Three brain SPECT region-of-interest templates in elderly people: normative values, hemispheric asymmetries, and a comparison of single- and multihead cameras.
Bibliographic record
Abstract
UNLABELLED: The purpose of this study was to generate anatomically guided region-of-interest (ROI) brain SPECT templates based on scans of elderly healthy volunteers. We describe normal tracer uptake and hemispheric asymmetries for each of 3 camera systems and compare these characteristics among systems. METHODS: 99mTc-hexamethyl propyleneamine oxime SPECT scans were acquired from 28 elderly healthy volunteers (mean age [+/-SD], 70.3 +/- 6.5 y) on a single-head rotating gamma camera (n = 15) or on dual- (n = 18) or triple-head (n = 13) cameras. The average number of counts in each ROI was calculated and referenced to counts in a cerebellar ROI, providing semiquantitative regional cerebral blood flow (rCBF) ratios. For the templates and ROI map, base images of a healthy volunteer were obtained with each camera. Data from individuals scanned with 2 cameras on the same day (n = 15) were used to evaluate rCBF differences across cameras. For each camera, averaged SPECT templates were made using automated image registration. The base volunteer's T1-weighted MR image was converted to stereotactic space with dimensions similar to those of the SPECT templates, and 79 bilateral ROIs were defined. To obtain ROI rCBF ratios, we aligned individual images to their appropriate template and then to this modified MR image. RESULTS: The ROI coefficients of variation indicated that the fit of the ROIs was acceptable (0.07-0.35). Mean rCBF ratios ranged from 0.57 to 1.0, 0.67 to 1.01, and 0.63 to 1.00 for single-, dual-, and triple-head cameras, respectively. The cuneus, occipital cortex, occipital pole, middle temporal gyrus, and posterior middle frontal gyrus showed consistent hemispheric asymmetry (right side greater than left side in 83%-100% of individuals). Mean rCBF ratios did not differ between dual- and triple-head cameras, whereas the ratios for single- and dual-head cameras differed significantly (39 ROIs differed), even after smoothing and filtering the dual-head images to the level of the single-head images. CONCLUSION: The use of SPECT templates based on elderly healthy volunteers is an important feature of this technique because most available templates have used young individuals. Another important feature is the use of MR image-based ROIs. These procedures are versatile because they use more than 1 camera. They can easily be implemented in clinical and research settings to detect camera-specific, abnormal deviations in rCBF ROI ratios and asymmetry magnitudes in diseases associated with aging, such as stroke and 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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".