STUDY DESIGN: Algorithm development for the automatic finite element modeling of patient vertebra. OBJECTIVE: To present a technique for automatic generation of patient specific computational fluid dynamics (CFD) models for intraosseous PMMA cement flow simulation. The secondary objective is to demonstrate the possibility of using resultant PMMA cement distribution for post-PVP stress-strain analyses. SUMMARY OF BACKGROUND DATA: There are no noninvasive methods for the visualization of PMMA cement flow. In addition, optimum volume and distribution of PMMA cement are still not known. Computational models that allow patient specific intraosseous PMMA cement flow visualization as well as postvertebroplasty mechanical evaluation would be advantageous. METHODS: We developed an algorithm coded into a custom platform that inputs patient CT datasets. Hounsfield unit values were used to assign permeability values as well as modulus to the finite element model before analyses. Several user inputs are required, and these reflect the decisions made by physicians that practice vertebroplasty. As a case study, we isolated a single L1 vertebra from patient CT dataset and used our platform for model generation. Simulated vertebroplasty was performed for different PMMA cement volumes and at different placements to study the effects of varying distribution. RESULTS: Increased needle injection pressure was observed as the volume of PMMA increases and as the distribution of PMMA is in close proximity to the cortical walls. Stiffness of augmented vertebral body also increases with increased volume of PMMA administered. Varying distributions, for the same volume, of PMMA cement did not alter stiffness drastically. CONCLUSION: Our custom platform and technique for modeling vertebral bodies may contribute significantly to the science of vertebroplasty. Intraosseous PMMA cement flow can be visualized before vertebroplasty, and needle position altered for optimization. Also, parametric computational studies on the postvertebroplasty biomechanical effects of vertebroplasty are now enhanced with such a modeling capability.
STUDY DESIGN: Algorithm development for the automatic finite element modeling of patient vertebra. OBJECTIVE: To present a technique for automatic generation of patient specific computational fluid dynamics (CFD) models for intraosseous PMMA cement flow simulation. The secondary objective is to demonstrate the possibility of using resultant PMMA cement distribution for post-PVP stress-strain analyses. SUMMARY OF BACKGROUND DATA: There are no noninvasive methods for the visualization of PMMA cement flow. In addition, optimum volume and distribution of PMMA cement are still not known. Computational models that allow patient specific intraosseous PMMA cement flow visualization as well as postvertebroplasty mechanical evaluation would be advantageous. METHODS: We developed an algorithm coded into a custom platform that inputs patient CT datasets. Hounsfield unit values were used to assign permeability values as well as modulus to the finite element model before analyses. Several user inputs are required, and these reflect the decisions made by physicians that practice vertebroplasty. As a case study, we isolated a single L1 vertebra from patient CT dataset and used our platform for model generation. Simulated vertebroplasty was performed for different PMMA cement volumes and at different placements to study the effects of varying distribution. RESULTS: Increased needle injection pressure was observed as the volume of PMMA increases and as the distribution of PMMA is in close proximity to the cortical walls. Stiffness of augmented vertebral body also increases with increased volume of PMMA administered. Varying distributions, for the same volume, of PMMA cement did not alter stiffness drastically. CONCLUSION: Our custom platform and technique for modeling vertebral bodies may contribute significantly to the science of vertebroplasty. Intraosseous PMMA cement flow can be visualized before vertebroplasty, and needle position altered for optimization. Also, parametric computational studies on the postvertebroplasty biomechanical effects of vertebroplasty are now enhanced with such a modeling capability.
Authors: Abdul Hakim Md Yusop; Nurizzati Mohd Daud; Hadi Nur; Mohammed Rafiq Abdul Kadir; Hendra Hermawan Journal: Sci Rep Date: 2015-06-09 Impact factor: 4.379
Authors: Sami M Tarsuslugil; Rochelle M O'Hara; Nicholas J Dunne; Fraser J Buchanan; John F Orr; David C Barton; Ruth K Wilcox Journal: Ann Biomed Eng Date: 2014-01-07 Impact factor: 3.934
Authors: Hossein Ahmadian; Prasath Mageswaran; Benjamin A Walter; Dukagjin M Blakaj; Eric C Bourekas; Ehud Mendel; William S Marras; Soheil Soghrati Journal: Int J Numer Method Biomed Eng Date: 2022-04-07 Impact factor: 2.648