MétaCan
Menu
Back to cohort
Record W2323291829 · doi:10.1097/rct.0000000000000064

The Effect of Respiratory and Cardiac Motion in Liver Diffusion Tensor Imaging (DTI)

2014· article· en· W2323291829 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Computer Assisted Tomography · 2014
Typearticle
Languageen
FieldMedicine
TopicMRI in cancer diagnosis
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster University
Fundersnot available
KeywordsMedicineDiffusion MRIRadiologyMagnetic resonance imaging

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the effect of respiratory and cardiac motion on diffusion tensor imaging (DTI) metrics in healthy human liver. METHODS: Fifteen healthy subjects, participating in either part of this study, were scanned using a 1.5-T magnetic resonance imaging (MRI) device. Coronal liver DTI (6 diffusion-encoding directions; b, 300 mm/s) during breath holding was compared to free breathing. Cardiac motion effects were evaluated by comparing breath-held DTI scans acquired during both diastole and systole. RESULTS: Free breathing resulted in a significantly increased mean diffusivity (P < 0.05), λ1 (P < 0.01), λ2 (P < 0.05), and λ3 (P < 0.01) compared to breath holding. During systole significant increases in fractional anisotropy (P < 0.05), mean diffusivity (P < 0.05), and λ1 (P < 0.05), compared to systole, were found in the left lobe. The right lobe, which is less affected by cardiac motion, showed no significant change in DTI metrics over the cardiac cycle. CONCLUSIONS: Respiratory and cardiac motion tends to increase liver DTI metrics.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.321

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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