A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients. (7th April 2022)
- Record Type:
- Journal Article
- Title:
- A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients. (7th April 2022)
- Main Title:
- A digital twin for simulating the vertebroplasty procedure and its impact on mechanical stability of vertebra in cancer patients
- Authors:
- Ahmadian, Hossein
Mageswaran, Prasath
Walter, Benjamin A.
Blakaj, Dukagjin M.
Bourekas, Eric C.
Mendel, Ehud
Marras, William S.
Soghrati, Soheil - Abstract:
- Abstract: We present the application of ReconGAN, introduced in a previous study, for simulating the vertebroplasty (VP) operation and its impact on the fracture response of a vertebral body. ReconGAN consists of a Deep Convolutional Generative Adversarial Network (DCGAN) and a finite element based shape optimization algorithm to virtually reconstruct the trabecular bone microstructure. The VP procedure involves injecting shear‐thinning liquid bone cement through a needle in the trabecular region to reinforce a diseased or fractured vertebra. To simulate this treatment modality, computational fluid dynamics (CFD) is employed to predict the morphology of the injected cement within the bone microstructure. A power‐law equation is utilized to characterize the non‐Newtonian shear‐thinning behavior of the polymethyl methacrylate (PMMA) bone cement during injection simulations. The CFD model is coupled with the level‐set method to simulate the motion of the interface separating bone cement and bone marrow. After predicting the cement morphology, a data co‐registration algorithm is employed to transform the CFD model to a high‐fidelity continuum damage mechanics (CDM) finite element model of the augmented vertebra for predicting the fracture response. A feasibility study is presented to demonstrate the ability of this CFD‐CDM framework to investigate the effect of VP on the mechanical integrity of the vertebral body in a cancer patient with a lytic metastatic tumor. Abstract : AnAbstract: We present the application of ReconGAN, introduced in a previous study, for simulating the vertebroplasty (VP) operation and its impact on the fracture response of a vertebral body. ReconGAN consists of a Deep Convolutional Generative Adversarial Network (DCGAN) and a finite element based shape optimization algorithm to virtually reconstruct the trabecular bone microstructure. The VP procedure involves injecting shear‐thinning liquid bone cement through a needle in the trabecular region to reinforce a diseased or fractured vertebra. To simulate this treatment modality, computational fluid dynamics (CFD) is employed to predict the morphology of the injected cement within the bone microstructure. A power‐law equation is utilized to characterize the non‐Newtonian shear‐thinning behavior of the polymethyl methacrylate (PMMA) bone cement during injection simulations. The CFD model is coupled with the level‐set method to simulate the motion of the interface separating bone cement and bone marrow. After predicting the cement morphology, a data co‐registration algorithm is employed to transform the CFD model to a high‐fidelity continuum damage mechanics (CDM) finite element model of the augmented vertebra for predicting the fracture response. A feasibility study is presented to demonstrate the ability of this CFD‐CDM framework to investigate the effect of VP on the mechanical integrity of the vertebral body in a cancer patient with a lytic metastatic tumor. Abstract : An integrated computational framework is presented to simulate the vertebroplasty operation in spinal metastasis cancer patients with fractured vertebra and studying its impact on restoring the mechanical integrity of vertebra. The cement injection process is simulated in a realistic digital twin of vertebra using computational fluid dynamics to predict the cured cement morphology, followed by performing high fidelity finite element analysis to simulate the vertebral compression fracture. This predictive capability is employed to study the effect of various parameters such as the needle tip location, injection flow rate, and cement volume on the risk of cement leakage through pedicles, as well as the mechanical stability of the augmented vertebra. … (more)
- Is Part Of:
- International journal for numerical methods in biomedical engineering. Volume 38:Number 6(2022)
- Journal:
- International journal for numerical methods in biomedical engineering
- Issue:
- Volume 38:Number 6(2022)
- Issue Display:
- Volume 38, Issue 6 (2022)
- Year:
- 2022
- Volume:
- 38
- Issue:
- 6
- Issue Sort Value:
- 2022-0038-0006-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-04-07
- Subjects:
- computational fluid dynamics -- finite element method -- spinal metastasis -- vertebral fracture -- Vertebroplasty
Biomedical engineering -- Periodicals
Imaging systems in medicine -- Periodicals
Numerical analysis -- Periodicals
Engineering mathematics -- Periodicals
610.28 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2040-7947 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/cnm.3600 ↗
- Languages:
- English
- ISSNs:
- 2040-7939
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.403550
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21823.xml