The incidence of breast cancer is increasing worldwide. As cancer screening has become more widespread, the rate of early breast cancer detection has increased and treatment methods have changed. Partial mastectomy is performed more often than total mastectomy for the surgical treatment of early breast cancer, and sentinel lymph node biopsy plays an important role. A high level of accuracy is necessary for the intraoperative examination of surgical margins and sentinel lymph nodes to identify malignancies. Therefore, several examination techniques, including Raman spectroscopy, that replace or supplement the currently used frozen-section methods are being studied. Raman spectroscopy has the ability to diagnose cancer in normal tissue by providing in real time a chemical fingerprint that can be used to differentiate between cells and tissues. Numerous studies have investigated the utilization of Raman spectroscopy to identify cancer in the margins of resected tissues and sentinel lymph nodes during breast cancer surgery, showing the potential of this technique for clinical applications. This article introduces and reviews the research on Raman spectroscopy for breast cancer surgery.

Background and Objectives: Near-infrared (NIR) fluorescence photo imaging provides real time parathyroid anatomy enhancement. Moreover, autofluorescence enables intraoperative virtual reality parathyroid exploration of the optical characteristics of the parathyroid gland. This study was performed to demonstrate the new technique of visualizing the parathyroid gland using video-guided autofluorescence during thyroid and parathyroid surgery and to evaluate the outcomes. This is the first study that introduces the video-monitoring technique for intraoperative parathyroid mapping.Subjects and Method A total of 26 patients underwent 18 total thyroidectomies and 8 hemithyroidectomies in 2016. Fifty-six parathyroid glands were enrolled in this study. Surgery was performed by NIR video-monitoring via thyroid lateral side dissection to find the parathyroid tissues and extract the thyroid glands. With the operation room light turned on, the parathyroid glands were identified by the video-guided autofluorescence detection technique carried out in 3 stages (P1, P2, and P3), which are imaging with surgeon’s eyes before parathyroids exposure (P1), after identification (P2), and in extracted specimen (P3). Results: The parathryoid autofluorescence could be video-monitored in real time by our NIR camera system with the indoor room light turned on. Of the total 56 parathyroids, 52 were detected by fluorescence. Of these, the location of 43 glands were predicted by using the high signal in a before-exposure state and the glands were confirmed as containing parathyroid tissues [in P1, sensitivity=82.69%, positive predictive value (PPV)=100.00%]. Of the nine glands that did not show high signals in P1, seven glands visually showed fluorescence signals (in P1 and P2, sensitivity=96.15%, PPV=100.00%). One of the two glands that showed high signals in the extracted tissue was identified as parathyroid, but the other one was proved not by histologic examination by despite high intensity fluorescence signal (in P1-P3, sensitivity=100.00%, PPV=98.08%). The accuracy of video-guided parathyroid mapping in P1, P2, and P3 were 83.93%, 96.43%, and 96.43%, respectively. Conclusion This is the first study that demonstrates the parathyroid gland autofluorescence as a real-time video-monitoring technique and shows that it could be applied to real surgery. Although parathyroid autofluorescence is a phenomenon seen in the invisible wavelength, our data suggest that the operator can see the parathyroid fluorescent signal in real time on the video-monitor. This technique could help the operator to predict the gland location and preserve them safely.