Dr. Ana Gabriela Salvio Profile

Dr. Ana Gabriela Salvio

at Hospital Amaral Carvalho

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Publications (8)

SPIE Journal Paper | 14 June 2022 Open Access

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

Priyanka Vasanthakumari, Renan Romano, Ramon G. Rosa, Ana G. Salvio, Vladislav Yakovlev, Cristina Kurachi, Jason Hirshburg, Javier Jo

JBO, Vol. 27, Issue 06, 066002, (June 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.6.066002

KEYWORDS: Skin, Melanoma, Luminescence, Tumor growth modeling, Skin cancer, Data analysis, Biopsy, Multispectral imaging, Feature extraction, Feature selection

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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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Proceedings Article | 3 March 2022 Presentation + Paper

AI-driven discrimination of benign from malignant pigmented skin lesions based on multispectral autofluorescence lifetime dermoscopy imaging

Priyanka Vasanthakumari, Renan Romano, Ramon G. Rosa, Ana Salvio, Vladislav Yakovlev, Cristina Kurachi, Javier Jo

Proceedings Volume 11934, 1193408 (2022) https://doi.org/10.1117/12.2610345

KEYWORDS: Skin, Melanoma, Skin cancer, Neurons, Biopsy, Performance modeling, Image classification, Machine learning, Fluorescence lifetime imaging

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Proceedings Article | 28 February 2020 Presentation + Paper

Classification of skin-cancer lesions based on fluorescence lifetime imaging

Priyanka Vasanthakumari, Renan Romano, Ramon G. Rosa, Ana Salvio, Vladislav Yakovlev, Cristina Kurachi, Javier Jo

Proceedings Volume 11317, 113170Z (2020) https://doi.org/10.1117/12.2548625

KEYWORDS: Fluorescence lifetime imaging, Skin, Tissues, Skin cancer, Data analysis, Feature extraction, Luminescence, Melanoma, Biopsy, Diagnostics

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Proceedings Article | 14 August 2019 Presentation

Economic evaluation of photodynamic therapy implementation for non-melanoma skin cancer in the Brazilian public health system (Conference Presentation)

Hilde Buzzá, Lilian Moriyama, José Vollet-Filho, Natalia Inada, Ana da Silva, Mirian Stringasci, Michelle Requena, Renan Romano, Kate Blanco, Cristina Kurachi, Ana Salvio, Vanderlei Bagnato

Proceedings Volume 11070, 110708Z (2019) https://doi.org/10.1117/12.2526164

KEYWORDS: Photodynamic therapy, Skin cancer, Melanoma, Skin, Medical equipment

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Proceedings Article | 14 March 2018 Presentation

Preclinical studies of dual-photosensitizer PDT combined with optical clearing for treatment of cutaneous melanoma (Conference Presentation)

Layla Pires, Ana Gabriela Sálvio, Vanderlei Bagnato, Brian Wilson, Cristina Kurachi

Proceedings Volume 10467, 104670U (2018) https://doi.org/10.1117/12.2288539

KEYWORDS: Photodynamic therapy, Melanoma, Tumors, Optical clearing, Skin cancer, Tissue optics, Light scattering, Surgery, Radiotherapy, Absorption

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SPIE Journal Paper | 19 October 2017 Open Access

Portable fluorescence lifetime spectroscopy system for in-situ interrogation of biological tissues

Marcelo Saito Nogueira, Alessandro Cosci, Ramon Gabriel Teixeira Rosa, Ana Gabriela Sálvio, Sebastião Pratavieira, Cristina Kurachi

JBO, Vol. 22, Issue 12, 121608, (October 2017) https://doi.org/10.1117/12.10.1117/1.JBO.22.12.121608

KEYWORDS: Luminescence, Tissues, Fluorescence spectroscopy, Skin, Spectroscopy, Tissue optics, Calibration, Bandpass filters, Pulsed laser operation, Collagen

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Proceedings Article | 19 June 2015 Paper

Asymmetry and irregularity border as discrimination factor between melanocytic lesions

David Sbrissa, Sebastião Pratavieira, Ana Gabriela Salvio, Cristina Kurachi, Vanderlei Salvadori Bagnato, Luciano Da Fontoura Costa, Gonzalo Travieso

Proceedings Volume 9531, 953122 (2015) https://doi.org/10.1117/12.2186180

KEYWORDS: Image segmentation, Melanoma, Image processing, Image analysis, Medical imaging, Databases, Cancer, Skin, Surface plasmons, Digital cameras

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Proceedings Article | 19 June 2015 Paper

Thermographic diagnostics to discriminate skin lesions: a clinical study

Mirian Denise Stringasci, Lilian Tan Moriyama, Ana Gabriela Salvio, Vanderlei Salvador Bagnato, Cristina Kurachi

Proceedings Volume 9531, 953135 (2015) https://doi.org/10.1117/12.2180967

KEYWORDS: Skin, Thermography, Melanoma, Diagnostics, Infrared radiation, Infrared imaging, Skin cancer, Phase shift keying, Cancer, Tumors

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Showing 5 of 8 publications

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