Image-guided therapy and intraoperative MRI in neurosurgery

Three-dimensional printing and 3D slicer powerful tools in understanding and treating neurosurgical diseases

With the development of the 3D printing industry, clinicians can research 3D printing in preoperative planning, individualized implantable materials manufacturing, and biomedical tissue modeling. Although the increased applications of 3D printing in many surgical disciplines, numerous doctors do not have the specialized range of abilities to utilize this exciting and valuable innovation. Additionally, as the applications of 3D printing technology have increased within the medical field, so have the number of printable materials and 3D printers. Therefore, clinicians need to stay up-to-date on this emerging technology for benefit. However, 3D printing technology relies heavily on 3D design. 3D Slicer can transform medical images into digital models to prepare for 3D printing. Due to most doctors lacking the technical skills to use 3D design and modeling software, we introduced the 3D Slicer to solve this problem. Our goal is to review the history of 3D printing and medical applications in this review. In addition, we summarized 3D Slicer technologies in neurosurgery. We hope this article will enable many clinicians to leverage the power of 3D printing and 3D Slicer.

Intraoperative Magnetic Resonance Imaging in Intracranial Glioma Resection: A Single-Center, Retrospective Blinded Volumetric Study

BACKGROUND

Intraoperative magnetic resonance imaging (IoMRI) was devised to overcome brain shifts during craniotomies. Yet, the acceptance of IoMRI is limited.

OBJECTIVE

To evaluate impact of IoMRI on intracranial glioma resection outcome including overall patient survival.

METHODS

A retrospective review of records was performed on a cohort of 164 consecutive patients who underwent resection surgery for newly diagnosed intracranial gliomas either with or without IoMRI technology performed by 2 neurosurgeons in our center. Patient follow-up was at least 5 years. Extent of resection (EOR) was calculated using pre- and postoperative contrast-enhanced and T2-weighted MR-images. Adjusted analysis was performed to compare gross total resection (GTR), EOR, permanent surgery-associated neurologic deficit, and overall survival between the 2 groups.

RESULTS

Overall median EOR was 92.1%, and 97.45% with IoMRI use and 89.9% without IoMRI, with crude (unadjusted) P < 0.005. GTR was achieved in 49.3% of IoMRI cases, versus in only 21.4% of no-IoMRI cases, P < 0.001. GTR achieved was more with the use of IoMRI among gliomas located in both eloquent and noneloquent brain areas, P = 0.017 and <0.001, respectively. Permanent surgery-associated neurologic deficit was not (statistically) more significant with no-IoMRI, P = 0.284 (13.8% vs. 6.7%). In addition, the IoMRI group had better 5-year overall survival, P < 0.001.

CONCLUSION

This study shows that the use of IoMRI was associated with greater rates of EOR and GTR, and better overall 5-year survival in both eloquent brain areas located and non-eloquent brain areas located gliomas, with no increased risk of neurologic complication.

Surgical navigation in the open MRI

The introduction of MRI into neurosurgery has opened multiple avenues, but also introduced new challenges. The open-configuration intraoperative MRI installed at the Brigham and Women's Hospital in 1996 has been used for more than 500 open craniotomies and beyond 100 biopsies. Furthermore the versatile applicability, employing the same principles, is evident by its frequent use in other areas of the body. However, while intraoperative scanning in the SignaSP yielded unprecedented imaging during neurosurgical procedures their usage for navigation proved bulky and unhandy. To be fully integrated into the procedure, acquisition and display of intraoperative data have to be dynamic and primarily driven by the surgeon performing the procedure. To use the benefits of computer-assisted navigation systems together with immediate availability of intraoperative imaging we developed a software package. This "3D Slicer" has been used routinely for biopsies and open craniotomies. The system is stable and reliable. Pre- and intraoperative data can be visualized to plan and perform surgery, as well as to accommodate for intraoperative deformations, "brain shift", by providing online data acquisition.

Non-rigid Registration of Serial Intra-operative Images for Automatic Brain Shift Estimation

Measurement of intra-operative brain motion is important to provide boundary conditions to physics-based deformation models that can be used to register pre- and intra-operative information. In this paper we present and test a technique that can be used to measure brain surface motion automatically. This method relies on a tracked laser range scanner (LRS) that can acquire simultaneously a picture and the 3D physical coordinates of objects within its field of view. This reduces the 3D tracking problem to a 2D non-rigid registration problem which we solve with a Mutual Information-based algorithm. Results obtained on images of a phantom and on images acquired intra-operatively that demonstrate the feasibility of the method are presented.

Cortical Shift Tracking Using a Laser Range Scanner and Deformable Registration Methods

A novel brain shift tracking protocol is introduced in this paper which utilizes laser range scan (LRS) data and 2D deformable image registration. This protocol builds on previous efforts to incorporate intra-operative LRS data into a model-updated image guided surgery paradigm for brain shift compensation. The shift tracking method employs the use of a LRS system capable of capturing textures of the intra-operative scene during range data acquisition. Textures from serial range images are then registered using a 2D deformable registration approach that uses local support radial basis functions and mutual information. Given the deformation field provided by the registration, 3D points in serial LRS datasets can then be tracked. Results from this paper indicate that the error associated with tracking brain movement is 1.1mm on average given brain shifts of approximately 20.5mm. Equally important, a strategy is presented to rapidly acquire intra-operative measurements of shift which are compatible with model-based strategies for brain deformation compensation.