Conventional SPECT Versus 3D Thresholded SPECT Imaging in the Diagnosis of ADHD: A Retrospective Study
Bibliographic record
Abstract
Brain single photon emission CT (SPECT) scans indirectly show functional activity via measurement of regional cerebral blood flow. In conventional SPECT scans, the typical tomographic slices are produced. In three-dimensional thresholded SPECT scans, pixels representing activity below a certain threshold are discarded. A retrospective analysis of 427 patients shows that three-dimensional thresholded SPECT scans yield a sensitivity for predicting clinical attention deficit hyperactivity disorder of 54% [95% confidence interval (CI), 46%-61%; specificity, 76%; 95% CI, 71%-81%] compared with 4% sensitivity [95% CI, 2%-8%; specificity, 97%; 95% CI, 94%-98%] for conventional SPECT scans. For 170 of the patients originating from a general psychiatry practice, conventional SPECT showed 10% sensitivity (95% CI, 4%-23%) and 98% specificity (95% CI, 93%-99%), whereas three-dimensional thresholded SPECT showed 83% sensitivity (95% CI, 68%-91%) and 77% specificity (95% CI, 69%-83%). These findings indicate that a much stronger signal is obtained when the three-dimensional thresholded SPECT scan is performed rather than the conventional SPECT scan in detecting attention deficit hyperactivity disorder and suggest similar results may be obtained for other psychiatric disorders.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".