Radiation Dose Comparison Between 70 kVp and 100 kVp With Spectral Beam Shaping for Non–Contrast-Enhanced Pediatric Chest Computed Tomography
Bibliographic record
Abstract
OBJECTIVE: The aim of this prospective randomized controlled study was to compare 2 techniques for radiation dose reduction in non-contrast-enhanced pediatric chest computed tomography (CT): low peak kilovoltage imaging at 70 kVp and spectral beam shaping at 100 kVp using a dedicated tin filter (100-kVp Sn). MATERIALS AND METHODS: All chest CT examinations were performed on a third-generation dual-source CT system (SOMATOM Force; Siemens Healthineers, Germany). Fifty children (mean age, 6.8 ± 5.1 years) were examined using the 100-kVp Sn protocol, whereas 25 children received the 70-kVp protocol (mean age, 5.7 ± 5.2 years; 2:1 randomization scheme). Radiation metrics and organ doses were compared between acquisition techniques using commercially available radiation dose analysis software (Radimetrics Inc, Bayer AG, Toronto, Ontario, Canada). Objective image quality, expressed by signal-to-noise ratio and subjective image quality based on a 4-point scale (1, best; 4, worst image quality), were compared. RESULTS: Volume CT dose index and size-specific dose estimate were significantly lower in the 100-kVp Sn group compared with the 70-kVp group (0.19 ± 0.12 mGy vs 0.81 ± 0.70 mGy and 0.34 ± 0.13 mGy vs 1.48 ± 1.11 mGy; P < 0.0001 for both). Accordingly, mean effective dose was significantly lower for the 100-kVp Sn examinations (0.21 ± 0.10 mSv) compared with the 70-kVp examinations (0.83 ± 0.49 mSv; P < 0.0001). Calculated organ doses were also significantly lower using the 100-kVp Sn protocol when compared with the 70-kVp protocol; for example, breast dose was reduced by a factor of 4.3. Signal-to-noise ratio was slightly superior for 70-kVp images while lung image quality of the 100-kVp Sn protocol was preferred in subjective analysis (P = 0.0004). CONCLUSIONS: Pediatric chest CT performed at 100 kVp with an additional tin filter for spectral shaping significantly reduces radiation dose when compared with low peak kilovoltage imaging at 70 kVp and therefore should be preferred in non-contrast-enhanced pediatric chest CT examinations, particularly (given the improved subjective image quality) when the main focus is evaluation of the lung parenchyma.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".