Systematic review and meta-analysis of the biomechanical properties of the human dura mater applicable in computational human head models.
Biomech Model Mechanobiol
; 21(3): 755-770, 2022 Jun.
Article
in En
| MEDLINE
| ID: mdl-35266061
ABSTRACT
Accurate biomechanical properties of the human dura mater are required for computational models and to fabricate artificial substitutes for transplantation and surgical training purposes. Here, a systematic literature review was performed to summarize the biomechanical properties of the human dura mater that are reported in the literature. Furthermore, anthropometric data, information regarding the mechanically tested samples, and specifications with respect to the used mechanical testing setup were extracted. A meta-analysis was performed to obtain the pooled mean estimate for the elastic modulus, ultimate tensile strength, and strain at maximum force. A total of 17 studies were deemed eligible, which focused on human cranial and spinal dura mater in 13 and 4 cases, respectively. Pooled mean estimates for the elastic modulus (n = 448), the ultimate tensile strength (n = 448), and the strain at maximum force (n = 431) of 68.1 MPa, 7.3 MPa and 14.4% were observed for native cranial dura mater. Gaps in the literature related to the extracted data were identified and future directions for mechanical characterizations of human dura mater were formulated. The main conclusion is that the most commonly used elastic modulus value of 31.5 MPa for the simulation of the human cranial dura mater in computational head models is likely an underestimation and an oversimplification given the morphological diversity of the tissue in different brain regions. Based on the here provided meta-analysis, a stiffer linear elastic modulus of 68 MPa was observed instead. However, further experimental data are essential to confirm its validity.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Dura Mater
/
Mechanical Phenomena
Type of study:
Systematic_reviews
Limits:
Humans
Language:
En
Journal:
Biomech Model Mechanobiol
Journal subject:
ENGENHARIA BIOMEDICA
Year:
2022
Document type:
Article
Affiliation country:
New Zealand