Scatter and attenuation correction for brain SPECT using attenuation distributions inferred from a head atlas.
Bibliographic record
Abstract
UNLABELLED: Sequential transmission scanning (TS)/SPECT is impractical for neurologically impaired patients who are unable to keep their heads motionless for the extended duration of the combined scans. To provide an alternative to TS, we have developed a method of inferring-attenuation distributions (IADs), from SPECT data, using a head atlas and a registration program. The validity of replacing TS with IAD was tested in 10 patients with mild dementia. METHODS: TS was conducted with each patient using a collimated 99mTc line source and fanbeam collimator; this was followed by hexamethyl propyleneamine oxime-SPECT. IAD was derived by deformably registering the brain component of a digital head atlas to a preliminary SPECT reconstruction and then applying the resulting spatial transformation to the full head atlas. SPECT data were reconstructed with scatter and attenuation correction. Relative regional cerebral blood flow was quantified in 12 threshold-guided anatomic regions of interest, with cerebellar normalization. SPECT reconstructions using IAD were compared with those using TS (which is the "gold standard") in terms of these regions of interest. RESULTS: When we compared all regions of interest across the population, the correlation between IAD-guided and TS-guided SPECT scans was 0.92 (P < 0.0001), whereas the mean absolute difference between the scans was 7.5%. On average, IAD resulted in slight underestimation of relative regional cerebral blood flow; however, this underestimation was statistically significant for only the left frontal and left central sulcus regions (P = 0.001 and 0.002, respectively). Error analysis indicated that approximately 10.0% of the total error was caused by IAD scatter correction, 36.6% was caused by IAD attenuation correction, 27.0% was caused by discrepancies in region-of-interest demarcation from quantitative errors in IAD-guided reconstructions, and 26.5% was caused by patient motion throughout the imaging procedure. CONCLUSION: SPECT reconstructions guided by IAD are sufficiently accurate to identify regional cerebral blood flow deficits of 10%, which are typical in moderate and advanced dementia.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".