Dual versus single energy cardiac CT to measure extracellular volume in cardiac amyloidosis: correlations with cardiac MRI
Bibliographic record
Abstract
Rationale and objectives: Determine in cardiac amyloid (CA) patients, whether cardiac CT derived extracellular volume (ECV) correlates with that obtained by MRI. Perform this correlation with single (SECT) versus dual energy (DECT) CT and evaluate whether a single sample volume ECV-measure was as reliable as a global (16 segment) assessment. Materials and methods: CA patients who had undergone a clinical cardiac MRI (CMR) were recruited prospectively. SECT and DECT cardiac scans were performed. Three ECG-triggered prospective SECT scans were acquired: non-contrast, arterial-phase contrast and 5-minute delayed images. A DECT scan was performed at 7 min. Post processing was used to determine ECV. Analyses of SECT or DECT global ECV versus CMR were performed using the Pearson correlation coefficient, Bland Altman analysis and Intraclass correlation coefficient (ICC). Similar analyses were performed to examine the performance of single-segment sampling by SECT or DECT versus CMR. Results: 25 patients were recruited, mean age was 80.0 ± 7.1 years, 80 % were male, 21 patients had transthyretin- CA, 4 had light chain- CA. Correlations were close with both SECT or DECT global ECV versus CMR (r = 0.79 and 0.88 respectively, p < 0.001 for both). Reliability of both SECT and DECT to assess global ECV in comparison to CMR was good: ICC for SECT was 0.88 (95 % CI 0.73-0.95) and 0.93 (95 % CI 0.82-0.97) for DECT. For single volume sampling techniques: correlations were close with both SECT or DECT versus CMR (r = 0.60 and 0.72 respectively, p < 0.01 for both) There was no difference in ICC for SECT (0.74, 95 %CI 0.41-0.88) versus DECT (0.84, 95 % CI 0.63-0.93). Wider confidence intervals were noted for ICC with single versus global CT derived ECV assessment. Mean effective radiation dose was for SECT was 5.49 ± 8.04 mSv and 6.90 ± 3.01 mSv for DECT dual energy CT (p = 0.75). Conclusions: Global ECV values derived by both DECT or SECT correlated with those obtained by CMR and demonstrated good reliability by ICC in a population of CA patients. DECT and SECT single sampling derived ECV values also demonstrated close correlation and good reliability but the ICCs for single sampling had wider confidence intervals than global ECV assessment.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".