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Record W3009655771 · doi:10.1002/jmri.27115

Rotator Cuff Tendon Assessment in Symptomatic and Control Groups Using Quantitative MRI

2020· article· en· W3009655771 on OpenAlexaboutno aff
Aria Ashir, Yajun Ma, Saeed Jerban, Hyungseok Jang, Zhao Wei, Nicole K. Le, Jiang Du, Eric Y. Chang

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2020
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Neurological Disorders and StrokeNational Institutes of HealthU.S. Department of Veterans Affairs
KeywordsMedicineAsymptomaticShouldersTendinopathyTendinosisRotator cuffRandomized controlled trialMagnetic resonance imagingTendonPopulationSurgeryNuclear medicineRadiology

Abstract

fetched live from OpenAlex

Background Relatively weak correlations between patient symptoms and rotator cuff tendon (RCT) tearing have been reported; however, the relationship between symptoms and tendinosis has been less well‐studied. Purpose/Hypothesis To use quantitative MRI to assess the bilateral RCTs in shoulders of both patients with unilateral symptomatic tendinopathy and control subjects. We hypothesized that quantitative MRI measures would differ between symptomatic patients and controls. Study Type Prospective imaging study. Population/Subjects In all, 48 shoulders from 24 subjects (mean age, 32.8 years), including 14 patients with unilateral symptomatic tendinopathy and 10 asymptomatic controls. Field Strength/Sequence 3T/3D ultrashort echo time Cones sequence with magnetization transfer preparation (UTE‐Cones‐MT) and Carr–Purcell–Meiboom–Gill. Assessment Macromolecular fraction (MMF) and T2 relaxation were measured in four regions of the superior RCT, including all‐segments, and lateral‐third, bursal‐sided, and articular‐sided segments. The Western Ontario Rotator Cuff (WORC) index and visual analog scale were assessed. Statistical Tests Three shoulder groups were evaluated, including symptomatic shoulders, contralateral asymptomatic shoulders in patients, and asymptomatic controls. MMF and T2 values were compared between groups using a bootstrap‐based comparison of means. Results Significant differences were found in both MMF and T2 values between symptomatic and control RCTs when analyzing all‐segments (P = 0.027 and P = 0.006, respectively) and articular‐sided segments (both P = 0.001). Significant differences between asymptomatic RCTs in patients and control RCTs were also found, including MMF in all four anatomic regions analyzed (P = 0.024–0.044), as well as T2 in all‐segments (P = 0.003), bursal‐sided segments (P = 0.021), and articular‐sided segments (P = 0.002). No significant differences in MMF (P = 0.420–0.950) or T2 (P = 0.380–0.910) were seen between ipsilateral symptomatic and contralateral asymptomatic RCTs in patients. Data Conclusion Symptomatic RCTs showed significantly lower MMF values and higher T2 values compared with control RCTs. In patients with unilateral symptomatic tendinopathy, the contralateral shoulder can demonstrate asymptomatic tendinopathy, which can be quantified using MMF or T2. Evidence Level 2 Technical Efficacy Stage 2. J. Magn. Reson. Imaging 2020;52:864–872.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.332
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations23
Published2020
Admission routes1
Has abstractyes

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