Sickle Cell Disease (SCD) is an inherited hemoglobin disorder associated with multiple organ damage caused by continuous inflammation and systemic vasculopathy. There is a need for comprehensive technologies that can characterize vascular hemodynamics at the bedside. Near-infrared spectroscopy (NIRS) techniques show promise as a non-invasive diagnostic tool for monitoring tissue hemodynamics. Subjects with SCD were recruited to undergo longitudinal optical measurements while participating in a long-term efficacy study of Mitapivat, a pyruvate kinase activator under clinical development. We demonstrate the sensitivity of multiple modalities to hemodynamic changes in patients that achieved a < 1g/dL increase in hemoglobin level.
The current standard of care for evaluating obstructive sleep apnea (OSA) is polysomnography (PSG), which requires a resource-intensive overnight study and relies on pulse oximetry to determine severity. PSG does not provide direct information about brain oxygenation, but studies have demonstrated that near-infrared spectroscopy (NIRS) technology can be useful in monitoring cerebral hemodynamics. These studies largely rely on commercial bedside tissue oxygenation monitors, although more portable instruments could permit use in home settings. In this work, we evaluate a prototype smartphone compatible NIRS device for assessing OSA, examine hemodynamic responses alongside PSG, and derive two novel metrics for disease severity.
Frequency-domain near infrared spectroscopy (fd-NIRS) is used to noninvasively characterize in vivo tissue structure and molecular composition by exploiting the deep tissue penetration of red and near-infrared light. However, the size, complexity, expense, and lack of scalability of current fd-NIRS hardware has slowed its translation to clinical applications. Here we present a broad-bandwidth 1.2 x 1.2 mm fd-NIRS application-specific integrated circuit that represents a critical step toward ultrasmall, easily scalable, and wearable fd-NIRS. We present the fd-NIRS integrated circuit design as well as results showing its optical property measurements are comparable to those measured with a standard reference system.
Significance: Diffuse optical spectroscopic imaging (DOSI) is a versatile technology sensitive to changes in tissue composition and hemodynamics and has been used for a wide variety of clinical applications. Specific applications have prompted the development of versions of the DOSI technology to fit specific clinical needs. This work describes the development and characterization of a multi-modal DOSI (MM-DOSI) system that can acquire metabolic, compositional, and pulsatile information at multiple penetration depths in a single hardware platform. Additionally, a 3D tracking system is integrated with MM-DOSI, which enables registration of the acquired data to the physical imaging area.
Aim: We demonstrate imaging, layered compositional analysis, and metabolism tracking capabilities using a single MM-DOSI system on optical phantoms as well as in vivo human tissue.
Approach: We characterize system performance with a silicone phantom containing an embedded object. To demonstrate multi-layer sensitivity, we imaged human calf tissue with a 4.8-mm skin-adipose thickness. Human thenar tissue was also measured using a combined broadband DOSI and continuous-wave near-infrared spectroscopy method (∼15 Hz acquisition rate).
Results: High-resolution optical property maps of absorption (μa) and reduced scattering (μs ′ ) were recovered on the phantom by capturing over 1000 measurement points in under 5 minutes. On human calf tissue, we show two probing depth layers have significantly different (p < 0.001) total-hemo/myoglobin and μs ′ composition. On thenar tissue, we calculate tissue arterial oxygen saturation, venous oxygen saturation, and tissue metabolic rate of oxygen consumption during baseline and after release of an arterial occlusion.
Conclusions: The MM-DOSI can switch between collection of broadband spectra, high-resolution images, or multi-depth hemodynamics without any hardware reconfiguration. We conclude that MM-DOSI enables acquisition of high resolution, multi-modal data consolidated in a single platform, which can provide a more comprehensive understanding of tissue hemodynamics and composition for a wide range of clinical applications.
Purpose: The recent coronavirus disease 2019 (COVID-19) pandemic, which spread across the globe in a very short period of time, revealed that the transmission control of disease is a crucial step to prevent an outbreak and effective screening for viral infectious diseases is necessary. Since the severe acute respiratory syndrome (SARS) outbreak in 2003, infrared thermography (IRT) has been considered a gold standard method for screening febrile individuals at the time of pandemics. The objective of this review is to evaluate the efficacy of IRT for screening infectious diseases with specific applications to COVID-19.
Approach: A literature review was performed in Google Scholar, PubMed, and ScienceDirect to search for studies evaluating IRT screening from 2002 to present using relevant keywords. Additional literature searches were done to evaluate IRT in comparison to traditional core body temperature measurements and assess the benefits of measuring additional vital signs for infectious disease screening.
Results: Studies have reported on the unreliability of IRT due to poor sensitivity and specificity in detecting true core body temperature and its inability to identify asymptomatic carriers. Airport mass screening using IRT was conducted during occurrences of SARS, Dengue, Swine Flu, and Ebola with reported sensitivities as low as zero. Other studies reported that screening other vital signs such as heart and respiratory rates can lead to more robust methods for early infection detection.
Conclusions: Studies evaluating IRT showed varied results in its efficacy for screening infectious diseases. This suggests the need to assess additional physiological parameters to increase the sensitivity and specificity of non-invasive biosensors.
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