Diffusion Magnetic Resonance Imaging with Applications to Cardiac Muscle: Short Review
Bibliographic record
Abstract
Abstract This review describes in brief recent magnetic resonance imaging (MRI) methods for assessing cardiac structure in healthy and pathologic state using diffusion-weighted (DW) and diffusion tensor imaging (DTI) approaches. A background on the theory and MR pulse sequences employed in DW/DT imaging is given, along with the calculation of diffusion tensor (D), apparent diffusion coefficient (ADC) and fractional anisotropy (FA). Parametric maps derived from DW/DT images can quantify microstructure alterations due to fibrotic collagen deposition, along with associated changes in cardiac muscle anisotropy. Representative examples of ADC and FA parametric maps are shown from ex vivo high-resolution DT images of explanted healthy and scarred hearts obtained from pre-clinical investigations. Furthermore, examples of fiber tractography demonstrating DTI-based 3D (three-dimensional) reconstruction of fiber directions within the heart are illustrated using advanced open-source software. Lastly, future developments and potential translation of DW/DT methods into routine clinical evaluation for cardiac MR imaging protocols are highlighted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".