Abstract P4-03-04: The potential use of Optical Coherence Tomography for intraoperative breast tumour margin width estimation
Bibliographic record
Abstract
Abstract Total mastectomy and lumpectomy with radiation have been shown to have equivalent patient outcomes, which has likely contributed to the more widespread adoption of breast conserving surgery (BCS) procedures. Assessment of breast lumpectomy margin widths in both an accurate and timely manner is essential to successful breast conservation procedures. Current BCS methodologies have been reported to result in reoperation rates of up to 20–60%, which represents a significant and unmet need for improved margin assessment. High reoperation rates present both increased treatment risk to patients and increased burden on healthcare systems. In the USA alone, over 150,000 lumpectomies are performed per year at an average cost between $11,000 and $19,000 USD per procedure. Assuming a relatively modest average repeat operation rate of 25%, potentially preventable repeat surgeries represent an approximate cost to the US healthcare system of $500M (USD) annually. Reducing the prevalence of repeat surgeries may be accomplished by providing faster and more accurate intraoperative tools for assessing margin widths during the time of the first surgery. One such potential technique involves the use of Optical Coherence Tomography (OCT) imaging, which uses light to produce images in much the same way that ultrasound produces images with sound. Compared to ultrasound, OCT provides decreased depth of penetration, but increased resolution capabilities. The increased resolution that OCT provides allows for the visualization of the internal cellular structure within a tissue sample and therefore, provides the potential ability to differentiate cancerous from normal or benign cells. We propose the use of an intraoperative OCT imaging system to provide near real-time imaging information about the internal structure of tissue samples excised during BCS procedures. Our hypothesis is that the overall rate of repeat operations can be reduced by providing a tool to assist surgeons with the task of margin width estimation during the time of surgery. We have developed an early stage prototype OCT imaging system that has completed laboratory phantom and preclinical studies. This paper will present the capabilities of an OCT imaging system to provide margin assessment information in biological breast tissue mimicking phantoms. The phantoms were designed to encompass imaging characteristics across a wide range of human breast densities. The paper will go on to describe preclinical imaging that was done in tumor specimens excised from human breast cancer rat models. The results obtained in the phantom and preclinical studies suggest the potential for OCT as a near-real time, intraoperative imaging tool to aid surgeons with breast lumpectomy margin width estimation. To help realize this potential, further research is required in to the use of OCT during BCS. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P4-03-04.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.008 | 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".