1. Use of a healthy volunteer imaging program to optimize clinical implementation of stereotactic MR-guided adaptive radiotherapy
- Author
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Jessica Penney, Iquan Usta, Elizabeth Huynh, Raymond H. Mak, Emily Neubauer Sugar, Patrick J. Boyle, Sara Boyle, Fred Hacker, Christopher S. Williams, Jennifer Campbell, Daniel N. Cagney, and Lisa Singer
- Subjects
lcsh:Medical physics. Medical radiology. Nuclear medicine ,medicine.medical_specialty ,Computer science ,Image quality ,lcsh:R895-920 ,MR-linac ,lcsh:RC254-282 ,030218 nuclear medicine & medical imaging ,Workflow ,03 medical and health sciences ,0302 clinical medicine ,Magnetic resonance imaging ,Healthy volunteers ,medicine ,Training ,Radiology, Nuclear Medicine and imaging ,Medical physics ,Adaptive radiotherapy ,Care Planning ,Contouring ,medicine.diagnostic_test ,Oncology (nursing) ,Health Policy ,Visibility (geometry) ,lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,030220 oncology & carcinogenesis ,New disease ,Mri guided ,Research Article - Abstract
Purpose MR-linacs (MRLs) have enabled the use of stereotactic magnetic resonance (MR) guided online adaptive radiotherapy (SMART) across many cancers. As data emerges to support SMART, uncertainty remains regarding optimal technical parameters, such as optimal patient positioning, immobilization, image quality, and contouring protocols. Prior to clinical implementation of SMART, we conducted a prospective study in healthy volunteers (HVs) to determine optimal technical parameters and to develop and practice a multidisciplinary SMART workflow. Methods HVs 18 years or older were eligible to participate in this IRB-approved study. Using a 0.35 T MRL, simulated adaptive treatments were performed by a multi-disciplinary treatment team in HVs. For each scan, image quality parameters were assessed on a 5-point scale (5 = extremely high, 1 = extremely poor). Adaptive recontouring times were compared between HVs and subsequent clinical cases with a t-test. Results 18 simulated treatments were performed in HVs on MRL. Mean parameters for visibility of target, visibility of nearby organs, and overall image quality were 4.58, 4.62, and 4.62, respectively (range of 4–5 for all measures). In HVs, mean ART was 15.7 min (range 4–35), comparable to mean of 16.1 (range 7–33) in the clinical cases (p = 0.8963). Using HV cases, optimal simulation and contouring guidelines were developed across a range of disease sites and have since been implemented clinically. Conclusions Prior to clinical implementation of SMART, scans of HVs on an MRL resulted in acceptable image quality and target visibility across a range of organs with similar ARTs to clinical SMART. We continue to utilize HV scans prior to clinical implementation of SMART in new disease sites and to further optimize target tracking and immobilization. Further study is needed to determine the optimal duration of HV scanning prior to clinical implementation.
- Published
- 2020