J Neurol Surg B Skull Base 2020; 81(S 01): S1-S272
DOI: 10.1055/s-0040-1702388
Oral Presentations
Georg Thieme Verlag KG Stuttgart · New York

3D Tractography in Skull Base Surgery: Technological Advances and Feasibility-Initial Experience

Srikant S. Chakravarthi
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Melanie B. Fukui
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Alejandro Monroy-Sosa
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Jonathan E. Jennings
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Austin Epping
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Sammy Khalili
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Lior Gonen
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Juanita M. Celix
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Bhavani Kura
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Nathaniel Kojis
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Richard A. Rovin
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
,
Amin B. Kassam
1   Aurora Neuroscience Innovation Institute, Milwaukee, Wisconsin, United States
› Author Affiliations
Further Information

Publication History

Publication Date:
05 February 2020 (online)

 

Background: Despite neural anatomy being one of the primary drivers of corridor selection in skull base surgery, 3D tractography has not previously been incorporated into routine image guidance for skull base surgery due to numerous obstacles.

Objective: The aim of the study is to determine the feasibility of incorporating automated generation of 3D white matter tractography into the routine skull base surgery planning and corridor selection using an integrated planning and navigation solution.

Methods: 100 skull base endonasal and transcranial procedures were planned in 94 patients and retrospectively reviewed. The main outcome measures were the following: (1) Ability to automate generation of 3D tractography; (2) Ability to co-register 3D tractography with CT and CTA in addition to structural MRI; (3) Accuracy of co-registration of 3D tractography to structural imaging (CT, CTA, and MRI); and (4) Ability to demonstrate real-time manipulation of 3D tractography intraoperatively for sequential reassessment of depth of resection and proximity to critical neural structures.

Results: The integrated planning software produced automated 3D tractography in all cases. In all cases, multiple imaging sequences were accurately merged to permit visualization of tractography overlaid on MRI, CT, and CTA during surgical planning and navigation. The registration of MRI, CT bone algorithm, and CTA images using an overlay tool was judged to be accurate in all cases. The geometric fit of 3D tractography was judged to be within 0.25 mm in all cases. In all cases, the full 3D tractography dataset was available for use during intraoperative navigation.

Conclusion: This initial series of 100 cases has established the feasibility of incorporating 3D tractography into the skull base surgical armamentarium.