Automated objective surgical planning for lateral skull base tumors.
PURPOSE: Surgical removal of pathology at the lateral skull base is challenging because of the proximity of critical anatomical structures which can lead to significant morbidity when damaged or traversed. Pre-operative computed surgical approach planning has the potential to aid in selection of the optimal approach to remove pathology and minimize complications. METHODS: We propose an automated surgical approach planning algorithm to derive the optimal approach to vestibular schwannomas in the internal auditory canal for hearing preservation surgery. The algorithm selects between the middle cranial fossa and retrosigmoid approach by utilizing a unique segmentation of each patient's anatomy and a cost function to minimize potential surgical morbidity. RESULTS: Patients who underwent hearing preservation surgery for vestibular schwannoma resection (n = 9) were included in the cohort. Middle cranial fossa surgery was performed in 5 patients, and retrosigmoid surgery was performed in 4. The algorithm favored the performed surgical approach in 6 of 9 patients. CONCLUSION: We developed a method for computing morbidity costs of surgical paths to objectively analyze surgical approaches at the lateral skull base. Computed pre-operative planning may assist in surgical decision making, trainee education, and improving clinical outcomes.
Duke Scholars
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Related Subject Headings
- Skull Base Neoplasms
- Skull Base
- Retrospective Studies
- Postoperative Complications
- Nuclear Medicine & Medical Imaging
- Neuroma, Acoustic
- Humans
- Ear, Inner
- 4603 Computer vision and multimedia computation
- 3202 Clinical sciences
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- Skull Base Neoplasms
- Skull Base
- Retrospective Studies
- Postoperative Complications
- Nuclear Medicine & Medical Imaging
- Neuroma, Acoustic
- Humans
- Ear, Inner
- 4603 Computer vision and multimedia computation
- 3202 Clinical sciences