Significance: Multi-laboratory initiatives are essential in performance assessment and standardization—crucial for bringing biophotonics to mature clinical use—to establish protocols and develop reference tissue phantoms that all will allow universal instrument comparison.
Aim: The largest multi-laboratory comparison of performance assessment in near-infrared diffuse optics is presented, involving 28 instruments and 12 institutions on a total of eight experiments based on three consolidated protocols (BIP, MEDPHOT, and NEUROPT) as implemented on three kits of tissue phantoms. A total of 20 synthetic indicators were extracted from the dataset, some of them defined here anew.
Approach: The exercise stems from the Innovative Training Network BitMap funded by the European Commission and expanded to include other European laboratories. A large variety of diffuse optics instruments were considered, based on different approaches (time domain/frequency domain/continuous wave), at various stages of maturity and designed for different applications (e.g., oximetry, spectroscopy, and imaging).
Results: This study highlights a substantial difference in hardware performances (e.g., nine decades in responsivity, four decades in dark count rate, and one decade in temporal resolution). Agreement in the estimates of homogeneous optical properties was within 12% of the median value for half of the systems, with a temporal stability of <5 % over 1 h, and day-to-day reproducibility of <3 % . Other tests encompassed linearity, crosstalk, uncertainty, and detection of optical inhomogeneities.
Conclusions: This extensive multi-laboratory exercise provides a detailed assessment of near-infrared Diffuse optical instruments and can be used for reference grading. The dataset—available soon in an open data repository—can be evaluated in multiple ways, for instance, to compare different analysis tools or study the impact of hardware implementations.
Significance: Signal contamination is a major hurdle in functional near-infrared spectroscopy (fNIRS) of the human head as the NIR signal is contaminated with the changes corresponding to superficial tissue, therefore occluding the functional information originating from the cerebral region. For continuous wave, this is generally handled through linear regression of the shortest source-detector (SD) distance intensity measurement from all of the signals. Although phase measurements utilizing frequency domain (FD) provide deeper tissue sampling, the use of the shortest SD distance phase measurement for regression of superficial signal contamination can lead to misleading results, therefore suppressing cortical signals.
Aim: An approach for FD fNIRS that utilizes a short-separation intensity signal directly to regress both intensity and phase measurements, providing a better regression of superficial signal contamination from both data-types, is proposed.
Approach: Simulated data from realistic models of the human head are used, and signal regression using both intensity and phase-based components of the FD fNIRS is evaluated.
Results: Intensity-based phase regression achieves a suppression of superficial signal contamination by 68% whereas phase-based phase regression is only by 13%. Phase-based phase regression is also shown to generate false-positive signals from the cortex, which are not desirable.
Conclusions: Intensity-based phase regression provides a better methodology for minimizing superficial signal contamination in FD fNIRS.
Performance assessment and standardization are indispensable for instruments of clinical relevance in general and clinical instrumentation based on photon migration/diffuse optics in particular. In this direction, a multi-laboratory exercise was initiated with the aim of assessing and comparing their performances. 29 diffuse optical instruments belonging to 11 partner institutions of a European level Marie Curie Consortium BitMap1 were considered for this exercise. The enrolled instruments covered different approaches (continuous wave, CW; frequency domain, FD; time domain, TD and spatial frequency domain imaging, SFDI) and applications (e.g. mammography, oximetry, functional imaging, tissue spectroscopy). 10 different tests from 3 well-accepted protocols, namely, the MEDPHOT2 , the BIP3 , and the nEUROPt4 protocols were chosen for the exercise and the necessary phantoms kits were circulated across labs and institutions enrolled in the study. A brief outline of the methodology of the exercise is presented here. Mainly, the design of some of the synthetic descriptors, (single numeric values used to summarize the result of a test and facilitate comparison between instruments) for some of the tests will be discussed.. Future actions of the exercise aim at deploying these measurements onto an open data repository and investigating common analysis tools for the whole dataset.
Brain tissue oxygen saturation, StO2, measured with near-infrared spectroscopy (NIRS) is of great clinical interest as it quantifies the balance between cerebral oxygen supply and demand. Some brain oximeters are based on spatially resolved spectroscopy (SRS), where NIRS data is collected at multiple distances from the light source to estimate a slope of light attenuation against distance. Other use a broadband approach which utilizes derivatives of the absorption spectra to estimate StO2, such as broadband fitting (BF). We describe a novel algorithm, broadband spatially resolved spectroscopy (BB-SRS), for estimating StO2. It is based on comparing the measured slope to a model of the attenuation slope, which depends on the optical properties of tissue. Fitting this model with a least squares fitting procedure recovers parameters describing absorption and scattering; the concentrations of oxy- and deoxy-haemoglobin and hence StO2 and the scattering parameters β and α describing the exponential dependence of scattering on wavelength. To demonstrate BB-SRS, a broadband spectrum (700 - 1000 nm, step size 2 nm) was simulated in NIRFAST and was analysed with BB-SRS, SRS and BF. The developed BB-SRS algorithm recovered StO2 with a relative error of -9%; the concentration of deoxyhaemoglobin with a relative error of +4% , oxyhaemoglobin -10%. The scattering parameters β and α were recovered with a relative error of -30% and -2%, respectively. Among the three algorithms, BB-SRS performed with the best relative error.
Performance assessment of instruments is a growing demand in the diffuse optics community and there is a definite need to get together to address this issue. Within the EU Network BITMAP1, we initiated a campaign for the performance evaluation of 10 diffuse optical instrumentation from 7 partner institutions adopting a set of 3 well accepted, standardized protocols. A preliminary analysis of the outcome along with future perspectives will be presented.
We propose a nonlocal diffusion equation (NDE) as a new forward model, which uses the concepts of differential operators under the nonlocal vector calculus. The discretization of the NDE is performed using an effective graph-based numerical method (GNM). We evaluate the proposed forward modelling method on a homogeneous slab where the analytical solution is available. Our experiments show that the results of the NDE (discretized by GNM) is quantitatively comparable to the analytical solution. The proposed method has an identical implementation for geometries in two and three dimensions due to the nature of the graph representation.
A continuous wave broadband near-infrared spectroscopy method is developed based on twolayered fitting of optical properties, to recover the haemoglobin concentrations and scattering parameters in cerebral and extra-cerebral tissues along with fitting for the extra-cerebral layer thickness. It is shown that tissue oxygenation for deep tissue and superficial tissue thickness is recovered with less than 4% error, whereas a homogeneous fit having an error of 15%.
Open Data philosophy is becoming more popular among scientists. Open Data approach aims to transform science by making high-quality and well-documented scientific data open to everybody in order to promote collaboration and transparency. In diffuse optical and near-infrared spectroscopy community, a large measurement dataset collected with state-of-the-art instrumentation applied on well-defined phantoms is still missing. Within that context, several European labs from BitMap network1 have collected diffuse optical data on standard phantoms involving the largest set of diffuse optics instruments published until now. In this work, we present a running project on the open dataset and associated reporting tools.
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