Atrial fibrillation (AF) is the most common arrhythmia worldwide. An increasingly common treatment option is catheter ablation. During this procedure, the clinician steers a catheter into the left atrium and ablates a lesion fence around the pulmonary veins, a common source of ectopic signals. This lesion fence blocks arrhythmogenic tissue from initiating an erroneous heartbeat. However, if the disease has progressed from paroxysmal to persistent, pathogenic tissue exists throughout the atrium, and common ablation schemes are not as effective. In this case, technologies exist to electroanatomically map the atrium and guide clinicians in targeting adjunctive AF ablation targets. Low voltages mapped in vivo are a well-documented way of identifying atrial fibrosis, an important substrate for AF. Ablating low voltage zones in patients with a more developed disease can help terminate AF and improve long-term outcomes, but low voltage measurements are not specific to fibrosis. Treatment results vary because the targeting that electroanatomical mapping provides is incomplete. Our group has shown that polarization-sensitive optical coherence tomography (PSOCT) and near infrared spectroscopy (NIRS) can monitor lesion formation in vivo and differentiate tissue types in the atrium. Now, we are investigating the technology's utility in identifying AF targets prior to ablation. We have collaborated in developing a swine model of AF that shows the atria remodels during the diseased state. Because of this, we can electroanatomically map these diseased hearts in vivo to measure low voltage zones. Subsequently, we examine the left atrium ex vivo using benchtop PSOCT, NIRS, and optical mapping (OM) and register these optical measurements to the in vivo low voltage zones. We show that OM confirms abnormal conduction, while PSOCT- and NIRS-derived metrics have promise for identifying low voltage zones. We confirm these measures with histological identification of fibrosis. This suggests the feasibility of using PSOCT-NIRS at the catheter tip to detect AF ablation targets.

Atrial fibrillation (AF) is the most common arrhythmia worldwide. An increasingly common treatment option is catheter ablation. During this procedure, the clinician steers a catheter into the left atrium and ablates a lesion fence around the pulmonary veins. This blocks arrhythmogenic tissue from initiating an erroneous heartbeat. Technological advancements in this maturing procedure have made ablations more widespread and effective for patients, but there is still a need to improve long term efficacy. With current intraprocedural feedback available to clinicians, it is difficult to assess whether a lesion line will remain durable or heal to initiate recurrent AF. Clinicians do not directly measure lesion qualities such as transmurality or diameter. Instead, the clinician will ablate until acute isolation is measured in vivo. Our group has shown that in vivo measurements of polarization sensitive optical coherence tomography (PSOCT) and near infrared spectroscopy (NIRS) can monitor lesions during an ablation procedure but are both individually limited in terms of imaging depth and morphological detail, respectively. By integrating both modalities into the same catheter, we mitigate the imaging depth limitations of PSOCT and inform spectral measurements made by NIRS to develop a new way of analyzing important lesion qualities. Here, we show that we can simultaneously monitor PSOCT, NIRS, and standard ablation feedback parameters in a single catheter. We show that we can monitor a single lesion as it forms by ablating fresh swine left atria with a novel catheter tip.

Atrial fibrillation (AF) is the most common arrhythmia worldwide. An increasingly common treatment option is catheter ablation. During this procedure, the electrophysiologist steers a catheter into the left atrium and ablates a lesion fence around common sources of ectopic signals. This blocks arrhythmogenic tissue from initiating an erroneous heartbeat. Technological advancements in this maturing procedure have made ablations more widespread and effective for patients, but there is still a need to improve long term efficacy of the procedure. The national rate of recurrent AF after an ablation is 20% to 40% and this is almost universally due to reconnection via poor lesion quality. With current catheter feedback available to clinicians, it is difficult to assess whether a lesion line will remain durable or heal to initiate recurrent AF. We have previously shown that polarization-sensitive optical coherence tomography (PSOCT) can monitor lesion formation in vivo during an ablation procedure. This feedback at the catheter tip may help clinicians assess lesion quality by measuring tissue changes. To further understand the technology’s utility and limitations, we are conducting experiments to characterize PSOCT detection of gaps between lesions. Lesion gaps are a common failure mode when AF recurrence is caused by reconnection. We ablate left atrial swine myocardium ex vivo and collect PSOCT images to compare with histology and identify the detection limits of small lesion gaps. Using PSOCT at the catheter tip to detect small gaps in lesion lines could help clinicians reduce recurrence by decreasing opportunities for reconnection.

Purpose: Retinopathy of prematurity (ROP) is a retinal vascular disease affecting premature infants that can culminate in blindness within days if not monitored and treated. A disease stage for scrutiny and administration of treatment within ROP is "plus disease" characterized by increased tortuosity and dilation of posterior retinal blood vessels. The monitoring of ROP occurs via routine imaging, typically using expensive instruments ($50 to $140 K) that are unavailable in low-resource settings at the point of care.Approach: As part of the smartphone-ROP program to enable referrals to expert physicians, fundus images are acquired using smartphone cameras and inexpensive lenses. We developed methods for artificial intelligence determination of plus disease, consisting of a preprocessing pipeline to enhance vessels and harmonize images followed by deep learning classification. A deep learning binary classifier (plus disease versus no plus disease) was developed using GoogLeNet.Results: Vessel contrast was enhanced by 90% after preprocessing as assessed by the contrast improvement index. In an image quality evaluation, preprocessed and original images were evaluated by pediatric ophthalmologists from the US and South America with years of experience diagnosing ROP and plus disease. All participating ophthalmologists agreed or strongly agreed that vessel visibility was improved with preprocessing. Using images from various smartphones, harmonized via preprocessing (e.g., vessel enhancement and size normalization) and augmented in physically reasonable ways (e.g., image rotation), we achieved an area under the ROC curve of 0.9754 for plus disease on a limited dataset.Conclusions: Promising results indicate the potential for developing algorithms and software to facilitate the usage of cell phone images for staging of plus disease.

Atrial fibrosis is an important cause of atrial fibrillation (AF) and is often targeted for radiofrequency ablation (RFA) treatment. However, fibrosis identification during an RFA procedure is indirect and not well established. Polarization-sensitive optical coherence tomography (PSOCT) provides high-resolution in-depth noninvasive structural and tissue birefringence images, which can be effective for detecting fibrosis. In this work, combining histology and optical mapping of atrial action potential activity, we demonstrated the identification of atrial fibrosis that caused abnormal impulse propagation in a pig model of AF with PSOCT. Results indicate that PSOCT may provide effective guidance for RFA procedures in the future.

Retinopathy of prematurity (ROP) is a retinal vascular disease that affects premature infants and can result in blindness within days if not monitored and treated. A disease stage for increased scrutiny and treatment within ROP is "plus disease," characterized by increased tortuosity and dilation of posterior retinal blood vessels. Monitoring of ROP occurs with routine imaging, typically using expensive instruments ranging from $50-140K. In low-resource areas of the world, smartphone cameras and inexpensive Volk 28D lenses are being used to image the fundus, albeit with lower fields of view and image quality than the expensive systems. We developed a preprocessing pipeline to enhance vessel visualization and harmonize images for automated analysis using deep learning algorithms. After preprocessing, vessel contrast was enhanced by 90% as assessed by the contrast improvement index. In an image quality evaluation, 441 images were evaluated by pediatric ophthalmologists from the US and South America, all with years of experience diagnosing ROP and plus disease. 100% of participating ophthalmologists either agreed or strongly agreed that vessel visibility was improved in the processed images. A preliminary deep learning binary classifier (plus vs. no plus disease) was developed using GoogLeNet. Using smartphone images harmonized via preprocessing (e.g., vessel enhancement and size normalization) and augmented in physically reasonable ways (e.g., image rotation), we achieved an exceptional accuracy of 0.96 for plus disease on a limited dataset. These promising results suggest the potential to create algorithms and software to improve usage of cell phone images for ROP staging.

Transseptal puncture (TSP) is commonly conducted under the guidance of fluoroscopy and/or intracardiac echocardiography (ICE) at the fossa ovalis (FO) to gain percutaneous access to the left atrium for intracardiac procedures. Issues with traditional TSP include: additional vascular access through a sheath, and fluoroscopy exposes patients to ionizing radiation. TSP, if not done appropriately can result in serious complications. We studied the feasibility of optical coherence tomography (OCT) guidance of TSP with ex vivo and in vivo experiments. Results show that OCT can provide detailed structure information to identify FO allowing for safe TSP.