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

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, R <sup>2</sup>, 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 CH<sub>2</sub>-CH<sub>3</sub> 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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Publication Details

Journal
Journal of Biophotonics
Published
2025-04-21
DOI
https://doi.org/10.1002/jbio.70040
Citations
2
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
3.27

Funders

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OCT
article

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

Bernhard Roth, Anatoly Fedorov Kukk, Rüdiger Panzer, Steffen Emmert et al.
2 citations
Journal of Biophotonics
Spectroscopy Techniques in Biomedical and Chemical Research
3.27
article

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

Bernhard Roth, Anatoly Fedorov Kukk, Rüdiger Panzer, Steffen Emmert, Di Wu
article en
2 citations

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, R <sup>2</sup>, 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 CH<sub>2</sub>-CH<sub>3</sub> 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.

Journal of BiophotonicsVol. 18(9)
Leibniz University Hannover (DE), University of Rostock (DE)
Deutsche Forschungsgemeinschaft
Good health and well-being
Openalex Percentile: Top 9%
Spectroscopy Techniques in Biomedical and Chemical Research
3.27
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