Improving colorectal cancer detection by extending the near-infrared wavelength range and tissue probed depth of diffuse reflectance spectroscopy: a support vector machine approach

Nogueira, Marcelo Saito; Maryam, Siddra; Amissah, Michael; Lu, Huihui; Lynch, Noel; Killeen, Shane; O’Ríordáin, Mícheál; Andersson‐Engels, Stefan

doi:10.1117/12.2610497

Cited by 3 publications

(5 citation statements)

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“…The SVM Gaussian kernel moves the data from the feature space to the higher dimensional kernel space and provides nonlinear separation in the kernel space. The Gaussian kernel function parameter k in Equation (7) takes the value

[ 32 ]. Here, p is the number of attributes.…”

Section: Methodsmentioning

confidence: 99%

A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models

2023

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This paper investigates new feature extraction and regression methods for predicting cuffless blood pressure from PPG signals. Cuffless blood pressure is a technology that measures blood pressure without needing a cuff. This technology can be used in various medical applications, including home health monitoring, clinical uses, and portable devices. The new feature extraction method involves extracting meaningful features (time and chaotic features) from the PPG signals in the prediction of systolic blood pressure (SBP) and diastolic blood pressure (DBP) values. These extracted features are then used as inputs to regression models, which are used to predict cuffless blood pressure. The regression model performances were evaluated using root mean squared error (RMSE), R2, mean square error (MSE), and the mean absolute error (MAE). The obtained RMSE was 4.277 for systolic blood pressure (SBP) values using the Matérn 5/2 Gaussian process regression model. The obtained RMSE was 2.303 for diastolic blood pressure (DBP) values using the rational quadratic Gaussian process regression model. The results of this study have shown that the proposed feature extraction and regression models can predict cuffless blood pressure with reasonable accuracy. This study provides a novel approach for predicting cuffless blood pressure and can be used to develop more accurate models in the future.

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[ 32 ]. Here, p is the number of attributes.…”

Section: Methodsmentioning

confidence: 99%

A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models

2023

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“…Moreover, the relative improvement in identification of nerves when using the full EWDRS spectrum is in general agreement with prior studies which directly compared VIS/NIR versus VIS/NIR/SWIR spectral bands for tissue classification. [18][19][20][21] Nachabé's group first reported the estimation of lipid and water concentration in SWIR region and further proved the benefit of extended wavelength up to SWIR range to estimate biological chromophores. 9,18 The general agreement in observed spectral features and classification performance during microsurgical dissection of the femoral nerve in the chicken thigh in comparison with findings in the literature from human and other animal studies 43 supports future use of the model for early-stage development and testing of spectroscopic nerve Fig.…”

Section: Ex Vivo Microsurgical Nerve Dissection Modelmentioning

confidence: 98%

“… 9 – 17 Recently, a number of studies have reported that DRS conducted across the VIS/NIR/SWIR spectral ranges using dual-spectrometer detection systems improves the ability to comprehensively characterize biologically important chromophores and tissue properties in comparison with a single spectral band alone. 18 – 21 This VIS/NIR/SWIR configuration for DRS has been described as either extended-wavelength DRS (EWDRS), 22 – 24 DRS over an extended-wavelength range, 20 , 21 , 25 , 26 or simply DRS or diffuse optical spectroscopy. 27 – 36 Applications include skin, colorectal, and breast cancer diagnosis, as well as differentiation of skin and liver tissues.…”

Section: Introductionmentioning

confidence: 99%

“… 27 – 36 Applications include skin, colorectal, and breast cancer diagnosis, as well as differentiation of skin and liver tissues. 20 – 37 A particularly valuable application of EWDRS configurations is the detection of nerves and neurovascular bundles (NVB). 38 – 43 NVB are a multilayered structure and can contain multiple nerves and vessels surrounded by fat and connective tissues and can be difficult to identify visually due to the range of sizes and scenarios with which they present during surgery.…”

Section: Introductionmentioning

confidence: 99%

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Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

et al. 2022

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. Significance: Fiber-optic extended-wavelength diffuse reflectance spectroscopy (EWDRS) using both visible/near-infrared and shortwave-infrared detectors enables improved detection of spectral absorbances arising from lipids, water, and collagen and has demonstrated promise in a variety of applications, including detection of nerves and neurovascular bundles (NVB). Development of future applications of EWDRS for nerve detection could benefit from the use of model-based analyses including Monte Carlo (MC) simulations and evaluation of agreement between model systems and empirical measurements. Aim: The aim of this work is to characterize agreement between EWDRS measurements and simulations and inform future applications of model-based studies of nerve-detecting applications. Approach: A model-based platform consisting of an ex vivo microsurgical nerve dissection model, unique two-layer optical phantoms, and MC model simulations of fiber-optic EWDRS spectroscopic measurements were used to characterize EWDRS and compare agreement across models. In addition, MC simulations of an EWDRS measurement scenario are performed to provide a representative example of future analyses. Results: EWDRS studies performed in the common chicken thigh femoral nerve microsurgical dissection model indicate similar spectral features for classification of NVB versus adjacent tissues as reported in porcine models and human subjects. A comparison of measurements from unique EWDRS issue mimicking optical phantoms and MC simulations indicates high agreement between the two in homogeneous and two-layer optical phantoms, as well as in dissected tissues. Finally, MC simulations of measurement over a simulated NVB indicate the potential of future applications for measurement of nerve plexus. Conclusions: Characterization of agreement between fiber-optic EWDRS measurements and MC simulations demonstrates strong agreement across a variety of tissues and optical phantoms, offering promise for further use to guide the continued development of EWDRS for translational applications.

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“…DRS works by sending light to the interrogated biological tissue and detecting the diffusively reflected light (i.e., the light that emerges from the tissue surface after being scattered inside it). Since the detected light traveled inside the tissue, it contains information about the tissue’s optical properties such as scattering and absorption [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. Light scattering is dependent on the refractive index mismatches of tissue including sets of molecules (e.g., collagen fibers and fibrils), organelles (e.g., mitochondria), cell membranes, and inhomogeneity of the intracellular and extracellular environment [ 10 , 19 , 20 , 21 ].…”

Section: Introductionmentioning

confidence: 99%

Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

Nogueira

Maryam

Amissah

et al. 2022

Cancers

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Colorectal cancer (CRC) is the third most common and second most deadly type of cancer worldwide. Early detection not only reduces mortality but also improves patient prognosis by allowing the use of minimally invasive techniques to remove cancer while avoiding major surgery. Expanding the use of microsurgical techniques requires accurate diagnosis and delineation of the tumor margins in order to allow complete excision of cancer. We have used diffuse reflectance spectroscopy (DRS) to identify the main optical CRC biomarkers and to optimize parameters for the integration of such technologies into medical devices. A total number of 2889 diffuse reflectance spectra were collected in ex vivo specimens from 47 patients. Short source-detector distance (SDD) and long-SDD fiber-optic probes were employed to measure tissue layers from 0.5 to 1 mm and from 0.5 to 1.9 mm deep, respectively. The most important biomolecules contributing to differentiating DRS between tissue types were oxy- and deoxy-hemoglobin (Hb and HbO2), followed by water and lipid. Accurate tissue classification and potential DRS device miniaturization using Hb, HbO2, lipid and water data were achieved particularly well within the wavelength ranges 350–590 nm and 600–1230 nm for the short-SDD probe, and 380–400 nm, 420–610 nm, and 650–950 nm for the long-SDD probe.

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Improving colorectal cancer detection by extending the near-infrared wavelength range and tissue probed depth of diffuse reflectance spectroscopy: a support vector machine approach

Cited by 3 publications

References 32 publications

A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models

A Novel Cuffless Blood Pressure Prediction: Uncovering New Features and New Hybrid ML Models

Model-based characterization platform of fiber optic extended-wavelength diffuse reflectance spectroscopy for identification of neurovascular bundles

Insights into Biochemical Sources and Diffuse Reflectance Spectral Features for Colorectal Cancer Detection and Localization

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