Robotic surgical rehearsal on patient-specific 3D-printed skull models for stereoelectroencephalography (SEEG)

AbstractPurposeMedically refractory epilepsy patients commonly require surgical alternatives for diagnosis and treatment. Stereoelectroencephalography (SEEG) is a useful diagnostic procedure in seizure focus elucidation. Modern techniques involve the use of robotics and neuronavigation for SEEG. A steep learning curve combined with multiple complex technologies employed during the case makes this procedure a perfect candidate for surgical rehearsal. This paper tests the feasibility of the use of patient-specific 3D-printed model for surgical rehearsal of robotic SEEG. MethodsA 3D-printed model was created using the patient’s cranial computed tomography and computed tomography angiography radiological imaging. A rehearsal in an operating room (OR) prior to the actual procedure date was used for surgical planning of SEEG electrodes, education of the residents and fellows as well as training of the support staff. Attention was paid to assure precise recreation of the surgical procedure.ResultsThe patient-specific 3D-printed model tolerated each step of the procedure from facial registration, to drilling, bolt insertion and lead placement. Accuracy of the designed trajectory to the electrode final position was visually confirmed at the end of procedure. Important modification to the plan of eventual surgery improved the efficiency of the real operation.ConclusionFor surgical planning, education and training purposes in robotic SEEG, 3D-printed models may be utilized as a realistic anatomy tool. Potential applications of this technique include trajectory feasibility evaluation, patient positioning optimization, increasing OR efficiency, as well as neurosurgical education and patient counseling.

[1]  K. Krishnan,et al.  The Application of Rapid Prototyping Techniques in Cranial Reconstruction and Preoperative Planning in Neurosurgery , 2003, The Journal of craniofacial surgery.

[2]  Jean Ciurea,et al.  A Personalized Stereotactic Fixture for Implantation of Depth Electrodes in Stereoelectroencephalography , 2014, Stereotactic and Functional Neurosurgery.

[3]  Vairavan Narayanan,et al.  Endoscopic skull base training using 3D printed models with pre-existing pathology , 2014, European Archives of Oto-Rhino-Laryngology.

[4]  J. Knott,et al.  Characteristics of electrical activity of human corpus striatum and neighboring structures. , 1949, Journal of neurophysiology.

[5]  J. Pisapia,et al.  3D printing in neurosurgery: A systematic review , 2016, Surgical neurology international.

[6]  W J Earwaker,et al.  Cerebrovascular biomodelling: a technical note. , 1999, Surgical neurology.

[7]  N. Kaneko,et al.  Microcatheter Shaping for Intracranial Aneurysm Coiling Using the 3-Dimensional Printing Rapid Prototyping Technology: Preliminary Result in the First 10 Consecutive Cases. , 2015, World neurosurgery.

[8]  Felix Rosenow,et al.  The history of invasive EEG evaluation in epilepsy patients , 2016, Seizure.

[9]  Sanju Lama,et al.  Robotics in the neurosurgical treatment of glioma , 2015, Surgical neurology international.

[10]  Tipu Aziz,et al.  Utility of multimaterial 3D printers in creating models with pathological entities to enhance the training experience of neurosurgeons. , 2014, Journal of neurosurgery.

[11]  A. Demetriades,et al.  3D printing of patient-specific anatomy: A tool to improve patient consent and enhance imaging interpretation by trainees , 2015, British journal of neurosurgery.

[12]  Yan Wang,et al.  Clinical application of computer-designed polystyrene models in complex severe spinal deformities: a pilot study , 2010, European Spine Journal.

[13]  Alejandro F. Frangi,et al.  Muliscale Vessel Enhancement Filtering , 1998, MICCAI.

[14]  Kevin Phan,et al.  The utility of 3D printing for surgical planning and patient-specific implant design for complex spinal pathologies: case report. , 2017, Journal of neurosurgery. Spine.

[15]  Francesco Cardinale,et al.  Implantation of Stereoelectroencephalography Electrodes: A Systematic Review , 2016, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[16]  Gabriel Taubin,et al.  Curve and surface smoothing without shrinkage , 1995, Proceedings of IEEE International Conference on Computer Vision.

[17]  P. Camarata,et al.  Individualized Surgical Approach Planning for Petroclival Tumors Using a 3D Printer , 2015, Journal of Neurological Surgery—Part B.

[18]  Juan Bulacio,et al.  Technique, Results, and Complications Related to Robot-Assisted Stereoelectroencephalography. , 2016, Neurosurgery.

[19]  Clayton J. Adam,et al.  The use of physical biomodelling in complex spinal surgery , 2007, European Spine Journal.

[20]  Frederik L. Giesel,et al.  3D printing based on imaging data: review of medical applications , 2010, International Journal of Computer Assisted Radiology and Surgery.

[21]  Kojiro Matsushita,et al.  Patient-Specific Cortical Electrodes for Sulcal and Gyral Implantation , 2015, IEEE Transactions on Biomedical Engineering.

[22]  Ahmed El-Henawy,et al.  A comparative Analytical Studies onAcaciapolyacantha gum Samples collected from three different locations in Sudan , 2014 .

[23]  Rickichard Izzo,et al.  The Vascular Modeling Toolkit: A Python Library for the Analysis of Tubular Structures in Medical Images , 2018, J. Open Source Softw..

[24]  Omar Tanweer,et al.  The utility of a multimaterial 3D printed model for surgical planning of complex deformity of the skull base and craniovertebral junction. , 2016, Journal of neurosurgery.

[25]  Christian Bottomley,et al.  Estimation of the burden of active and life-time epilepsy: A meta-analytic approach , 2010, Epilepsia.

[26]  Ron D. Shippert A Study of Time-Dependent Operating Room Fees and How to save $100 000 by Using Time-Saving Products , 2005 .

[27]  B. Tomancok,et al.  Cerebrovascular stereolithographic biomodeling for aneurysm surgery. Technical note. , 2004, Journal of neurosurgery.

[28]  P. Kwan,et al.  Early identification of refractory epilepsy. , 2000, The New England journal of medicine.

[29]  Satrajit S. Ghosh,et al.  Evaluation of volume-based and surface-based brain image registration methods , 2010, NeuroImage.

[30]  D. Pritchard,et al.  What Contributes Most to High Health Care Costs? Health Care Spending in High Resource Patients. , 2016, Journal of managed care & specialty pharmacy.

[31]  Naoyuki Harada,et al.  A neurosurgical simulation of skull base tumors using a 3D printed rapid prototyping model containing mesh structures , 2016, Acta Neurochirurgica.