Dual in vivo Photoacoustic and Fluorescence Imaging of HER2 Expression in Breast Tumors for Diagnosis, Margin Assessment, and Surgical Guidance
Bibliographic record
Abstract
Biomarker-specific imaging probes offer ways to improve molecular diagnosis, intraoperative margin assessment, and tumor resection. Fluorescence and photoacoustic imaging probes are of particular interest for clinical applications because the combination enables deeper tissue penetration for tumor detection while maintaining imaging sensitivity compared to a single optical imaging modality. Here we describe the development of a human epidermal growth factor receptor 2 (HER2)-targeting imaging probe to visualize differential levels of HER2 expression in a breast cancer model. Specifically, we labeled trastuzumab with Black Hole Quencher 3 (BHQ3) and fluorescein for photoacoustic and fluorescence imaging of HER2 overexpression, respectively. The dual-labeled trastuzumab was tested for its ability to detect HER2 overexpression in vitro and in vivo. We demonstrated an over twofold increase in the signal intensity for HER2-overexpressing tumors in vivo, compared to low-HER2-expressing tumors, using photoacoustic imaging. Furthermore, we demonstrated the feasibility of detecting tumors and positive surgical margins by fluorescence imaging. These results suggest that multimodal HER2-specific imaging of breast cancer using the BHQ3-fluorescein trastuzumab enables molecular-level detection and surgical margin assessment of breast tumors in vivo. This technique may have future clinical impact for primary lesion detection, as well as intraoperative molecular-level surgical guidance in breast cancer.
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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".