Technical Note: Immunohistochemical evaluation of mouse brain irradiation targeting accuracy with 3D‐printed immobilization device
Bibliographic record
Abstract
PURPOSE: Small animal immobilization devices facilitate positioning of animals for reproducible imaging and accurate focal radiation therapy. In this study, the authors demonstrate the use of three-dimensional (3D) printing technology to fabricate a custom-designed mouse head restraint. The authors evaluate the accuracy of this device for the purpose of mouse brain irradiation. METHODS: A mouse head holder was designed for a microCT couch using cad software and printed in an acrylic based material. Ten mice received half-brain radiation while positioned in the 3D-printed head holder. Animal placement was achieved using on-board image guidance and computerized asymmetric collimators. To evaluate the precision of beam localization for half-brain irradiation, mice were sacrificed approximately 30 min after treatment and brain sections were stained for γ-H2AX, a marker for DNA breaks. The distance and angle of the γ-H2AX radiation beam border to longitudinal fissure were measured on histological samples. Animals were monitored for any possible trauma from the device. RESULTS: Visualization of the radiation beam on ex vivo brain sections with γ-H2AX immunohistochemical staining showed a sharp radiation field within the tissue. Measurements showed a mean irradiation targeting error of 0.14±0.09 mm (standard deviation). Rotation between the beam axis and mouse head was 1.2°±1.0° (standard deviation). The immobilization device was easily adjusted to accommodate different sizes of mice. No signs of trauma to the mice were observed from the use of tooth block and ear bars. CONCLUSIONS: The authors designed and built a novel 3D-printed mouse head holder with many desired features for accurate and reproducible radiation targeting. The 3D printing technology was found to be practical and economical for producing a small animal imaging and radiation restraint device and allows for customization for study specific needs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".