P303Maximum likelihood reconstruction of activity and attenuation (MLAA) for CO2 stress in Rb-82 PET/CT respiratory gated imaging
Bibliographic record
Abstract
Funding Acknowledgements: NSERC ENGAGE grant EGP-463679-14 and Ontario Research Fund grant ORF-RE07-021 Introduction: Cardiac stress testing with positron emission tomography (PET) is a recognized modality for detection and evaluation of the severity of coronary artery disease. Typically, this involves the use of pharmacological agents (dipyridamole/adenosine) which can have side effects and be adversely affected by other drugs such as caffeine. A potential alternative is inhaled carbon dioxide (CO2) which acts as a coronary vasodilator. However, CO2 stress increases the tidal volume and respiratory rate of patients leading to reconstruction artifacts. A potential solution is maximum likelihood reconstruction of activity and attenuation (MLAA), which creates a separate phase-matched transmission image (MLAA-TR) for every respiratory gate. But the original MLAA can only reconstruct images up to an unknown scaling factor, preventing quantitative imaging. Purpose: Our three objectives were: to determine the number of iterations required for MLAA to converge with optimal MLAA-TR; to restore quantitative accuracy by compensating for the unknown scaling factor; and to validate improved attenuation correction using respiratory-gated patient data. Methods: 12 healthy volunteers were recruited. Images were acquired on a scanner. Most participants had an initial stress 82Rb (10 MBq/kg over 30 seconds) PET scan at 60 mmHg of end-tidal CO2 using sequential gas delivery for breath-by-breath control of arterial blood gases, followed by a repeat scan after 10 minutes (20 successful scans in total). Data were acquired for 6 minutes following 82Rb administration. A low dose CT was acquired at end-expiration for attenuation correction of stress scans, and used as an initial estimate for MLAA. Both time of flight (ToF) and MLAA reconstructions were performed. Static and ECG gated data were used to test the scaling correction. Cardiac/respiratory phases were split into 8 even time intervals (gates). A-priori values from the CT were used to correct scaling during reconstruction by fixing the mu-values in the MLAA-TR. Results: MLAA-TR attenuation values became stable at 6 iterations (24 subsets). Significant differences for ECG gated data (due to scaling) between ToF and MLAA reconstruction were corrected using MLAA-adjusted reconstruction. Artifacts typically present at end-inspiration with ToF reconstruction were either greatly reduced or eliminated using MLAA. The MLAA segmental variance was significantly lower for all acquisition types and motion frozen analysis (using the F-test two-sample variance with P < 0.05), showing increased homogeneity for MLAA reconstruction. Conclusion(s): MLAA-adjusted reconstruction can compensate for CTAC artifacts with phase matched transmission images derived from an initial low dose CT. Myocardial activity was more homogeneous in healthy normal subjects, and the quantitative accuracy was maintained by offset correction. Further research is required to validate the method in dynamic imaging. Abstract P303 Figure.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".