Bibliographic record
Abstract
Purpose: Determining cardiac CT scan range on scan projection radiographs<br/>(SPR) can lead to overscanning and unnecessary radiation. Using Tin(Sn)<br/>beam filtration combined with high pitch enables doses below the minimum<br/>achievable using conventional techniques. We examine the potential for scan<br/>range and total dose reduction using this scan mode for planning functional<br/>cardiac CT contrast scans.<br/>Methods or Backround: 40 patients undergoing CT measurement of left<br/>ventricular ejection fraction (LVEF) were examined on a 3rd generation dual<br/>source CT (DSCT). Using established standard criteria for cardiac CT (carina<br/>to cardiac apex), an ultra-low dose scan was planned on SPR’s and performed<br/>with tube voltage 100(Sn) kVp, reference mAs of 10, pitch 3.2 and automatic<br/>exposure correction (AEC). This scan was used to locate the left ventricle and<br/>to plan the contrast scan to only include anatomy of interest. An ECG-gated<br/>helical CT of the entire cardiac cycle was then performed. Scan range, CTDI &<br/>DLP were recorded. Potential dose saving was based on extrapolation of<br/>contrast scan range to initial planned range.<br/>Results or Findings: Mean CTDI and DLP for the plan scan was 0.32 mGy<br/>and 1.26 mGycm respectively, corresponding to an effective excess dose of<br/>0.02 mSv. The mean scan length was 10.3 cm, compared to 14.7 cm when<br/>planning on SPR’s. Mean calculated dose saving was 0.47 mSv. Relevant<br/>anatomy was included in all scans.<br/>Conclusion: High-pitch tin-filtered planning scans is a feasible way to<br/>implement scan range reduction, with dose reduction far outweighing the<br/>excess dose imparted.<br/>Limitations: The number of patients was low.<br/>Ethics committee approval: "Ultra-lowdose CT for measurement of left<br/>ventricular ejection fraction (LVEF)" (Project ID: S-20210094) Approved by The<br/>Regional Committees on Health Research Ethics for Southern Denmark .<br/>Funding for this study: Funded by the Esbjerg Fund, Karola Jørgensen
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".