MétaCan
Menu
Back to cohort
Record W4213419451 · doi:10.1007/s00256-022-04018-4

MRI in axial spondyloarthritis: understanding an ‘ASAS-positive MRI’ and the ASAS classification criteria

2022· review· en· W4213419451 on OpenAlexaff
Torsten Diekhoff, R. Lambert, Kay‐Geert Hermann

Bibliographic record

VenueSkeletal Radiology · 2022
Typereview
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsAlberta Medical AssociationUniversity of Alberta
FundersCharité – Universitätsmedizin Berlin
KeywordsMedicineSacroiliitisAxial spondyloarthritisMagnetic resonance imagingRadiologySimplicityClinical PracticeDifferential diagnosisMedical physicsPhysical therapyPathology

Abstract

fetched live from OpenAlex

In 2009, the Assessment of SpondyloArthritis international Society (ASAS) published a definition of 'active sacroiliitis on magnetic resonance imaging (MRI) for classification of axial spondyloarthritis'. This new definition of an 'ASAS-positive MRI' was integral to new classification criteria for axial spondyloarthritis that were published in the same year. The ASAS MRI definition had the considerable advantage of simplicity and the definition gained popularity as guidance for interpreting MRI of the sacroiliac joints in clinical practice. However, classification criteria are not designed for use in clinical practice with the consequence that overreliance on the presence of bone marrow edema, which is the principal determinant of an 'ASAS-positive MRI', may result in a tendency to overcall inflammatory sacroiliitis in the clinical setting. This article aims to inform the reader about the rationale behind the ASAS definition of a positive MRI and ASAS classification criteria, their proper use in research and why they should not be used in clinical practice. The article also contains guidance for an updated imaging protocol and interpretation of images including typical imaging findings, differential diagnosis, and common pitfalls.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.083
GPT teacher head0.359
Teacher spread0.276 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations70
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueSkeletal RadiologySame topicSpondyloarthritis Studies and TreatmentsFrench-language works237,207