Nikhil V. Navkar

Visualization and planning of neurosurgical interventions with straight access

Image-guided neurosurgical interventional procedures utilize medical imaging techniques to identify the most appropriate path for accessing a targeted structure. Often, preoperative planning entails the use of multi-contrast or multi-modal imaging for assessing different aspects of patients pathophysiology related to the procedure. Comprehensive visualization and manipulation of such large volume of three-dimensional anatomical information is a major challenge. In this work we propose a technique for simple and efficient visualization of the region of intervention for neurosurgical procedures. It is done through the generation of access maps on the surface of the patients skin, which assists a neurosurgeon in selecting the most appropriate path of access by avoiding vital structures and minimizing potential trauma to healthy tissue. Our preliminary evaluation showed that this technique is effective as well as easy to use for planning neurosurgical interventions such as biopsies, deep brain stimulation, ablation of brain lesions.

Visual and force-feedback guidance for robot-assisted interventions in the beating heart with real-time MRI

Robot-assisted surgical procedures are perpetually evolving due to potential improvement in patient treatment and healthcare cost reduction. Integration of an imaging modality intraoperatively further strengthens these procedures by incorporating the information pertaining to the area of intervention. Such information needs to be effectively rendered to the operator as a human-in-the-loop requirement. In this work, we propose a guidance approach that uses real-time MRI to assist the operator in performing robot-assisted procedure in a beating heart. Specifically, this approach provides both real-time visualization and force-feedback based guidance for maneuvering an interventional tool safely inside the dynamic environment of a hearts left ventricle. Experimental evaluation of the functionality of this approach was tested on a simulated scenario of transapical aortic valve replacement and it demonstrated improvement in control and manipulation by providing effective and accurate assistance to the operator in real-time.

MR-based real time path planning for cardiac operations with transapical access

Minimally invasive surgeries (MIS) have been perpetually evolving due to their potential high impact on improving patient management and overall cost effectiveness. Currently, MIS are further strengthened by the incorporation of magnetic resonance imaging (MRI) for amended visualization and high precision. Motivated by the fact that real-time MRI is emerging as a feasible modality especially for guiding interventions and surgeries in the beating heart; in this paper we introduce a real-time path planning algorithm for intracardiac procedures. Our approach creates a volumetric safety zone inside a beating heart and updates it on-the-fly using real-time MRI during the deployment of a robotic device. In order to prove the concept and assess the feasibility of the introduced method, a realistic operational scenario of transapical aortic valve replacement in a beating heart is chosen as the virtual case study.

Generation of 4d access corridors from real-time multislice MRI for guiding transapical aortic valvuloplasties

Real-time image-guided cardiac procedures (manual or robot-assisted) are emerging due to potential improvement in patient management and reduction in the overall cost. These minimally invasive procedures require both real-time visualization and guidance for maneuvering an interventional tool safely inside the dynamic environment of a heart. In this work, we propose an approach to generate dynamic 4D access corridors from the apex to the aortic annulus for performing real-time MRI guided transapical valvuloplasties. Ultrafast MR images (collected every 49.3 ms) are processed on-the-fly using projections to extract a conservative dynamic trace in form of a three-dimensional access corridor. Our experimental results show that the reconstructed corridors can be refreshed with a delay of less than 0.5ms to reflect the changes inside the left ventricle caused by breathing motion and the heartbeat.

A Framework for Integrating Real-Time MRI With Robot Control: Application to Simulated Transapical Cardiac Interventions

The advent of intraoperative real-time image guidance has led to the emergence of new surgical interventional paradigms including image-guided robot assistance. Most often the use of an intraoperative imaging modality is limited to visual perception of the area of procedure. In this study, we propose a framework for performing robot-assisted interventions with real-time magnetic resonance imaging (rtMRI) guidance. The described computational core of this framework, processes on-the-fly rtMRI, integrates the processed information with robot control and renders it on the human-machine interfaces. This information is rendered on a visualization and force-feedback interface for enhanced perception of a dynamic area of procedure and for assisting the operator in the safe and accurate maneuvering of a robotic manipulator. The framework was experimentally tested by applying it to a simulated Transapical aortic valve implantation with a virtual robotic manipulator. rtMRI data were processed on-the-fly in a rolling-window scheme and together with a multithreaded and multihardware implementation, the core delivered appropriate speed of 20 Hz for visualization and 1000 Hz for force feedback. The experimental results demonstrate significant improvement in the simulated task by both decreasing the duration of the procedure by half and increasing safety in the presence of cardiac and breathing motion by reducing the duration or incidents the operator collides with the tissue.

Magnetic resonance based control of a robotic manipulator for interventions in the beating heart

As a part of an ongoing project, in this paper we introduce the first version of a system which has a novel methodology for Cine (as in cinema) MRI based control of a cardiac robot for beating heart surgeries. The system uses the preoperative planning approach that we developed earlier, and integrates it to the intraoperative algorithms for controlling a robot and tracking some specific landmarks of a highly dynamical surgical field. In particular, our late studies presented herein aim to demonstrate the feasibility of integrating appropriate computational tools to achieve the volumetric image guidance for minimally invasive surgeries in the beating heart. We conceive of the system as practicable for in vitro experiments upon the completion of the first physical prototype, which may pave the way for expansion of the approach for other complex surgeries as well.

Intraoperative registration of preoperative 4D cardiac anatomy with real-time MR images

Co-registering pre- and intra- operative MR data is an important yet challenging problem due to different acquisition parameters, resolutions, and plane orientations. Despite its importance, previous approaches are often computationally intensive and thus cannot be employed in real-time. In this paper, a novel three-step approach is proposed to dynamically register pre-operative 4D MR data with intra-operative 2D RT-MRI to guide intracardiac procedures. Specifically, a novel preparatory step, executed in the pre-operative phase, is introduced to generate bridging information that can be used to significantly speed up the on-the-fly registration in the intraoperative procedure. Our experimental results demonstrate an accuracy of 0.42 mm and a processing speed of 26 FPS of the proposed approach on an off-the-shelf PC. This approach, is in particularly developed for performing intra-cardiac procedures with real-time MR guidance.

Extracting geometric features of aortic valve annulus motion from dynamic MRI for guiding interventions

Transcatheter aortic valve implant (TAVI) has emerged as a prominent approach for treating aortic stenosis. Success of such implants depends upon the accurate assessment of the geometric features such as the diameter, center and orientation of the aortic valve annulus (AVA). In this paper, we present a method for extracting these geometric features from magnetic resonance images (MRI). The method is based on finding an optimal fit for a circular ring mimicking AVA in the aortic root. Moreover, the presented approach provides dynamic tracking of the AVA in CINE MR images. This approach can be used for preoperative planning of prosthetic valve implantation, as well as for the emerging MRI guided manual, or with robot-assisted, annuloplasty.

Implementation of a force-feedback interface for robotic assisted interventions with real-time MRI guidance

Efficient and intuitive interfacing of the interventionalist to the information and tools available from image-guided robotic assisted surgeries is required to achieve the full benefit of these technologies. Ongoing research has been performed into the use of forbidden region guided fixtures (FRVF) for human-in-the-loop control of image-guided procedures via haptic force-feedback devices (FFD). Although commercially available FFD provide sufficient degrees-of-freedom (DoF), collaborating clinicians, as well as the results of our previous work indicate that these systems are not completely intuitive for controlling fixed-point access interventional tool which have a remote center of motion. Within this context, we introduce a new FFD which is designed with the same DoF constraints as a fixed-point access interventional tool. The device is tested in a clinical simulation of a robot assisted trans-apical valve implantation under guidance from real-time magnetic resonance imaging. Pre-acquired real-time images are used in the clinical simulation to dynamically update the FRVF and therefore provide guiding forces to allow the operator to see the safe boundaries of operation via a visualization interface and physically feel them through the FFD. Inertial and gravity compensation and per DoF dynamic response of the physical prototype are validated and the frequency response of the system demonstrates it is adequate for tactile sensing. During clinical simulation the operator was successfully able to maneuver the tool within the safe path to the region of interest with the guidance of visual and force-feedback.