Experimental validation of a kV source model and dose computation method for CBCT imaging in an anthropomorphic phantom
Bibliographic record
Abstract
We present an experimental validation of a kilovoltage (kV) X-ray source characterization model in an anthropomorphic phantom to estimate patient-specific absorbed dose from kV cone-beam computed tomography (CBCT) imaging procedures and compare these doses to nominal weighted CT-dose index (CTDIw) dose estimates. We simulated the default Varian on-board imager 1.4 (OBI) default CBCT imaging protocols (i.e., standard-dose head, low-dose thorax, pelvis, and pelvis spotlight) using our previously developed and easy to implement X-ray point-source model and source characterization approach. We used this characterized source model to compute absorbed dose in homogeneous and anthropomorphic phantoms using our previously validated in-house kV dose computation software (kVDoseCalc). We compared these computed absorbed doses to doses derived from ionization chamber measurements acquired at several points in a homogeneous cylindrical phantom and from thermoluminescent detectors (TLDs) placed in the anthropomorphic phantom. In the homogeneous cylindrical phantom, computed values of absorbed dose relative to the center of the phantom agreed with measured values within ≤2% of local dose, except in regions of high-dose gradient where the distance to agreement (DTA) was 2 mm. The computed absorbed dose in the anthropomorphic phantom generally agreed with TLD measurements, with an average percent dose difference ranging from 2.4% ± 6.0% to 5.7% ± 10.3%, depending on the characterized CBCT imaging protocol. The low-dose thorax and the standard dose scans showed the best and worst agreement, respectively. Our results also broadly agree with published values, which are approximately twice as high as the nominal CTDIw would suggest. The results demonstrate that our previously developed method for modeling and characterizing a kV X-ray source could be used to accurately assess patient-specific absorbed dose from kV CBCT procedures within reasonable accuracy, and serve as further evidence that existing CTDIw assessments underestimate absorbed dose delivered to patients.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".