Evidence map›Paper›PMID 40157988›Full record

ArticleScientific reports2025

Impact of optimized and conventional facility designs on outpatient abdominal MRI workflow efficiency.

Alexander Herold, Leo L Tsai, Wei-Ching Lo, Azadeh Tabari, Barbara D Wichtmann, Andrew Sharp, Bryan Clifford, Min Lang, Sean P Hartman, Lauren M Melski and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

16 authors.

Alexander HeroldDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Leo L TsaiDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Wei-Ching LoSiemens Medical Solutions USA, Boston, MA, USA.
Azadeh TabariDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Barbara D WichtmannDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Andrew SharpDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Bryan CliffordSiemens Medical Solutions USA, Boston, MA, USA.
Min LangDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Sean P HartmanDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Lauren M MelskiDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Majeed WaqasSiemens Medical Solutions USA, Boston, MA, USA.
Michael WeberDepartment of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
Oleg PianykhDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Susie Y HuangDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Mukesh G HarisinghaniDepartment of Radiology, Massachusetts General Hospital, Harvard University Medical School, Boston, MA, USA.
Onofrio A CatalanoDivision of Abdominal Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, White Building, Room 270, Boston, MA, 02114, USA. ocatalano@mgh.harvard.edu.ORCID http://orcid.org/0000-0001-7733-4138

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe goal of this study was to evaluate the outpatient workflow efficiency of an optimized facility (OF) compared to an established reference facility (RF) for abdominal magnetic resonance imaging (MRI).

methodsIn this retrospective study, we analyzed 2,723 contrast-enhanced liver and prostate MRI examinations conducted between March 2022 and April 2024. All examinations were performed on 3T scanners (MAGNETOM Vida, Siemens Healthineers) at two different imaging facilities within our institution. The optimized facility featured a three-bay setup, with each bay consisting of one magnet, two dockable tables, and one dedicated preparation room, while the reference facility utilized a single scanner-single table setup with one dedicated preparation room. Workflow metrics were extracted from scanner logs and electronic health records. Three-way ANOVA and chi-square tests were used to assess the impact of facility design, body region, and date on workflow metrics.

resultsThe OF significantly reduced mean table turnaround times (4.6 min vs. 8.3 min, p < 0.001) and achieved shorter total process cycle times for both liver (30.6 min vs. 32.7 min, p < 0.01) and prostate exams (32.5 min vs. 36.4 min, p < 0.001) compared to the RF. Additionally, the OF achieved turnaround times of ≤ 1 min in 37.2% of exams, compared to just 0.6% at the RF (p < 0.001). On-time performance was also notably higher at the OF (79.4% vs. 66.0%, p < 0.001). Furthermore, the mean time from patient arrival to exam start was reduced by 9 min at the OF (p < 0.001). Minor differences in acquisition times were observed between facilities, with both benefiting from deep learning reconstruction techniques.

conclusionThe optimized MRI facility demonstrated superior outpatient workflow efficiency compared to an already efficient reference facility, particularly in table turnover time, resulting in increased patient throughput for abdominal MRI examinations. These findings highlight that even highly efficient MRI facilities can significantly benefit from comprehensive redesign strategies.

Indexed as

AbdomenFacility Design and ConstructionMagnetic Resonance ImagingWorkflowFemaleHumansLiverMaleMiddle AgedOutpatientsRetrospective StudiesAbdominal MRIDeep learningDockable tablesTurnaround timeWorkflow optimization

Identifiers

PMID40157988
PMCPMC11954900

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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.