Left ventricular volumes are different with PET vs SPECT myocardial perfusion imaging
Bibliographic record
Abstract
1765 Objectives Normal reference values for left ventricular (LV) volumes using Rb-82 PET and Tc-99m SPECT have not been well established. The purpose of this investigation is to establish and compare normal reference ranges for LV measurements by Rb-82 PET and SPECT with sodium iodide (NaI) and cadmium-zinc-telluride (CZT) gamma cameras. Methods Consecutive patients who underwent Rb-82 PET and Tc-99m tetrofosmin SPECT myocardial perfusion imaging were screened. Patients with a history of myocardial infarction, coronary revascularization, abnormal myocardial perfusion imaging or known LV dysfunction/reduced ejection fraction (EF) were excluded. A total of 2267 normal patients (1945 SPECT and 322 PET) with LV end diastolic volume (EDV) and end systolic volume (ESV) measurements were analyzed. After stratifying according to sex, LV volumes indexed to body surface area (BSA) were compared across the different modalities and gamma cameras. Results PET measured lower EDVi than both the CZT and NaI-based SPECT gamma cameras (40.4±8.6mL/m2 vs. 53.6±10.4mL/m2 and 48.6±10.1mL/m2 for men and 33.1±7.9mL/m2 vs. 43.3±8.9mL/m2 and 37.8±9.3mL/m2 for women; p Conclusions This study establishes normal references ranges for Rb-82 PET and SPECT measures of LV volumes for site- and equipment-specific evaluations.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".