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Record W2049696735 · doi:10.1097/rli.0b013e31817e909f

Diffusion Tensor Magnetic Resonance Imaging of the Human Calf

2008· article· en· W2049696735 on OpenAlexaff
Nadja Saupe, Lawrence M. White, Marshall S. Sussman, Andrea Kassner, George Tomlinson, Michael D. Noseworthy

Bibliographic record

VenueInvestigative Radiology · 2008
Typearticle
Languageen
FieldMedicine
TopicAdvanced Neuroimaging Techniques and Applications
Canadian institutionsUniversity Health NetworkUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsDiffusion MRIFractional anisotropyMagnetic resonance imagingNuclear magnetic resonanceAnisotropyPhysicsNuclear medicineMedicineOpticsRadiology

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare diffusion tensor-magnetic resonance imaging (DT-MRI) of human calf muscles at 1.5 T and 3.0 T, and to measure a number of quantitative parameters to characterize diffusion anisotropy in organized muscle tissue using similar imaging parameters. METHODS AND MATERIALS: After Institutional Review Board approval and informed consent, five healthy volunteers were studied. Imaging was performed on both 1.5 T and 3.0 T MR systems using the similar imaging protocol. Diffusion-sensitized single-shot spin-echo echo planar imaging pulse sequences were used to collect 2-dimensional images through the calf. Imaging was performed using b-values of 0, 300, 500, and 700 s/mm. Image analyses and tensor calculations were performed offline using DT imaging studio (Johns Hopkins University, Baltimore, MD). The eigenvalues (lambda1, lambda2, lambda3), trace of the diffusion tensor (TrD), fractional anisotropy, relative anisotropy, and volume ratio were calculated in 3 different calf muscles (medial and lateral gastrocnemius and soleus). Signal-to-noise ratios (SNRs) were compared for both field strengths (1.5 T and 3.0 T), the different muscles and all b-values. A regression analysis was performed to look at within-subject effects (linear mixed effect model). RESULTS: No significant differences were found between all quantitative measured DT-MRI parameters, b-values, and muscle groups at 3.0 T and 1.5 T (P = 0.105; P = 0.719). The mean of SNR on the 2 different field strengths (3.0:1.5 T) was 1.64, which was significantly different (P < 0.0001). Significant differences in SNR in all 3 muscles were found between sequences using b = 300 s/mm and 700 s/mm (P < 0.001; P = 0.006) and between sequences using b = 300 s/mm and 500 s/mm (P < 0.001; P = 0.03), and 500 s/mm and 700 s/mm (P = 0.005; P = 0.03), respectively, for medial gastrocnemius and soleus muscle. CONCLUSIONS: This study demonstrates useful parameters to perform DT-MRI at 1.5 T and 3.0 T. DT-MRI at 1.5 T and 3.0 T provide in vivo validation of quantitative structural analysis of human skeleletal muscle.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.075
GPT teacher head0.327
Teacher spread0.252 · 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

Citations26
Published2008
Admission routes1
Has abstractyes

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