Evidence map›Paper›PMID 35088162›Full record

ArticleSkeletal radiology2022

CT-like MRI: a qualitative assessment of ZTE sequences for knee osseous abnormalities.

Upasana Upadhyay Bharadwaj, Adam Coy, Daria Motamedi, Dong Sun, Gabby B Joseph, Roland Krug, Thomas M Link

Open access · greenAbstract read
In one paragraph

Article in Skeletal radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.3field-weighted citation impact, top 4% 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

21 citing papers in PubMed, 34 citations in OpenAlex.

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  16. Utility of Zero Echo Time MRI for the Diagnosis and Characterization of Ankle Fractures.HSS journal : the musculoskeletal journal of Hospital for Special Surgery · 2024
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  19. Shoulder Bone Segmentation with DeepLab and U-Net.Osteology (Basel, Switzerland) · 2024
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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

7 authors at 1 institution in 2 countries.

Upasana Upadhyay BharadwajMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA. Upasana.Bharadwaj@ucsf.edu.ORCID http://orcid.org/0000-0002-4710-809X
Adam CoyMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
Daria MotamediMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
Dong SunMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
Gabby B JosephMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
Roland KrugMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
Thomas M LinkMusculoskeletal Imaging, Department of Radiology and Biomedical Imaging, University of California San Francisco, 185 Berry Street, Suite 350, San Francisco, CA, 94107, USA.
University of California, San Francisco · US

Funding

Biomedical Imaging for Clinician ScientistsT32EB001631 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI THOMAS M LINK · 2005 to 2026
$5.6M
Impact of Weight loss on Knee Joint Biochemical and Structural DegenerationR01AR064771 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LINK, THOMAS M · 2014 to 2019
$1.6M
NIAMS NIH HHS R01 AR064771NIBIB NIH HHS T32 EB001631
6 · The paper itself

Abstract

objectiveTo qualitatively evaluate the utility of zero echo-time (ZTE) MRI sequences in identifying osseous findings and to compare ZTE with optimized spoiled gradient echo (SPGR) sequences in detecting knee osseous abnormalities. MATERIALS AND

methodsZTE and standard knee MRI sequences were acquired at 3T in 100 consecutive patients. Three radiologists rated confidence in evaluating osseous abnormalities and image quality on a 5-grade Likert scale in ZTE compared to standard sequences. In a subset of knees (n = 57) SPGR sequences were also obtained, and diagnostic confidence in identifying osseous structures was assessed, comparing ZTE and SPGR sequences. Statistical significance of using ZTE over SPGR was characterized with a paired t-test.

resultsImage quality of the ZTE sequences was rated high by all reviewers with 278 out of 299 (100 studies, 3 radiologists) scores ≥ 4 on the Likert scale. Diagnostic confidence in using ZTE sequences was rated "very high confidence" in 97%, 85%, 71%, and 73% of the cases for osteophytosis, subchondral cysts, fractures, and soft tissue calcifications/ossifications, respectively. In 74% of cases with osseous findings, reviewer scores indicated confidence levels (score ≥ 3) that ZTE sequences improved diagnostic certainty over standard sequences. The diagnostic confidence in using ZTE over SPGR sequences for osseous structures as well as abnormalities was favorable and statistically significant (p < 0.01).

conclusionIncorporating ZTE sequences in the standard knee MRI protocol was technically feasible and improved diagnostic confidence for osseous findings in relation to standard MR sequences. In comparison to SPGR sequences, ZTE improved assessment of osseous abnormalities.

Indexed as

Bone and BonesMagnetic Resonance ImagingHumansTomography, X-Ray ComputedBone diseasesDiagnostic imagingKneeKnee jointMagnetic resonance imaging/methods

Identifiers

PMID35088162
PMCPMC9198000
OpenAlexW4210749447

What OpenQuestion holds

Textmetadata
LicenceTDM
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.