Compensation of ocular refractive error is essential for obtaining high-quality OCT/OCTA retinal images for retinal diagnostics across patients with different refractive power. During point-of-care ophthalmic imaging with handheld OCT systems, the clinical ergonomics of operator-driven focal adjustments to accommodate refractive error can disrupt clinical workflow. Here, we present a closed-loop automated hands-free focus tracking method to overcome limitations of conventional manual focus adjustment, and demonstrate its performance when integrated with our handheld spectrally encoded coherence tomography and reflectometry (HH-SECTR) probe. We predict automated focus tracking will improve clinical ergonomics for more efficient point-of-care ophthalmic imaging.
Intraoperative OCT (iOCT) has been shown to help guide ophthalmic surgical management by allowing for verification of the completion of surgical objectives. However, iOCT systems are limited by static OCT fields-of-view (FOVs) that require manual alignment to surgical regions-of-interest, preventing real-time volumetric imaging of surgical maneuvers. Here, we demonstrate an automated instrument-tracking method that leverages multimodal ophthalmic imaging and deep-learning-based object detection for localization of multiple surgical instruments within the OCT FOV. We present video-rate 4D imaging of mock surgical maneuvers in ex vivo porcine eyes at 16 volumes/second, which can be used to provide real-time feedback on instrument-tissue dynamics.
Traditional benchtop OCT systems require upright patient fixation and often impede ophthalmic imaging in bedridden, uncooperative, and pediatric patients. Point-of-care OCT systems have demonstrated ophthalmic imaging in supine patients. However, manually aligning and correcting for refractive power variations between patient eyes to ensure optimal image quality can be clinically cumbersome with point-of-care imaging systems. Here, we demonstrate our improved handheld spectrally encoded coherence tomography and reflectometry (HH-SECTR) imaging probe with mechanical focus-adjust and improved optical throughput in a clinically robust form-factor. SECTR uses spatiotemporally co-registered multimodal spectrally encoded reflectometry (SER) and OCT acquisition for volumetric motion-correction and retinal mosaicking. Our previous HH-SECTR prototype had three major limitations: 1) poor alignment stability caused by reduced mechanical stiffness in a completely rapid-prototyped resin body; 2) lossy SER optical throughput; and 3) manual focus adjust that was cumbersome during point-of-care imaging. Here, we demonstrate optical and optomechanical design improvements to address these limitations, including a modular aluminum probe chassis and increased optical power throughput for sustained system alignment and imaging performance. We have also incorporated a mechanical focusing subsystem to correct refractive errors, which can be integrated with our acquisition software for hands-free focus tracking. We demonstrate in vivo human retinal imaging, and mechanical focusing capabilities using a stationary model eye and stepping through ± 10 diopters focal shift. We predict the addition of focusing capabilities and design improvements in form-factor and optical throughput to our HH-SECTR probe will benefit clinical translation and point-of-care multimodal OCT imaging.
Ophthalmic surgery is conventionally performed under white-light microscopy which has limited benefit for identifying tissue layers and providing depth-resolved feedback. Intraoperative optical coherence tomography (iOCT) has enabled depth-resolved intraoperative imaging of retinal microstructures. Recent advancements have enabled faster imaging speeds and video-rate, volumetric iOCT imaging of surgical dynamics, and en face retinal imaging that enables robust visualization of surgical instruments for tool-tracking. Here, we demonstrate our intraoperative spectrally encoded coherence tomography and reflectometry imaging (iSECTR) system with enhanced optical throughput and mechanical focus-adjust in a more clinically robust form-factor. iSECTR uses spatiotemporally co-registered multimodal spectrally encoded reflectometry (SER) and OCT for automated en face instrument-tracking and volumetric visualization of surgical dynamics. Here, we demonstrate several optical and optomechanical design improvements, which include the design of a modular aluminum skeleton to house SECTR imaging optics and optomechanics throughput to maintain system alignment and imaging performance. Mechanical focusing capabilities were integrated to accommodate for any adjustments to surgical oculars made by the ophthalmic surgeon before surgery for simultaneous optimal imaging in both iSECTR and the ocular view of the surgical field. We demonstrate ex vivo cornea and retinal imaging, and mechanical focusing capabilities using a stationary model eye and stepping through ± 10 diopters focal shift. We predict the addition of focusing capabilities and improvements in form-factor and optical throughput to our iSECTR system will benefit surgical translation and workflow for ophthalmic surgeries.
Intraoperative OCT (iOCT) provides real-time imaging data that can be used to aid clinical decision-making and verify completion of surgical goals. However, video-rate 4D iOCT imaging of surgical dynamics is limited by the need to manually align the OCT field-of-view (FOV) to the region-of-interest, thus significantly impacting surgical workflow. Here, we demonstrate automated instrument-tracking at over 120 Hz. We present video-rate 4D imaging and tracking of 25G internal limiting membrane forceps at 16 volumes/second. The proposed method and improvements will facilitate the broad adoption of iOCT technology by providing real-time volumetric feedback on surgical dynamics and instrument-tissue interactions.
Ophthalmic OCT image-quality is highly variable and directly impacts clinical diagnosis of disease. Computational methods such as frame-averaging, filtering, deep-learning approaches are generally constrained by either extended imaging times when acquiring repeated-frames, over-smoothing and loss of features, or the need for extensive training sets. Self-fusion is a robust OCT image-enhancement method that overcomes these aforementioned limitations by averaging serial OCT frames weighted by their respective similarity. Here, we demonstrated video-rate self-fusion using a convolutional neural network. Our experimental results show a near doubling of OCT contrast-to-noise ratio at a frame-rate of ~22 fps when integrated with custom OCT acquisition software.
Intraoperative optical coherence tomography (iOCT) has enabled depth-resolved intraoperative imaging of retinal microstructures. Despite recent advancements, iOCT of surgical maneuvers remains challenging because the imaging field-of-view requires manual adjustment and tracking. To overcome this limitation, we previously demonstrated spectrally encoded coherence tomography and reflectometry (SECTR), which provides OCT imaging and a complementary en face view for visualization of surgical instruments and tool-tracking. Here, we demonstrate ophthalmic imaging with an intraoperative SECTR (iSECTR) system integrated with a surgical microscope. We believe that iSECTR will allow for real-time feedback on the location and depth of surgical instruments to better guide ophthalmic surgery.
Optical coherence tomography (OCT) sampling density and acquisition time is directly related to scanning mirror performance. A galvanometer impulse response that is broad or rings reduces the linearly-sampled regions of OCT B-scans and can increase total acquisition time, cause nonlinear distortions, and reduce resolution and contrast in OCT angiography (OCTA). Here, we utilize hardware and software optimizations to improve galvanometer frequency response in order to minimize scanner settling time and are thus able to improve imaging speed and maximize sampling linearity and field-of-view (FOV). We believe these methods can benefit both real-time retinal tracking in OCT and OCTA acquisition protocols.
Current-generation optical coherence tomographic angiography (OCTA) systems are slit-lamp based, which limits imaging to patients who are able to sit upright and fixate. Prototype handheld OCTA has demonstrated imaging of supine patients, but these systems are susceptible to bulk-motion artifacts that degrade OCTA resolution and contrast. Here, we demonstrate bulk-motion correction and multi-volumetric mosaicking of OCTA volumes acquired using our handheld spectrally encoded coherence tomography and reflectometry (SECTR) system. In addition, we leverage variable-velocity scanning to reduce OCTA acquisition times. We believe SECTR overcomes the limitations of current-generation handheld OCT/OCTA and will enable functional imaging in bedridden patients and infants.
Temperature mapping during thermotherapy can help precisely control the heating process, both temporally and spatially, to efficiently kill the tumor cells and prevent the healthy tissues from heating damage. Photoacoustic tomography (PAT) has been used for noninvasive temperature mapping with high sensitivity, based on the linear correlation between the tissue’s Grüneisen parameter and temperature. However, limited by the tissue’s unknown optical properties and thus the optical fluence at depths beyond the optical diffusion limit, the reported PAT thermometry usually takes a ratiometric measurement at different temperatures and thus cannot provide absolute measurements. Moreover, ratiometric measurement over time at different temperatures has to assume that the tissue’s optical properties do not change with temperatures, which is usually not valid due to the temperature-induced hemodynamic changes. We propose an optical-diffusion-model-enhanced PAT temperature mapping that can obtain the absolute temperature distribution in deep tissue, without the need of multiple measurements at different temperatures. Based on the initial acoustic pressure reconstructed from multi-illumination photoacoustic signals, both the local optical fluence and the optical parameters including absorption and scattering coefficients are first estimated by the optical-diffusion model, then the temperature distribution is obtained from the reconstructed Grüneisen parameters. We have developed a mathematic model for the multi-illumination PAT of absolute temperatures, and our two-dimensional numerical simulations have shown the feasibility of this new method. The proposed absolute temperature mapping method may set the technical foundation for better temperature control in deep tissue in thermotherapy.
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