Spine Computed Tomography Radiation Dose Reduction
Bibliographic record
Abstract
STUDY DESIGN: Retrospective dose-simulation comparison. OBJECTIVE: To determine if sufficient detail for preoperative analysis of bony anatomy can be acquired at substantially lower doses than those typically used. SUMMARY OF BACKGROUND DATA: Computed tomography (CT) is a preoperative planning tool for spinal surgery. The pediatric population is at risk to express the harmful effects of ionizing radiation. Preoperative CT scans are presently performed at standard pediatric radiation doses not tailored for surgical planning. METHODS: We used the validated GE Noise Injection software to retrospectively modify existing spine and chest CT scans from 10 patients to create CT images that simulated a standard dose (100%), 50% dose, and 25% dose scans. 4 orthopedic surgeons and a pediatric radiologist, blinded to dose, measured minimum medial-lateral pedicle width and maximum anterior-posterior bony length along the axis of presumed pedicle screw placement. A total of 90 axial images were generated to create our sample set. Measurements were evaluated for accuracy, precision, and consistency. RESULTS: For any given rater, there was no clinically relevant difference between measurements at the different dose levels and no apparent degradation in precision at the different dose levels. Consistent variation was observed between raters, the likely result of individual differences in measurement approach. CONCLUSION: Spinal CT scans done for preoperative planning can be performed at 25% of current radiation doses without a loss in surgical planning measurement accuracy or precision. These 25% dose-reduced scans would have average Computed Tomography Dose Index volume dose levels of roughly 1.0 to 2.5 mGy (depending on patient size) and size-specific dose estimates of roughly 2.5 mGy representing a substantial dose savings compared to current practice for many sites. Standardization of consistent landmarks may be useful to further improve inter-rater concordance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".