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Record W4281649170 · doi:10.1016/j.asmr.2022.04.020

Automated 3D Analysis of Clinical Magnetic Resonance Images Demonstrates Significant Reductions in Cam Morphology Following Arthroscopic Intervention in Contrast to Physiotherapy

2022· article· en· W4281649170 on OpenAlexaff
Jessica M. Bugeja, Ying Xia, Shekhar S. Chandra, Nicholas J. Murphy, Jillian Eyles, Libby Spiers, ‪Stuart Crozier‬, David J. Hunter, Jürgen Fripp, Craig Engstrom

Bibliographic record

VenueArthroscopy Sports Medicine and Rehabilitation · 2022
Typearticle
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsAlberta Bone and Joint Health Institute
FundersMedical Research CouncilAustralian e-Health Research CentreUniversity of QueenslandNational Health and Medical Research CouncilPfizerEli Lilly and Company
KeywordsMagnetic resonance imagingContrast (vision)MedicineMorphology (biology)Intervention (counseling)Physical therapyPhysical medicine and rehabilitationRadiologyComputer scienceArtificial intelligenceBiologyNursing

Abstract

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Purpose To obtain automated measurements of cam volume, surface area, and height from baseline (preintervention) and 12‐month magnetic resonance (MR) images acquired from male and female patients allocated to physiotherapy (PT) or arthroscopic surgery (AS) management for femoroacetabular impingement (FAI) in the Australian FASHIoN trial. Methods An automated segmentation pipeline (CamMorph) was used to obtain cam morphology data from three‐dimensional (3D) MR hip examinations in FAI patients classified with mild, moderate, or major cam volumes. Pairwise comparisons between baseline and 12‐month cam volume, surface area, and height data were performed within the PT and AS patient groups using paired t ‐tests or Wilcoxon signed‐rank tests. Results A total of 43 patients were included with 15 PT patients (9 males, 6 females) and 28 AS patients (18 males, 10 females) for premanagement and postmanagement cam morphology assessments. Within the PT male and female patient groups, there were no significant differences between baseline and 12‐month mean cam volume (male: 1269 vs 1288 mm 3 , t [16] = −0.39; female: 545 vs 550 mm, 3 t [10] = −0.78), surface area (male: 1525 vs 1491 mm 2 , t [16] = 0.92; female: 885 vs 925 mm, 2 t [10] = −0.78), maximum height (male: 4.36 vs 4.32 mm, t [16] = 0.34; female: 3.05 vs 2.96 mm, t [10] = 1.05) and average height (male: 2.18 vs 2.18 mm, t [16] = 0.22; female: 1.4 vs 1.43 mm, t [10] = −0.38). In contrast, within the AS male and female patient groups, there were significant differences between baseline and 12‐month cam volume (male: 1343 vs 718 mm 3 , W = 0.0; female: 499 vs 240 mm 3 , t [18] = 2.89), surface area (male: 1520 vs 1031 mm 2 , t (34) = 6.48; female: 782 vs 483 mm 2 , t (18) = 3.02), maximum‐height (male: 4.3 vs 3.42 mm, W = 13.5; female: 2.85 vs 2.24 mm, t (18) = 3.04) and average height (male: 2.17 vs 1.52 mm, W = 3.0; female: 1.4 vs 0.94 mm, W = 3.0). In AS patients, 3D bone models provided good visualization of cam bone mass removal postostectomy. Conclusions Automated measurement of cam morphology from baseline (preintervention) and 12‐month MR images demonstrated that the cam volume, surface area, maximum‐height, and average height were significantly smaller in AS patients following ostectomy, whereas there were no significant differences in these cam measures in PT patients from the Australian FASHIoN study. Level of Evidence Level II, cohort study.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.012
GPT teacher head0.373
Teacher spread0.361 · 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 teacher head, 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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Citations5
Published2022
Admission routes1
Has abstractyes

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