Toward a Multimodal Diagnostic Exploratory Visualization of Focal Cortical Dysplasia

Interactive mining of neural pathways to preoperative neurosurgical planning

BACKGROUND AND OBJECTIVE

Preoperative understanding of white matter anatomy, including its spatial relationship with pathology and superficial landmarks, is vital for effective surgical planning. The ability to interactively synthesize neural pathways from diffusion data and dynamically discern neuroanatomy-referenced fiber patterns enables neurosurgeons to construct detailed mental models of the patient's brain and assess surgical risks. We present a novel interactive software designed for real-time mining of neural pathways from diffusion-weighted magnetic resonance imaging (DW-MRI) data. This software leverages a user-guided approach, integrating curvilinear reformatting and surgeon expertise with diffusion tensor imaging (DTI) data, and employs a finite-state machine interaction model to facilitate intuitive use through a windows, icons, menus, and pointers (WIMP) interface.

METHODS

The proposed system merges user analytical skills with neuroanatomy-referenced DTI data, including scalar maps, tensor glyphs, and streamlines, within a visually interactive environment. Key features of the system include optimized GPU-based rendering for enhanced graphical representation and the proposed finite-state machine model that enables seamless interaction through intuitive controls. This approach allows for real-time manipulation of DTI data and dynamic generation of depth maps for each frame, facilitating practical exploration and analysis.

RESULTS

After testing seven control volumes, our system demonstrates tract reconstruction capabilities comparable to MRTrix software's. The evaluation of GPU-based fiber tracking and rendering performance, using NVIDIA Nsight Visual Studio Edition, confirms the system's interactive responsiveness. Preliminary results indicate that the environment effectively extracts critical fibers and evaluates their spatial relationships with surgical targets and landmarks. This functionality provides valuable insights for refining preoperative planning, optimizing surgical approaches, and minimizing potential functional damage.

CONCLUSION

Our WIMP-based interactive environment empowers surgeons with enhanced capabilities for real-time manipulation of neuroanatomy-referenced DTI data. Integrating curvilinear reformatting and finite-state machine interaction enhances user experience significantly, making it a valuable tool for improving surgical safety and precision. This low-cost, accessible approach has the potential to facilitate minimally invasive procedures, accurate landmark identification, and reduced functional damage, particularly in resource-limited settings.

Accurate Image-guided (Re)Placement of NIRS Probes

BACKGROUND AND OBJECTIVE

Functional near-infrared spectroscopy (fNIRS) has become an attractive choice to neuroscience because of its high temporal resolution, ease of use, non-invasiveness, and affordability. With the advent of wearable fNIRS technology, on-the-spot studies of brain function have become viable. However, the lack of within-subject reproducibility is one of the barriers to the full acceptability of fNIRS. To support the validation of the claim that within-subject reproducibility of fNIRS could benefit from accurate anatomical information, we present in this paper a method to develop an image-based system that improves the placement of the sensors on the scalp at interactive rates.

METHODS

The proposed solution consists of an electromagnetic digitizer and an interactive visualization system that allows monitoring the movements of the digitizer on a real head with respect to the underlying cerebral cortical structures. GPU-based volume raycasting rendering is applied to unveil these structures from the corresponding magnetic resonance imaging volume. Scalp and cortical surface are estimated from the scanned volume to improve depth perception. An alignment algorithm between the real and scanned heads is devised to visually feedback the position of the stylus of the digitizer. Off-screen rendering of the depthmaps of the visible surfaces makes spatial positioning of a 2D interaction pointer possible.

RESULTS

We evaluated the alignment accuracy using four to eight anatomical landmarks and found seven to be a good compromise between precision and efficiency. Next, we evaluated reproducibility in positioning five arbitrarily chosen points on three volunteers by four operators over five sessions. In every session, seven anatomical landmarks were applied in the alignment of the real and the scanned head. For the same volunteer, one-way analysis of variance (ANOVA) revealed no significant differences within the five points digitized by the same operator over five sessions (α = 0.05). In addition, preliminary study of motor cortex activation by right-hand finger tapping showed the potential of our approach to increase functional fNIRS reproducibility.

CONCLUSIONS

Results of experiments suggest that the enhancement of the visualization of the location of the probes on the scalp, relative to the underlying cortical structures, improves reproducibility of fNIRS measurements. As further work, we plan to study the fNIRS reproducibility in other cortical regions and in clinical settings using the proposed system.