SlicerCBM: automatic framework for biomechanical analysis of the brain.
Biomechanics
Brain deformation
Brain shift
Framework
Journal
International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225
Informations de publication
Date de publication:
Oct 2023
Oct 2023
Historique:
received:
29
09
2022
accepted:
17
03
2023
medline:
13
9
2023
pubmed:
3
4
2023
entrez:
2
4
2023
Statut:
ppublish
Résumé
Brain shift that occurs during neurosurgery disturbs the brain's anatomy. Prediction of the brain shift is essential for accurate localisation of the surgical target. Biomechanical models have been envisaged as a possible tool for such predictions. In this study, we created a framework to automate the workflow for predicting intra-operative brain deformations. We created our framework by uniquely combining our meshless total Lagrangian explicit dynamics (MTLED) algorithm for computing soft tissue deformations, open-source software libraries and built-in functions within 3D Slicer, an open-source software package widely used for medical research. Our framework generates the biomechanical brain model from the pre-operative MRI, computes brain deformation using MTLED and outputs results in the form of predicted warped intra-operative MRI. Our framework is used to solve three different neurosurgical brain shift scenarios: craniotomy, tumour resection and electrode placement. We evaluated our framework using nine patients. The average time to construct a patient-specific brain biomechanical model was 3 min, and that to compute deformations ranged from 13 to 23 min. We performed a qualitative evaluation by comparing our predicted intra-operative MRI with the actual intra-operative MRI. For quantitative evaluation, we computed Hausdorff distances between predicted and actual intra-operative ventricle surfaces. For patients with craniotomy and tumour resection, approximately 95% of the nodes on the ventricle surfaces are within two times the original in-plane resolution of the actual surface determined from the intra-operative MRI. Our framework provides a broader application of existing solution methods not only in research but also in clinics. We successfully demonstrated the application of our framework by predicting intra-operative deformations in nine patients undergoing neurosurgical procedures.
Identifiants
pubmed: 37004646
doi: 10.1007/s11548-023-02881-7
pii: 10.1007/s11548-023-02881-7
pmc: PMC10497672
mid: NIHMS1897519
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1925-1940Subventions
Organisme : NIBIB NIH HHS
ID : P41EB028741
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB027134
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB032387
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA235589
Pays : United States
Organisme : NIBIB NIH HHS
ID : P41 EB028741
Pays : United States
Organisme : NIBIB NIH HHS
ID : P41 EB015902
Pays : United States
Informations de copyright
© 2023. The Author(s).
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