99mTc-WBC scintigraphy with SPECT/CT in the evaluation of arterial graft infection
Bibliographic record
Abstract
OBJECTIVE: The goals of our study were to retrospectively review our experience in using Tc-white blood cell (WBC) single-photon emission computed tomography/computed tomography (SPECT/CT) imaging in the evaluation of possible arterial graft infection and to attempt to establish objective criteria for assessment. METHODS: Eleven Tc-WBC SPECT/CT studies performed for the evaluation of clinically suspected arterial graft infection were retrospectively reviewed and compared with reference outcomes. In an attempt to define objective criteria for interpretation, comparison was also made with background liver and bone marrow activity. RESULTS: When compared with reference outcomes, the subjective scan interpretations showed 6 of 11 true positives (TP), 4 of 11 true negatives (TN), and 1 of 11 false positive (FP). Using the liver as a comparator resulted in 4 of 10 TP, 5 of 10 TN, and 1 of 10 FN. Using the bone marrow as a comparator resulted in 3 of 10 TP, 5 of 10 TN, and 2 of 10 FN. In one patient neither the liver nor the bone marrow was in the field of view. CONCLUSION: These findings suggest a high accuracy for Tc-WBC SPECT/CT in assessing clinically suspected arterial graft infection. Furthermore, the liver may be the best objective comparator for standardized interpretation.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".