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Record W4323310158 · doi:10.21203/rs.3.rs-2631622/v1

Validation of a shortened MR imaging protocol for pediatric spinal pathology

2023· preprint· en· W4323310158 on OpenAlexaff
Winnie Shu Yu Wu, Elka Miller, Julie Hurteau-Miller, Madhura Thipse, Cassandra Kapoor, Richard Webster, David McAuley, Albert Tu

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicSpinal Dysraphism and Malformations
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineSyrinx (medicine)Magnetic resonance imagingWork-upRadiologyLumbarSyringomyelia

Abstract

fetched live from OpenAlex

Abstract Objective Conventional pediatric spine MRI protocols have multiple sequences resulting in long acquisition times. Sedation is consequently required. This study evaluates the diagnostic capability of a limited MRI spine protocol for selected common pediatric indications. Methods Spine MRIs at CHEO between 2017 and 2020 were reviewed across pediatric patients younger than four years old. Two blinded neuroradiologists reviewed limited scan sequences and results were independently compared to previously reported findings from the complete imaging series. T2 sagittal sequences from the craniocervical junction to sacrum and T1 axial sequence of the lumbar spine constitute the short protocol, with the outcomes of interest being cerebellar ectopia, syrinx, level of conus, filum < 2mm, fatty filum, and spinal dysraphism. Results 105 studies were evaluated in 54 male and 51 female patients (mean age 19.2 months). The average combined scan time of the limited sequences was 15 minutes compared to 35 minutes for conventional protocols (delta = 20 minutes). The average percent agreement between full and limited sequences was > 95% in all but identifying a filum < 2mm, where the percent agreement was 87%. Using limited MR sequences had high sensitivity (> 0.91) and specificity (> 0.99) for the detection of cerebellar ectopia, syrinx, fatty filum, and spinal dysraphism. Conclusion This study demonstrates that selected spinal imaging sequences allow for consistent and accurate diagnosis of specific clinical conditions. A limited spine imaging protocol has potential as a screening test to reduce the need for full sequence MRI scans. Further work is needed to determine utility of selected imaging for other clinical indications.

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)0.002
metaresearch head score (Gemma)0.001
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.417
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.183
GPT teacher head0.505
Teacher spread0.322 · 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
GenreProtocol

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

Citations1
Published2023
Admission routes1
Has abstractyes

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