High-Quality Multimodal Volume Rendering for Preoperative Planning of Neurosurgical Interventions

Abstract

Surgical approaches tailored to an individual patient's anatomy and pathology have become standard in neurosurgery. Precise preoperative planning of these procedures, however, is necessary to achieve an optimal therapeutic effect. Therefore, multiple radiological imaging modalities are used prior to surgery to delineate the patient's anatomy, neurological function, and metabolic processes. Developing a three-dimensional perception of the surgical approach, however, is traditionally still done by mentally fusing multiple modalities. Concurrent 3D visualization of these datasets can, therefore, improve the planning process significantly. In this paper we introduce an application for planning of individual neurosurgical approaches with high-quality interactive multimodal volume rendering. The application consists of three main modules which allow to (1) plan the optimal skin incision and opening of the skull tailored to the underlying pathology; (2) visualize superficial brain anatomy, function and metabolism; and (3) plan the patient-specific approach for surgery of deep-seated lesions. The visualization is based on direct multi-volume raycasting on graphics hardware, where multiple volumes from different modalities can be displayed concurrently at interactive frame rates. Graphics memory limitations are avoided by performing raycasting on bricked volumes. For preprocessing tasks such as registration or segmentation, the visualization modules are integrated into a larger framework, thus supporting the entire workflow of preoperative planning.

Guiding Deep Brain Stimulation interventions by fusing multimodal uncertainty regions

“…Skull stripping. We implemented the skull stripping algorithm as presented by Beyer et al [4]. Although a complete segmentation would provide better results, we want to avoid the necessary user interaction.…”

“…Khlebnikov et al suggested a system to find optimal access paths by interpreting tumors as light sources and determining the cost-function based on light transport [15]. A visualization system for the pre-operative planning was provided by Beyer et al, who proposed a multi-volume renderer employing cut-away views to allow for visual access to the brain structures of interest [4]. Furthermore, they included a skull peeling algorithm, which we have also incorporated into our system.…”

Volume Visualization: A Technical Overview with a Focus on Medical Applications

“…As exemplified by Beyer et al, 181 who used GPU-based raycasting to display fused multimodal brain datasets in real time for preoperative planning of neurosurgical procedures, there is a trend toward using TF-based methods for anatomical feature enhancement, tissue separation, and obtaining complementary diagnostic information from different image modalities. In a GPU-based raycasting framework, Weber et al 182 segmented a volume into regions in the form of branches of a hierarchical contour tree, and created a unique TF for each of these regions.…”

“…Furthermore, to render large out-of-core datasets, Moloney et al 206 presented a volume bricking-based sort-first algorithm to balance parallelized data loading and frame-to-frame coherence. The bricked volume technique was also used by Beyer et al 181 to display multimodal volume using GPU raycasting. Similarly, Ljung 185 presented a multiresolution scheme to render large out-of-core CT human cadaver volumes using GPU raycasting, in which techniques such as load-on-demand data management and TF-based data reduction were employed.…”

Multimodal Visualization of DTI and fMRI Data Using Illustrative Methods

“…However, deriving these visualizations of high quality is a challenging task and an issue of ongoing research. Numerous such multimodal brain visualizations exist (such as [2,3]) , but (to our knowledge) no illustrative approaches have been employed so far. However, they appear to be quite suitable for this task, since the goal of these methods is to mimic hand-drawn sketches (as, e.g., in anatomy atlases) and discern important from unimportant information by emphasizing major features and neglecting irrelevant details.…”