Evidence map›Paper›PMID 31655315›Full record

ArticleEuropean journal of radiology2019

Assessment of an in vitro model of rotator cuff degeneration using quantitative magnetic resonance and ultrasound imaging with biochemical and histological correlation.

Tan Guo, Ya-Jun Ma, Rachel A High, Qingbo Tang, Jonathan H Wong, Michal Byra, Adam C Searleman, Sarah C To, Lidi Wan, Nicole Le and 2 more

Open access · greenAbstract readEvaluation Study
In one paragraph

Article in European journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

12 authors at 4 institutions in 3 countries.

Tan GuoDepartment of Radiology, Beijing Hospital, Beijing, China; Department of Radiology, University of California, San Diego, CA, United States. Electronic address: guotan369@hotmail.com.
Ya-Jun MaDepartment of Radiology, University of California, San Diego, CA, United States. Electronic address: yam013@ucsd.edu.
Rachel A HighDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: rachelahigh@gmail.com.
Qingbo TangDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: q1tang@ucsd.edu.
Jonathan H WongDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: jhw033@ucsd.edu.
Michal ByraDepartment of Radiology, University of California, San Diego, CA, United States; Department of Ultrasound, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland. Electronic address: byra.michal@gmail.com.
Adam C SearlemanDepartment of Radiology, University of California, San Diego, CA, United States. Electronic address: asearleman@ucsd.edu.
Sarah C ToDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: sarahcto23@gmail.com.
Lidi WanDepartment of Radiology, University of California, San Diego, CA, United States. Electronic address: qldxt_wld1993@163.com.
Nicole LeDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: lenicolem@gmail.com.
Jiang DuDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: jiangdu@ucsd.edu.
Eric Y ChangDepartment of Radiology, University of California, San Diego, CA, United States; Research Service, VA San Diego Healthcare System, San Diego, CA, United States. Electronic address: ericchangmd@gmail.com.
University of California, San Diego · USVA San Diego Healthcare System · USBeijing Hospital · CNInstitute of Fundamental Technological Research · PL

Funding

Quantitative UTE MR Imaging: Sensitive Biomarkers for OsteoarthritisR01AR062581 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2013 to 2022
$4.1M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
UTE Magnetic Resonance Imaging: New Biomarkers for Multiple SclerosisR01NS092650 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2015 to 2019
$1.9M
Three-dimensional Ultrashort Echo Time Magnetic Resonance Imaging of EnthesesR01AR075825 · NIAMS · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI CHANG, ERIC Y · 2019 to 2023
$1.8M
Ultrashort Echo Time Magnetic Resonance Imaging of Bone Stress InjuriesR21AR073496 · NIAMS · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI CHANG, ERIC Y · 2018 to 2019
$343k
Quantitative Magnetic Resonance Imaging of Human Rotator Cuff TendonI01CX001388 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI CHANG, ERIC Y · 2016 to 2024
–
Quantitative Measurement of Joint pH with Magnetic Resonance ImagingI01RX002604 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI CHANG, ERIC Y · 2018 to 2022
–
CSRD VA I01 CX001388NIAMS NIH HHS R01 AR062581NIAMS NIH HHS R01 AR075825NIAMS NIH HHS R21 AR073496NIBIB NIH HHS T32 EB005970NINDS NIH HHS R01 NS092650RRD VA I01 RX002604
6 · The paper itself

Abstract

purposeQuantitative imaging methods could improve diagnosis of rotator cuff degeneration, but the capability of quantitative MR and US imaging parameters to detect alterations in collagen is unknown. The goal of this study was to assess quantitative MR and US imaging measures for detecting abnormalities in collagen using an in vitro model of tendinosis with biochemical and histological correlation.

method36 pieces of supraspinatus tendons from 6 cadaveric donors were equally distributed into 3 groups (2 subjected to different concentrations of collagenase and a control group). Ultrashort echo time MR and US imaging measures were performed to assess changes at baseline and after 24 h of enzymatic digestion. Biochemical and histological measures, including brightfield, fluorescence, and polarized microscopy, were used to verify the validity of the model and were compared with quantitative imaging parameters. Correlations between the imaging parameters and biochemically measured digestion were analyzed.

resultsAmong the imaging parameters, macromolecular fraction (MMF), adiabatic T1ρ, T2*, and backscatter coefficient (BSC) were useful in differentiating between the extent of degeneration among the 3 groups. MMF strongly correlated with collagen loss (r=-0.81; 95% confidence interval [CI]: -0.90,-0.66), while the adiabatic T1ρ (r = 0.66; CI: 0.42,0.81), T2* (r = 0.58; CI: 0.31,0.76), and BSC (r = 0.51; CI: 0.22,0.72) moderately correlated with collagen loss.

conclusionsMMF, adiabatic T1ρ, and T2* measured and US BSC can detect alterations in collagen. Of the quantitative MR and US imaging measures evaluated, MMF showed the highest correlation with collagen loss and can be used to assess rotator cuff degeneration.

Indexed as

AdultCadaverCollagenasesEvaluation Studies as TopicHumansIn Vitro TechniquesMagnetic Resonance ImagingMiddle AgedReproducibility of ResultsRotator CuffRotator Cuff InjuriesUltrasonographyCollagenasesQuantitative MRIQuantitative ultrasoundRotator cuff tendonTendinopathyUTE

Identifiers

PMID31655315
PMCPMC6881559
OpenAlexW2981146509

What OpenQuestion holds

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LicenceTDM
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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.