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Prior to performing a robot-assisted coronary artery bypass grafting procedure, a pre-operative computed tomography scan is used to assess patient candidacy and to identify the location of the target vessel. The surgeon then determines the optimal port locations to ensure proper reach to the target with the robotic instruments, while assuming that the heart does not undergo any significant changes between the pre- and intra-operative stages. However, the peri-operative workflow itself leads to changes in heart position and consequently the intra-operative target vessel location. As such, the pre-operative plan must be adequately updated to adjust the target vessel location to better suit the intra-operative condition. Here we propose a technique to predict the position of the peri-operative target vessel location with ~ 3.5 mm RMS accuracy. We believe this technique will potentially reduce the rate of conversion of robot-assisted procedures to traditional open-chest surgery due to poor planning. [ABSTRACT FROM AUTHOR]

Minimally invasive beating heart intracardiac surgery is an area of research with many unique challenges. Surgical targets are in constant motion in a blood-filled environment that prevents direct line-of-sight guidance. The restrictive workspace requires compact, yet robust tools for proper therapy delivery. Our novel method for approaching multiple targets inside the beating heart allows their identification and access under augmented reality-assisted image guidance. The surgical platform integrates real-time ultrasound imaging with virtual models of the surgical instruments, along with virtual cardiac anatomy acquired from pre-operative images. Extensive in vitro studies were performed to assess the operator΄s ability to ˵deliver therapy″ to dynamic intracardiac targets via both transmural and transluminal access, and demonstrated significantly more accurate targeting under augmented reality guidance compared to ultrasound image guidance alone, accompanied by a reduction of procedure time by half. Moreover, preliminary in vivo acute studies on porcine models showed successful prosthesis positioning for beating-heart septal defect repair and mitral valve implantation via direct surgical access. While still in its infancy, this work emphasizes the promise of ultrasound-enhanced model-guided environments for minimally-invasive cardiac therapy, whether delivered via a catheter introduced into the vascular system or a cannula inserted through the heart wall. [ABSTRACT FROM AUTHOR]

In image-guided interventions, anatomical models of organs are often generated from pre-operative images and further employed in planning and guiding therapeutic procedures. However, the accuracy of these models, along with their registration to the subject are crucial for successful therapy delivery. These factors are amplified when manipulating soft tissue undergoing large deformations, such as the heart. When used in guiding beating-heart procedures, pre-operative models may not be sufficient for guidance and they are often complemented with real-time, intra-operative cardiac imaging. Here we demonstrate via in vitro endocardial ˵therapy″ that ultrasound-enhanced model-guided navigation provides sufficient guidance to preserve a clinically-desired targeting accuracy of under 3 mm independently of the model-to-subject misregistrations. These results emphasize the direct benefit of integrating real-time imaging within intra-operative visualization environments considering that model-to-subject misalignments are often encountered clinically. [ABSTRACT FROM AUTHOR]

Minimally invasive techniques for electrophysiological cardiac data mapping and catheter ablation therapy have been driven through advancements in computer-aided technologies, including magnetic tracking systems, and virtual and augmented-reality environments. The objective of this work is to extend current cardiac mapping techniques to collect and display data in the temporal domain, while mapping on patient-specific cardiac models. This paper details novel approaches to collecting spatially tracked cardiac electrograms, registering the data with a patient-specific cardiac model, and interpreting the data directly on the model surface, with the goal of giving a more comprehensive cardiac mapping system in comparison to current systems. To validate the system, laboratory studies were conducted to assess the accuracy of navigating to both physical and virtual landmarks. Subsequent to the laboratory studies, an in-vivo porcine experiment was conducted to assess the systems overall ability to collect spatial tracked electrophysiological data, and map directly onto a cardiac model. The results from these experiments show the new dynamic cardiac mapping system was able to maintain high accuracy of locating physical and virtual landmarks, while creating a dynamic cardiac map displayed on a dynamic cardiac surface model. [ABSTRACT FROM AUTHOR]

In an effort to reduce morbidity of cardiac interventions, minimizing invasiveness inevitably leads to limited visual access to the surgical targets. To address these limitations, we provide the surgeons with a robust visualization environment that integrates interventional ultrasound imaging augmented with pre-operative anatomical models and virtual surgical instruments within a virtual reality environment. Here we present an in vitro study on a cardiac phantom that mimics an ablation therapy procedure, which allows us to assess the feasibility of our surgical system in comparison to traditional intra-operative ultrasound imaging. Following surgical target identification via an electro-anatomical model, the ˵ablation procedure″ is performed blindly. A 2.8 mm RMS targeting error is achieved using our novel surgical system. This level of accuracy is adequate from both a clinical and engineering perspective, under the inherent procedure requirements and limitations of the system. [ABSTRACT FROM AUTHOR]

We have developed a visualization environment to assist surgeons with therapy delivery inside the beating heart, in absence of direct vision. This system employs virtual reality techniques to integrate pre-operative anatomical models, real-time intra-operative imaging, and models of magnetically-tracked surgical tools. Visualization is enhanced via 3D dynamic cardiac models constructed from high-resolution pre-operative MR or CT data and registered within the intra-operative imaging environment. In this paper, we report our experience with a feature-based registration technique to fuse the pre- and intra-operative data during an in vivo intracardiac procedure on a porcine subject. Good alignment of the pre- and intra-operative anatomy within the virtual reality environment is ensured through the registration of easily identifiable landmarks. We present our initial experience in translating this work into the operating room and employing this system to guide typical intracardiac interventions. Given its extensive capabilities in providing surgical guidance in the absence of direct vision, our virtual environment is an ideal candidate for performing off-pump intracardiac interventions. [ABSTRACT FROM AUTHOR]

Surgeons need a robust interventional system capable of providing reliable, real-time information regarding the position and orientation of the surgical targets and tools to compensate for the lack of direct vision and to enhance manipulation of intracardiac targets during minimally-invasive, off-pump cardiac interventions. In this paper, we describe a novel method for creating dynamic, pre-operative, subject-specific cardiac models containing the surgical targets and surrounding anatomy, and how they are used to augment the intra-operative virtual environment for guidance of valvular interventions. The accuracy of these pre-operative models was established by comparing the target registration error between the mitral valve annulus characterized in the pre-operative images and their equivalent structures manually extracted from 3D US data. On average, the mitral valve annulus was extracted with a 3.1 mm error across all cardiac phases. In addition, we also propose a method for registering the pre-operative models into the intra-operative virtual environment. [ABSTRACT FROM AUTHOR]