekta AB, Sweden 2017). Individual participants' contours were then compared with Experts' STAPLE contours. RESULTS: When compared to the Experts' STAPLE, GTV_P had the best agreement among all participants, while GTV_N showed the lowest agreement among all participants. There were no statistically significant differences in all studied parameters for all TVs for cases with 4D-CT versus cases with 3D-CT simulation scans. CONCLUSIONS: High degree of inter-observer variation was noted for all target volume except for GTV_P, unveiling potentials for protocol modification for subsequent clinically meaningful improvement in target definition. Various similarity indices exist that can be used to guide multi-institutional radiotherapy delineation QA credentialing.

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