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432ing or specially preparing the tissue.</p> 433 <p>âThe promise of this technology is that it could give clinicians another way to look beneath the surface of a skin lesion without immediately having to remove tissue,â said Andrew Terentis, Ph.D., senior author, professor and chair, Department of Chemistry and Biochemistry, FAU <a href="/science/">Charles E. Schmidt College of Science</a>. âBy combining the molecular information provided by Raman spectroscopy with machine learning, we are beginning to see how subtle differences in tissue chemistry can be used to distinguish cancer from normal skin.â</p> 434 <p>To test the approach, researchers used a mobile Raman spectroscopy system equipped with a 785-nanometer diode laser and handheld probe. They analyzed more than 50 clinical samples ex vivo, including BCC, SCC and normal skin. They generated nearly 1,000 Raman spectra and assessed a variety of machine-learning methods to determine how accurately the spectral data could distinguish among the three tissue types.</p> 435 <p>Results of the study, published in the <a href="https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13864/138640A/Raman-spectroscopy-based-optical-diagnostics-of-skin-cancer--evaluation/10.1117/12.3082236.full">Proceedings of SPIE</a> as part of Advanced Chemical Microscopy for Life Science and Translational Medicine 2026, showed that several machine-learning approaches could identify patterns in Raman spectra that distinguish normal skin from cancerous tissue. K-nearest neighbors and support vector machine classifiers achieved the highest overall test accuracy, at about 84%. The support vector machine achieved 78.7% sensitivity and 88.6% specificity, while a shallow neural network achieved 80.8% accuracy and the highest receiver operating characteristic area under the curve, or ROC AUC, at 0.910.</p> 436 <p>The researchers first examined the Raman spectra to identify molecular patterns associated with the different tissue types. The analysis showed that normal tissue could be distinguished relatively well from the two types of skin cancer, while BCC and SCC showed greater overlap in their molecular signatures. Raman spectra from the cancerous samples tended to show stronger protein-related signals, while normal tissue showed stronger lipid-related signals, providing clues about the molecular characteristics that could help differentiate tissue types.</p> 437 <p>âOur results are preliminary, but they point toward a future in which a rapid, non-invasive measurement could help guide clinical decisions and potentially reduce unnecessary biopsies,â said Terentis.</p> 438 <p>The researchers are now looking toward larger studies, further optimization of the machine-learning models and more advanced approaches, including deep neural networks, which could improve diagnostic performance.</p> 439 <p>âRaman spectroscopy gives us a wealth of molecular information, but the challenge is teaching a computer to recognize which patterns matter most,â said Terentis. âWith more samples and better-trained models, we believe there is significant potential to improve the accuracy of this approach. Ultimately, we want to develop technology that is not only accurate, but also practical, portable and accessible enough to become a useful tool in the clinical setting.â</p> 440 <p>The study demonstrates how advances in optical spectroscopy and machine learning could provide a new path toward faster, non-invasive skin cancer assessment, potentially complementing conventional biopsy and helping clinicians make more informed decisions about which lesions require further evaluation.</p> 441 <p>Study co-authors are Venkata Dhulipalla, a former FAU graduate student; John Strasswimmer, M.D., Ph.D., an affiliate professor of dermatology and research biochemistry in FAUâs <a href="/medicine/">Charles E. Schmidt College of Medicine</a>; and FAU undergraduate students Phuong Nguyen, Lizzie Klein and Max McCain.</p> 442 443 <p class="text-center">-FAU-</p> 444 </div> 445 <div class="col-sm-4"><p><strong>Tags:</strong> <a href="/newsdesk/tags.php?tag=research">research</a> | <a href="/newsdesk/tags.php?tag=technology">technology</a> | <a href="/newsdesk/tags.php?tag=science">science</a> | <a href="/newsdesk/tags.php?tag=faculty and staff">faculty and staff</a></p><div class="widget widget-popular widget-popular--wrapper"> 446 <div class="h1">Categories</div> 447 <hr class="separator" /> 448 <ul id="accordion" class="col-links col-links--popular"> 449 <li><div class="col-link--content"><a class="col-links__arrow" href="/newsdesk/academic-campus-life.php">Academic / Campus Life</a></div></li> 450 <li><div class="col-link--content"><a class="col-links__arrow" href="/newsdesk/research.php">Research</a></div></li> 451 <li><div class="col-link--content"><a class="col-links__arrow" href="/newsdesk/student-life.php">Student Life</a></div></li> 452 <li><div class="col-link--content"><a class="col-links__arrow" href="/newsdesk/arts-and-culture.php">Arts & Culture</a></div></li> 453 <li><div class="col-link--content"><a class="col-links__arrow" href="/newsdesk/university-initiatives.php">University Initiatives</a></div></li> 454 </ul> 455</div> 456</div> 457 </div> 458 </section> 459 </div> 460 </div> 461 462 <!--nav-links--> 463<div class="email-signup"> 464 <div class="email-signup--wrapper"> 465 <div class="section"> 466 <div class="applynow__donate" role="complementary"><a href="/about/apply.php" class="main-navigation--btn main-navigation__apply-now button">Apply Now</a> 467<a href="https://fauf.fau.edu/giveagift" class="main-navigation--btn main-navigation__donate button">Give to FAU</a></div></div></div></div><!--nav-links--> 468 469<!--footer--> 470<footer> 471 <div class="footer footer--wrapper color--white"> 472 <div class="footer-content section"> 473 <!--footer-nav--> 474 <nav> 475 <div class="footer-navigation toUpperCase spacer--bottom--10"> 476 <ul class="inline-nav"> 477 <li><a href="//www.fau.edu/privacypolicy/">Privacy Policy</a></li> 478 <li><a href="//www.fau.edu/policies/policiesregulations.php">Regulations & Policies</a></li> 479 <li><a href="//www.fau.edu/finaid/resources/other-resources.php#consumer-info">Consumer Information</a></li> 480 <li><a href="//fau.edu/jobs/" target="_blank">Employment Opportunities</a></li> 481 <li><a href="//onestop.fau.edu/">Get Help</a></li> 482 <li><a href="//www.fau.edu/report/">Report a Concern</a></li> 483 <li><a href="//www.fau.edu/about/site-index.php">Site Index</a></li> 484 <li><a href="//www.fau.edu/sas/">Student Accessibility</a></li> 485 <li><a href="//www.fau.edu/publicaffairs/media-relations/public-records.php">Public Records</a></li> 486 <li><a href="/about/contact.php">Contact us</a></li> 487 </ul>
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