Poster — Thur Eve — 53: Reproducibility of TI‐201 for Cardiac Micro SPECT Imaging with a Rat Model
Bibliographic record
Abstract
Serial imaging with micro SPECT/CT is an important 3D in vivo technique used to study heart disease in small‐animal models and develop new therapies and new radiotracers. Measurement of myocardial perfusion uniformity (PH), ejection fraction (EF), end systolic volume (ESV) and, end diastolic volume (EDV) in rat model are important indices of heart function that can be derived from SPECT images. Knowledge of the uncertainty of these measurements is critical to discerning true changes and to determining sample sizes. The aim of this study is to produces the inter‐ and intra‐ subject reproducibility of left ventricular volumes, ejection fraction and perfusion homogeneity with Tl‐201, a common cardiac perfusion tracer, in a rat model using micro SPECT/CT. The scanner has four heads with nine pinholes each (total 36 pinholes). Three healthy rats were injected with 0.5mCi of Tl‐201 and scanned weekly for five weeks. Each scan lasted 30 min and began 30 min post‐injection. The images were reconstructed and processed with a clinical software package (4DM‐SPECT) to get the heart functions (EDV, ESV, EF and PH). EDV and ESV were corrected for changes in rat weight. The standard deviation in the measured values (across scans) was 5.88% for EDV and 6.90% for ESV, 3.2% for EF, and 6% for PH. The reproducibility between rats was similar.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".