KEYWORDS: Data modeling, Image segmentation, Fourier transforms, Deep learning, Sensors, Medical research, Machine learning, Functional near infrared spectroscopy, Digital signal processing
Functional near-infrared spectroscopy (fNIRS) presents an affordable and light-weight method to monitor the cerebral hemodynamics of the brain. However, noise and artefacts hamper the analysis of fNIRS signals. Thus, the signal quality assessment is a crucial step when planning fNIRS experiments. Currently no standardized method exists for the evaluation. Commonly used visual inspection of the signals is time consuming and prone to subjective bias. Recently use of machine learning and deep learning approaches have been applied for the fNIRS signal quality assessment, showing promising results. However, currently there are only a few experiments which have investigated the use of these approaches to evaluate fNIRS signal quality. In this human brain study, we utilized previously developed deep learning approach used for the assessment of PPG signal quality with short-time Fourier transform (STFT) to evaluate the quality of raw fNIRS signals with wavelengths 690 nm, 810 nm, 830 nm and 980 nm. The data was collected from 38 subjects with a two-channel fNIRS device, measured during breath hold protocol in sitting position. A total of 10,144 segments were extracted using a window of 10 seconds length without overlap and annotated for SQA by three independent evaluators. The segments were transformed with STFT, and further processed into 2D images. The images were used as input data for CNN deep learning network, and the output further used to classify the segments as acceptable or unacceptable. The results show high potential of using DL approach for fNIRS signal quality assessment with classification accuracy of 87.89 %.
KEYWORDS: Hemodynamics, Brain, Oxygenation, Near infrared spectroscopy, LED lighting, Light emitting diodes, Frequency response, Medicine, Light sources and illumination
Transcranial photobiomodulation (tPBM) has emerged as a promising economical point-of-care tool to enhance mitochondrial dynamics, mitigate neuroinflammation, improve sleep and cognitive functions in various CNS disorders. Its propensity to modulate cerebrovascular tone can potentially alter cerebral hemodynamics. We set out to investigate whether tPBM can influence the brain oxygenation as assessed by fNIRS in healthy subjects with a body positional challenge.
Signal quality is crucial in any signal analysis. Typically, the reason for bad signal quality is inappropriate sensor placement which is also highly dependent on the measurement location. It is usually quite easy to get a good optical signal from finger, but not from the brain. This study aims to provide a real-time signal quality assessment method to help clinical personnel in placement of the fNIRS sensors on head to ensure good signal quality. Signal was segmented for each 10 seconds and a band-pass filter at 0.5-3 Hz was applied to isolate signal in cardiac band. Each segmented signal was subject to visual quality assessment to get bad, fair, and good labels. We used maximum to mean power ratio to generate signal quality index (SQI) score. Other methods included were skewness and kurtosis of the heart rate variability (HRV). Results showed that power ratio provides better consistency and separation among three different labels. Both skewness and kurtosis failed to separate fair and good segments. Using two threshold values, indices from power ration can be transformed into red (bad), yellow (fair), and green (good) alarm to help healthcare practitioners, who have no expertise to assess signal quality, to fix sensor placement to get good or acceptable signals.
The Monro-Kellie doctrine states that the sum of the contents of the intracranial cavity is constant, and consequently dynamics of blood and cerebrospinal fluid (CSF) volumes should be in an anti-correlation relationship. This phenomenon helped to explain many abnormalities in intracranial hypotension and CSF depletion. We aimed to validate the same phenomenon in mice during a blood pressure (BP) lowering test. Eight 2–3-month-old C57/Bl6N (Charles River) female mice were used in this study. We used both nicardipine hydrochloride and sodium nitroprusside (SNP) infusion into the femoral vein to lower the BP. A multi-wavelength NIRS (685, 830, and 980 nm) measuring hemoglobin and water concentrations, sampled at 800 Hz, was used. The fiber probes for the light source and detector were inserted into the ear canals and positioned towards the brain, giving a distance of approximately 1 cm. Following the Monro-Kellie doctrine, the blood volume, i.e., total hemoglobin (HbT), and CSF volume should be in an anti-correlation relationship. Our experiments showed that concentration changes of total hemoglobin (HbT) and water, are in anti-correlation with correlation coefficients of -0.991 ± 0.007.
Obtaining parameters that characterize cerebral fluid interactions in the human brain is of high interest particularly as regards studies of the brain clearance and in relation to neurodegeneration diseases (NDD). Furthermore, disturbances in sleep affecting brain clearance have been linked to NDDs like Alzheimer’s disease (AD). At present, polysomnography (PSG) is the methodological gold standard in sleep research being used in sleep labs. However, it does not provide direct information on cerebral fluid dynamics which may be an important parameter linked to brain clearance activity during sleep. We have developed functional near-infrared spectroscopy (fNIRS) based method for assessment of human cerebral fluid dynamics during sleep. It is optimized as a wearable sleep monitoring device enabling overnight sleep recordings at home without disturbing natural sleep. In this paper, we study spectral entropy (SE) of cerebral fluid dynamics during sleep study. Developed fNIRS technique measures, in addition to cerebral hemodynamics, cortical water concentration changes reflecting dynamics of the cerebrospinal fluid (CSF) volume in macroscale. Our preliminary results of overnight fNIRS sleep measurements from 10 adult subjects show that SE values fluctuate in cycle during the whole night sleep. It may indicate the transition among sleep stages.
Functional magnetic resonance imaging (fMRI) is a common medical device to diagnose Alzheimer’s disease (AD), but it is not for all subjects due to its cost and other issues. We investigated the potential of functional near-infrared spectroscopy (fNIRS) to separate AD patients from controls as a pre-screening prior to more thorough examination using fMRI. For this purpose, two-channel fNIRS device with 690 nm and 830 nm, sampled at 10 Hz, was placed on the forehead with 3 cm distance between light source and detector to provide resting state fNIRS signals from both sides of pre-frontal cortex. We applied fractional amplitude of physiological fluctuation (fAPF), modified from fractional amplitude of low frequency fluctuation (fALFF), to oxy-, deoxy-, and total-hemoglobin in very low frequency (0.008-0.1 Hz), respiratory (0.1-0.6 Hz), and cardiac (0.6-5 Hz) bands. A t-test at 0.05 significance level was used to evaluate if the fAPF score from AD patients and healthy controls is significantly different. We found that fAPF score of total hemoglobin from both side at cardiac band showed its potential to distinguish AD patients from healthy controls. This finding was in-line with the recent finding that heart failure may co-occur in AD patients with the prevalence of one third of cases.
Photoplethysmography (PPG) waveform is primary formed by absorbance and scattering of light caused by blood volume changes in the microvascular bed of tissue. The volume of blood is constantly changing due to cardiac activity and various low frequency physiological components, such as, respiration and sympathetic nervous system. Importantly, elastic property of blood vessels and blood pressure also greatly affects the volume of blood and thus PPG waveform inversely contains information on vessel elasticity and pressure that has been studied using e.g., pulse decomposition analysis (PDA) models. We emulated PPG waveform by using a simplified mock circulatory loop mimicking human circulatory system to study how changing elasticity of 3D printed vessels and blood pressure affects the PPG waveform, aiming to validate presented pulse decomposition analysis model for estimating vessel stiffness and blood pressure. The circulatory system built for the study is controlled via custom-made LabView software. Pumping frequency, pressure and flow of blood mimicking liquid can be controlled and accurately measured for a reference. The main analysis relied on the PDA that extracted five log-normal pulses for further analysis. In particular, we focused on the centre parameter of each log-normal pulse and observed it changes depending on the emulated parameters.
Obtaining parameters that characterize cerebral fluid interactions in the human brain is of high interest particularly as regards studies of the glymphatic system and in relation to neurodegeneration diseases. Near-infrared spectroscopy (NIRS) based techniques commonly measure cerebral hemodynamics using a combination of wavelengths approximately between 650 nm and 950 nm, where light is to a lesser amount attenuated by water, enabling light to reach the brain. By adding a wavelength that is dominantly absorbed by water, while still penetrating below skull, we may have a possibility to measure also cortical water concentration changes, particularly dynamics of the cerebrospinal fluid (CSF) volume, which have been connected to brain’s waste removal system. In this study, we show based on in vivo human experiments that small dynamical variations in the CSF layer, between the human skull and brain cortex determined by MRI, correlate with near infrared (NIR) light intensity changes particularly above 960 nm when measured at long (< 3 cm) source-detector distance. In addition, based on the previously reported anti-correlation between total haemoglobin (HbT) and water signal fluctuations measured with NIRS, we further investigated the differences in the anti-correlations when using short (< 2 cm) and long source-detector distances. In general, at a short source-detector distance the NIRS measurement volume does not reach a depth below human skull. In consequence, our results from 12 healthy subjects show greater anti-correlation between HbT and water when using a long source-detector distance, supporting the idea that NIRS can be used to monitor also human cortical water fluctuations non-invasively.
SignificanceCancer therapy treatments produce extensive changes in the physiological and morphological properties of tissues, which are also individual dependent. Currently, a key challenge involves developing more tailored cancer therapy, and consequently, individual biological response measurement during therapy, such as tumor hypoxia, is of high interest. This is the first time human cerebral haemodynamics and cerebral tissue oxygenation index (TOI) changes were measured during the irradiation in clinical radiotherapy and functional near-infrared spectroscopy (fNIRS) technique was demonstrated as a feasible technique for clinical use in radiotherapy, based on 34 online patient measurements.AimOur aim is to develop predictive biomarkers and noninvasive real-time methods to establish the effect of radiotherapy during treatment as well as to optimize radiotherapy dose planning for individual patients. In particular, fNIRS-based technique could offer an effective and clinically feasible online technique for continuous monitoring of brain tissue hypoxia and responses to chemo- and radiotherapy, which involves modulating tumor oxygenation to increase or decrease tumor hypoxia. We aim to show that fNIRS is feasible for repeatability measuring in patient radiotherapy, the temporal alterations of tissue oxygenation induced by radiation.ApproachFiber optics setup using multiwavelength fNIRS was built and combined with a medical linear accelerator to measure cerebral tissue oxygenation changes during the whole-brain radiotherapy treatment, where the radiation dose is given in whole brain area only preventing dosage to eyes. Correlation of temporal alterations in cerebral haemodynamics and TOI response to brain irradiation was quantified.ResultsOnline fNIRS patient measurement of cerebral haemodynamics during clinical brain radiotherapy is feasible in clinical environment, and results based on 34 patient measurements show strong temporal alterations in cerebral haemodynamics and decrease in TOI during brain irradiation and confirmed the repeatability. Our proof-of-concept study shows evidently that irradiation causes characteristic immediate changes in brain tissue oxygenation.ConclusionsIn particular, TOI seems to be a sensitive parameter to observe the tissue effects of radiotherapy. Monitoring the real-time interactions between the subjected radiation dose and corresponding haemodynamic effects may provide important tool for the researchers and clinicians in the field of radiotherapy. Eventually, presented fNIRS technique could be used for improving dose planning and safety control for individual patients.
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