Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Mamouei, Mohammad; Budidha, Karthik; Baishya, Nystha; Qassem, Meha; Kyriacou, P. A.

doi:10.1038/s41598-020-73406-4

Cited by 20 publications

(12 citation statements)

References 54 publications

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“…Thus, the calibration of the sensor cannot be achieved through any standard regression analysis, and supervised machine learning algorithms must be incorporated. Observations from the in-silico investigations also agree with our previous experience where we explored a preliminary sophisticated algorithm to analyze our in-vitro experimental data 4 .…”

Section: Discussionsupporting

confidence: 86%

“…As a step towards the development of such a device, researchers have investigated the feasibility of using short-wave infrared (SWIR) light (typically, between the range of 1300nm -2500nm) to detect the optical signature of lactate in blood and estimated the concentration of lactate from the acquired spectra using various regression models [2][3][4][5][6][7][8] . These preliminary in-vitro investigations have shown great promise and have paved the way for the development of a novel optical sensor for the blood-lactate measurements.…”

Section: Introductionmentioning

confidence: 99%

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In-Silico Investigation towards the Non-Invasive Optical Detection of Blood Lactate

Chatterjee

Budidha

Qassem

et al. 2021

Preprint

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This paper uses Monte Carlo simulations to investigate the interaction of shortwave infrared (SWIR) light with vascular tissue as a step toward the development of a non-invasive optical sensor for measuring blood lactate in humans. The primary focus of this work was to determine the optimal source-detector separation, penetration depth of light at SWIR wavelengths in tissue, and the optimal light power required for reliable detection of lactate. The investigation also focused on determining the non-linear variations in absorbance of lactate at a few select SWIR wavelengths. SWIR photons only penetrated 1.3 mm and did not travel beyond the hypodermal fat layer. The maximum output power was only 2.51% of the input power, demonstrating the need for a highly sensitive detection system. Simulations optimized a source-detector separation of 1 mm at 1684 nm for accurate measurement of lactate in blood.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

In-Silico Investigation towards the Non-Invasive Optical Detection of Blood Lactate

Chatterjee

Budidha

Qassem

et al. 2021

Preprint

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“…The optimal wavelength selection offers two clear benefits. Firstly, it has been shown that the inclusion of uninformative wavelengths in the training process negatively affects the accuracy of predictions and model interpretability [ 48 , 49 ]. Secondly, from a more practical point of view, the identification of a few wavelengths, or regions of the optical spectrum, that contain information about chemical species, significantly reduces the time and cost associated with their measurement and enables the development of portable and high-speed optical sensors.…”

Section: Resultsmentioning

confidence: 99%

Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares

Wang

2021

Molecules

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A direct, reagent-free, ultraviolet spectroscopic method for the simultaneous determination of nitrate (NO3−), nitrite (NO2−), and salinity in seawater is presented. The method is based on measuring the absorption spectra of the raw seawater range of 200–300 nm, combined with partial least squares (PLS) regression for resolving the spectral overlapping of NO3−, NO2−, and sea salt (or salinity). The interference from chromophoric dissolved organic matter (CDOM) UV absorbance was reduced according to its exponential relationship between 275 and 295 nm. The results of the cross-validation of calibration and the prediction sets were used to select the number of factors (4 for NO3−, NO2−, and salinity) and to optimize the wavelength range (215–240 nm) with a 1 nm wavelength interval. The linear relationship between the predicted and the actual values of NO3−, NO2−, salinity, and the recovery of spiked water samples suggest that the proposed PLS model can be a valuable alternative method to the wet chemical methods. Due to its simplicity and fast response, the proposed PLS model can be used as an algorithm for building nitrate and nitrite sensors. The comparison study of PLS and a classic least squares (CLS) model shows both PLS and CLS can give satisfactory results for predicting NO3− and salinity. However, for NO2− in some samples, PLS is superior to CLS, which may be due to the interference from unknown substances not included in the CLS algorithm. The proposed method was applied to the analysis of NO3−, NO2−, and salinity in the Changjiang (Yangtze River) estuary water samples and the results are comparable with that determined by the colorimetric Griess assay.

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“…[24] showed the potential of NIR spectra in the estimation of lactate concentration in blood, reporting a coefficient of determination of 0.96 with cross-validation, 2 . [25] applied a number of variable selection methods to the mid-IR spectra of lactate and showed that highly accurate estimates, 2 = 0.996, can be achieved with models that only use a small subset of wavelengths. [26] conducted a comprehensive comparison of the different regions of the optical spectrum, namely ultraviolet/visible, NIR, and mid-IR, for the measurement of lactate and highlighted the merits of mid-IR for in-vitro applications and NIR for transcutaneous applications.…”

Section: An Empirical Investigation Of Deviations From the Beer-lambementioning

confidence: 99%

An empirical investigation of deviations from the Beer-Lambert law in near-infrared spectroscopy: A case study of lactate in aqueous solutions, serum, blood and tissue

Mamouei

Budidha

Baishya

et al. 2021

Preprint

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The linear relationship between optical absorbance and the concentration of analytes -as postulated by the Beer-Lambert law- is one of the fundamental assumptions that much of the optical spectroscopy literature is explicitly or implicitly based upon. The common use of linear regression models such as principal component regression and partial least squares exemplifies how the linearity assumption is upheld in practical applications. However, the literature also establishes that deviations from the Beer-Lambert law can be expected when a) the light source is far from monochromatic, b) the concentrations of analytes are very high and c) the medium is highly scattering. The lack of a quantitative understanding of when such nonlinearities can become predominant, along with the mainstream use of nonlinear machine learning models in different fields, have given rise to the use of methods such as random forests, support vector regression, and neural networks in spectroscopic applications. This raises the question that, given the small number of samples and the high number of variables in many spectroscopic datasets, are nonlinear effects significant enough to justify the additional model complexity? In the present study, we empirically investigate this question in relation to lactate, an important biomarker. Particularly, to analyze the effects of scattering matrices, three datasets were generated by varying the concentration of lactate in phosphate buffer solution, human serum, and sheep blood. Additionally, the fourth dataset pertained to invivo, transcutaneous spectra obtained from healthy volunteers in an exercise study. Linear and nonlinear models were fitted to each dataset and measures of model performance were compared to attest the assumption of linearity. To isolate the effects of high concentrations, the phosphate buffer solution dataset was augmented with six samples with very high concentrations of lactate between (100-600 mmol/L). Subsequently, three partly overlapping datasets were extracted with lactate concentrations varying between 0-11 mmol/L, 0-20 mmol/L and 0-600 mmol/L. Similarly, the performance of linear and nonlinear models were compared in each dataset. This analysis did not provide any evidence of substantial nonlinearities due high concentrations. However, the results suggest that nonlinearities in scattering media may be substantial, justifying the use of complex, nonlinear models.

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Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Cited by 20 publications

References 54 publications

In-Silico Investigation towards the Non-Invasive Optical Detection of Blood Lactate

In-Silico Investigation towards the Non-Invasive Optical Detection of Blood Lactate

Ultraviolet Spectroscopic Detection of Nitrate and Nitrite in Seawater Simultaneously Based on Partial Least Squares

An empirical investigation of deviations from the Beer-Lambert law in near-infrared spectroscopy: A case study of lactate in aqueous solutions, serum, blood and tissue

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