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Tissue-simulating Phantoms for Assessing Potential Near-infrared Fluorescence Imaging Applications in Breast Cancer Surgery
Published on: September 19, 2014
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Optical Emission Spectroscopy for the Real-Time Identification of Malignant Breast Tissue
Selin Guergan1, Bettina Boeer1, Regina Fugunt1
1Department of Women's Health, Tuebingen University Hospital, 72076 Tübingen, Germany.
Diagnostics (Basel, Switzerland)
|February 10, 2024
Summary
Optical emission spectroscopy (OES) effectively differentiates cancerous from healthy breast tissue during surgery. This technique achieved 96.9% accuracy, paving the way for improved breast cancer margin assessment.
Area of Science:
- Oncology
- Biomedical Engineering
- Spectroscopy
Background:
- Breast-conserving surgery requires clear margins for optimal early breast cancer treatment.
- Accurate intraoperative differentiation between normal and malignant breast tissue is crucial for achieving these clear margins.
Purpose of the Study:
- To identify specific spectroscopic features of healthy and neoplastic breast tissue using ex vivo optical emission spectroscopy (OES).
- To evaluate the feasibility of OES for real-time tissue differentiation and margin assessment during breast cancer surgery.
Main Methods:
- Ex vivo characterization of normal and abnormal breast tissue samples using optical emission spectroscopy (OES).
- Analysis of 972 spectra generated by electrosurgical sparking.
- Training a support vector classifier (SVC) using selected spectroscopic features for tissue classification.
Main Results:
- The OES-based support vector classifier achieved an average classification accuracy of 96.9% for differentiating breast tissues.
- Mean sensitivity was 94.8%, specificity 99.0%, positive predictive value (PPV) 99.1%, and negative predictive value (NPV) 96.1%.
- 100% classification accuracy was reached for 66.6% of patients.
Conclusions:
- Optical emission spectroscopy (OES) demonstrates high accuracy in distinguishing between normal and malignant breast tissues.
- The findings suggest OES is a feasible technology for real-time intraoperative margin assessment in breast cancer surgery.
- Further clinical application of OES for enhancing surgical outcomes in breast cancer is promising.
Keywords:
breast cancerelectrosurgerymachine learningoptical emission spectroscopysupport vector machinetumor margintumor tissueMore Related Videos
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