In Vivo Differentiation of Cutaneous Melanoma From Benign Nevi With Dual-Modal System of Optical Coherence Tomography and Raman Spectroscopy

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Authors

  • Di Wu
  • Anatoly Fedorov Kukk
  • Rüdiger Panzer
  • Steffen Emmert
  • Bernhard Roth
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Details

Original languageEnglish
Article numbere70040
Number of pages10
JournalJournal of biophotonics
Volume18
Issue number9
Publication statusPublished - 4 Sept 2025

Abstract

A multimodal method comprising optical imaging using OCT and molecular detection using Raman spectroscopy was developed to explore its capability for noninvasive differentiation between melanoma skin cancer and benign skin lesions. Key OCT parameters like the attenuation coefficient, R2, and RMSE, extracted through exponential fitting, were incorporated into machine learning, achieving 96.9% accuracy and an AUC-ROC of 0.99 in 10-fold cross-validation. Raman spectroscopy revealed differences in carotenoid, amide-I, and CH2–CH3 structures between melanoma and nevi, supporting the OCT findings. Autofluorescence background intensity variations further distinguished lesion types and enhanced lesion assessment. Future work will include the investigation of larger patient groups and the combination of both data sets in a combined algorithm. Also, the integration of both modalities and the developed method with photoacoustic tomography and high-frequency ultrasound appears beneficial toward achieving an optical biopsy of melanoma skin cancer and improving diagnostics.

Keywords

    attenuation coefficient, melanoma diagnosis, multimodal noninvasive cancer diagnosis, optical coherence tomography, Raman spectroscopy

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

In Vivo Differentiation of Cutaneous Melanoma From Benign Nevi With Dual-Modal System of Optical Coherence Tomography and Raman Spectroscopy. / Wu, Di; Fedorov Kukk, Anatoly; Panzer, Rüdiger et al.
In: Journal of biophotonics, Vol. 18, No. 9, e70040, 04.09.2025.

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abstract = "A multimodal method comprising optical imaging using OCT and molecular detection using Raman spectroscopy was developed to explore its capability for noninvasive differentiation between melanoma skin cancer and benign skin lesions. Key OCT parameters like the attenuation coefficient, R2, and RMSE, extracted through exponential fitting, were incorporated into machine learning, achieving 96.9% accuracy and an AUC-ROC of 0.99 in 10-fold cross-validation. Raman spectroscopy revealed differences in carotenoid, amide-I, and CH2–CH3 structures between melanoma and nevi, supporting the OCT findings. Autofluorescence background intensity variations further distinguished lesion types and enhanced lesion assessment. Future work will include the investigation of larger patient groups and the combination of both data sets in a combined algorithm. Also, the integration of both modalities and the developed method with photoacoustic tomography and high-frequency ultrasound appears beneficial toward achieving an optical biopsy of melanoma skin cancer and improving diagnostics.",
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AU - Wu, Di

AU - Fedorov Kukk, Anatoly

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AU - Emmert, Steffen

AU - Roth, Bernhard

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