Vishnu Mallapragada

Robot-Assisted Real-Time Tumor Manipulation for Breast Biopsy

Breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. The current procedure allows the clinician to determine the location and extent of a tumor in the patient breast before inserting the needle. However, there are several problems with this procedure: the complex interaction dynamics between the needle force and the breast tissue will likely displace the tumor from its original position, necessitating multiple insertions, causing clinicianspsila fatigue, patients discomfort, and compromising the integrity of the tissue specimen. In this paper, we present a new concept for real-time manipulation of a tumor using a robotic controller that monitors the image of the tumor to generate appropriate external force to position the tumor at a desired location. The idea here is to demonstrate that it is possible to manipulate a tumor in real time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. Experiments on breast phantoms are presented to demonstrate the essence of this concept. The success of this approach has the potential to reduce the number of attempts a clinician makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, reduce patient discomfort, and eliminate false negative results.

Toward a Robot-Assisted Breast Intervention System

Minimally invasive breast biopsies have several advantages, such as low morbidity and decreased cost. However, success of these procedures is critically dependent on precise placement of the biopsy probe at the tumor location. In addition, during manual image-guided breast interventions, freehand ultrasound (US) imaging is challenging and coordinating image acquisition with probe insertion and breast stabilization simultaneously requires high level of skill. To address these problems, a novel robotic breast intervention device is presented in this paper. This system assists the clinician by: 1) ensuring accurate placement of the instrument at the tumor location and 2) autonomously acquiring real-time images of the tumor. Experimental results on breast phantoms demonstrate the efficacy of this device. This system has the potential to increase targeting accuracy while at the same time reducing the level of skill required to perform minimally invasive breast interventional procedures.

A New Method of Force Control for Unknown Environments

We propose a new control technique for force control on unknown environments. In particular, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling direct force controller to track the desired force by adjusting control gains based on online parameter estimation. However, the ANN is tolerant to imprecise estimation of environment parameters. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed

Autonomously Adapting Robotic Assistance for Rehabilitation Therapy

The goal of our research is to develop a novel control framework to provide robotic assistance for rehabilitation of the hemiparetic upper extremity after stroke. The control framework is designed to provide an optimal time-varying assistive force to stroke patients in varying physical and environmental conditions. An artificial neural network (ANN) based proportional-integral (PI) gain scheduling direct force controller is designed to provide optimal force assistance in a precise and smooth manner. The human arm model is integrated within the control framework where ANN uses estimated human arm parameters to select the appropriate PI gains. Experimental results are presented to demonstrate the effectiveness and feasibility of the proposed control framework

Adaptable force control in robotic rehabilitation

This paper presents initial work on a direct force control framework that would be used to assist stroke patients during rehabilitation therapy in the future. This framework is expected to provide an optimal time-varying assistive force to stroke patients in varying physical and environmental conditions. This control structure has two main modules. The first module is a human arm parameter estimation model. The second module is an artificial neural network (ANN)-based PI-gain scheduling controller. The ANN uses estimated human arm parameters to select the appropriate PI gains for the direct force controller. The feasibility and efficacy of the controller is demonstrated with a PUMA 560 robotic manipulator on various artificial environments.

Autonomous coordination of imaging and tumor manipulation for robot assisted breast biopsy

Breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. During percutaneous needle biopsy, large tissue deformation will likely displace the tumor from its original position necessitating multiple insertions, causing surgeonspsila fatigue, patientpsilas discomfort, and compromising integrity of the tissue specimen. Tumor mobility also poses significant difficulty in imaging the target and the needle using an ultrasound probe. In addition, simultaneous coordination of freehand ultrasound imaging, needle insertion, target localization and breast stabilization is a challenging task for the surgeon. In this work, we present a new concept for coordinated real-time tumor manipulation and ultrasound imaging using a hybrid control architecture. The idea here is to demonstrate that it is possible to (1) manipulate a tumor in real-time by applying controlled external force (2) control the position of the ultrasound probe for tracking out-of-plane target movement and maintaining surface contact (3) coordinate the above systems in an autonomous manner such that the tumor does not deviate from the path of the needle. Experiments are performed on phantoms to demonstrate essence of this technique. The success of this approach has the potential to reduce the number of attempts a surgeon makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, and reduce patient discomfort.

Robotic system for tumor manipulation and ultrasound image guidance during breast biopsy

Tumor mobility poses significant difficulty in obtaining tissue samples during ultrasound guided breast biopsy. In this work, we present a new concept for coordinated real-time tumor manipulation and ultrasound imaging using a hybrid control architecture. The idea here is to demonstrate that it is possible to (1) manipulate a tumor in real-time by applying controlled external force, (2) control the position of the ultrasound probe for tracking out-of-plane target movement, and (3) coordinate the above systems in an automated way such that the tumor does not deviate from the path of the needle. Experiments are performed on breast tissue mimicking phantoms to demonstrate the efficacy of this technique. The success of this approach has the potential to reduce the number of attempts a surgeon makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, and reduce patient discomfort.

A Robotic System for Real-Time Tumor Manipulation During Image Guided Breast Biopsy

Breast biopsy guided by imaging techniques is widely used to evaluate suspicious masses within the breast. Current procedure allows the physician to determine location and extent of a tumor in the patient breast before inserting the needle. There are several problems with this procedure: Complex interaction dynamics between needle and breast tissue will likely displace the tumor from its original position necessitating multiple insertions, causing surgeons’ fatigue, patient’s discomfort, and compromising integrity of the tissue specimen. We present a new concept for real-time manipulation of a tumor using a robotic system that monitors the image of the tumor to generate appropriate external force to position the tumor at a desired location. The objective is to demonstrate that it is possible to manipulate a tumor in real-time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. We have demonstrated efficacy of this approach on breast phantoms. The robotic system consists of an ultrasound probe for image acquisition, a guiding mechanism for automatic probe orientation, image processing algorithm for extracting tumor position and PID (proportional-integral-derivative) controlled actuators for tumor manipulation. We have successfully tested this system for accessing mobile lesions during multiple needle insertion trials. This approach has the potential to reduce the number of attempts a surgeon makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, and reduce patient discomfort.