Three-Dimensionally Printed Surgical Simulation Tool for Brain Mapping Training and Preoperative Planning.
3D printing
Awake craniotomy
Brain mapping
Neurophysiologic monitoring
Surgical simulation
Journal
Operative neurosurgery (Hagerstown, Md.)
ISSN: 2332-4260
Titre abrégé: Oper Neurosurg (Hagerstown)
Pays: United States
ID NLM: 101635417
Informations de publication
Date de publication:
15 11 2021
15 11 2021
Historique:
received:
08
04
2021
accepted:
18
07
2021
pubmed:
26
9
2021
medline:
11
3
2022
entrez:
25
9
2021
Statut:
ppublish
Résumé
Brain mapping is the most reliable intraoperative tool for identifying surrounding functional cortical and subcortical brain parenchyma. Brain mapping procedures are nuanced and require a multidisciplinary team and a well-trained neurosurgeon. Current training methodology involves real-time observation and operation, without widely available surgical simulation. To develop a patient-specific, anatomically accurate, and electrically responsive biomimetic 3D-printed model for simulating brain mapping. Imaging data were converted into a 2-piece inverse 3D-rendered polyvinyl acetate shell forming an anatomically accurate brain mold. Functional and diffusion tensor imaging data were used to guide wire placement to approximate the projection fibers from the arm and leg areas in the motor homunculus. Electrical parameters were generated, and data were collected and processed to differentiate between the 2 tracts. For validation, the relationship between the electrical signal and the distance between the probe and the tract was quantified. Neurosurgeons and trainees were interviewed to assess the validity of the model. Material testing of the brain component showed an elasticity modulus of 55 kPa (compared to 140 kPa of cadaveric brain), closely resembling the tactile feedback a live brain. The simulator's electrical properties approximated that of a live brain with a voltage-to-distance correlation coefficient of r2 = 0.86. Following 32 neurosurgeon interviews, ∼96% considered the model to be useful for training. The realistic neural properties of the simulator greatly improve representation of a live surgical environment. This proof-of-concept model can be further developed to contain more complicated tractography, blood and cerebrospinal fluid circulation, and more in-depth feedback mechanisms.
Sections du résumé
BACKGROUND
Brain mapping is the most reliable intraoperative tool for identifying surrounding functional cortical and subcortical brain parenchyma. Brain mapping procedures are nuanced and require a multidisciplinary team and a well-trained neurosurgeon. Current training methodology involves real-time observation and operation, without widely available surgical simulation.
OBJECTIVE
To develop a patient-specific, anatomically accurate, and electrically responsive biomimetic 3D-printed model for simulating brain mapping.
METHODS
Imaging data were converted into a 2-piece inverse 3D-rendered polyvinyl acetate shell forming an anatomically accurate brain mold. Functional and diffusion tensor imaging data were used to guide wire placement to approximate the projection fibers from the arm and leg areas in the motor homunculus. Electrical parameters were generated, and data were collected and processed to differentiate between the 2 tracts. For validation, the relationship between the electrical signal and the distance between the probe and the tract was quantified. Neurosurgeons and trainees were interviewed to assess the validity of the model.
RESULTS
Material testing of the brain component showed an elasticity modulus of 55 kPa (compared to 140 kPa of cadaveric brain), closely resembling the tactile feedback a live brain. The simulator's electrical properties approximated that of a live brain with a voltage-to-distance correlation coefficient of r2 = 0.86. Following 32 neurosurgeon interviews, ∼96% considered the model to be useful for training.
CONCLUSION
The realistic neural properties of the simulator greatly improve representation of a live surgical environment. This proof-of-concept model can be further developed to contain more complicated tractography, blood and cerebrospinal fluid circulation, and more in-depth feedback mechanisms.
Identifiants
pubmed: 34561704
pii: 6375128
doi: 10.1093/ons/opab331
pmc: PMC8637789
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
523-532Subventions
Organisme : NCI NIH HHS
ID : P30 CA015083
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA216855
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1 TR002378
Pays : United States
Organisme : NIH HHS
ID : R43CA221490
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
© Congress of Neurological Surgeons 2021.
Références
J Biomech. 1970 Mar;3(2):211-21
pubmed: 5521539
Clin Neurophysiol. 2019 Aug;130(8):1320-1328
pubmed: 31185363
Int J Med Robot. 2018 Aug;14(4):e1914
pubmed: 29708640
Neurosurgery. 2020 Aug 1;87(2):E207
pubmed: 32335679
Curr Neurol Neurosci Rep. 2015;15(2):517
pubmed: 25467408
Acta Neurochir (Wien). 2020 Jul;162(7):1709-1720
pubmed: 32388682
Neuroimage. 2008 Jan 1;39(1):231-7
pubmed: 17913514
J Neurosurg. 2019 Jul 5;:1-8
pubmed: 31277069
J Neurosurg. 2003 Aug;99(2):311-8
pubmed: 12924706
Neurocrit Care. 2020 Jun;32(3):894-898
pubmed: 31332627
Int J Surg. 2012;10(8):393-8
pubmed: 22609475
Clin Anat. 2020 Sep;33(6):823-832
pubmed: 31749198
Neurosurg Clin N Am. 2004 Oct;15(4):537-47
pubmed: 15450888
Magn Reson Imaging. 2012 Nov;30(9):1323-41
pubmed: 22770690
Neurosurgery. 2005 Apr;56(2 Suppl):E439; discussion E439
pubmed: 15794843
J Neurooncol. 2020 Jul;148(3):587-598
pubmed: 32524393
World Neurosurg. 2021 Feb;146:64-74
pubmed: 33229311
Neurosurgery. 2017 Sep 1;81(3):481-489
pubmed: 28327900
J Mech Behav Biomed Mater. 2015 Jun;46:318-30
pubmed: 25819199
Cureus. 2020 Feb 23;12(2):e7081
pubmed: 32226682
Handb Clin Neurol. 2016;134:201-18
pubmed: 26948356
J Neurosurg. 2018 Jun;128(6):1865-1872
pubmed: 28862541
Acad Emerg Med. 2005 Aug;12(8):782-5
pubmed: 16079434
Front Psychol. 2019 Oct 25;10:2396
pubmed: 31708836
Clin Neurophysiol. 2020 Apr;131(4):828-835
pubmed: 32066101
Oper Neurosurg (Hagerstown). 2018 Dec 1;15(suppl_1):S1-S9
pubmed: 30260422
J Biomech. 1970 Jul;3(4):453-8
pubmed: 5000415
Turk J Obstet Gynecol. 2019 Mar;16(1):72-75
pubmed: 31019843
World Neurosurg. 2020 Aug;140:173-179
pubmed: 32360916
Neurosurg Focus. 2020 Mar 1;48(3):E18
pubmed: 32114554
J Surg Educ. 2011 Sep-Oct;68(5):421-7
pubmed: 21821224
Cortex. 2012 Jan;48(1):7-14
pubmed: 20510407
J Neurol Surg A Cent Eur Neurosurg. 2018 May;79(3):239-246
pubmed: 29346829
Clin Anat. 2020 Apr;33(3):428-430
pubmed: 31885101
Neurosurg Clin N Am. 2021 Jan;32(1):1-8
pubmed: 33223018
World Neurosurg. 2020 Sep;141:260
pubmed: 32585378
Neurosurgery. 2004 Jan;54(1):113-7; discussion 118
pubmed: 14683547