Comparison of Tl-201 myocardial perfusion on a dedicated cardiac SPECT camera
Bibliographic record
Abstract
1151 Objectives Dedicated cardiac SPECT cameras have been developed that offer greatly improved sensitivity over traditional systems. Most evaluation to date of these systems has been with Tc-99m-based tracers. However, many centers continue to use Tl-201 for perfusion imaging and the value of this alternative isotope was highlighted in the recent Tc-99m shortage. Our objective is to compare myocardial perfusion imaging with Tl-201 on a dedicated cardiac camera to that measured on a traditional system. Methods 189 patients undergoing a clinical myocardial perfusion study with Tl-201 at our center were recruited. All patients were imaged according to our standard clinical protocol of stress/4-hr redistribution imaging. 130 MBq of Tl-201 was injected at peak stress and imaging on a traditional camera (Infinia, GE Healthcare) was started 10-15min post-injection: 30 projections over 180 deg. at 45s/projection. Patients were imaged again after 4 hrs (redist). Immediately following stress imaging and immediately before or after redist. imaging, patients were re-imaged on a Discovery NM 530c (GE Healthcare): 3min stress / 5min redist. All images were reconstructed using vendor software and our standard clinical imaging parameters. Images were anonymized, randomized, and evaluated using 4DM SPECT (Invia Medical Solutions). Normalized perfusion polar maps were created and summed stress/rest/and difference scores (SSS/SRS/SDS) were generated numerically. Results The intraclass correlation was excellent (ICCr=0.93 SSS, 0.90 SRS). Linear regression of the SSS and SRS had a slope of 0.99 and 1.0 respectively with intercepts of 0.7 and 1.4. The difference histograms showed a matched increase in SSS/SRS for the Infinia system as seen with tetrofosmin studies indicating an increased amount of attenuation artifact. The dedicated camera showed a mild increase in ischemia (SDS differences of 1-2). Conclusions Myocardial perfusion imaging with Tl-201 on a dedicated cardiac SPECT camera shows excellent agreement with traditional imaging
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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 | 0.002 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".