Depth-Based, Motion-Stabilized Colorization of Microscope-Integrated Optical Coherence Tomography Volumes for Microscope-Independent Microsurgery

Abstract

Purpose: We develop and assess the impact of depth-based, motion-stabilized colorization (color) of microscope-integrated optical coherence tomography (MIOCT) volumes on microsurgical performance and ability to interpret surgical volumes.

Methods: Color was applied in real-time as gradients indicating axial position and stabilized based on calculated center of mass. In a test comparing colorization versus grayscale visualizations of prerecorded intraoperative volumes from human surgery, ophthalmologists (N = 7) were asked to identify retinal membranes, the presence of an instrument, its contact with tissue, and associated deformation of the retina. In a separate controlled trial, trainees (N = 15) performed microsurgical skills without conventional optical visualization and compared colorized versus grayscale MIOCT visualization on a stereoptic screen. Skills included thickness identification, instrument placement, and object manipulation, and were assessed based on time, performance metrics, and confidence.

Results: In intraoperative volume testing, colorization improved ability to differentiate membrane from retina (P < 0.01), correctly identify instrument contact with membrane (P = 0.03), and retinal deformation (P = 0.01). In model microsurgical skills testing, trainees working with colorized volumes were faster (P < 0.01) and more correct (P < 0.01) in assessments of thickness for recessed and elevated objects, were less likely to inadvertently contact a surface when approaching with an instrument (P < 0.01), and uniformly more confident (P < 0.01 for each) in conducting each skill.

Conclusions: Depth-based colorization enables effective identification of retinal membranes and tissue deformation. In microsurgical skill testing, it improves user efficiency, and confidence in microscope-independent, OCT-guided model surgical maneuvers.

Translational relevance: Novel depth-based colorization and stabilization technology improves the use of intraoperative MIOCT.

Keywords: intraoperative imaging; microsurgery; ophthalmic surgery; optical coherence tomography; visualization.

Figures

Figure 1

MIOCT volumes and B-scans demonstrate the colorization and stabilization processes. A non-colorized MIOCT volume (A) is filtered with a threshold at the 99th percentile of reflectivity values (B), center of mass is calculated (C, red line) and color is applied (D). Top and bottom sequences demonstrate stability with axial motion.

Figure 2

Grayscale and colorized MIOCT volumes from membrane peeling cases shown during intraoperative volume testing. 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. Color is applied with red superiorly, yellow medially and green (blue in [C]) inferiorly. Color boundaries were individually chosen to highlight surface features.

Figure 3

Grayscale (top) and colorized (bottom) MIOCT volume examples from each microsurgical skill. Example surfaces with recessed (A) and elevated (B) objects respectively, the surface approach skill with the flexible loop approaching a flat surface (C), and the object grasp skill with the forceps attempting to grasp a membrane-like object (D). Color is applied with red superiorly, yellow medially and blue inferiorly. Color boundaries were applied just above (just below for [A]) the surface. While this figure uses 2D representations of the 3D volume, subjects viewed stereoptic images while completing each task.

Figure 4

Box and whisker plots summarizing measured outcomes of the thickness assessment (A), surface approach (B) and object grasp (C) skills. Data are presented as paired differences between colorized and grayscale trials. Data for each outcome was normalized from −1 to 1 based on the largest absolute value for that outcome. As such, time and confidence measures are plotted on consistent axes between skills while other measures are on unique axes. Axes are oriented such that values to the right of center support colorization, while values to the left of center support grayscale for all outcomes. The grey line delineates the point of no difference between colorized and grayscale visualization. Dashed lines delineate measures for each of the three tested skills. P values for each paired comparison are listed on the left and marked (*) when meeting the specified significance value of 0.05.