Development of a CT-Compatible, Anthropomorphic Skull and Brain Phantom for Neurosurgical Planning, Training, and Simulation.

CT compatible phantom anthropomorphic phantom brain biopsy brain phantom endonasal skull-base surgery external ventricular drain neurosurgical simulation skull phantom

Journal

Bioengineering (Basel, Switzerland)
ISSN: 2306-5354
Titre abrégé: Bioengineering (Basel)
Pays: Switzerland
ID NLM: 101676056

Informations de publication

Date de publication:
09 Oct 2022
Historique:
received: 15 09 2022
revised: 04 10 2022
accepted: 08 10 2022
entrez: 27 10 2022
pubmed: 28 10 2022
medline: 28 10 2022
Statut: epublish

Résumé

Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations. The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements. The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom. A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost.

Sections du résumé

BACKGROUND BACKGROUND
Neurosurgical procedures are complex and require years of training and experience. Traditional training on human cadavers is expensive, requires facilities and planning, and raises ethical concerns. Therefore, the use of anthropomorphic phantoms could be an excellent substitute. The aim of the study was to design and develop a patient-specific 3D-skull and brain model with realistic CT-attenuation suitable for conventional and augmented reality (AR)-navigated neurosurgical simulations.
METHODS METHODS
The radiodensity of materials considered for the skull and brain phantoms were investigated using cone beam CT (CBCT) and compared to the radiodensities of the human skull and brain. The mechanical properties of the materials considered were tested in the laboratory and subsequently evaluated by clinically active neurosurgeons. Optimization of the phantom for the intended purposes was performed in a feedback cycle of tests and improvements.
RESULTS RESULTS
The skull, including a complete representation of the nasal cavity and skull base, was 3D printed using polylactic acid with calcium carbonate. The brain was cast using a mixture of water and coolant, with 4 wt% polyvinyl alcohol and 0.1 wt% barium sulfate, in a mold obtained from segmentation of CBCT and T1 weighted MR images from a cadaver. The experiments revealed that the radiodensities of the skull and brain phantoms were 547 and 38 Hounsfield units (HU), as compared to real skull bone and brain tissues with values of around 1300 and 30 HU, respectively. As for the mechanical properties testing, the brain phantom exhibited a similar elasticity to real brain tissue. The phantom was subsequently evaluated by neurosurgeons in simulations of endonasal skull-base surgery, brain biopsies, and external ventricular drain (EVD) placement and found to fulfill the requirements of a surgical phantom.
CONCLUSIONS CONCLUSIONS
A realistic and CT-compatible anthropomorphic head phantom was designed and successfully used for simulated augmented reality-led neurosurgical procedures. The anatomic details of the skull base and brain were realistically reproduced. This phantom can easily be manufactured and used for surgical training at a low cost.

Identifiants

pubmed: 36290503
pii: bioengineering9100537
doi: 10.3390/bioengineering9100537
pmc: PMC9598361
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : European Union's Horizon 2020 research and innovation program under the Marie Skłodow-ska-Curie grant agreement
ID : 721766

Références

Childs Nerv Syst. 2002 Dec;18(12):705-6
pubmed: 12483355
Phys Med Biol. 2013 Aug 21;58(16):5511-25
pubmed: 23880566
Eur Spine J. 2020 Aug;29(8):1823-1832
pubmed: 32591881
IEEE Trans Med Imaging. 2013 Jul;32(7):1215-26
pubmed: 23372078
3D Print Med. 2018;4(1):3
pubmed: 29782617
Clin Neurol Neurosurg. 2021 Jul;206:106719
pubmed: 34088541
Acta Neurochir (Wien). 2022 Apr;164(4):947-966
pubmed: 35122126
Sci Rep. 2017 May 17;7:44301
pubmed: 28513626
3D Print Med. 2021 Mar 23;7(1):9
pubmed: 33759067
Int J Med Robot. 2018 Apr;14(2):
pubmed: 29282850
Sci Rep. 2020 Apr 21;10(1):6767
pubmed: 32317726
Eur Arch Otorhinolaryngol. 2015 Mar;272(3):753-7
pubmed: 25294050
Sensors (Basel). 2022 Aug 14;22(16):
pubmed: 36015828
Sci Rep. 2021 Mar 26;11(1):7005
pubmed: 33772092
World Neurosurg. 2015 Mar;83(3):351-61
pubmed: 24141000
J Med Educ Curric Dev. 2022 Mar 7;9:23821205221080703
pubmed: 35280123
PLoS One. 2020 Jan 16;15(1):e0227312
pubmed: 31945082
Pol J Radiol. 2017 Jul 25;82:398-409
pubmed: 28811848
World Neurosurg. 2018 Sep;117:e99-e105
pubmed: 29870846
Surg Oncol Clin N Am. 2000 Jan;9(1):61-79, vii
pubmed: 10601525
Med Image Anal. 2017 Dec;42:241-256
pubmed: 28881251
Magn Reson Imaging. 2012 Nov;30(9):1323-41
pubmed: 22770690
Patient Educ Couns. 2019 Oct;102(10):1875-1881
pubmed: 31113688
J Neurosurg. 2014 Feb;120(2):489-92
pubmed: 24321044
Br J Neurosurg. 2014 Dec;28(6):707-12
pubmed: 24799274
Cancer. 2007 Dec 1;110(11):2457-67
pubmed: 17894390
3D Print Med. 2019 Aug 1;5(1):11
pubmed: 31372773
Ann Nucl Med. 2013 Jan;27(1):25-36
pubmed: 23011903
PLoS One. 2015 Sep 02;10(9):e0136370
pubmed: 26331717
J Digit Imaging. 2017 Aug;30(4):449-459
pubmed: 28577131
J Biomech. 2020 Jan 2;98:109380
pubmed: 31630775
Neurosurg Focus. 2021 Aug;51(2):E7
pubmed: 34333469
Radiology. 1977 Mar;122(3):699-702
pubmed: 841054
Surg Neurol Int. 2021 May 10;12:213
pubmed: 34084640
Ann Transl Med. 2020 Mar;8(6):370
pubmed: 32355814
J Neurosurg Pediatr. 2015 Jan;15(1):82-8
pubmed: 25360853
Eur Arch Otorhinolaryngol. 2017 Feb;274(2):1097-1102
pubmed: 27785571
World Neurosurg. 2020 Jun;138:285-290
pubmed: 32200018

Auteurs

Marco Lai (M)

Philips Research, High Tech Campus 34, 5656 Eindhoven, The Netherlands.
Department of Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands.

Simon Skyrman (S)

Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.
Department of Neurosurgery, Karolinska University Hospital, 17164 Stockholm, Sweden.

Flip Kor (F)

Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands.

Robert Homan (R)

Philips Healthcare, 5684 Best, The Netherlands.

Victor Gabriel El-Hajj (VG)

Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.
Department of Neurosurgery, Karolinska University Hospital, 17164 Stockholm, Sweden.

Drazenko Babic (D)

Philips Research, High Tech Campus 34, 5656 Eindhoven, The Netherlands.

Erik Edström (E)

Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.
Department of Neurosurgery, Karolinska University Hospital, 17164 Stockholm, Sweden.

Adrian Elmi-Terander (A)

Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden.
Department of Neurosurgery, Karolinska University Hospital, 17164 Stockholm, Sweden.

Benno H W Hendriks (BHW)

Philips Research, High Tech Campus 34, 5656 Eindhoven, The Netherlands.
Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands.

Peter H N de With (PHN)

Department of Engineering, Eindhoven University of Technology (TU/e), 5612 Eindhoven, The Netherlands.

Classifications MeSH