Planning, simulation and assistance with intraoperative MRI

Neuronavigation in the surgical management of brain tumors: current and future trends

Neuronavigation has become an ubiquitous tool in the surgical management of brain tumors. This review describes the use and limitations of current neuronavigational systems for brain tumor biopsy and resection. Methods for integrating intraoperative imaging into neuronavigational datasets developed to address the diminishing accuracy of positional information that occurs over the course of brain tumor resection are discussed. In addition, the process of integration of functional MRI and tractography into navigational models is reviewed. Finally, emerging concepts and future challenges relating to the development and implementation of experimental imaging technologies in the navigational environment are explored.

MR-Safe Pneumatic Rotation Stepping Actuator

Magnetic Resonance Imaging (MRI) is widely used not only for diagnosis but also for surgical navigation, etc. Surgeons and surgery-support systems can conduct surgeries less invasively because they derive accurate positional relationships between surgical instruments and anatomical regions of interest from preoperative or intraoperative MRI images. Many surgical robots intended for use within MRI gantries have been developed. Some of them use pneumatic actuators that are difficult to control accurately or that have many components, however, causing high fabrication cost, low durability and low sterilizability. To solve these problems, we have developed a φ30-mm pneumatic rotation stepping actuator. The actuator consists of three Direct Acting gears (D.A. gears) and a Rotation gear (R gear). When all of the D.A. gears are pushed sequentially up by compressed air, the R gear rotates because it engages all of them. In a fundamental performance experiment, the maximum angular error was 2.1° and maximum torque was approximately 150 mNm using 0.6 MPaG. Additionally, in an MR safety evaluation, the actuator was not found to cause any distortion or artifacts in MRI images. The actuator can therefore be applied to MR-safe positioning or puncturing robots.

Intraoperative imaging in neurosurgery: where will the future take us?

Intraoperative MRI (ioMRI) dates back to the 1990s and since then has been successfully applied in neurosurgery for three primary reasons with the last one becoming the most significant today: (1) brain shift-corrected navigation, (2) monitoring/controlling thermal ablations, and (3) identifying residual tumor for resection. IoMRI, which today is moving into other applications, including treatment of vasculature and the spine, requires advanced 3T MRI platforms for faster and more flexible image acquisitions, higher image quality, and better spatial and temporal resolution; functional capabilities including fMRI and DTI; non-rigid registration algorithms to register pre- and intraoperative images; non-MRI imaging improvements to continuously monitor brain shift to identify when a new 3D MRI data set is needed intraoperatively; more integration of imaging and MRI-compatible navigational and robot-assisted systems; and greater computational capabilities to handle the processing of data. The Brigham and Women's Hospital's "AMIGO" suite is described as a setting for progress to continue in ioMRI by incorporating other modalities including molecular imaging. A call to action is made to have other researchers and clinicians in the field of image guided therapy to work together to integrate imaging with therapy delivery systems (such as laser, MRgFUS, endoscopic, and robotic surgery devices).

Capturing intraoperative deformations: research experience at Brigham and Women's Hospital

During neurosurgical procedures the objective of the neurosurgeon is to achieve the resection of as much diseased tissue as possible while achieving the preservation of healthy brain tissue. The restricted capacity of the conventional operating room to enable the surgeon to visualize critical healthy brain structures and tumor margin has lead, over the past decade, to the development of sophisticated intraoperative imaging techniques to enhance visualization. However, both rigid motion due to patient placement and nonrigid deformations occurring as a consequence of the surgical intervention disrupt the correspondence between preoperative data used to plan surgery and the intraoperative configuration of the patient's brain. Similar challenges are faced in other interventional therapies, such as in cryoablation of the liver, or biopsy of the prostate. We have developed algorithms to model the motion of key anatomical structures and system implementations that enable us to estimate the deformation of the critical anatomy from sequences of volumetric images and to prepare updated fused visualizations of preoperative and intraoperative images at a rate compatible with surgical decision making. This paper reviews the experience at Brigham and Women's Hospital through the process of developing and applying novel algorithms for capturing intraoperative deformations in support of image guided therapy.