Dr. Renan Arnon Romano Profile

Dr. Renan Arnon Romano

at Instituto de Física de São Carlos

SPIE Involvement:

Author

Renan Arnon Romano is a Ph.D. student in the São Carlos Institute of Physics – University of São Paulo. He graduated in Physics and received a Master degree from the same institute. His expertise is pattern recognition in images and spectras. His research emphasizes understanding the photodynamic inactivation protocols using microscopy images. He is mainly interested in diagnostic optical and photonics systems.

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 | 4 March 2019 Paper

Label-free multispectral lifetime fluorescence to distinguish skin lesions

Renan Romano, Ramon G. Rosa, Javier Jo, Cristina Kurachi

Proceedings Volume 10890, 108902L (2019) https://doi.org/10.1117/12.2510498

KEYWORDS: Luminescence, Skin, Fluorescence lifetime imaging, Skin cancer, Cancer, Biopsy, Tissue optics, Tissues, In vivo imaging, Optical inspection

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Proceedings Article | 14 March 2018 Presentation

In vitro and in vivo studies of 2-photon photodynamic therapy for the treatment of conjunctival melanoma (Conference Presentation)

Layla Pires, Shireen Khattak, Sebastião Pratavieira, Renan Romano, Vanderlei Bagnato, Yeni Yucel, Cristina Kurachi, Brian Wilson

Proceedings Volume 10476, 104760O (2018) https://doi.org/10.1117/12.2288544

KEYWORDS: Melanoma, Photodynamic therapy, Tumors, In vitro testing, In vivo imaging, Near infrared, Heat therapy, Low-intensity laser therapy, Absorption, Cell death

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Proceedings Article | 14 February 2018 Presentation + Paper

Dual-channel (green and red) fluorescence microendoscope with subcellular resolution

Camila de Paula D'Almeida, Thereza Cury Fortunato, Ramon Gabriel Teixeira Rosa, Renan Arnon Romano, Lilian Tan Moriyama, Sebastião Pratavieira

Proceedings Volume 10470, 1047016 (2018) https://doi.org/10.1117/12.2290923

KEYWORDS: Luminescence, Tissues, Photodynamic therapy, Fluorescent markers, Tissue optics, Optical filters, Biopsy

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Proceedings Article | 28 July 2017 Paper

Curcumin uptake enhancement using low dose light illumination during incubation in Candida albicans

Renan Romano, Sebastião Pratavieira, Ana da Silva, Cristina Kurachi, Vanderlei Bagnato, Francisco E. G. Guimarães

Proceedings Volume 10413, 104130N (2017) https://doi.org/10.1117/12.2286271

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Proceedings Article | 28 July 2017 Paper

Multispectral confocal microscopy images and artificial neural nets to monitor the photosensitizer uptake and degradation in Candida albicans cells

Renan Romano, Sebastião Pratavieira, Ana da Silva, Cristina Kurachi, Francisco E. Guimarães

Proceedings Volume 10414, 104140D (2017) https://doi.org/10.1117/12.2282806

KEYWORDS: Confocal microscopy, Neural networks, Multispectral imaging

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Proceedings Article | 19 June 2015 Paper

Optical fluorescence spectroscopy to detect hepatic necrosis after normothermic ischemia: animal model

Renan Romano, Jose Vollet-Filho, Sebastião Pratavieira, Jorge Fernandez, Cristina Kurachi, Vanderlei Bagnato, Orlando Castro-e-Silva, Ajith Sankarankutty

Proceedings Volume 9531, 95313V (2015) https://doi.org/10.1117/12.2180897

KEYWORDS: Ischemia, Liver, Tissues, Luminescence, Transplantation, Fluorescence spectroscopy, Tissue optics, Laser induced fluorescence, Ocean optics, Animal model studies

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