Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor

Early detection and continuous monitoring of diseases are critical to improving patient outcomes, treatment adherence, and diagnostic accuracy. Traditional melanoma diagnosis relies primarily on visual assessment and biopsy, with reported accuracies ranging from 50% to 90% and significant inter-obse...

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Main Authors: Miguel Ángel Nava Blanco, Gerardo Antonio Castañón Ávila
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Sensors
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Online Access:https://www.mdpi.com/1424-8220/25/12/3792
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author Miguel Ángel Nava Blanco
Gerardo Antonio Castañón Ávila
author_facet Miguel Ángel Nava Blanco
Gerardo Antonio Castañón Ávila
author_sort Miguel Ángel Nava Blanco
collection DOAJ
description Early detection and continuous monitoring of diseases are critical to improving patient outcomes, treatment adherence, and diagnostic accuracy. Traditional melanoma diagnosis relies primarily on visual assessment and biopsy, with reported accuracies ranging from 50% to 90% and significant inter-observer variability. Among emerging diagnostic technologies, Raman spectroscopy has demonstrated considerable promise for non-invasive disease detection, particularly in early-stage skin cancer identification. A portable, real-time Raman spectroscopy system could significantly enhance diagnostic precision, reduce biopsy reliance, and expedite diagnosis. However, miniaturization of Raman spectrometers for portable use faces significant challenges, including weak signal intensity, fluorescence interference, and inherent trade-offs between spectral resolution and the signal-to-noise ratio. Recent advances in silicon photonics present promising solutions by facilitating efficient light collection, enhancing optical fields via high-index-contrast waveguides, and allowing compact integration of photonic components. This work introduces a numerical analysis of an integrated digital Fourier transform spectrometer implemented on a silicon-nitride (SiN) platform, specifically designed for Raman spectroscopy. The proposed system employs a switch-based digital Fourier transform spectrometer architecture coupled with a single optical power meter for detection. Utilizing a regularized regression method, we successfully reconstructed Raman spectra in the 800 cm<sup>−1</sup> to 1800 cm<sup>−1</sup> range, covering spectra of both benign and malignant skin lesions. Our results demonstrate the capability of the proposed system to effectively differentiate various skin cancer types, highlighting its feasibility as a non-invasive diagnostic sensor.
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spelling doaj-art-2d5981e1d4e04ded88c3fb0ba38c5fd92025-08-20T03:29:52ZengMDPI AGSensors1424-82202025-06-012512379210.3390/s25123792Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer BiosensorMiguel Ángel Nava Blanco0Gerardo Antonio Castañón Ávila1School of Engineering and Science, Tecnologico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, MexicoSchool of Engineering and Science, Tecnologico de Monterrey, Ave. Eugenio Garza Sada 2501, Monterrey 64849, MexicoEarly detection and continuous monitoring of diseases are critical to improving patient outcomes, treatment adherence, and diagnostic accuracy. Traditional melanoma diagnosis relies primarily on visual assessment and biopsy, with reported accuracies ranging from 50% to 90% and significant inter-observer variability. Among emerging diagnostic technologies, Raman spectroscopy has demonstrated considerable promise for non-invasive disease detection, particularly in early-stage skin cancer identification. A portable, real-time Raman spectroscopy system could significantly enhance diagnostic precision, reduce biopsy reliance, and expedite diagnosis. However, miniaturization of Raman spectrometers for portable use faces significant challenges, including weak signal intensity, fluorescence interference, and inherent trade-offs between spectral resolution and the signal-to-noise ratio. Recent advances in silicon photonics present promising solutions by facilitating efficient light collection, enhancing optical fields via high-index-contrast waveguides, and allowing compact integration of photonic components. This work introduces a numerical analysis of an integrated digital Fourier transform spectrometer implemented on a silicon-nitride (SiN) platform, specifically designed for Raman spectroscopy. The proposed system employs a switch-based digital Fourier transform spectrometer architecture coupled with a single optical power meter for detection. Utilizing a regularized regression method, we successfully reconstructed Raman spectra in the 800 cm<sup>−1</sup> to 1800 cm<sup>−1</sup> range, covering spectra of both benign and malignant skin lesions. Our results demonstrate the capability of the proposed system to effectively differentiate various skin cancer types, highlighting its feasibility as a non-invasive diagnostic sensor.https://www.mdpi.com/1424-8220/25/12/3792Raman spectroscopyskin cancersilicon integrated photonics
spellingShingle Miguel Ángel Nava Blanco
Gerardo Antonio Castañón Ávila
Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
Sensors
Raman spectroscopy
skin cancer
silicon integrated photonics
title Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
title_full Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
title_fullStr Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
title_full_unstemmed Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
title_short Numerical Analysis of a SiN Digital Fourier Transform Spectrometer for a Non-Invasive Skin Cancer Biosensor
title_sort numerical analysis of a sin digital fourier transform spectrometer for a non invasive skin cancer biosensor
topic Raman spectroscopy
skin cancer
silicon integrated photonics
url https://www.mdpi.com/1424-8220/25/12/3792
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AT gerardoantoniocastanonavila numericalanalysisofasindigitalfouriertransformspectrometerforanoninvasiveskincancerbiosensor