Evidence map›Paper›PMID 35391765›Full record

ArticleRadiology. Artificial intelligence2022

Clinical Assessment of Deep Learning-based Super-Resolution for 3D Volumetric Brain MRI.

Jeffrey D Rudie, Tyler Gleason, Matthew J Barkovich, David M Wilson, Ajit Shankaranarayanan, Tao Zhang, Long Wang, Enhao Gong, Greg Zaharchuk, Javier E Villanueva-Meyer

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

Article in Radiology. Artificial intelligence, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 pooled it
11.5field-weighted citation impact, top 1% 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

51 citing papers in PubMed, 2 syntheses or guidelines pooled it, 84 citations in OpenAlex.

  1. Guideline
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Effects of Artificial Intelligence-based Reconstruction on Image Quality and Voxel-based Morphometry Analysis of Atrophy in Accelerated MPRAGE.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026
    Article
  8. The Effect of AI on the Radiologist Workforce: A Task-Based Analysis.medRxiv : the preprint server for health sciences · 2025
    Article
  9. Article
  10. Using Deep Learning to Simultaneously Reduce Noise and Motion Artifacts in Brain MR Imaging.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025
    Article
  11. Article
  12. Article
  13. Article
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  15. Article
  16. Review
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  19. Article
  20. Deep learning-based Intraoperative MRI reconstruction.European radiology experimental · 2025
    Article
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

10 authors at 1 institution in 1 country.

Jeffrey D RudieDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID https://orcid.org/0000-0001-8609-8421
Tyler GleasonDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID https://orcid.org/0000-0003-0752-8329
Matthew J BarkovichDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID 0000-0002-8257-423X
David M WilsonDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID 0000-0002-1095-046X
Ajit ShankaranarayananDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID 0000-0001-9395-8768
Tao ZhangDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID 0000-0002-3147-794X
Long WangDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).
Enhao GongDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).
Greg ZaharchukDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID 0000-0001-5781-8848
Javier E Villanueva-MeyerDepartment of Radiology & Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, L-352, San Francisco, CA 94143 (J.D.R., T.G., M.J.B., D.M.W., J.E.V.M.); Subtle Medical, Menlo Park, Calif (A.S., T.Z., L.W., E.G.); and Department of Radiology, Stanford University, Stanford, Calif (G.Z.).ORCID https://orcid.org/0000-0002-5910-0757
Stanford University · US

Funding

Low- and Zero-dose Contrast-enhanced MRI Using Deep LearningR44EB027560 · NIBIB · SUBTLE MEDICAL, INC. · PI GONG, ENHAO · 2019 to 2021
$1.7M
NIBIB NIH HHS R44 EB027560
6 · The paper itself

Abstract

Artificial intelligence (AI)-based image enhancement has the potential to reduce scan times while improving signal-to-noise ratio (SNR) and maintaining spatial resolution. This study prospectively evaluated AI-based image enhancement in 32 consecutive patients undergoing clinical brain MRI. Standard-of-care (SOC) three-dimensional (3D) T1 precontrast, 3D T2 fluid-attenuated inversion recovery, and 3D T1 postcontrast sequences were performed along with 45% faster versions of these sequences using half the number of phase-encoding steps. Images from the faster sequences were processed by a Food and Drug Administration-cleared AI-based image enhancement software for resolution enhancement. Four board-certified neuroradiologists scored the SOC and AI-enhanced image series independently on a five-point Likert scale for image SNR, anatomic conspicuity, overall image quality, imaging artifacts, and diagnostic confidence. While interrater κ was low to fair, the AI-enhanced scans were noninferior for all metrics and actually demonstrated a qualitative SNR improvement. Quantitative analyses showed that the AI software restored the high spatial resolution of small structures, such as the septum pellucidum. In conclusion, AI-based software can achieve noninferior image quality for 3D brain MRI sequences with a 45% scan time reduction, potentially improving the patient experience and scanner efficiency without sacrificing diagnostic quality.

Indexed as

Brain/Brain StemCNSMR ImagingReconstruction Algorithms

Identifiers

PMID35391765
PMCPMC8980882
OpenAlexW4205454992

What OpenQuestion holds

Textmetadata
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.