TH‐C‐351‐01: Design of the Washington University Small Animal Conformal Micro Irradiator
Bibliographic record
Abstract
Purpose: To design a conformal small animal micro radiation therapy (microRT) instrument, consisting of a cone beam microCT subsystem for submillimeter low dose structural imaging and image guided radiotherapy and an orthovoltage conformal micro irradiator with high radiation dose rate for high throughput conformal irradiation. Method and Materials: The microCT subsystem is based on an 80kVp micro‐focus x‐ray source with 75×75 um2 focal spot and a flat panel amorphous silicon detector with 1024×1024 pixels. The microRT subsystem design utilizes a 320kVp orthovoltage source with dual focus spots (0.4×0.4 mm2 at 800W and 1×1 mm2 at 1800 W). The orthovoltage beam is collimated using two orthogonal jaws and exchangeable apertures. The resolution of the cone‐beam micro CT and the therapy beam spatial precision was determined using a numerical model. The microCT radiation dose, the orthovoltage source spectral output, and dose rate were evaluated using a mouse digital phantom (MOBY) and a pencil beam algorithm. Results: microCT reconstructed tomographic data with a resolution of 125 μm is achievable using 128 projections and a maximum radiation dose of 2cGy. Automatic animal positioning and handling is performed within a precision of 100 μm. The treatment beam can be aimed at different latitude and longitude angles in steps of 2 arc min. and translated at 50μm steps (x,y,z). The beam cross section can be modulated with submillimeter precision using steps of 50μm. A radiation dose rate of 40 Gy/min is delivered when the system is operated at an average half‐value layer of 4.6 mm Cu and a maximum beam penumbra of 0.35 mm. Conclusion: We designed and numerically evaluated the performance of a microRT system integrated with a microCT for conformal radiotherapy of murine animal models. This work supported in part by NIH grant CA108677.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".