Tele-Operated MRI-Guided Needle Insertion for Prostate Interventions

Author:

Moreira Pedro1ORCID,Kuil Leanne1,Dias Pedro2,Borra Ronald34,Misra Sarthak15

Affiliation:

1. Surgical Robotics Laboratory, Department of Biomechanical Engineering, University of Twente, The Netherlands

2. Department of Biomechanical Engineering, Universidade Nova de Lisboa, Portugal

3. Faculty of Medical Sciences, Department of Nuclear Medicine and Molecular Imaging, University of Groningen and University Medical Center Groningen, The Netherlands

4. Medical Imaging Centre of Southwest Finland, Department of Diagnostic Radiology, Turku University Hospital, Turku, Finland

5. Surgical Robotics Laboratory, Department of Biomedical Engineering, University of Groningen and University Medical Center Groningen, The Netherlands

Abstract

Prostate cancer is one of the leading causes of death in men. Prostate interventions using magnetic resonance imaging (MRI) benefits from high tissue contrast if compared to other imaging modalities. The Minimally Invasive Robotics In An MRI environment (MIRIAM) robot is an MRI-compatible system able to steer different types of needles towards a point of interest using MRI guidance. However, clinicians can be reluctant to give the robot total control of the intervention. This work integrates a haptic device in the MIRIAM system to allow input from the clinician during the insertion. A shared control architecture is achieved by letting the clinician control the insertion depth via the haptic device, while the robotic system controls the needle orientation. The clinician receives haptic feedback based on the insertion depth and tissue characteristics. Four control laws relating the motion of the master robot (haptic device) to the motion of the slave robot (MIRIAM robot) are presented and evaluated. Quantitative and qualitative results from 20 human subjects demonstrate that the squared-velocity control law is the most suitable option for our application. Additionally, a pre-operative target localization algorithm is presented in order to provide the robot with the target location. The target localization and reconstruction algorithm are validated in phantom and patient images with an average dice similarity coefficient (DSC) of 0.78. The complete system is validated through experiments by inserting a needle towards a target within the MRI scanner. Four human subjects perform the experiment achieving an average targeting error of 3.4[Formula: see text]mm.

Publisher

World Scientific Pub Co Pte Lt

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