Displaying 3D radiation dose on endoscopic video for therapeutic assessment and surgical guidance
Bibliographic record
Abstract
We have developed a method to register and display 3D parametric data, in particular radiation dose, on two-dimensional endoscopic images. This registration of radiation dose to endoscopic or optical imaging may be valuable in assessment of normal tissue response to radiation, and visualization of radiated tissues in patients receiving post-radiation surgery. Electromagnetic sensors embedded in a flexible endoscope were used to track the position and orientation of the endoscope allowing registration of 2D endoscopic images to CT volumetric images and radiation doses planned with respect to these images. A surface was rendered from the CT image based on the air/tissue threshold, creating a virtual endoscopic view analogous to the real endoscopic view. Radiation dose at the surface or at known depth below the surface was assigned to each segment of the virtual surface. Dose could be displayed as either a colorwash on this surface or surface isodose lines. By assigning transparency levels to each surface segment based on dose or isoline location, the virtual dose display was overlaid onto the real endoscope image. Spatial accuracy of the dose display was tested using a cylindrical phantom with a treatment plan created for the phantom that matched dose levels with grid lines on the phantom surface. The accuracy of the dose display in these phantoms was 0.8-0.99 mm. To demonstrate clinical feasibility of this approach, the dose display was also tested on clinical data of a patient with laryngeal cancer treated with radiation therapy, with estimated display accuracy of ∼2-3 mm. The utility of the dose display for registration of radiation dose information to the surgical field was further demonstrated in a mock sarcoma case using a leg phantom. With direct overlay of radiation dose on endoscopic imaging, tissue toxicities and tumor response in endoluminal organs can be directly correlated with the actual tissue dose, offering a more nuanced assessment of normal tissue toxicities following radiation therapy and accurate registration of radiation dose to the surgical field.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".