Broadband NIRS Cerebral Cytochrome-C-Oxidase Response to Anoxia Before and After Hypoxic-Ischaemic Injury in Piglets

Bale, Gemma; Rajaram, Ajay; Kewin, Matthew; Morrison, Laura; Bainbridge, Alan; Diop, Mamadou; Lawrence, Keith St.; Tachtsidis, Ilias

doi:10.1007/978-3-319-91287-5_24

Cited by 8 publications

(3 citation statements)

References 13 publications

(13 reference statements)

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“…With appropriate selection of light wavelengths, fNIRS characterization of neurovascular coupling can be expanded to also include metabolic function, for example using cytochrome c oxidase (CCO) (Bale et al, 2018;Holper and Mann, 2018;Lange et al, 2019). Coupled with the ability to simultaneously measure fNIRS together with other neuroimaging analysis techniques such as EEG and neural network learning (Yang et al, 2019) fNIRS has the potential for widespread clinical applications in neuroscience.…”

Section: Introductionmentioning

confidence: 99%

Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions

et al. 2020

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Similar to functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS) detects the changes of hemoglobin species inside the brain, but via differences in optical absorption. Within the near-infrared spectrum, light can penetrate biological tissues and be absorbed by chromophores, such as oxyhemoglobin and deoxyhemoglobin. What makes fNIRS more advantageous is its portability and potential for long-term monitoring. This paper reviews the basic mechanisms of fNIRS and its current clinical applications, the limitations toward more widespread clinical usage of fNIRS, and current efforts to improve the temporal and spatial resolution of fNIRS toward robust clinical usage within subjects. Oligochannel fNIRS is adequate for estimating global cerebral function and it has become an important tool in the critical care setting for evaluating cerebral oxygenation and autoregulation in patients with stroke and traumatic brain injury. When it comes to a more sophisticated utilization, spatial and temporal resolution becomes critical. Multichannel NIRS has improved the spatial resolution of fNIRS for brain mapping in certain task modalities, such as language mapping. However, averaging and group analysis are currently required, limiting its clinical use for monitoring and real-time event detection in individual subjects. Advances in signal processing have moved fNIRS toward individual clinical use for detecting certain types of seizures, assessing autonomic function and cortical spreading depression. However, its lack of accuracy and precision has been the major obstacle toward more sophisticated clinical use of fNIRS. The use of high-density whole head optode arrays, precise sensor locations relative to the head, anatomical co-registration, short-distance channels, and multi-dimensional signal processing can be combined to improve the sensitivity of fNIRS and increase its use as a widespread clinical tool for the robust assessment of brain function.

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Section: Introductionmentioning

confidence: 99%

Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions

et al. 2020

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“…Given the small concentration of CCO in the brain and confounding by competing for absorption by hemoglobin, CCO measurement has only recently become practical. Broadband NIRS has been demonstrated in piglet models of HIE [ 37 ] as well as pilot studies of human neonates with HIE [ 35 , 38 ].…”

Section: Equipmentmentioning

confidence: 99%

Neonatal NIRS monitoring: recommendations for data capture and review of analytics

2021

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Brain injury is one of the most consequential problems facing neonates, with many preterm and term infants at risk for cerebral hypoxia and ischemia. To develop effective neuroprotective strategies, the mechanistic basis for brain injury must be understood. The fragile state of neonates presents unique research challenges; invasive measures of cerebral blood flow and oxygenation assessment exceed tolerable risk profiles. Near-infrared spectroscopy (NIRS) can safely and non-invasively estimate cerebral oxygenation, a correlate of cerebral perfusion, offering insight into brain injury-related mechanisms. Unfortunately, lack of standardization in device application, recording methods, and error/artifact correction have left the field fractured. In this article, we provide a framework for neonatal NIRS research. Our goal is to provide a rational basis for NIRS data capture and processing that may result in better comparability between studies. It is also intended to serve as a primer for new NIRS researchers and assist with investigation initiation.

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“…So far, these biomarkers were focused on either cerebral oximetry using multidistance NIRS or broadband NIRS (bNIRS) or diffuse correlation spectroscopy (DCS) 6 . bNIRS brain tissue measurements of the oxidation state of Cytochrome -coxidase (oxCCO) have shown that it can reveal information on brain injury severity 7,8,9 . In this study, we present an assessment of the severity of HIE using optical data captured by FLORENCE, an integrated hybrid broadband near infrared spectrometer (bNIRS) and diffusion correlation spectrometer (DCS) instrument and a machine learning pipeline based on k-means clustering for classification.…”

Section: Introductionmentioning

confidence: 99%

Classification of brain injury severity using a hybrid broadband NIRS and DCS instrument with a machine learning approach

Bili,

Lange,

Harvey Jones

et al. 2023

Diffuse Optical Spectroscopy and Imaging IX

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Optical biomarkers of neonatal hypoxic ischemic (HI) brain injury can offer the advantage of continuous, cot-side assessment of the degree of injury; research thus far has focused on examining different optical measured brain physiological signals and feature combinations to achieve this. To maximize the breadth of physiological characteristics being taken into consideration, a multimodal optical platform has been developed, allowing unique physiological insights into brain injury. In this paper we present an assessment of severity of injury using a state-of-the-art hybrid broadband Near Infrared Spectrometer (bNIRS) and Diffusion Correlation Spectrometer (DCS) instrument called FLORENCE with a machine learning pipeline. We demonstrate in the preclinical neonatal model (the newborn piglet) that our approach can identify different HI insult severity (controls, mild, severe). We show that a machine learning pipeline based on k-means clustering can be used to differentiate between the controls and the HI piglets with an accuracy of 78%, the mild severity insult piglets from the severe insult piglets with an accuracy of 90% and can also differentiate the 3 piglet groups with an accuracy of 80%. So, this analytics pipeline demonstrates how optical data from multiple instruments can be processed towards markers of brain health.

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Broadband NIRS Cerebral Cytochrome-C-Oxidase Response to Anoxia Before and After Hypoxic-Ischaemic Injury in Piglets

Cited by 8 publications

References 13 publications

Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions

Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions

Neonatal NIRS monitoring: recommendations for data capture and review of analytics

Classification of brain injury severity using a hybrid broadband NIRS and DCS instrument with a machine learning approach

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