Surgical microscope integrated MHz SS-OCT with live volumetric visualization

Visualization of Cataract Surgery Steps With 4D Microscope-Integrated Swept-Source Optical Coherence Tomography in Ex Vivo Porcine Eyes

Purpose

To investigate the visualization capabilities of high-speed swept-source optical coherence tomography (SS-OCT) in cataract surgery.

Methods

Cataract surgery was simulated in wet labs with ex vivo porcine eyes. Each phase of the surgery was visualized with a novel surgical microscope-integrated SS-OCT with a variable imaging speed of over 1 million A-scans per second. It was designed to provide four-dimensional (4D) live-volumetric videos, live B-scans, and volume capture scans.

Results

Four-dimensional videos, B-scans, and volume capture scans of corneal incision, ophthalmic viscosurgical device injection, capsulorrhexis, phacoemulsification, intraocular lens (IOL) injection, and position of unfolded IOL in the capsular bag were recorded. The flexibility of the SS-OCT system allowed us to tailor the scanning parameters to meet the specific demands of dynamic surgical steps and static pauses. The entire length of the eye was recorded in a single scan, and unfolding of the IOL was visualized dynamically.

Conclusions

The presented novel visualization method for fast ophthalmic surgical microscope-integrated intraoperative OCT imaging in cataract surgery allowed the visualization of all major steps of the procedure by achieving large imaging depths covering the entire eye and high acquisition speeds enabling live volumetric 4D-OCT imaging. This promising technology may become an integral part of routine and advanced robotic-assisted cataract surgery in the future.

Translational Relevance

We demonstrate the visualization capabilities of a cutting edge swept-source OCT system integrated into an ophthalmic surgical microscope during cataract surgery.

Virtual Hall sensor triggered multi-MHz endoscopic OCT imaging for stable real-time visualization

Circumferential scanning in endoscopic imaging is crucial across various disciplines, and optical coherence tomography (OCT) is often the preferred choice due to its high-speed, high-resolution, and micron-scale imaging capabilities. Moreover, real-time and high-speed 3D endoscopy is a pivotal technology for medical screening and precise surgical guidance, among other applications. However, challenges such as image jitter and non-uniform rotational distortion (NURD) are persistent obstacles that hinder real-time visualization during high-speed OCT procedures. To address this issue, we developed an innovative, low-cost endoscope that employs a brushless DC motor for scanning, and a sensorless technique for triggering and synchronizing OCT imaging with the scanning motor. This sensorless approach uses the motor's electrical feedback (back electromotive force, BEMF) as a virtual Hall sensor to initiate OCT image acquisition and synchronize it with a Fourier Domain Mode-Locked (FDML)-based Megahertz OCT system. Notably, the implementation of BEMF-triggered OCT has led to a substantial reduction in image jitter and NURD (<4 mrad), thereby opening up a new window for real-time visualization capabilities. This approach suggests potential benefits across various applications, aiming to provide a more accurate, deployable, and cost-effective solution. Subsequent studies can explore the adaptability of this system to specific clinical scenarios and its performance under practical endoscopic conditions.

Five degrees-of-freedom mechanical arm with remote center of motion (RCM) device for volumetric optical coherence tomography (OCT) retinal imaging

Handheld optical coherence tomography (HH-OCT) is gaining popularity for diagnosing retinal diseases in neonates (e.g. retinopathy of prematurity). Diagnosis accuracy is degraded by hand tremor and patient motion when using commercially available handheld retinal OCT probes. This work presents a low-cost arm designed to address ergonomic challenges of holding a commercial OCT probe and alleviating hand tremor. Experiments with a phantom eye show enhanced geometric uniformity and volumetric accuracy when obtaining OCT scans with our device compared to handheld imaging approaches. An in-vivo porcine volumetric image was also obtained with the mechanical arm demonstrating clinical deployability.

Visualization of surgical maneuvers using intraoperative real-time volumetric optical coherence tomography

Ophthalmic microsurgery is traditionally performed using stereomicroscopes and requires visualization and manipulation of sub-millimeter tissue structures with limited contrast. Optical coherence tomography (OCT) is a non-invasive imaging modality that can provide high-resolution, depth-resolved cross sections, and has become a valuable tool in clinical practice in ophthalmology. While there has been substantial progress in both research and commercialization efforts to bring OCT imaging into live surgery, its use is still somewhat limited due to factors such as low imaging speed, limited scan configurations, and suboptimal data visualization. In this paper we describe, to the best of our knowledge, the translation of the fastest swept-source intraoperative OCT system with real-time volumetric imaging with stereoscopic data visualization provided via a heads-up display into the operating room. Results from a sampling of human anterior segment and retinal surgeries chosen from 93 human surgeries using the system are shown and the benefits that this mode of intrasurgical OCT imaging provides are discussed.

Geometrically accurate real-time volumetric visualization of the middle ear using optical coherence tomography

We introduce a novel system for geometrically accurate, continuous, live, volumetric middle ear optical coherence tomography imaging over a 10.9mm×30∘×30∘ field of view (FOV) from a handheld imaging probe. The system employs a discretized spiral scanning (DC-SC) pattern to rapidly collect volumetric data and applies real-time scan conversion and lateral angular distortion correction to reduce geometric inaccuracies to below the system's lateral resolution over 92% of the FOV. We validate the geometric accuracy of the resulting images through comparison with co-registered micro-computed tomography (micro-CT) volumes of a phantom target and a cadaveric middle ear. The system's real-time volumetric imaging capabilities are assessed by imaging the ear of a healthy subject while performing dynamic pressurization of the middle ear in a Valsalva maneuver.

Methods for real-time feature-guided image fusion of intrasurgical volumetric optical coherence tomography with digital microscopy

4D-microscope-integrated optical coherence tomography (4D-MIOCT) is an emergent multimodal imaging technology in which live volumetric OCT (4D-OCT) is implemented in tandem with standard stereo color microscopy. 4D-OCT provides ophthalmic surgeons with many useful visual cues not available in standard microscopy; however it is challenging for the surgeon to effectively integrate cues from simultaneous-but-separate imaging in real-time. In this work, we demonstrate progress towards solving this challenge via the fusion of data from each modality guided by segmented 3D features. In this way, a more readily interpretable visualization that combines and registers important cues from both modalities is presented to the surgeon.

Live 4D-OCT denoising with self-supervised deep learning

By providing three-dimensional visualization of tissues and instruments at high resolution, live volumetric optical coherence tomography (4D-OCT) has the potential to revolutionize ophthalmic surgery. However, the necessary imaging speed is accompanied by increased noise levels. A high data rate and the requirement for minimal latency impose major limitations for real-time noise reduction. In this work, we propose a low complexity neural network for denoising, directly incorporated into the image reconstruction pipeline of a microscope-integrated 4D-OCT prototype with an A-scan rate of 1.2 MHz. For this purpose, we trained a blind-spot network on unpaired OCT images using a self-supervised learning approach. With an optimized U-Net, only a few milliseconds of additional latency were introduced. Simultaneously, these architectural adaptations improved the numerical denoising performance compared to the basic setup, outperforming non-local filtering algorithms. Layers and edges of anatomical structures in B-scans were better preserved than with Gaussian filtering despite comparable processing time. By comparing scenes with and without denoising employed, we show that neural networks can be used to improve visual appearance of volumetric renderings in real time. Enhancing the rendering quality is an important step for the clinical acceptance and translation of 4D-OCT as an intra-surgical guidance tool.