Fat-water separated myocardial T1 mapping with IDEAL-T1 saturation recovery gradient echo imaging
Bibliographic record
Abstract
Myocardial T 1 mapping is emerging as powerful tool for tissue characterization, however the presence of intramyocardial or epicardial fat can contaminate T 1 values through partial voluming, or preclude analysis, particularly in areas of infarct or thin walled myocardium, such as the right ventricle. We propose and evaluate a new combined fat-water separated saturation-recovery imaging sequence (IDEAL-T 1 ) for water-separated T 1 mapping. The IDEAL-T 1 approach combines a gated, segmented multi-echo gradient recalled echo readout for fat-water separation, based on the "iterative decomposition of water and fat with echo asymmetry and least squares estimation" (IDEAL) method[ 1 ], with saturation recovery T 1 mapping[ 2 – 4 ]. Images at 4 saturation recovery (TS) times were acquired at a basal slice in diastole over 2 breathholds; one for a non-saturation prepared image, with >4 seconds of recovery between segments, and another for 3 images with incremental TS times. Typical parameters: (Siemens Sonata, 1.5T) TE 2.06, 4.43, 6.8 ms, TR 8.59, flip angle 20°, TS 302-701 ms, FOV 360 × 259 mm, acquisition matrix 256 × 129, phase resolution 70%, 6/8 partial Fourier, 27 views per segments (4 shots per image). Data from water-separated images was scaled by the non-saturated image and fit to a 1-parameter mono-exponential curve, using a Bloch equations simulation look-up table approach to correct for readout-effects on apparent saturation efficiency. In phantom experiments, with a physiologic range of T 1 and T 2 values (14 phantoms), IDEAL-T 1 was validated against an inversion spin-echo sequence. In-vivo evaluation of myocardial T 1 was completed in 6 healthy individuals and compared to a single-shot saturation recovery sequence (SASHA)[ 2 ] in the left ventricle. Simulations reveal negligible dependence on T 1 , T 2 , and off-resonance (up to 250 Hz), but dependence on B1 errors and saturation efficiency. Phantom experiments show excellent correlation with spin-echo values (R2 0.9996, p < 0.0001) with a mean underestimation of 2.4 ms (Figure 1 ) and a standard deviation of the difference of 7.4 ms. In vivo evaluation shows a larger underestimation, with a mean difference of -32.5 ms (Figure 1 ) and a standard deviation of the difference of 12.3 ms. Sample fat and water separated images are shown in Figure 2 , where a thin rim of RV fat is revealed on the fat image, and a fat and water profile through the wall illustrates the large region of fat and water overlap. Bland-Altman analysis for phantom (top) and in vivo (bottom) experiments . IDEAL-T 1 images showing typical water separated image (top), fat separated image (middle), and signal profile (bottom) across the right ventricle free wall . A small rim of fat is not otherwise visible unless noted on fat separated image. IDEAL-T 1 provides the benefit of fat-water separation with quantitative myocardial T 1 -mapping with a small underestimation in T 1 . Areas of thin myocardium, including the right ventricle, may benefit from resolving zones of partial voluming with fat by having water only images for analysis.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".