Our current research areas are listed below.
For more information, please visit:
AIM Lab Main Web Page
Prof. Gregory Fischer's Personal Web Page
Please see the Publications page for a complete listing of published works.
Magnetic Resonance Imaging (MRI) is an excellent imaging modality for many conditions, but to date there has been limited success in harnessing this modality for the guidance of interventional procedures. MRI is an ideal interventional guidance modality: it provides near real-time high-resolution images at arbitrary orientations and is able to monitor therapeutic agents, surgical tools, biomechanical tissue properties, and physiological function. At the same time, MRI poses formidable engineering challenges by severely limited access to the patient and high magnetic field that prevents the use of conventional materials and electronic equipment.
Direct MR image guidance during deep brain stimulation (DBS) insertion offers many benefits; most significantly, interventional MRI can be used for planning, monitoring of tissue deformation, real-time visualization of insertion, and confirmation of placement. The accuracy of standard stereotactic insertion is limited by registration errors and brain movement during surgery. With real-time acquisition of high-resolution MR images during insertion, probe placement can be confirmed intra-operatively. Direct MR guidance has not taken hold because it is often confounded by a number of issues including: MR-compatibility of existing stereotactic surgery equipment and patient access in the scanner bore. The high resolution images required for neurosurgical planning and guidance require high-field MR (1.5-3T); thus, any system must be capable of working within the constraints of a closed, long-bore diagnostic magnet. Currently, no technological solution exists to assist MRI guided neurosurgical interventions in an accurate, simple, and economical manner.
The objective of our research is to make conventional diagnostic closed high-field MRI scanners available for guiding deep brain stimulation electrode placement interventions for treatment of Parkinson's Disease and other neurological disorders including severe depression and Alzheimer's Disease.
Our approach is to employ an MRI-compatible robotic assistant for guiding DBS electrode insertion under direct, real-time MR image guidance. The system will allow interactive probe alignment under real-time imaging in standard diagnostic high-field MR scanners. Use of a robotic assistant will minimize the potential for human error and mis-registration associated with the current procedure and will better address the practical issues of operating in an MR scanner bore.
MRI has potential to be a superior medical imaging modality for guiding and monitoring prostatic interventions. MRI can provide high-quality 3D visualization of prostate and surrounding tissue. However, the benefits can not be readily harnessed for interventional procedures due to difficulties that surround the use of high-field (1.5T or greater). The strong magnetic field prevents the use of conventional mechatronics and the confined physical space makes it extremely challenging to access the patient. We have designed a robotic assistant system that overcomes these difficulties and promises safe and reliable intra-prostatic needle placement inside closed high-field MRI scanners.
The unavailability of robot control interfaces that are compatible with the MRI environment has severely limited the ability to do research in the field. The high cost of entry into MRI robotics has been primarily due to the need for each researcher to develop and evaluate their control system in the scanner. We have developed an MRI compatible robot controller that sits in the scanner room without interfering with scanner imaging. The controller is modular and allows many different inputs and output and communicates to a high level planning and navigation software workstation through fiber optic connections.
Traditional actuators are often contraindicated by the strong magnetic and electric fields present in the MRI scanner bore. Further, it is critical that the devices not introduce noise or distortion into the acquired images. We are evaluating different actuator schemes including pneumatics and piezoelectric actuators. We are investigating ways of optimizing piezoelectric motors for MR-compatibility and developing high-accuracy pneumatic control systems.
Traditional sensors in robotics include force and positioning sensing. However, off-the-shelf sensors are not suiatable for use in MRI due to the potential for image degradation, malfunction, or safety issues. We are evaluating and developing sensors to be used in the MR environment. The current focus is on optical techniques for force and position sensing that do not compromise image quality and will allow for haptic feedback during MRI-guided interventions.
Magnetic Resonance Imaging (MRI) provides great potential for planning, guiding, monitoring and controlling interventions. MR arthrography (MRAr) is the imaging gold standard to assess small ligament and fibrocartilage injury in joints. In contemporary practice, MRAr consists of two consecutive sessions: 1) an interventional session where a needle is driven to the joint space and MR contrast is injected under fluoroscopy or CT guidance, and 2) A diagnostic MRI imaging session to visualize the distribution of contrast inside the joint space and evaluate the condition of the joint. Our approach to MRAr is to eliminate the separate radiologically guided needle insertion and contrast injection procedure by performing those tasks on conventional high-field closed MRI scanners. We propose a 2D augmented reality image overlay device to guide needle insertion procedures. This approach makes diagnostic high-field magnets available for interventions without a complex and expensive engineering entourage. In preclinical trials, needle insertions have been performed in the joints of porcine and human cadavers using MR image overlay guidance; insertions successfully reached the joint space on the first attempt in all cases.
Description of the MRI Image Overlay on the NSF ERC Achievements Showcase:
MRI-Guided Needle Placement with Augmented Reality Guidance
Image-guided percutaneous needle-based surgery has become part of routine clinical practice in performing procedures such as biopsies and injections. Image-guided needle placement procedures in CT/MR benefit from an accurate and effective augmented reality (AR) system. In order to operate the system the user has to be trained. Therefore, we have developed a laboratory validation and training system for measuring operator performance under different assistance techniques for needle-based surgical guidance systems named “The Perk Station.” Three techniques are fitted in this training suite: the image overlay, bi-plane laser guide, and traditional freehand techniques. An electromagnetic tracking system is applied in the validation system. The Perk Station, an inexpensive, simple and easily reproducible surgical navigation workstation for laboratory practice incorporating all the above mentioned functions in a “self-contained” unit, is introduced.
We are developing robotic systems applicable to teaching the fundamentals of robotics. The first generation of the robot has been successfully used to teach the junior level undergraduate Robotics Engineering courses at WPI.
No one hardware platform provides all of the tools required to teach a robotics engineering curriculum. We are developing a unified platform specifically designed for multidisciplinary undergraduate robotics education.
The goal of this work is to study the conceptions about the use of robotis in surgery. We are specifically investigating the differences in these perceptions among different patient and medical professional populations. The work is primarily focussed on use of the da Vinci Surgical System.