July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Axial Position-Based Colorization Improves Intraoperative Visualization of Live Volumetric (4D) Microscope-Integrated Optical Coherence Tomography (MIOCT)
Author Affiliations & Notes
  • Isaac Bleicher
    Duke University School of Medicine, Durham, North Carolina, United States
  • Moseph Jackson-Atogi
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Christian Viehland
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Hesham Gabr
    Vitreoretinal Disease, Duke University Eye Center, Durham, North Carolina, United States
  • Joseph A. Izatt
    Biomedical Engineering, Duke University, Durham, North Carolina, United States
  • Cynthia A Toth
    Vitreoretinal Disease, Duke University Eye Center, Durham, North Carolina, United States
  • Footnotes
    Commercial Relationships   Isaac Bleicher, Providing Surface Contrast in Rendering of Three-Dimensional Images for Micro-Surgical Applications (P); Moseph Jackson-Atogi, Providing Surface Contrast in Rendering of Three-Dimensional Images for Micro-Surgical Applications (P); Christian Viehland, Providing Surface Contrast in Rendering of Three-Dimensional Images for Micro-Surgical Applications (P); Hesham Gabr, None; Joseph Izatt, Carl Zeiss Meditec (R), Leica Microsystems (R), Leica Microsystems (P), Providing Surface Contrast in Rendering of Three-Dimensional Images for Micro-Surgical Applications (P); Cynthia Toth, Alcon (R), Providing Surface Contrast in Rendering of Three-Dimensional Images for Micro-Surgical Applications (P)
  • Footnotes
    Support  NIH R01 EY023039
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 284. doi:
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      Isaac Bleicher, Moseph Jackson-Atogi, Christian Viehland, Hesham Gabr, Joseph A. Izatt, Cynthia A Toth; Axial Position-Based Colorization Improves Intraoperative Visualization of Live Volumetric (4D) Microscope-Integrated Optical Coherence Tomography (MIOCT). Invest. Ophthalmol. Vis. Sci. 2018;59(9):284.

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

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Abstract

Purpose : MIOCT enables intraoperative assessment and guidance of surgical maneuvers with live volumetric (three dimensional (3D) images over time, or “4D”) imaging in vitreoretinal surgery. Grayscale rendering of surgical fields are difficult to interpret, since 3D images are displayed in two dimensions. We developed colorization and stabilization for MIOCT volumes to improve their utility intraoperatively.

Methods : Approaches for colorizing MIOCT volumes were developed. Colorization stability was validated using porcine eyes translated by known intervals along the axial dimension. Colorization was applied to MIOCT data from previous human membrane peeling surgeries. Surgeons (n=7) were each shown 5 grayscale volumes, and asked to identify retinal membranes, the presence of an instrument, its contact with tissue, and any associated deformation of the retina. Colorized versions of the same volumes were shown and the questions repeated. Comparisons were made between responses and independent review of B-scans from the volume data.

Results : We developed a technique applying color as a gradient indicating position along the axial dimension, adding 3-4 milliseconds to rendering. Surgical motion was managed by applying the gradient relative to a calculated center of mass (COM) after thresholding to isolate the most reflective retinal layers. Validation showed precise COM tracking (normalized COM 0.00 pixels, standard deviation 1.42 pixels) and subjectively stable colorization. Colorization (Fig. 1) improved ability to differentiate membrane from retina (49% of images with grayscale, 91% after subsequent colorization, p<0.01) and to correctly identify instrument positioning and retinal deformation (69% of images with grayscale, 85% after subsequent colorization, p<0.01). Surgeons preferred colorization in 81% of cases.

Conclusions : We report a novel color mapping denoting axial position for 4D MIOCT volumes rendered within the acquisition time of the MIOCT volume. This improves surgeon ability to effectively identify membranes, track instrumentation and monitor tissue deformation during vitreoretinal surgery.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

Grayscale and colorized volumes from membrane peeling cases. Instrument traction on membrane (a), membrane pulled by forceps (b), retina deformation by flexible loop (c) and flexible loop above retina surface (d) are more clearly visualized in color.

Grayscale and colorized volumes from membrane peeling cases. Instrument traction on membrane (a), membrane pulled by forceps (b), retina deformation by flexible loop (c) and flexible loop above retina surface (d) are more clearly visualized in color.

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