Abstract
Soft tissue sarcomas (STS) are a rare and heterogeneous group of malignant tumors that are often treated via surgical resection. Inadequate resection can lead to local recurrence and decreased survival rates. In this study, we investigate the hypothesis that near-infrared (NIR) autofluorescence can be utilized for tumor margin analysis by differentiating STS from the surrounding normal tissue. Intraoperative in vivo measurements were acquired from 30 patients undergoing STS resection and were characterized to differentiate between normal tissue and STS. Overall, normal muscle and fat were observed to have the highest and lowest autofluorescence intensities, respectively, with STS falling in between. With the exclusion of well-differentiated liposarcomas, the algorithm's accuracy for classifying muscle, fat, and STS was 93%, 92%, and 88%, respectively. These findings suggest that NIR autofluorescence spectroscopy has potential as a rapid and nondestructive surgical guidance tool that can inform surgeons of suspicious margins in need of immediate re-excision.
Original language | English (US) |
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Pages (from-to) | 5498-5501 |
Number of pages | 4 |
Journal | Optics Letters |
Volume | 40 |
Issue number | 23 |
DOIs | |
State | Published - Dec 1 2015 |
Funding
National Cancer Institute (NCI) (F31CA200358); Orthopaedic Research and Education Foundation (OREF) (#14-010); Vanderbilt Orthopaedic Institute; Vanderbilt University School of Medicine. We would like to thank Dr. Herbert Schwartz, Dr. Jennifer Halpern, Dr. Krishna Reddy, Dr. NathanMesko, and all participating surgical personnel for their patience and assistance in this work.
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics