Quantification of tissue chromophore concentration via water-peak measurements in near-infrared spectroscopy

1993 ◽  
Author(s):  
Steven J. Matcher ◽  
Mark Cope ◽  
David T. Delpy
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Chromophore Concentration

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 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.

Near-infrared spectroscopy (NIRS) – a promising brain imaging method in Psychiatry?

2008 ◽  
Vol 39 (01) ◽  
Author(s):  
AJ Fallgatter ◽  
AC Ehlis ◽  
MM Richter ◽  
M Schecklmann ◽  
MM Plichta
Keyword(s):  
Infrared Spectroscopy ◽  
Brain Imaging ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Imaging Method
Sign in / Sign up

Export Citation Format

Share Document