Autofluorescence spectroscopy of cutaneous neoplasia under ultraviolet, visible and near infrared excitation

Borisova, Ekaterina; Ivanov, Deyan; Kolev, Boyko; Genova, Tsanislava; Mircheva, Victoria; Ilyov, Stoyan; Zaharieva, Lidia; Lihachova, Ilze; Lihachovs, Aleksejs; Spīgulis, Jānis; Troyanova, P.

doi:10.1117/12.2555982

Cited by 4 publications

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“…Assoc. Prof. Ekaterina Borisova was always ready to embrace new ideas and scientific horizons, for instance, by adopting multimodal techniques, including multispectral, fluorescence lifetime and Raman imaging/spectroscopy for skin diagnosis/analysis [37][38] and autofluorescence spectroscopy of cutaneous neoplasia under different spectral domain excitation wavelengths [39].…”

Section: Skin Optical Biopsymentioning

confidence: 99%

A review of career devoted to Biophotonics – In memoriam to Ekaterina Borisova (1978–2021)

Genova¹,

Avramov²,

Kolev³

et al. 2021

J-BPE

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Regretfully, because of her sudden demise, Assoc. Prof. Ekaterina Borisova is no longer amongst us. COVID-19 pulled away a brilliant scientist during the peak of her scientific career (see Fig. 1). All authors would like to express deepest condolences and sincere support to her family, friends, relatives and colleagues! We, therefore, rightfully commemorate her dedicated and devoted contribution to biophotonics, her readiness to always support, help, motivate and inspire all her colleagues and collaborators. Fig. 1 Assoc. Prof. Ekaterina Borisova examining samples under microscope.

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Section: Skin Optical Biopsymentioning

confidence: 99%

A review of career devoted to Biophotonics – In memoriam to Ekaterina Borisova (1978–2021)

Genova¹,

Avramov²,

Kolev³

et al. 2021

J-BPE

Self Cite

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“…Several animal and human tissue studies have been published on the autofluorescence properties of skin cancer lesions. 31 – 35 Pastore et al. 36 conducted experiments with mouse models to study the autofluorescence response from melanoma skin lesions using multiphoton excitation at 740 and 900 nm and emission spectral bands at 447 and 540 nm.…”

Section: Introductionmentioning

confidence: 99%

Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning

et al. 2022

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. Significance: Accurate early diagnosis of malignant skin lesions is critical in providing adequate and timely treatment; unfortunately, initial clinical evaluation of similar-looking benign and malignant skin lesions can result in missed diagnosis of malignant lesions and unnecessary biopsy of benign ones. Aim: To develop and validate a label-free and objective image-guided strategy for the clinical evaluation of suspicious pigmented skin lesions based on multispectral autofluorescence lifetime imaging (maFLIM) dermoscopy. Approach: We tested the hypothesis that maFLIM-derived autofluorescence global features can be used in machine-learning (ML) models to discriminate malignant from benign pigmented skin lesions. Clinical widefield maFLIM dermoscopy imaging of 41 benign and 19 malignant pigmented skin lesions from 30 patients were acquired prior to tissue biopsy sampling. Three different pools of global image-level maFLIM features were extracted: multispectral intensity, time-domain biexponential, and frequency-domain phasor features. The classification potential of each feature pool to discriminate benign versus malignant pigmented skin lesions was evaluated by training quadratic discriminant analysis (QDA) classification models and applying a leave-one-patient-out cross-validation strategy. Results: Classification performance estimates obtained after unbiased feature selection were as follows: 68% sensitivity and 80% specificity with the phasor feature pool, 84% sensitivity, and 71% specificity with the biexponential feature pool, and 84% sensitivity and 32% specificity with the intensity feature pool. Ensemble combinations of QDA models trained with phasor and biexponential features yielded sensitivity of 84% and specificity of 90%, outperforming all other models considered. Conclusions: Simple classification ML models based on time-resolved (biexponential and phasor) autofluorescence global features extracted from maFLIM dermoscopy images have the potential to provide objective discrimination of malignant from benign pigmented lesions. ML-assisted maFLIM dermoscopy could potentially assist with the clinical evaluation of suspicious lesions and the identification of those patients benefiting the most from biopsy examination.

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Hybrid Endoscopes Applications for Internal Organs Oncology Diagnostics

Zaichenko

Gurevich

2020

2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)

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Autofluorescence spectroscopy of cutaneous neoplasia under ultraviolet, visible and near infrared excitation

Cited by 4 publications

References 0 publications

A review of career devoted to Biophotonics – In memoriam to Ekaterina Borisova (1978–2021)

A review of career devoted to Biophotonics – In memoriam to Ekaterina Borisova (1978–2021)

Discrimination of cancerous from benign pigmented skin lesions based on multispectral autofluorescence lifetime imaging dermoscopy and machine learning

Hybrid Endoscopes Applications for Internal Organs Oncology Diagnostics

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