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Record W3092157907 · doi:10.1002/nbm.4427

High spatial resolution nerve‐specific DTI protocol outperforms whole‐brain DTI protocol for imaging the trigeminal nerve in healthy individuals

2020· article· en· W3092157907 on OpenAlexafffund
H. T. Danyluk, Tejas Sankar, Christian Beaulieu

Bibliographic record

VenueNMR in Biomedicine · 2020
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
FundersCanada Research Chairs
KeywordsDiffusion MRIFractional anisotropyTractographyMedicineFluid-attenuated inversion recoveryTrigeminal neuralgiaNuclear medicineMagnetic resonance imagingRadiologyAnesthesia

Abstract

fetched live from OpenAlex

Diffusion tensor imaging (DTI) can provide markers of axonal micro‐structure of the trigeminal nerve (cranial nerve five [CNV]), which may be affected in trigeminal neuralgia (TN) and other disorders. Previous attempts to image CNV have used low spatial resolution DTI protocols designed for whole‐brain acquisition that are susceptible to errors from partial volume effects, particularly with adjacent cerebrospinal fluid (CSF). The purpose of this study was to develop a nerve‐specific DTI protocol in healthy subjects that provides more accurate CNV tractography and diffusion quantification than whole‐brain protocols. Four DTI protocols were compared in five healthy individuals (age 22–45 years, three males) on a 3 T Siemens Prisma MRI scanner: two newly developed nerve‐specific high resolution (1.2 x 1.2 x 1.2 = 1.7 mm 3 ) DTI protocols without (3.5 minutes) and with CSF suppression (fluid‐attenuated inversion recovery [FLAIR]; 7.5 minutes) with limited slice‐coverage, and two typical whole‐brain protocols with either isotropic (2 x 2 x 2 = 8 mm 3 ) or thicker slice anisotropic (1.9 x 1.9 x 3 = 10.8 mm 3 ) voxels. Deterministic tractography was used to identify the CNV and quantify bilateral fractional anisotropy (FA), and mean (MD), axial (AD) and radial diffusivity (RD). CNV volume was determined by manual tracing on T1‐weighted images. High spatial resolution nerve‐specific protocols yielded better delineation of CNV, with less distortions and blurring, and markedly different diffusion parameters (42% higher FA, 35% lower MD, 27% lower RD and 43% lower AD) compared with the two lower resolution whole‐brain protocols. The anisotropic whole‐brain protocol showed a positive correlation between CNV FA and volume. The high resolution nerve‐specific protocol with FLAIR yielded additional reductions in CNV AD and MD with a value of 1.0 x 10 −3 mm 2 /s, approaching that expected for healthy young adult white matter. In conclusion, high resolution nerve‐specific DTI with FLAIR enhances the identification of CNV and provides more accurate quantification of diffusion compared with lower resolution whole‐brain approaches.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.557
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.120
GPT teacher head0.421
Teacher spread0.301 · 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 designNot applicable
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

Citations12
Published2020
Admission routes2
Has abstractyes

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