Investigation of the quarter-dose 18F-FDG total-body PET in routine clinical practice and its clinical value
Bibliographic record
Abstract
OBJECTIVE: The purpose of the study was to evaluate the routine clinical application of total-body PET with quarter-dose 18 F-FDG. METHODS: The contrast recovery coefficient (CRC) and coefficient of variation (COV) were evaluated among full-, half-, and quarter-dose groups with an acquisition duration of 10-, 5-, 3-, and 1-min in the NEMA (IQ) phantom test. Fifty patients undergoing total-body PET/CT with quarter-dose (0.925MBq/kg) of 18 F-FDG were included in the prospective study. The acquisition time was 10 min, divided into duration groups of 5-, 3-, and 1-min, referred to as G10, G5, G3, and G1. Visual scores were assessed based on overall visual assessment, noise scoring, and lesion conspicuity. Lesion SUV max and TBR were evaluated in semi-quantitative analysis. G10 was used as the gold reference to evaluate lesion detectability. RESULTS: In the phantom study, the COV value of the images with quarter-dose 18 F-FDG and 10-min acquisition time was 11.52%. For spheres with 10 mm diameter, the CRC of quarter-dose PET images was relatively stable compared to that of full-dose groups with all acquisition durations. In the human study, the visual score in G10, G5, and G3 was significantly higher than that in G1. The differences in lesion SUV max and TBR for G1-G10 were significantly higher than that for G5-G10 and G3-G10. All lesions in G10 could be identified in G5 and G3. CONCLUSION: The phantom and human findings demonstrated the feasibility of quarter-dose 18 F-FDG PET with 3-min acquisition time, which can maintain image quality with reduced radiation dose.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".