Detecting head and neck lymph node metastases with white light reflectance spectroscopy; a pilot study

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Introduction: A challenge in the treatment of patients with head and neck cancer is the management of occult cervical lymph node (LN) metastases. Single-fiber reflectance (SFR) spectroscopy has the potential to detect physiological tissue changes that occur in a positive LN. This pilot study aimed to investigate whether SFR spectroscopy could serve as an alternative or additional technique to detect cervical lymph node metastases. Materials and Methods: We performed intraoperative SFR spectroscopy measurements of LNs with and without malignancies. We analyzed if physiological and scattering parameters were significantly altered in positive LNs. Results: Nine patients with a total of nineteen LNs were included. Three parameters, blood volume fraction (BVF), microvascular saturation (StO2), and Rayleigh amplitude, were significantly lower in positive LNs. They were combined into one optical parameter ‘delta’, using discriminant analysis. Delta was significantly decreased in positive LNs, p = 0,0006. It had a high diagnostic accuracy where the sensitivity, specificity, PPV, and NPV were 90,0%, 88.9%, 90,0%, and 88.9%, respectively. The area under the ROC curve was 96.7% (95% confidence interval 89.7–100.0%). Conclusion: This proof of principle study is a first step in the development of an SFR spectroscopy technique to detect LN metastases in real time. A next step towards this goal is replicating these results in LNs with smaller metastases and in a larger cohort of patients. This future study will combine SFR spectroscopy with fine-needle aspiration, using the same needle, to perform preoperative in vivo measurements.

Original languageEnglish
Article number105627
JournalOral Oncology
Early online date23 Nov 2021
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
The authors would like the thank Iris Schmidt from the University Medical Center Groningen for assistance with calibration and data analysis.

Publisher Copyright:
© 2021 The Authors


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