GW24-e2918 Quantitative myocardial CT perfusion with rapid kV switching dual energy CT: a microspheres validation study
Bibliographic record
Abstract
Objectives We validated the usefulness of beam hardening (BH) reduction with a rapid kV switching dual energy CT (DECT) protocol in quantitative myocardial perfusion (MP) imaging against microspheres measurement of MP. Methods Normal pigs were scanned using a Discovery 750HD scanner (GE Healthcare (GE)) with a DECT protocol: 140/80 kilovolts (kV) alternating at 0.2 ms intervals, 640 mA and 0.35 s gantry period. In each study, 22 axial scans covering 40 mm of the heart were triggered under normal physiologic conditions every 1–2 heart beat at mid-diastole together with contrast injection at 4 ml×s -1 . Single energy CT (SECT) and DECT monochromatic 70 keV images were reconstructed with 140 kV and both 80 and 140 kV projections respectively. The SECT images were also corrected for BH using an image-based correction algorithm (iBHC). Each image set was analysed using CT Perfusion (GE) to derive MP functional maps. Fluorescent microspheres were injected into the left atrial appendage of the heart after the CT perfusion studies to measure MP. Mean MP in the lateral, apical and septal segments over 4 to 6 consecutive 5-mm-thick slices measured by microspheres and from the three CT image sets were compared using linear regression and Bland-Altman analysis. A total of 57 segments in 19 slices in four pigs were analysed in this study. Results DECT exhibited the highest correlation with microspheres (R = 0.77) compared to SECT with (R = 0.56) and without (R = 0.49) iBHC. DECT also had the smallest difference in mean MP from microspheres (2.2 ml × min -1 × 100 g -1 ) compared to SECT without iBHC (29.2). Despite a comparable mean difference from microspheres (-2.0), SECT with iBHC showed a wider limits of agreement (-45.0 to 41.0 ml × min -1 × 100 g -1 ) than DECT (-30.7 to 35.2). Conclusions In SECT MP imaging, BH induced significant shifts in CT number in different myocardial segments lead to spatially inconsistent overestimation of MP. While such BH errors are reduced after iBHC is applied, DECT provides better BH correction and more accurate MP measurements that are better correlated with and have smaller differences from the gold standard microspheres measurements of MP. DECT minimises beam hardening in contrast-enhanced cardiac images which leads to a more accurate MP measurement with CT Perfusion to facilitate reliable assessment of ischemic heart disease.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".