Motion robust imaging for continuous intraoperative MRI

Robust nonrigid registration to capture brain shift from intraoperative MRI

We present a new algorithm to register 3-D preoperative magnetic resonance (MR) images to intraoperative MR images of the brain which have undergone brain shift. This algorithm relies on a robust estimation of the deformation from a sparse noisy set of measured displacements. We propose a new framework to compute the displacement field in an iterative process, allowing the solution to gradually move from an approximation formulation (minimizing the sum of a regularization term and a data error term) to an interpolation formulation (least square minimization of the data error term). An outlier rejection step is introduced in this gradual registration process using a weighted least trimmed squares approach, aiming at improving the robustness of the algorithm. We use a patient-specific model discretized with the finite element method in order to ensure a realistic mechanical behavior of the brain tissue. To meet the clinical time constraint, we parallelized the slowest step of the algorithm so that we can perform a full 3-D image registration in 35 s (including the image update time) on a heterogeneous cluster of 15 personal computers. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift of up to 14 mm. The results show a good ability to recover large displacements, and a limited decrease of accuracy near the tumor resection cavity.

Future perspectives for intraoperative MRI

MRI-guided neurosurgery not only represents a technical challenge but a transformation from conventional hand-eye coordination to interactive navigational operations. In the future, multimodality-based images will be merged into a single model, in which anatomy and pathologic changes are at once distinguished and integrated into the same intuitive framework. The long-term goals of improving surgical procedures and attendant outcomes, reducing costs, and achieving broad use can be achieved with a three-pronged approach: 1. Improving the presentation of preoperative and real-time intraoperative image information 2. Integrating imaging and treatment-related technology into therapy delivery systems 3. Testing the clinical utility of image guidance in surgery The recent focus in technology development is on improving our ability to understand and apply medical images and imaging systems. Areas of active research include image processing, model-based image analysis, model deformation, real-time registration, real-time 3D (so-called "four-dimensional") imaging, and the integration and presentation of image and sensing information in the operating room. Key elements of the technical matrix also include visualization and display platforms and related software for information and display, model-based image understanding, the use of computing clusters to speed computation (ie, algorithms with partitioned computation to optimize performance), and advanced devices and systems for 3D device tracking (navigation). Current clinical applications are successfully incorporating real-time and/or continuously up-dated image-based information for direct intra-operative visualization. In addition to using traditional imaging systems during surgery, we foresee optimized use of molecular marker technology, direct measures of tissue characterization (ie, optical measurements and/or imaging), and integration of the next generation of surgical and therapy devices (including image-guided robotic systems). Although we expect the primary clinical thrusts of MRI-guided therapy to remain in neurosurgery, with the possible addition of other areas like orthopedic, head, neck, and spine surgery, we also anticipate increased use of image-guided focal thermal ablative methods (eg, laser, RF, cryoablation, high-intensity focused ultrasound). By validating the effectiveness of MRI-guided therapy in specific clinical procedures while refining the technology that serves as its underpinning at the same time, we expect many neurosurgeons will eventually embrace MRI as their intraoperative imaging choice. Clearly, intraoperative MRI offers several palpable advantages. Most important among these are improved medical outcomes, shorter hospitalization, and better and faster procedures with fewer complications. Certain economic and practical barriers also impede the large-scale use of intraoperative MRI. Although there has been a concerted technical effort to increase the benefit/cost ratio by gathering more accurate information, designing more localized and less invasive treatment devices, and developing better methods to orient and position therapy end-effectors, further research is needed. Indeed, the drive to improve and upgrade technology is ongoing. Specifically, in the context of the real-time representation of the patient's anatomy, we have improved the quality and utility of the information presented to the surgeon, which, in turn, contributes to more successful surgical outcomes. We can also expect improvements in intraoperative imaging systems as well as increased use of nonimaging sensors and robotics to facilitate more widespread use of intraoperative MRI.

Future perspectives in intraoperative imaging

Of all the advances in imaging science in the past twenty years, none has had a greater impact than Magnetic Resonance Imaging. Since its introduction as a diagnostic tool in the mid-1980's, MRI has evolved into the premier neuroimaging modality, and with the addition of higher field magnets, we are able to achieve spatial resolution of such superb quality that even the most exquisite details of the brain anatomy can be visualized. With the implementation of intraoperative, neurosurgical MRI, we can not only monitor brain shifts and deformations; we can achieve intraoperative navigation using intraoperative image updates. In the future, intraoperative MRI can be used not only to localize, target, and resect brain tumors and other lesions but also to fully comprehend the surrounding cortical and white matter functional anatomy. In addition to the inclusion of new imaging methods such as diffusion tensor imaging, new therapeutic methods will be applied. Especially encouraging are the promising results in MRI-guided Focused Ultrasound Surgery, in which the non-invasive thermal ablation of tumors is monitored and controlled by MRI. With the clinical introduction of these advances, intraoperative MRI is changing the face of Neurosurgery today.

[Evaluation of three-dimensional contrast-enhanced MRA using differential rate k-space sampling (DRKS)]

The progress of three-dimensional (3D) magnetic resonance angiography used in combination with contrast medium (CE-MRA) has been remarkable. Currently, angiography aims at improvements in time resolution without sacrificing spatial resolution. We conducted a basic study of 3D differential rate k-space sampling (DRKS) in which the slice direction of the k-space is divided into two or more areas, the echo data near zero encoding is sampled by a higher time resolution than data in other areas, and reconstruction is done within a short time. This technique involved a problem in which ghost artifacts occur easily when the concentration of contrast medium changes extremely or when signal intensity changes suddenly. This is probably due to a difference in the time to sample data between the low- and high-frequency areas. When we used DRKS to grasp these characteristics, however, it was useful because it allowed reconstruction with an extremely high time resolution.