Functional Imaging Using Diffuse Optical Spectroscopy of Neoadjuvant Chemotherapy Response in Women with Locally Advanced Breast Cancer
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Bibliographic record
Abstract
PURPOSE: Functional imaging with tomographic near-infrared diffuse optical spectroscopy (DOS) can measure tissue concentration of deoxyhemoglobin (Hb), oxyhemoglobin (HbO2), percent water (%water), and scattering power (SP). In this study, we evaluated tumor DOS parameters and described their relationship to clinical and pathologic outcome in patients undergoing neoadjuvant therapy for locally advanced breast cancer. EXPERIMENTAL DESIGN: Ten patients were enrolled and intended to undergo five scans each. Scans were taken up to 3 days before treatment and at 1, 4, and 8 weeks after neoadjuvant treatment before surgery. Changes in volume of interest weighted tissue Hb, HbO2, %water, and SP corresponding to the tumor were compared with clinical and pathologic response. RESULTS: All patients' tumor volumes of interest were significantly different compared with background tissue for all parameters. Five patients had a good pathologic response. Four patients were considered nonresponders. One patient initially did not respond to chemotherapy but, after a change in chemotherapy, had a good response. In the five patients with a good response, the mean drop in Hb, HbO2, %water, and SP from baseline to the 4-week scan was 67.6% (SD = 20.8), 58.9% (SD = 20.3), 51.2% (SD = 28.3), and 52.6% (SD = 26.4), respectively. In contrast, the four nonresponders had a mean drop of 17.7% (SD = 9.8), 18.0% (SD = 20.8), 15.4% (SD = 11.7), and 12.6% (SD = 10.2) for Hb, HbO2, %water, and SP, respectively. CONCLUSIONS: Responders and nonresponders were significantly different for all functional parameters at the 4-week scan, except for %water, which approached significance. Thus, DOS could be used as an early detector of tumor response.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it