Problems created in attenuation-corrected SPECT images by artifacts in attenuation maps: a simulation study.
Bibliographic record
Abstract
UNLABELLED: The importance of accurate attenuation correction, especially for imaging of the thorax region, is widely acknowledged. Appropriate compensation methods have been developed and introduced into clinical practice. Most of these methods use attenuation maps obtained using various transmission scanning systems. However, when maps are inaccurate, the correction procedure may introduce artifacts into the final images that can be difficult to identify and might inadvertently alter diagnosis and study outcome. As a result, attenuation correction is often avoided in clinical practice. Our objective was to examine issues related to the quality of attenuation maps and the effects that map artifacts may have on attenuation-corrected emission images. METHODS: The topics that are investigated include the problem of low transmission counts, cross-talk contributions from the emission isotope, truncation of the transmission data, and methods of map reconstruction and segmentation. Examples of patient studies displaying specific problems guided our investigations, but, because truth in these studies is seldom known, analytic and Monte Carlo-simulated data were used in the analysis. Attenuation maps and final emission images were visually checked for artifacts and for the presence of perfusion defects. In addition, quantitative evaluation of map uniformity, defect visibility, and size variation was performed. RESULTS: The statistical paired-sample t test showed significant (P < 0.05) improvement of relative SD for attenuation maps reconstructed with iterative methods as compared with filtered backprojection and for maps created with higher photon fluxes. When maps with artifacts were used to correct emission data, an increase in myocardial infarct size and creation of false heart defects were observed. CONCLUSION: Our study strongly recommends that at least a visual inspection of the quality of attenuation maps be performed before their use in compensation procedures. To improve image quality, remove artifacts, and increase diagnostic confidence, attenuation maps used in the correction procedure must be accurate and free of artifacts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".