Optical Coherence Tomography for Quantitative Assessment of Microstructural and Microvascular Alterations in Late Oral Radiation Toxicity
Bibliographic record
Abstract
More than half of head-and-neck cancer patients undergo radiotherapy at some point during their treatment. Even though the use of conformed therapeutic beams has increased radiation dose localization to the tumor, resulting in more normal tissue sparing, still, in many head-and-neck cancer patients, the healthy tissue of the oral cavity still receives a sizeable amount of radiation. This causes acute and / or late complications in these patients. The latter occur as late as several months or even years after the completion of treatment and are typically associated with severe symptoms. Currently, the clinical method for diagnosing these complications is visual examination of the oral tissue surface. However, it has been well established that such complications originate in subsurface oral tissue layers including its microvasculature. Therefore, to better understand the mechanism of these complications and to be able to diagnose them earlier, there exists a need for subsurface monitoring of the irradiated oral tissue. Histology has been used as such a tool for research purposes; however, its use in clinical diagnosis is limited due to its invasive and hazardous nature. Therefore, in this thesis, I propose to use optical coherence tomography (OCT) as a subsurface, micron-scale resolution optical imaging tool that can provide images of oral tissue subsurface layers down to a depth of 1-2 mm (structural OCT), as well as images demonstrating vessel morphology (speckle variance OCT) and blood flow information (Doppler OCT). \nThis thesis explains the development of an OCT setup and an oral probe to acquire images in-vivo. Moreover, it introduces a software-based quantification platform for extracting specific biologically-meaningful metrics from the structural and vascular OCT images. It then describes the application of the developed imaging and quantification platform in a feasibility clinical study that was performed on 15 late oral radiation toxicity patients and 5 age-matched healthy volunteers. The results of this clinical study show that: 1) the value of the developed metrics (such as epithelium to lamina propria thickness, vessel diameter, and blood velocity) is significantly different between the two cohorts; 2) radiation-induced abnormalities in structural OCT images are primarily observed in the regions where the total radiation dose exceeded ~50 Gy. \nThe results of this study demonstrate the promising ability of the developed OCT imaging and quantification platform to highlight biologically meaningful differences between late oral radiation toxicity patients and healthy volunteers in the structural and vascular images. This methodology may also be used in prognostic studies to monitor the efficacy of the medication prescribed to late oral radiation toxicity patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".