Abstract 19147: Fast, Free-breathing, Heart-rate Independent Quantitative Myocardial Oxygenation MRI at 3T for Detecting Ischemic Heart Disease Without Contrast Agents With Simultaneous 13N-Ammonia PET Validation
Bibliographic record
Abstract
Introduction: Myocardial BOLD MRI is an emerging non-contrast approach for the assessment of ischemic heart disease. Current BOLD MR methods are limited in part by poor spatial coverage, heart rate dependency and image artifacts, particularly at 3T. To address these limitations, we developed a heart-rate independent, free-breathing 3D T2 mapping technique at 3T that utilizes near perfect imaging efficiency, which can be completed within 3 minutes. We tested our approach in a canine model and validated our findings with simultaneously acquired 13N-ammonia PET perfusion data in a clinical hybrid PET-MR system. Methods: Healthy dogs (n=8) were studied with a state of the art PET-MR system (Siemens Healthcare). For validation, dynamic 13N-ammonia PET scans were simultaneously acquired with BOLD MR data. PET images were analyzed using qPET (Cedars-Sinai Medical Center). T2 values were measured from basal, mid and apical slices at rest and adenosine stress in BOLD images. Myocardial BOLD reserve (T2(stress):T2(rest)) and perfusion reserve (Q(stress):Q(rest)) were computed on a slice basis and regressed. Results: A representative set of BOLD and PET images acquired at rest and adenosine stress are shown in Fig. 2. T2 measures at stress were significantly greater than at rest (T2: 39.5±2.5 ms (rest) vs. 44.0±3.3 ms (stress), p<0.05)); similar results were observed for Q (Q: 0.8±0.1 ml/mg/min (rest) vs. 2.0±0.9 ml/mg/min (stress); p<0.05). Linear regression of BOLD and perfusion reserves showed high correlation (R2=0.6, p<0.05). Conclusions: This is the first study to examine myocardial BOLD MRI with simultaneously acquired PET perfusion data. Our findings showed that BOLD response is highly correlated with PET perfusion suggesting that the proposed BOLD MR method is a viable non-contrast approach for imaging myocardial perfusion. Further studies are required to examine its utility in the setting of ischemic heart disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".