Optical coherence tomography-based consensus definition for lamellar macular hole.

BackgroundA consensus on an optical coherence tomography definition of lamellar macular hole (LMH) and similar conditions is needed.MethodsThe panel reviewed relevant peer-reviewed literature to reach an accord on LMH definition and to differentiate LMH from other similar conditions.ResultsThe panel reached a consensus on the definition of three clinical entities: LMH, epiretinal membrane (ERM) foveoschisis and macular pseudohole (MPH). LMH definition is based on three mandatory criteria and three optional anatomical features. The three mandatory criteria are the presence of irregular foveal contour, the presence of a foveal cavity with undermined edges and the apparent loss of foveal tissue. Optional anatomical features include the presence of epiretinal proliferation, the presence of a central foveal bump and the disruption of the ellipsoid zone. ERM foveoschisis definition is based on two mandatory criteria: the presence of ERM and the presence of schisis at the level of Henle's fibre layer. Three optional anatomical features can also be present: the presence of microcystoid spaces in the inner nuclear layer (INL), an increase of retinal thickness and the presence of retinal wrinkling. MPH definition is based on three mandatory criteria and two optional anatomical features. Mandatory criteria include the presence of a foveal sparing ERM, the presence of a steepened foveal profile and an increased central retinal thickness. Optional anatomical features are the presence of microcystoid spaces in the INL and a normal retinal thickness.ConclusionsThe use of the proposed definitions may provide uniform language for clinicians and future research

Context-aware learning for robot-assisted endovascular catheterization

Endovascular intervention has become a mainstream treatment of cardiovascular diseases. However, multiple challenges remain such as unwanted radiation exposures, limited two-dimensional image guidance, insufficient force perception and haptic cues. Fast evolving robot-assisted platforms improve the stability and accuracy of instrument manipulation. The master-slave system also removes radiation to the operator. However, the integration of robotic systems into the current surgical workflow is still debatable since repetitive, easy tasks have little value to be executed by the robotic teleoperation. Current systems offer very low autonomy, potential autonomous features could bring more benefits such as reduced cognitive workloads and human error, safer and more consistent instrument manipulation, ability to incorporate various medical imaging and sensing modalities. This research proposes frameworks for automated catheterisation with different machine learning-based algorithms, includes Learning-from-Demonstration, Reinforcement Learning, and Imitation Learning. Those frameworks focused on integrating context for tasks in the process of skill learning, hence achieving better adaptation to different situations and safer tool-tissue interactions. Furthermore, the autonomous feature was applied to next-generation, MR-safe robotic catheterisation platform. The results provide important insights into improving catheter navigation in the form of autonomous task planning, self-optimization with clinical relevant factors, and motivate the design of intelligent, intuitive, and collaborative robots under non-ionizing image modalities.Open Acces

A Deep Segmentation Network of Stent Structs Based on IoT for Interventional Cardiovascular Diagnosis

[EN] The Internet of Things (IoT) technology has been widely introduced to the existing medical system. An eHealth system based on IoT devices has gained widespread popularity. In this article, we propose an IoT eHealth framework to provide an autonomous solution for patients with interventional cardiovascular diseases. In this framework, wearable sensors are used to collect a patient's health data, which is daily monitored by a remote doctor. When the monitoring data is abnormal, the remote doctor will ask for image acquisition of the patient's cardiovascular internal conditions. We leverage edge computing to classify these training images by the local base classifier; thereafter, pseudo-labels are generated according to its output. Moreover, a deep segmentation network is leveraged for the segmentation of stent structs in intravascular optical coherence tomography and intravenous ultrasound images of patients. The experimental results demonstrate that remote and local doctors perform real-time visual communication to complete telesurgery. In the experiments, we adopt the U-net backbone with a pretrained SeResNet34 as the encoder to segment the stent structs. Meanwhile, a series of comparative experiments have been conducted to demonstrate the effectiveness of our method based on accuracy, sensitivity, Jaccard, and dice.This work was supported by the National Key Research and Development Program of China (Grant no. 2020YFB1313703), the National Natural Science Foundation of China (Grant no. 62002304), and the Natural Science Foundation of Fujian Province of China (Grant no. 2020J05002).Huang, C.; Zong, Y.; Chen, J.; Liu, W.; Lloret, J.; Mukherjee, M. (2021). A Deep Segmentation Network of Stent Structs Based on IoT for Interventional Cardiovascular Diagnosis. IEEE Wireless Communications. 28(3):36-43. https://doi.org/10.1109/MWC.001.2000407S364328

Virtual and Augmented Reality Techniques for Minimally Invasive Cardiac Interventions: Concept, Design, Evaluation and Pre-clinical Implementation

While less invasive techniques have been employed for some procedures, most intracardiac interventions are still performed under cardiopulmonary bypass, on the drained, arrested heart. The progress toward off-pump intracardiac interventions has been hampered by the lack of adequate visualization inside the beating heart. This thesis describes the development, assessment, and pre-clinical implementation of a mixed reality environment that integrates pre-operative imaging and modeling with surgical tracking technologies and real-time ultrasound imaging. The intra-operative echo images are augmented with pre-operative representations of the cardiac anatomy and virtual models of the delivery instruments tracked in real time using magnetic tracking technologies. As a result, the otherwise context-less images can now be interpreted within the anatomical context provided by the anatomical models. The virtual models assist the user with the tool-to-target navigation, while real-time ultrasound ensures accurate positioning of the tool on target, providing the surgeon with sufficient information to ``see\u27\u27 and manipulate instruments in absence of direct vision. Several pre-clinical acute evaluation studies have been conducted in vivo on swine models to assess the feasibility of the proposed environment in a clinical context. Following direct access inside the beating heart using the UCI, the proposed mixed reality environment was used to provide the necessary visualization and navigation to position a prosthetic mitral valve on the the native annulus, or to place a repair patch on a created septal defect in vivo in porcine models. Following further development and seamless integration into the clinical workflow, we hope that the proposed mixed reality guidance environment may become a significant milestone toward enabling minimally invasive therapy on the beating heart

Clinical applications of robotic technology in vascular and endovascular surgery

BackgroundEmerging robotic technologies are increasingly being used by surgical disciplines to facilitate and improve performance of minimally invasive surgery. Robot-assisted intervention has recently been introduced into the field of vascular surgery to potentially enhance laparoscopic vascular and endovascular capabilities. The objective of this study was to review the current status of clinical robotic applications in vascular surgery.MethodsA systematic literature search was performed in order to identify all published clinical studies related to robotic implementation in vascular intervention. Web-based search engines were searched using the keywords “surgical robotics,” “robotic surgery,” “robotics,” “computer assisted surgery,” and “vascular surgery” or “endovascular” for articles published between January 1990 and November 2009. An evaluation and critical overview of these studies is reported. In addition, an analysis and discussion of supporting evidence for robotic computer-enhanced telemanipulation systems in relation to their applications in laparoscopic vascular and endovascular surgery was undertaken.ResultsSeventeen articles reporting on clinical applications of robotics in laparoscopic vascular and endovascular surgery were detected. They were either case reports or retrospective patient series and prospective studies reporting laparoscopic vascular and endovascular treatments for patients using robotic technology. Minimal comparative clinical evidence to evaluate the advantages of robot-assisted vascular procedures was identified. Robot-assisted laparoscopic aortic procedures have been reported by several studies with satisfactory results. Furthermore, the use of robotic technology as a sole modality for abdominal aortic aneurysm repair and expansion of its applications to splenic and renal artery aneurysm reconstruction have been described. Robotically steerable endovascular catheter systems have potential advantages over conventional catheterization systems. Promising results from applications in cardiac interventions and preclinical studies have urged their use in vascular surgery. Although successful applications in endovascular repair of abdominal aortic aneurysm and lower extremity arterial disease have been reported, published clinical experience with the endovascular robot is limited.ConclusionsRobotic technology may enhance vascular surgical techniques given preclinical evidence and early clinical reports. Further clinical studies are required to quantify its advantages over conventional treatments and define its role in vascular and endovascular surgery

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots