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Record W2587566976 · doi:10.1093/neuonc/now188.219

P09.10 Clinical fMRI in low grade glioma patients: impact on surgical decision making and patient outcomes

2016· article· en· W2587566976 on OpenAlexaff
Suzanne Kosteniuk, Jonathan C. Lau, Joseph Megyesi

Bibliographic record

VenueNeuro-Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsWestern UniversityRobarts Clinical Trials
Fundersnot available
KeywordsMedicineSurgical excisionGliomaClinical decision makingPhysical medicine and rehabilitationSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

BACKGROUND: This study aims to evaluate the impact of preoperative functional magnetic resonance imaging (fMRI) on low grade glioma (LGG) patients’ outcomes and surgical planning. METHODS: In this retrospective matched cohort study of a single surgeon’s patients, we are comparing two groups of LGG patients (WHO grade II) based on exposure to fMRI. Sixteen LGG patients who underwent fMRI were selected, and 32 control (non-fMRI exposed) patients are being selected through propensity score matching from a pool of 764 brain tumour patients. Outcomes being compared include time between clinical presentation and surgery, adverse surgical outcomes, extent of tumour resection, preoperative and postoperative functional status, and overall mortality. To assess the impact of fMRI data on clinicians’ decision making process, neurosurgeons within a single centre are completing questionnaires regarding treatment options for each LGG fMRI patient based on clinical data and structural imaging before and after fMRI. The questionnaire includes questions regarding expectations of the tumours’ eloquence, preferred treatment option, expected extent of resection, and degree of confidence that the preferred treatment option is optimal. RESULTS: Within the group of 16 LGG patients who have undergone fMRI studies over a 12-year period, mean age was 40 years, and most presented with seizures (81%). Most lesions were left-sided (81%), and the lobes most commonly involved were frontal (75%) and temporal (31%). Patients underwent either craniotomy (50%), stereotactic biopsy (25%) or nonsurgical management (25%). Nine patients had 1p/19q analysis performed, and three (33%) showed 1p/19q codeletion. Mean time between clinical presentation and fMRI was 3.3 ± 1.9 weeks. In patients who were initially managed surgically, mean time between fMRI and surgery was 3.8 ± 2.0 weeks. Surgical complications or post-operative neurological deficits were seen in four patients who underwent craniotomy (50%) and one patient who underwent biopsy (25%). All complications were mild and/or temporary. In surgical patients, between pre-operative assessment and eight week post-operative follow-up, mean modified Rankin scale improved from 1.80 ± 0.79 to 1.50 ± 0.97. In our cohort, 5-year mortality was 12.5% (mean follow-up duration 5.46 years). CONCLUSIONS: Data analysis is ongoing with plans to compare relevant demographics and outcomes of brain tumour patients based on exposure to fMRI, and to analyse questionnaires to elucidate how surgeons incorporate fMRI data into their therapeutic approach.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.382
Teacher spread0.351 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2016
Admission routes1
Has abstractyes

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