Characterization of image quality and image‐guidance performance of a preclinical microirradiator
Bibliographic record
Abstract
PURPOSE: To assess image quality and image-guidance capabilities of a cone-beam CT based small-animal image-guided irradiation unit (micro-IGRT). METHODS: A micro-IGRT system has been developed in collaboration with the authors' laboratory as a means to study the radiobiological effects of conformal radiation dose distributions in small animals. The system, the X-Rad 225Cx, consists of a 225 kVp x-ray tube and a flat-panel amorphous silicon detector mounted on a rotational C-arm gantry and is capable of both fluoroscopic x-ray and cone-beam CT imaging, as well as image-guided placement of the radiation beams. Image quality (voxel noise, modulation transfer, CT number accuracy, and geometric accuracy characteristics) was assessed using water cylinder and micro-CT test phantoms. Image guidance was tested by analyzing the dose delivered to radiochromic films fixed to BB's through the end-to-end process of imaging, targeting the center of the BB, and irradiation of the film/BB in order to compare the offset between the center of the field and the center of the BB. Image quality and geometric studies were repeated over a 5-7 month period to assess stability. RESULTS: CT numbers reported were found to be linear (R2 0.998) and the noise for images of homogeneous water phantom was 30 HU at imaging doses of approximately 1 cGy (to water). The presampled MTF at 50% and 10% reached 0.64 and 1.35 mm(-1), respectively. Targeting accuracy by means of film irradiations was shown to have a mean displacement error of [deltax, deltay, deltaz] = [-0.12, -0.05, -0.02] mm, with standard deviations of [0.02, 0.20, 0.17] mm. The system has proven to be stable over time, with both the image quality and image-guidance performance being reproducible for the duration of the studies. CONCLUSIONS: The micro-IGRT unit provides soft-tissue imaging of small-animal anatomy at acceptable imaging doses (< or =1 cGy). The geometric accuracy and targeting systems permit dose placement with submillimeter accuracy and precision. The system has proven itself to be stable over 2 yr of routine laboratory use (>1800 irradiations) and provides a platform for the exploration of targeted radiation effects in small-animal models.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".