SU‐E‐T‐20: A Novel Hybrid CBCT, Bioluminescence and Fluorescence Tomography System for Preclinical Radiation Research
Bibliographic record
Abstract
Purpose: A novel standalone bioluminescence and fluorescence tomography (BLT and FT) system equipped with high resolution CBCT has been built in our group. In this work, we present the system calibration method and validate our system in both phantom and in vivo environment. Methods: The CBCT is acquired by rotating the animal stage while keeping the x‐ray source and detector panel static. The optical signal is reflected by the 3‐mirror system to a multispectral filter set and then delivered to the CCD camera with f/1.4 lens mounted. Nine fibers passing through the stage and in contact with the mouse skin serve as the light sources for diffuse optical tomography (DOT) and FT. The anatomical information and optical properties acquired from the CBCT and DOT, respectively, are used as the priori information to improve the BLT/FT reconstruction accuracy. Flat field correction for the optical system was acquired at multiple wavelengths. A home‐built phantom is used to register the optical and CBCT coordinates. An absolute calibration relating the CCD photon counts rate to the light fluence rate emitted at animal surface was developed to quantify the bioluminescence power or fluorophore concentration. Results: An optical inhomogeneous phantom with 2 light sources (3mm separation) imbedded is used to test the system. The optical signal is mapped onto the mesh generated from CBCT for optical reconstruction. Our preliminary results show that the center of mass can be reconstructed within 2.8mm accuracy. A live mouse with the light source imbedded is also used to validate our system. Liver or lung metastatic luminescence tumor model will be used for further testing. Conclusion: This hybrid system transforms preclinical research to a level that even sub‐palpable volume of cells can be imaged rapidly and non‐invasively, which largely extends the scope of radiobiological research. The research is supported by the NCI grant R01CA158100‐01
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".