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Record W2111821826 · doi:10.1186/1748-7161-10-s2-s7

Measurement of axial vertebral rotation using three-dimensional ultrasound images

2015· article· en· W2111821826 on OpenAlexafffund
Quang Nhat Vo, Edmond Lou, Lawrence H. Le

Bibliographic record

VenueScoliosis · 2015
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Alberta
FundersWomen and Children's Health Research InstituteNatural Sciences and Engineering Research Council of CanadaChildren's Health Research Institute
KeywordsMedicineVertebraUltrasoundRotation (mathematics)Cadaveric spasmNuclear medicine3D ultrasoundTransverse planeAnatomyOrthodonticsRadiologyArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Axial vertebral rotation (AVR) is one of the important parameters to evaluate the severity and predict the progression of scoliosis. However, the AVR measurements on radiographs may underestimate its actual value. This pilot study investigated a new three-dimensional (3D) ultrasound method to measure AVR. METHODS: Three cadaveric vertebrae T7, L1, and L3 were scanned with a 3D medical ultrasound system. Nine sets of ultrasound data, the vertebral rotation from 0 to 40° with 5° increments, were recorded from each vertebra. An in-house program was developed to reconstruct and measure the 3D vertebral images. The rotation of each reconstructed vertebra was determined by the angle between the line going through the centres of either laminae (L-L) or transverse processes (TP-TP) and a reference vertical plane. Three raters measured the rotation in 3 sessions, in which they used the mouse pointer to select the L-L or TP-TP according to their knowledge of vertebral anatomy. The program detected the 3D coordinates of these points and calculated the AVR. The intra-class correlation coefficients (ICCs) were used to calculate the intra-reliability and inter-reliability. The mean absolute difference (MAD±SD) and the range of difference (RD) between the actual values and the average measurements of each rater were computed to evaluate the accuracy of methods. RESULTS: When rotation was greater than 30° for both L1 and L3, all raters found it difficult to determine one of the lamina areas due to the lack of ultrasound information in an area behind the spinous process. Therefore, the corresponding measurements were excluded. The ICC values of the intra-reliability (L-L, TP-TP) for the three raters were (0.987, 0.991), (0.989, 0.998) and (0.997, 1.000), respectively; meanwhile, the inter-reliability were 0.991 for (L-L) and 0.992 for (TP-TP). All ICC values were greater than 0.98 indicating both methods were highly reliable. The MAD±SD values (L-L, TP-TP) for the three raters were (1.5±0.3°, 1.2±0.2°), (1.6±0.3°, 1.3±0.3°), and (1.7±0.5°, 0.9±0.2°), respectively. The RD (L-L, TP-TP) were (0-4.5°, 0-3.5°), (0-5.1°, 0-4.3°), and (0-5.1°, 0-2.8°) for the three raters, respectively. CONCLUSIONS: The (L-L) and (TP-TP) methods could be used to measure AVR reliability from the 3D ultrasound images.

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)0.000
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: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

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

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 head0.088
GPT teacher head0.312
Teacher spread0.224 · 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".

Quick stats

Citations17
Published2015
Admission routes2
Has abstractyes

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