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Use of a healthy volunteer imaging program to optimize clinical implementation of stereotactic MR-guided adaptive radiotherapy.
Boyle, Patrick J; Huynh, Elizabeth; Boyle, Sara; Campbell, Jennifer; Penney, Jessica; Usta, Iquan; Neubauer Sugar, Emily; Hacker, Fred; Williams, Christopher; Cagney, Daniel; Mak, Raymond; Singer, Lisa.
Afiliação
  • Boyle PJ; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Huynh E; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Boyle S; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Campbell J; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Penney J; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Usta I; Lahey Medical Center, Peabody, MA, USA.
  • Neubauer Sugar E; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Hacker F; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Williams C; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Cagney D; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Mak R; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
  • Singer L; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Article em En | MEDLINE | ID: mdl-33305025
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Observational_studies / Sysrev_observational_studies Aspecto: Implementation_research Idioma: En Revista: Tech Innov Patient Support Radiat Oncol Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Observational_studies / Sysrev_observational_studies Aspecto: Implementation_research Idioma: En Revista: Tech Innov Patient Support Radiat Oncol Ano de publicação: 2020 Tipo de documento: Article