Patient-Specific Finite Element Modeling of the Whole Lumbar Spine Using Clinical Routine Multi-Detector Computed Tomography (MDCT) Data—A Pilot Study

Author:

Rayudu Nithin Manohar,Subburaj Karupppasamy,Mohan Rajesh ElaraORCID,Sollmann NicoORCID,Dieckmeyer MichaelORCID,Kirschke Jan S.ORCID,Baum ThomasORCID

Abstract

(1) Background: To study the feasibility of developing finite element (FE) models of the whole lumbar spine using clinical routine multi-detector computed tomography (MDCT) scans to predict failure load (FL) and range of motion (ROM) parameters. (2) Methods: MDCT scans of 12 subjects (6 healthy controls (HC), mean age ± standard deviation (SD): 62.16 ± 10.24 years, and 6 osteoporotic patients (OP), mean age ± SD: 65.83 ± 11.19 years) were included in the current study. Comprehensive FE models of the lumbar spine (5 vertebrae + 4 intervertebral discs (IVDs) + ligaments) were generated (L1–L5) and simulated. The coefficients of correlation (ρ) were calculated to investigate the relationship between FE-based FL and ROM parameters and bone mineral density (BMD) values of L1–L3 derived from MDCT (BMDQCT-L1-3). Finally, Mann–Whitney U tests were performed to analyze differences in FL and ROM parameters between HC and OP cohorts. (3) Results: Mean FE-based FL value of the HC cohort was significantly higher than that of the OP cohort (1471.50 ± 275.69 N (HC) vs. 763.33 ± 166.70 N (OP), p < 0.01). A strong correlation of 0.8 (p < 0.01) was observed between FE-based FL and BMDQCT-L1-L3 values. However, no significant differences were observed between ROM parameters of HC and OP cohorts (p = 0.69 for flexion; p = 0.69 for extension; p = 0.47 for lateral bending; p = 0.13 for twisting). In addition, no statistically significant correlations were observed between ROM parameters and BMDQCT- L1-3. (4) Conclusions: Clinical routine MDCT data can be used for patient-specific FE modeling of the whole lumbar spine. ROM parameters do not seem to be significantly altered between HC and OP. In contrast, FE-derived FL may help identify patients with increased osteoporotic fracture risk in the future.

Funder

Deutsche Forschungsgemeinschaft

SGP Healthcare Fund

Publisher

MDPI AG

Subject

General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

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