scholarly journals Near-Infrared Spectroscopy of the Bladder: New Parameters for Evaluating Voiding Dysfunction

2011 ◽  
Vol 2011 ◽  
pp. 1-8 ◽  
Author(s):  
Andrew Macnab ◽  
Babak Shadgan ◽  
Kourosh Afshar ◽  
Lynn Stothers
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Voiding Dysfunction ◽  
Outlet Obstruction ◽  
Positive Trend ◽  
Healthy Children ◽  
Silicon Photodiode ◽  
Light Emitting ◽  
Chromophore Concentration

We describe innovative methodology for monitoring alterations in bladder oxygenation and haemodynamics in humans using near-infrared spectroscopy (NIRS). Concentrations of the chromophores oxygenated (O2Hb) and deoxygenated (HHb) haemoglobin and their sum (total haemoglobin) differ during bladder contraction in health and disease. A wireless device that incorporates three paired light emitting diodes (wavelengths 760 and 850 nanometers) and silicon photodiode detector collects data transcutaneously (10 Hz) with the emitter/detector over the bladder during spontaneous bladder emptying. Data analysis indicates comparable patterns of change in chromophore concentration in healthy children and adults (positive trend during voiding, predominantly due to elevated O2Hb), but different changes in symptomatic subjects with characteristic chromophore patterns identified for voiding dysfunction due to specific pathophysiologies: bladder outlet obstruction (males), overactive bladder (females), and nonneurogenic dysfunction (children). Comparison with NIRS muscle data suggests altered bladder haemodynamics and/or oxygenation may underlie voiding dysfunction offering new insight into the causal physiology.

scholarly journals Imaging System Based on Silicon Photomultipliers and Light Emitting Diodes for Functional Near-Infrared Spectroscopy

2020 ◽  
Vol 10 (3) ◽  
pp. 1068 ◽  
Author(s):  
Giovanni Maira ◽  
Antonio M. Chiarelli ◽  
Stefano Brafa ◽  
Sebania Libertino ◽  
Giorgio Fallica ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Human Brain ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Light Emitting Diodes ◽  
Optical Tomography ◽  
System Optimization ◽  
Infrared Light ◽  
Functional Near Infrared Spectroscopy ◽  
Light Emitting

We built a fiber-less prototype of an optical system with 156 channels each one consisting of an optode made of a silicon photomultiplier (SiPM) and a pair of light emitting diodes (LEDs) operating at 700 nm and 830 nm. The system uses functional near-infrared spectroscopy (fNIRS) and diffuse optical tomography (DOT) imaging of the cortical activity of the human brain at frequencies above 1 Hz. In this paper, we discuss testing and system optimization performed through measurements on a multi-layered optical phantom with mechanically movable parts that simulate near-infrared light scattering inhomogeneities. The baseline optical characteristics of the phantom are carefully characterized and compared to those of human tissues. Here we discuss several technical aspects of the system development, such as LED light output drift and its possible compensation, SiPM linearity, corrections of channel signal differences, and signal-to-noise ratio (SNR). We implement an imaging algorithm that investigates large phantom regions. Thanks to the use of SiPMs, very large source-to-detector distances are acquired with a high SNR and 2 Hz time resolution. The overall results demonstrate the high potentialities of a system based on SiPMs for fNIRS/DOT human brain imaging applications.

scholarly journals Algorithm construction methodology for diagnostic classification of near-infrared spectroscopy data

2011 ◽  
Vol 25 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Ramón Guevara ◽  
Lynn Stothers ◽  
Andrew Macnab
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Pelvic Floor Muscle ◽  
Classification And Regression Tree ◽  
Data Sets ◽  
Linear Discriminant ◽  
Cart Analysis ◽  
Chromophore Concentration ◽  
Nirs Data

Background: Near-infrared spectroscopy (NIRS) has recognized potential but limited application for non-invasive diagnostic evaluation. Data analysis methodology that reproducibly distinguishes between the presence or absence of physiologic abnormality could broaden clinical application of this optical technique.Methods: Sample data sets from simultaneous NIRS bladder monitoring and invasive urodynamic pressure-flow studies (UDS) are used to illustrate how a diagnostic algorithm is constructed using classification and regression tree (CART) analysis. Misclassification errors of CART and linear discriminant analysis (LDA) are computed and examples of other urological NIRS data likely amenable to CART analysis presented.Results: CART generated a clinically relevant classification algorithm (error 4%) using 46 data sets of changes in chromophore concentration composed of the whole time series without specifying features. LDA did not (error 16%). Using CART NIRS data provided comparable discriminant ability to the UDS diagnostic nomogram for the presence or absence of obstructive pathology (88% specificity, 84% precision). Pilot data examples from children with and without voiding dysfunction and women with mild or severe pelvic floor muscle dysfunction also show potentially diagnostic differences in chromophore concentration.Conclusions: CART analysis can likely be applied in other NIRS monitoring applications intended to classify patients into those with and without pathology.

Tissue Monitoring with Three-Wavelength Light Emitting Diode–Based Near-Infrared Spectroscopy

2016 ◽  
Vol 32 (09) ◽  
pp. 712-718 ◽  
Author(s):  
Jonathon Olenczak ◽  
Daniel Murariu ◽  
Keita Ikeda ◽  
Robert Thiele ◽  
Chris Campbell
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Light Emitting Diode ◽  
Light Emitting ◽  
Wavelength Light

scholarly journals Ambulant monitoring of bladder oxygenation and hemodynamics using wireless near-infrared spectroscopy

2013 ◽  
Vol 7 (1-2) ◽  
pp. 98 ◽  
Author(s):  
Andrew John Macnab ◽  
Babak Shadgan ◽  
Lynn Stothers ◽  
Kourosh Afshar
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Symphysis Pubis ◽  
Bladder Volume ◽  
Lower Urinary Tract Dysfunction ◽  
Detrusor Muscle ◽  
Silicon Photodiode ◽  
Nirs Data ◽  
Asymptomatic Subjects

Introduction: Near-infrared spectroscopy (NIRS) non-invasively detects changes in the concentration of the chromophores oxygenated (ΔO2Hb) and deoxygenated hemoglobin (ΔHHb) as the bladder detrusor muscle contracts during voiding. Such data provide novel information on bladder oxygenation and hemodynamics. We evaluated the feasibility of monitoring ambulant subjects using a wireless NIRS device.Methods: The wireless device uses paired light-emitting diodes (wavelengths 760 and 850 nm) and a silicon photodiode detector. We monitored 14 asymptomatic subjects (10 adults, 4 children) and 6 symptomatic children with non-neurogenic lower urinary tract dysfunction (NLUTD) during spontaneous voiding after natural filling. The device was taped to the abdominal skin 2 cm above the symphysis pubis across the midline. The wireless NIRS data (patterns of change in chromophore concentration) were compared between subjects and to the data obtained using a laser-powered instrument.Results: Graphs of ΔO2Hb, ΔHHb and total hemoglobin (ΔtHb) were obtained from all 20 patients. Data during uroflow showed reproducible patterns of bladder chromophore change between asymptomatic subjects (rise in ΔtHb/ΔO2Hb), consistent with laser instrument data. In contrast, all 6 symptomatic children had a negative trend in ΔtHb, with falls in ΔO2Hb. One adult experienced “shy” bladder and changes in hemodynamics/oxygenation occurred while bladder volume was unchanged.Conclusions: Wireless NIRS bladder monitoring is feasible in ambulant adults and children; wireless and laser-derived data in asymptomaticsubjects are comparable. Pilot data suggest that subjects with symptomatic NLUTD have impaired bladder oxygenation/hemodynamics. The fact that chromophore changes occur when bladder volume remains constant supports the concept that NIRS data are a physiologic measure.

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