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Record W4380589751 · doi:10.1002/jmri.28840

Characterizing the Myoarchitecture of the Supraspinatus and Infraspinatus Muscles With <scp>MRI</scp> Using Diffusion Tensor Imaging

2023· article· en· W4380589751 on OpenAlexafffund
Cyril Tous, Alexandre Jodoin, Beau Pontré, Detlev Grabs, Mickaël Begon, Nathalie J. Bureau, Elijah Van Houten

Bibliographic record

VenueJournal of Magnetic Resonance Imaging · 2023
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsUniversité de SherbrookeUniversité de MontréalUniversité du Québec à Trois-RivièresCentre Hospitalier de l’Université de Montréal
FundersRéseau en Bio-Imagerie du Quebec
KeywordsMedicineDiffusion MRIRotator cuffRepeatabilityAnatomyNuclear medicineMagnetic resonance imagingRadiologyMathematics

Abstract

fetched live from OpenAlex

Background The societal cost of shoulder disabilities in our aging society keeps rising. Providing biomarkers of early changes in the microstructure of rotator cuff (RC) muscles might improve surgical planning. Elevation angle (E1A) and pennation angle (PA) assessed by ultrasound change with RC tears. Furthermore, ultrasounds lack repeatability. Purpose To propose a repeatable framework to quantify the myocyte angulation in RC muscles. Study Type Prospective. Subjects Six asymptomatic healthy volunteers (1 female aged 30 years; 5 males, mean age 35 years, range 25–49 years), who underwent three repositioned scanning sessions (10 minutes apart) of the right infraspinatus muscle (ISPM) and supraspinatus muscle (SSPM). Field Strength/Sequence 3‐T, T1‐weighted and diffusion tensor imaging (DTI; 12 gradient encoding directions, b‐values of 500 and 800 s/mm2). Assessment Each voxel was binned in percentage of depth defined by the shortest distance in the antero‐posterior direction (manual delineation), i.e. the radial axis. A second order polynomial fit for PA across the muscle depth was used, while E1A described a sigmoid across depth: . Statistical Tests Repeatability was assessed with the nonparametric Wilcoxon's rank‐sum test for paired comparisons across repeated scans in each volunteer for each anatomical muscle region and across repeated measures of the radial axis. A P‐value <0.05 was considered statistically significant. Results In the ISPM, E1A was constantly negative, became helicoidal, then mainly positive across the antero‐posterior depth, respective at the caudal, central and cranial regions. In the SSPM, posterior myocytes ran more parallel to the intramuscular tendon (), while anterior myocytes inserted with a pennation angle (). E1A and PA were repeatable in each volunteer (error < 10%). Intra‐repeatability of the radial axis was achieved (error < 5%). Data Conclusion ElA and PA in the proposed framework of the ISPM and SSPM are repeatable with DTI. Variations of myocyte angulation in the ISPM and SSPM can be quantified across volunteers. Evidence Level 2 Technical Efficacy Stage 2

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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".

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Citations7
Published2023
Admission routes2
Has abstractyes

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