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Record W4382537060 · doi:10.3174/ajnr.a7907

MR Imaging Findings in a Large Population of Autoimmune Encephalitis

2023· article· en· W4382537060 on OpenAlexaff
S. Gillon, M. Chan, Joshua Chen, Elan L. Guterman, Xin Wu, Christine M. Glastonbury, Yi Li

Bibliographic record

VenueAmerican Journal of Neuroradiology · 2023
Typearticle
Languageen
FieldMedicine
TopicAutoimmune Neurological Disorders and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineLimbic encephalitisAutoimmune encephalitisAutoantibodyEncephalitisPathologyAntibodyPopulationImmunologyInternal medicine

Abstract

fetched live from OpenAlex

<h3>BACKGROUND AND PURPOSE:</h3> Autoimmune encephalitis is a rare condition in which autoantibodies attack neuronal tissue, causing neuropsychiatric disturbances. This study sought to evaluate MR imaging findings associated with subtypes and categories of autoimmune encephalitis. <h3>MATERIALS AND METHODS:</h3> Cases of autoimmune encephalitis with specific autoantibodies were identified from the medical record (2009–2019). Cases were excluded if no MR imaging of the brain was available, antibodies were associated with demyelinating disease, or &gt;1 concurrent antibody was present. Demographics, CSF profile, antibody subtype and group (group 1 intracellular antigen or group 2 extracellular antigen), and MR imaging features at symptom onset were reviewed. Imaging and clinical features were compared across antibody groups using χ<sup>2</sup> and Wilcoxon rank-sum tests. <h3>RESULTS:</h3> Eighty-five cases of autoimmune encephalitis constituting 16 distinct antibodies were reviewed. The most common antibodies were anti-<i>N</i>-methyl-D-aspartate (<i>n</i> = 41), anti-glutamic acid decarboxylase (<i>n</i> = 7), and anti-voltage-gated potassium channel (<i>n</i> = 6). Eighteen of 85 (21%) were group 1; and 67/85 (79%) were group 2. The median time between MR imaging and antibody diagnosis was 14 days (interquartile range, 4–26 days). MR imaging had normal findings in 33/85 (39%), and 20/33 (61%) patients with normal MRIs had anti-<i>N</i>-methyl-D-aspartate receptor antibodies. Signal abnormality was most common in the limbic system (28/85, 33%); 1/68 (1.5%) had susceptibility artifacts. Brainstem and cerebellar involvement were more common in group 1, while leptomeningeal enhancement was more common in group 2. <h3>CONCLUSIONS:</h3> Sixty-one percent of patients with autoimmune encephalitis had abnormal brain MR imaging findings at symptom onset, most commonly involving the limbic system. Susceptibility artifact is rare and makes autoimmune encephalitis less likely as a diagnosis. Brainstem and cerebellar involvement were more common in group 1, while leptomeningeal enhancement was more common in group 2.

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 score0.016
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.011
GPT teacher head0.287
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.

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
Published2023
Admission routes1
Has abstractyes

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