Method of autofluorescence diagnostics of skin neoplasms in the near infrared region

Khristoforova, Yulia А.; Bratchenko, Ivan А.; Artemyev, Dmitry N.; Myakinin, Oleg O.; Kozlov, Sergey V.; Moryatov, Alexander A.; Zakharov, Valery P.

doi:10.18287/jbpe-2015-1-3-186

Cited by 13 publications

(4 citation statements)

References 21 publications

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“…Accordingly, the biopsy ratio for Raman classification of MM and pigmented lesions is 3.95:1 at the 90% sensitivity. The biopsy ratio for AF classification of MM and pigmented lesions is 3.33:1 at the 90% sensitivity that also proves that NIR AF estimation has a fairly low potential for diagnosing skin neoplasms 23,40 . The best biopsy ratios for differentiation of malignant from benign neoplasms and differentiation of MM from SK are as low as 1.53:1 and 0.92:1, respectively.…”

Section: Discussionmentioning

confidence: 68%

In vivo diagnosis of skin cancer with a portable Raman spectroscopic device

Bratchenko

Moryatov

et al. 2021

Experimental Dermatology

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In this study, we performed in vivo diagnosis of skin cancer based on implementation of a portable low‐cost spectroscopy setup combining analysis of Raman and autofluorescence spectra in the near‐infrared region (800–915 nm). We studied 617 cases of skin neoplasms (615 patients, 70 melanomas, 122 basal cell carcinomas, 12 squamous cell carcinomas and 413 benign tumors) in vivo with a portable setup. The studies considered the patients examined by GPs in local clinics and directed to a specialized Oncology Dispensary with suspected skin cancer. Each sample was histologically examined after excisional biopsy. The spectra were classified with a projection on latent structures and discriminant analysis. To check the classification models stability, a 10‐fold cross‐validation was performed. We obtained ROC AUCs of 0.75 (0.71–0.79; 95% CI), 0.69 (0.63–0.76; 95% CI) and 0.81 (0.74–0.87; 95% CI) for classification of a) malignant and benign tumors, b) melanomas and pigmented tumors and c) melanomas and seborrhoeic keratosis, respectively. The positive and negative predictive values ranged from 20% to 52% and from 73% to 99%, respectively. The biopsy ratio varied from 0.92:1 to 4.08:1 (at sensitivity levels from 90% to 99%). The accuracy of automatic analysis with the proposed system is higher than the accuracy of GPs and trainees, and is comparable or less to the accuracy of trained dermatologists. The proposed approach may be combined with other optical techniques of skin lesion analysis, such as dermoscopy‐ and spectroscopy‐based computer‐assisted diagnosis systems to increase accuracy of neoplasms classification.

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Section: Discussionmentioning

confidence: 68%

In vivo diagnosis of skin cancer with a portable Raman spectroscopic device

Bratchenko

Moryatov

et al. 2021

Experimental Dermatology

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“…29 Another study also showed that the autofluorescence approach allows the diagnosis of malignant melanomas with the accuracy for ex vivo and in vivo studies in line with our in vitro study. 30 This imaging method and the developed image processing code, which result in the intensity of autofluorescence quantifications, seem to be feasible and promising for application as a quantified optical technique in cancerous and non-cancerous skin melanoma or treatment monitoring in melanoma studies. We have some more ongoing studies to investigate the treatment response monitoring of A375 melanoma cells and to evaluate the alterations of A375 melanoma cell autofluorescence on various days post-treatment.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Autofluorescence Imaging of A375 Human Melanoma Cell Samples: A Pilot Study

et al. 2021

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Introduction: Skin cancer is one of the most common types of malignancy worldwide. Human skin naturally contains several endogenous fluorophores, as potential sources can emit inherent fluorescence, called intrinsic autofluorescence (AF). The melanin endogenous fluorophore in the basal cell layer of the epidermis seems to have a strong autofluorescence signal among other ones in the skin. This pilot study aimed to investigate the feasibility of the detection of autofluorescence signals in the A375 human melanoma cell line in the cell culture stage using the FluoVision optical imaging system. Methods: The human skin melanoma cell line (A375) donated as a gift from Switzerland (University Hospital Basel) was cultured. For the imaging of the A375 human melanoma cell sample in this pilot study, the FluoVision optical imaging device (Tajhiz Afarinan Noori Parseh Co) was applied. The proposed clustering image processing code was developed based on the K-mean segmentation method, using MATLAB software (version 16). Results: The quantification of color pixels in the color bar along with the intensity score of the autofluorescence signal ranged between 0 and 70 was written in the image processing code execution and a threshold higher than 40%, proportional to the ratio of autofluorescent cells. The percentage of the signal of A375 autofluorescent melanoma cells in the 3 studied cell samples was calculated as 3.11%±0.6. Conclusion: This imaging method has the advantage of no need for fluorophore labels over the existing fluorescence imaging methods, and it can be regarded as one of the important choices of label-free imaging for this A375 melanoma cell line containing the intrinsic endogenous fluorophore in cell studies.

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“…33 Details of AF spectra curvature calculation can be found elsewhere. 34 According to observed VIS AF spectra ( Fig. 4), we propose to use a number of criteria to monitor the changes of flavins, lipids, and porphyrins content in skin tissues.…”

Section: Tissue Samplesmentioning

confidence: 99%

“…And these coefficients may be measured simultaneously with Raman signal. Such an approach was first described in our study, 34 where only the curvature sign of the spectrum approximation function [Eq. 2] was used for sample differentiation.…”

Section: Near-infrared Autofluorescence Tissue Studymentioning

confidence: 99%

Combined Raman and autofluorescence ex vivo diagnostics of skin cancer in near-infrared and visible regions

et al. 2017

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The differentiation of skin melanomas and basal cell carcinomas (BCCs) was demonstrated based on combined analysis of Raman and autofluorescence spectra stimulated by visible and NIR lasers. It was ex vivo tested on 39 melanomas and 40 BCCs. Six spectroscopic criteria utilizing information about alteration of melanin, porphyrins, flavins, lipids, and collagen content in tumor with a comparison to healthy skin were proposed. The measured correlation between the proposed criteria makes it possible to define weakly correlated criteria groups for discriminant analysis and principal components analysis application. It was shown that the accuracy of cancerous tissues classification reaches 97.3% for a combined 6-criteria multimodal algorithm, while the accuracy determined separately for each modality does not exceed 79%. The combined 6-D method is a rapid and reliable tool for malignant skin detection and classification.

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Method of autofluorescence diagnostics of skin neoplasms in the near infrared region

Cited by 13 publications

References 21 publications

In vivo diagnosis of skin cancer with a portable Raman spectroscopic device

In vivo diagnosis of skin cancer with a portable Raman spectroscopic device

Quantitative Autofluorescence Imaging of A375 Human Melanoma Cell Samples: A Pilot Study

Combined Raman and autofluorescence ex vivo diagnostics of skin cancer in near-infrared and visible regions

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