Evidence map›Paper›PMID 36466748›Full record

ArticleClinical and translational radiation oncology2023

Patterns of utilization and clinical adoption of 0.35 Tesla MR-guided radiation therapy in the United States - Understanding the transition to adaptive, ultra-hypofractionated treatments.

Michael D Chuong, Mary Ann Clark, Lauren E Henke, Amar U Kishan, Lorraine Portelance, Parag J Parikh, Michael F Bassetti, Himanshu Nagar, Stephen A Rosenberg, Minesh P Mehta and 7 more

Abstract read
In one paragraph

Article in Clinical and translational radiation oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

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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

17 authors.

Michael D ChuongMiami Cancer Institute, Miami, FL, United States.
Mary Ann ClarkViewRay, Inc., Denver, CO, United States.
Lauren E HenkeWashington University, School of Medicine, St. Louis, MO, United States.
Amar U KishanUniversity of California, Los Angeles Medical Center, Los Angeles, CA, United States.
Lorraine PortelanceUniversity of Miami, Miami, FL, United States.
Parag J ParikhHenry Ford Health System, Grosse Pointe Farms, MI, United States.
Michael F BassettiUniversity of Wisconsin, Madison, WI, United States.
Himanshu NagarWeill Cornell Medicine, New York, NY, United States.
Stephen A RosenbergH. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States.
Minesh P MehtaMiami Cancer Institute, Miami, FL, United States.
Tamer RefaatLoyola University Chicago, Stritch School of Medicine, Department of Radiation Oncology, Cardinal Bernardin Cancer Center, Maywood, IL, United States.
Justin M RineerOrlando Health, Orlando, FL, United States.
Adam SmithMcGlinn Cancer Institute at Reading Hospital, Tower Health, Reading, PA, United States.
Steven SeungProvidence Cancer Institute, Portland, OR, United States.
Bassem I ZakiDartmouth-Hitchcock Norris Cotton Cancer Center, Lebanon, NH, United States.
Martin FussViewRay, Inc., Denver, CO, United States.
Raymond H MakDana Farber/Brigham and Women's Cancer Center, Boston, MA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose/Objective: Magnetic resonance-guided radiation therapy (MRgRT) utilization is rapidly expanding worldwide, driven by advanced capabilities including continuous intrafraction visualization, automatic triggered beam delivery, and on-table adaptive replanning (oART). Our objective was to describe patterns of 0.35Tesla(T)-MRgRT (MRIdian) utilization in the United States (US) among early adopters of this novel technology. Materials/Methods: Anonymized administrative data from all US MRIdian treatment systems were extracted for patients completing treatment from 2014 to 2020. Detailed treatment information was available for all MRIdian linear accelerator (linac) systems and some cobalt systems. Results: Seventeen systems at 16 centers delivered 5736 courses and 36,389 fractions (fraction details unavailable for 1223 cobalt courses), of which 21.1% were adapted. Ultra-hypofractionation (UHfx) (1-5 fractions) was used in 70.3% of all courses. At least one adaptive fraction was used for 38.5% of courses (average 1.7 adapted fractions/course), with higher oART use in UHfx dose schedules (47.7% of courses, average 1.9 adapted fractions per course). The most commonly treated organ sites were pancreas (20.7%), liver (16.5%), prostate (12.5%), breast (11.5%), and lung (9.4%). Temporal trends show a compounded annual growth rate (CAGR) of 59.6% in treatment courses delivered, with a dramatic increase in use of UHfx to 84.9% of courses in 2020 and similar increase in use of oART to 51.0% of courses. Conclusions: This is the first comprehensive study reporting patterns of utilization among early adopters of MRIdian in the US. Intrafraction MR image-guidance, advanced motion management, and increasing adoption of adaptive radiation therapy has led to a substantial transition to ultra-hypofractionated regimens. 0.35

Indexed as

APBI, accelerated partial breast irradiationARTART, adaptive radiotherapyBED, biologically equivalent doseCAGR, compound annual growth rateCare patternsCBCT, cone beam computerized tomographyGDPR, General Data Protection RegulationGy, grayHIPAA, Health Insurance Portability and Accountability ActH&N, head and neckIGRT, image-guided radiation therapylinac, linear acceleratorMRgRT, magnetic resonance-guided radiotherapyMRIdian, 0.35Tesla(T)-MRgRTMR-IGRTMRI-guided radiotherapyMRI, magnetic resonance imagingMR, magnetic resonanceMVCT, mega-voltage CTNSCLC, non-small cell lung cancerOAR, organs at riskoARToART, on-table adaptive radiation therapyOn-table adaptive radiation therapyPHI, protected health informationPTV, planning target volumeRT, radiation therapySABR, stereotactic ablative radiation therapySBRTSBRT, stereotactic body radiotherapyStereotactic body radiotherapyT, TeslaUHfx, ultra-hypofractionated

Identifiers

PMID36466748
PMCPMC9712826

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Registered trials

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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.