Evidence map›Paper›PMID 33305025›Full record

ArticleTechnical innovations & patient support in radiation oncology2020

Use of a healthy volunteer imaging program to optimize clinical implementation of stereotactic MR-guided adaptive radiotherapy.

Patrick J Boyle, Elizabeth Huynh, Sara Boyle, Jennifer Campbell, Jessica Penney, Iquan Usta, Emily Neubauer Sugar, Fred Hacker, Christopher Williams, Daniel Cagney and 2 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Technical innovations & patient support in radiation oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Patrick J BoyleBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Elizabeth HuynhBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Sara BoyleBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Jennifer CampbellBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Jessica PenneyBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Iquan UstaLahey Medical Center, Peabody, MA, USA.
Emily Neubauer SugarBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Fred HackerBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Christopher WilliamsBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Daniel CagneyBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Raymond MakBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Lisa SingerBrigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Brigham and Women's Hospital · USLahey Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMR-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.

methodsHVs 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

results18 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.

conclusionsPrior 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.

Indexed as

Adaptive radiotherapyMagnetic resonance imagingMR-linacTrainingWorkflow

Identifiers

PMID33305025
PMCPMC7710639
OpenAlexW3106656287

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.