Robotic systems for breast biopsy using MRI and ultrasound imaging
Vincent Groenhuis is a PhD student in the research group Robotics anbd Mechatronics (RAM). His supervisor is prof.dr.ir. S. Stramigioli from the Faculty of Electrical Engineering, Mathematics and Computer Science.
In breast cancer screening the radiologist searches for suspicious lesions inside the breast. If the lesion is only visible on MRI then it is difficult to precisely target it for a biopsy. The current manual procedure is inaccurate and inefficient, so research has been done to develop suitable alternatives using robotics. Two different robotic system projects have been conducted to tackle the clinical challenge: the MURAB project and the Stormram project.
The MURAB project combines different imaging modalities including MRI, ultrasound, elastography and stereo vision to create a detailed patient-specific model for the biopsy. The setup consists of a metallic robot arm with end-effector positioned under a patient bed. The patient is first scanned in the MRI and then by the robotic arm, resulting in 3D scans in MRI, ultrasound and elastography. A patient-specific simulation model is created and the intervention planned, taking tissue deformations into account. The biopsy needle is manually inserted by the radiologist. The different sub-parts of the system were investigated in a broad range of phantom experiments, while preliminary experiments with the full setup on phantoms were conducted as well. The MURAB setup has shown that it is effectively able to apply deformation compensation techniques in targeting lesions.
The Stormram project takes a different approach into the same clinical challenge. An MR safe needle manipulator is placed inside the MRI scanner, allowing to insert the biopsy needle robotically straight after the MRI scan without moving the patient. The manipulator is actuated by pneumatic stepper motors which are entirely made of non-metallic materials and are extensively described and evaluated. A total of five distinct prototypes have been built within the Stormram project. The Stormram 4 has shown to have a needle positioning accuracy in MRI of 2 mm.
Both the MURAB and Stormram projects show that it is possible to tackle the clinical challenge using a robotic system, taking tissue deformations into account. Several new technologies and combinations have been developed within both projects and these also demonstrate the value of the conducted research.