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Record W2139894346 · doi:10.1148/radiol.12112640

Augmented Reality Visualization with Use of Image Overlay Technology for MR Imaging–guided Interventions: Assessment of Performance in Cadaveric Shoulder and Hip Arthrography at 1.5 T

2012· article· en· W2139894346 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRadiology · 2012
Typearticle
Languageen
FieldComputer Science
TopicAugmented Reality Applications
Canadian institutionsQueen's University
FundersNational Cancer Institute
KeywordsMedicineCadaveric spasmCadaverShouldersMagnetic resonance imagingNuclear medicineOverlayShoulder jointOperator (biology)RadiologySurgeryComputer science

Abstract

fetched live from OpenAlex

PURPOSE: To prospectively assess overlay technology in providing accurate and efficient targeting for magnetic resonance (MR) imaging-guided shoulder and hip joint arthrography. MATERIALS AND METHODS: A prototype augmented reality image overlay system was used in conjunction with a clinical 1.5-T MR imager. A total of 24 shoulder joint and 24 hip joint injections were planned in 12 human cadavers. Two operators (A and B) participated, each performing procedures on different cadavers using image overlay guidance. MR imaging was used to confirm needle positions, monitor injections, and perform MR arthrography. Accuracy was assessed according to the rate of needle adjustment, target error, and whether the injection was intraarticular. Efficiency was assessed according to arthrography procedural time. Operator differences were assessed with comparison of accuracy and procedure times between the operators. Mann-Whitney U test and Fisher exact test were used to assess group differences. RESULTS: Forty-five arthrography procedures (23 shoulders, 22 hips) were performed. Three joints had prostheses and were excluded. Operator A performed 12 shoulder and 12 hip injections. Operator B performed 11 shoulder and 10 hip injections. Needle adjustment rate was 13% (six of 45; one for operator A and five for operator B). Target error was 3.1 mm±1.2 (standard deviation) (operator A, 2.9 mm±1.4; operator B, 3.5 mm±0.9). Intraarticular injection rate was 100% (45 of 45). The average arthrography time was 14 minutes (range, 6-27 minutes; 12 minutes [range, 6-25 minutes] for operator A and 16 minutes [range, 6-27 min] for operator B). Operator differences were not significant with regard to needle adjustment rate (P=.08), target error (P=.07), intraarticular injection rate (P>.99), and arthrography time (P=.22). CONCLUSION: Image overlay technology provides accurate and efficient MR guidance for successful shoulder and hip arthrography in human cadavers.

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.

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)0.000
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: none
Teacher disagreement score0.644
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.046
GPT teacher head0.357
Teacher spread0.311 · 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