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A standardized RS process compliant with medical device regulatory standards was established, and spectra were collected from tumor tissue, margins, and healthy regions. A pronounced learning-curve effect reduced measurement time from 30+ min to 2 min after 15 patients, and interpretable data from 35 patients showed clear spectral differences. The workflow is now established for the ongoing clinical 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in vivo Raman spectroscopy during head and neck cancer surgery  \nAyman Bali1, Thomas Bitter1, Mussab Kouka1, Jonas Ballmaier1, Ines Latka2,  \nFlorian Windirsch2, David Pertzborn1, Nadja Ziller1, Marcela Mafra1, Nikolaus Gaßler3, Jürgen Popp2,4, Anna Mühlig1, Ferdinand von Eggeling1, Orlando Guntinas-Lichius1,6􀀍 &  \nIwanW. Schie2,5,6  \nAs first part of an ongoing prospective feasibility trial (DRKS00028114) this work explored the integration of in vivo Raman spectroscopy (RS) into the routine setting workflow of head and neck cancer (HNC) surgery. In vivo RS was performed intraoperatively on 30 patients with HNC cell carcinoma and 10 patients with inflammatory diseases as a control group. A standardized process was established using a Raman system complied with stringent medical device regulatory standards. Spectra were collected in vivo from the tumor site, the tumor margins, and healthy tissue. The learning curve ofthe HNC team significantly improved measurement times from over 30 min initially to 2 min after 15 patients. Data from 35 patients were interpretable, demonstrating clear spectral differences between tumor and healthy tissues. The intraoperative in vivo RS workflow is now well established and is being used in the ongoing clinical trial.  \nHead and necksquamous cell carcinoma (HNSCC) encompass a diverse group of malignancies. These cancers rank as the sixth leading cause of cancer-related mortality worldwide1,2. Treatment typically involves a comprehensive multidisciplinary strategy that includes surgery, radiation therapy, chemotherapy, immunotherapy, or a combination of these modalities. A common treatment approach is surgical removal, aimed at excising the tumor comprehensively3,4. Current methods for assessing tumor margins intraoperatively primarily involve histopathological techniques such as the frozen section analysis procedure (Fig. 1A) . Although widely utilized, this method faces significant challenges, including limitations in accuracy (63.1–97.2%) and subjectivity, as well as lengthy processing times (approximately 20–30 min per probe) and a notable potential for sampling errors5–8. These issues not only increase the time and costs associated with surgery but also frequently lead to suboptimal surgical outcomes. This can manifest as either insufficient tumor margins or excessive removal of healthy tissue, ultimately affecting patient recovery and prognosis8–11.  \nIn response to these challenges, recent advancements in photonic technologies have introduced new possibilities for enhancing surgical precision. Among these, Raman spectroscopy has emerged as a particularly promising tool due to its ability to provide real-time, label-free molecular insights into tissues12. Raman spectroscopy captures a unique molecular ’fingerprint’ of tissues, enabling the differentiation of malignant from non-malignant tissues almost instantaneously13–23 with high sensitivity (85–92%) and specificity (78–89%)24. Raman spectroscopy has been applied both in vivo and ex vivo across various organs, including the esophagus, stomach, colon, cervix, lung, brain, nasopharynx, larynx, and the oral cavity where it has been instrumental in detecting precancerous and cancerous changes25. The non-destructive, label-free, and non-ionizing nature of the technique keeps the specimen safe, while the rapid analysis capabilities make it especially suitable for integration into surgical workflows, offering the potential to significantly reduce the duration of surgery and improve surgical accuracy26–40.  \n1Department of Otorhinolaryngology, Jena University Hospital Department, Am Klinikum 1, 07747 Jena, Germany.  \n2Leibniz Institute of Photonic Technology, Jena, Germany. 3Section Pathology of the Institute of Forensic Medicine, Jena University Hospital, Jena, Germany. 4Institute of Physical Chemistry and Abbe Centre of Photon","cbCait8noWFKtBzn","https://ap.wps.com/l/cbCait8noWFKtBzn","pdf",6764821,12,"English","# Background\n## Limitations of frozen section margin assessment\n# Raman spectroscopy rationale\n## Label-free molecular fingerprinting and diagnostic performance\n# Study workflow and evaluation\n## Prospective feasibility trial design and patient cohorts\n## Standardized intraoperative RS workflow and spectral collection\n## Learning curve and interpretability of results","[{\"question\":\"What problem does the clinical workflow aim to address in head and neck cancer surgery?\",\"answer\":\"It targets challenges of current intraoperative tumor-margin assessment, including limited accuracy, subjectivity, long processing times, and sampling errors that can affect surgical outcomes.\"},{\"question\":\"How was in vivo Raman spectroscopy implemented during surgery?\",\"answer\":\"A standardized, regulation-compliant Raman system was used for intraoperative measurements directly on tumor tissue, tumor margins, and healthy tissue, without relying on prolonged frozen-section processing.\"},{\"question\":\"What results indicate improvement and clinical feasibility?\",\"answer\":\"The team’s learning curve shortened measurement time from over 30 minutes initially to about 2 minutes after 15 patients, and interpretable data from 35 patients showed clear spectral differences between tumor and healthy tissues.\"}]","Establishment of a clinical workflow for in vivo Raman spectroscopy during head and neck cancer surgery | PDF",1790201973]