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Record W3172858896 · doi:10.3390/neurolint13020025

Diagnostic Dilemma: An Atypical Case of Astrocytoma in a Patient with Relapsing–Remitting Multiple Sclerosis

2021· article· en· W3172858896 on OpenAlexaff
Chantal Kahovec, Aman Saini, Michael C. Levin

Bibliographic record

VenueNeurology International · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of SaskatchewanSaskatchewan Health Authority
Fundersnot available
KeywordsMedicineMultiple sclerosisMagnetic resonance imagingLesionRadiologyNeurosurgeryAstrocytomaNeuroimagingBrain tumorWhite matterPositron emission tomographyCraniotomyNeurological examinationPathologyGliomaSurgeryPsychiatry

Abstract

fetched live from OpenAlex

Distinguishing between tumefactive demyelinating lesions (TDLs) and brain tumors in multiple sclerosis (MS) can be challenging. A progressive course is highly common with brain tumors in MS and no single neuroimaging technique is foolproof when distinguishing between the two. We report a case of a 41-year-old female with relapsing-remitting multiple sclerosis, who had a suspicious lesion within the left frontal hemisphere, without a progressive course. The patient experienced paresthesias primarily to her right hand but remained stable without any functional decline and new neurological symptoms over the four years she was followed. The lesion was followed with brain magnetic resonance imaging (MRI) scans, positron emission tomography-computed tomography scans, and magnetic resonance spectroscopy. Together, these scans favored the diagnosis of a TDL, but a low-grade tumor was difficult to rule out. Examination of serial brain MRI scans showed an enlarging lesion in the left middle frontal gyrus involving the deep white matter. Neurosurgery was consulted and an elective left frontal awake craniotomy was performed. Histopathology revealed a grade II astrocytoma. This case emphasizes the importance of thorough and continuous evaluation of atypical MRI lesions in MS and contributes important features to the literature for timely diagnosis and treatment of similar cases.

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)0.005
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 score0.020
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.046
GPT teacher head0.299
Teacher spread0.254 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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