The National Cancer Institute reports that prostate cancer is the most common cancer in men, second only to skin cancer. Following lung cancer, prostate cancer is the second leading cause of cancer-related deaths in men in the United States.
Light reflectance spectroscopy has been used by surgeons during prostate cancer procedures as a way to help differentiate 
between benign and malignant tissue. The technology brings with it an 85% accuracy and could even lead to real-time tissue analysis during the surgical procedure itself.
Researchers from the University of Texas Southwestern Medical Center reported that surgeons who use the light-reflectance spectroscopy probe are able to more accurately evaluate surgical margins on radical prostatectomy tissue specimens. The margins can then be correlated with pathological examination and could allow the surgeons to remove all cancerous tissue to minimize the likelihood of a cancer recurrence or from the patient having to go under the knife for a second procedure.
What is light reflectance spectroscopy?
It is a technology that measures “light intensity backscattered from tissues”. The device is used in the removal of the prostate gland and surrounding tissue in the radical prostatectomy procedure. Traditional surgical procedures are lengthier and the surgeon may not have enough real-time info to know whether he’s removed all of the margins around the tumor. Undetectable cancer cells left behind are called positive surgical margins and could mean the patient will need another surgical procedure to remove the remaining cells.
Patients in the study underwent the radical prostatectomy and following that, the light reflectance spectroscopy was performed on suspected benign and malignant margins. The samples were analyzed and pathological samples selected and tested. With the light reflectance spectroscopy, there was an 85 percent accuracy rate with testing the margins.
Researchers explained that further study needs to be performed to analyze whether the technology can be used in real time to assist surgeons in making decisions on tumor margin removal during the procedure.
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