June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Oxygen Signal Extraction from Bulk Retinal Tissue using Hyperspectral Image Mapping Spectrometry
Author Affiliations & Notes
  • Jason G Dwight
    Bioengineering, Rice University, Houston, Texas, United States
  • Christina Y Weng
    Ophthalmology, Baylor College of Medicine, Houston, Texas, United States
  • Michal E Pawlowski
    Bioengineering, Rice University, Houston, Texas, United States
  • Tomasz S. Tkaczyk
    Bioengineering, Rice University, Houston, Texas, United States
  • Footnotes
    Commercial Relationships   Jason Dwight, None; Christina Weng, None; Michal Pawlowski, None; Tomasz Tkaczyk, None
  • Footnotes
    Support  NIH Grant R01CA186132
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 3815. doi:
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      Jason G Dwight, Christina Y Weng, Michal E Pawlowski, Tomasz S. Tkaczyk; Oxygen Signal Extraction from Bulk Retinal Tissue using Hyperspectral Image Mapping Spectrometry. Invest. Ophthalmol. Vis. Sci. 2017;58(8):3815.

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      © ARVO (1962-2015); The Authors (2016-present)

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Purpose : Retinal oximetry is a proven technique for measuring oxygen saturation values in large, resolvable vessels using 2 or 3 wavelength values; however, applicability as a clinical diagnostic tool has remained elusive. Here, we use the Image Mapping Spectrometer (IMS) for the extraction of oxygen signals from heterogeneous bulk retinal tissue as a new diagnostic tool for monitoring oxygen distribution in the retina. This proof-of-concept study demonstrates the IMS’s ability to reveal distinct oxyhemoglobin spectra using its 40 wavelengths to aid the signal extraction from tissue with many spectral endmembers.

Methods : Using a mirror array, the IMS fractionalizes images relayed from a Topcon TRC-50EX fundus camera’s side port into separated spatial and spectral information with no scanning. Recorded images can be reformatted with minimal computational power into a hyperspectral datacube (350x350 spatial values, 40 spectral values). An average reflectance spectrum from the foveal avascular zone of the macula is used to normalize the average spectrum from different radial regions in 3 different patient eyes—2 normal and 1 with non-proliferative diabetic retinopathy (NPDR)—removing fundus spectral constituents not associated with blood vessels. The result, an average absorbance signal from 5 regions in a radial map, is then compared between the normal and diseased eyes.

Results : The spectral channels for normal patient #1 are displayed (Figure 1a) in color. The blue region in Figure 1b is the estimated position of the macula based on the fluorescein angiogram (FA). The average absorption spectrum for 5 radial regions 25 pixels apart are shown. Normal patient #2 is shown in Figure 2 alongside the absorption spectra for the patient with NPDR.

Conclusions : Distinct spectral peaks associated with oxyhemoglobin at 540 nm and 580 nm can be seen in Figure 1. As the radius increases, the magnitude of these peaks increases, indicating increased oxygen. This result is supported by the FA map showing increasing vessel density propagating outward from the macula. The normal eye in Figure 2 validates this trend. The diabetic eye displays weaker signals and less oxygen signal difference when compared to the macula, supporting the idea of lower perfusion in such eyes. The IMS can resolve oxyhemoglobin spectra beyond individual vessels and may prove to be a useful tool in building non-invasive oxygen and perfusion maps.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.




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