Di Wu, Anatoly Fedorov Kukk, Rüdiger Panzer, Steffen Emmert, Bernhard Roth
{"title":"用光学相干断层扫描和拉曼光谱双峰系统在体内鉴别皮肤黑色素瘤和良性痣。","authors":"Di Wu, Anatoly Fedorov Kukk, Rüdiger Panzer, Steffen Emmert, Bernhard Roth","doi":"10.1002/jbio.70040","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":94068,"journal":{"name":"Journal of biophotonics","volume":" ","pages":"e70040"},"PeriodicalIF":2.3000,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In Vivo Differentiation of Cutaneous Melanoma From Benign Nevi With Dual-Modal System of Optical Coherence Tomography and Raman Spectroscopy.\",\"authors\":\"Di Wu, Anatoly Fedorov Kukk, Rüdiger Panzer, Steffen Emmert, Bernhard Roth\",\"doi\":\"10.1002/jbio.70040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":94068,\"journal\":{\"name\":\"Journal of biophotonics\",\"volume\":\" \",\"pages\":\"e70040\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2025-04-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of biophotonics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/jbio.70040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of biophotonics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/jbio.70040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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, 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.