Finite Element Analysis Helps Predict Spinal Fractures
|
By HospiMedica International staff writers Posted on 01 Jan 2020 |
|
Image: Finite analysis can help determine cervical bone strength (Photo courtesy of SUTD)
A new study introduces a novel vertebral strength assessment tool that can assist accurate prediction of osteoporotic vertebral fracture (OVF) risk.
Developed at the Singapore University of Technology and Design (SUTD) and Munich Technical University (TUM; Germany), the semi-automatic computational tool is designed to extract structural information, such as failure load, from radiological scans of patients using functional spinal units (FSUs). The calculated FSU predicted failure load was compared to the bone mineral density (BMD) values of the single central vertebra with experimentally measured failure load in order to assess finite element (FE) correlation.
To do so, the FSUs underwent clinical multi-detector computed tomography (MDCT), and BMD was then determined for the FSUs from the MDCT images of the central vertebrae. FE-predicted failure load was then calculated in the single central vertebra alone, and the entire FSUs. The results revealed that while BMD of the central vertebrae correlated significantly with experimentally measured failure load, the FE-predicted failure load of the central vertebra showed no significant correlation. However, FE-predicted failure load of the FSUs best predicted experimentally measured failure load. The study was published on December 10, 2019, in Spine.
“There is an urgent need to implement computational biomechanical analysis in the clinical scenario, since it is a powerful tool for non-invasive evaluation of bone strength,” said senior author Subburaj Karupppasamy, PhD, of the SUTD Medical Engineering and Design (MED) laboratory. “Accordingly, this work lays the foundation towards extracting valuable structural information from improved spine models, such as FSUs, in the diagnosis of osteoporosis and prediction of OVFs.”
Computational prediction of failure load through numerical simulation, known popularly as FE analysis, is a non-invasive tool for examination of the spine, which also provides a holistic quantitative evaluation of bone strength. As the spine consists of many different spinal segments, it is essential to include these all load-bearing segments when considering the structural strength of spine. FSUs have the advantage of mimicking the biomechanical requirements of the spine better than each isolated vertebral segment.
Related Links:
Singapore University of Technology and Design
Munich Technical University
Developed at the Singapore University of Technology and Design (SUTD) and Munich Technical University (TUM; Germany), the semi-automatic computational tool is designed to extract structural information, such as failure load, from radiological scans of patients using functional spinal units (FSUs). The calculated FSU predicted failure load was compared to the bone mineral density (BMD) values of the single central vertebra with experimentally measured failure load in order to assess finite element (FE) correlation.
To do so, the FSUs underwent clinical multi-detector computed tomography (MDCT), and BMD was then determined for the FSUs from the MDCT images of the central vertebrae. FE-predicted failure load was then calculated in the single central vertebra alone, and the entire FSUs. The results revealed that while BMD of the central vertebrae correlated significantly with experimentally measured failure load, the FE-predicted failure load of the central vertebra showed no significant correlation. However, FE-predicted failure load of the FSUs best predicted experimentally measured failure load. The study was published on December 10, 2019, in Spine.
“There is an urgent need to implement computational biomechanical analysis in the clinical scenario, since it is a powerful tool for non-invasive evaluation of bone strength,” said senior author Subburaj Karupppasamy, PhD, of the SUTD Medical Engineering and Design (MED) laboratory. “Accordingly, this work lays the foundation towards extracting valuable structural information from improved spine models, such as FSUs, in the diagnosis of osteoporosis and prediction of OVFs.”
Computational prediction of failure load through numerical simulation, known popularly as FE analysis, is a non-invasive tool for examination of the spine, which also provides a holistic quantitative evaluation of bone strength. As the spine consists of many different spinal segments, it is essential to include these all load-bearing segments when considering the structural strength of spine. FSUs have the advantage of mimicking the biomechanical requirements of the spine better than each isolated vertebral segment.
Related Links:
Singapore University of Technology and Design
Munich Technical University
Gold Member
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
New
Medical Adhesive
MED 5570U
New
Syringe Pump
SP50 Series
Latest AI News
- AI Analysis of Pericardial Fat Refines Long-Term Heart Disease Risk
- Machine Learning Approach Enhances Liver Cancer Risk Stratification
- New AI Approach Monitors Brain Health Using Passive Wearable Data
- AI Tool Maps Early Risk Patterns in Bloodstream Infections
- AI Model Identifies Rare Endocrine Disorder from Hand Images
- AI Tool Promises to Reduce Length of Hospital Stays and Free Up Beds
Channels
Artificial Intelligence
view channel
AI Analysis of Pericardial Fat Refines Long-Term Heart Disease Risk
Accurately identifying long-term cardiovascular disease risk in asymptomatic adults remains challenging for clinicians. Missed or underestimated risk delays preventive therapy and increases the chance... Read more
Machine Learning Approach Enhances Liver Cancer Risk Stratification
Hepatocellular carcinoma, the most common form of primary liver cancer, is often detected late despite targeted surveillance programs. Current screening guidelines emphasize patients with known cirrhosis,... Read more
Critical Care
view channel
Noninvasive Monitoring Device Enables Earlier Intervention in Heart Failure
Hospitalizations for heart failure with preserved ejection fraction (HFpEF) remain common because lung congestion often worsens before symptoms prompt treatment changes. Missed early decompensation... Read more
Automated IV Labeling Solution Improves Infusion Safety and Efficiency
Medication administration in high-acuity settings is often complicated by multiple concurrent infusions, making accurate line identification essential. In a 10-hospital intensive care unit study, 60% of... Read more
Surgical Techniques
view channel
Ultrasound Technology Aims to Replace Invasive BPH Procedures
Benign prostatic hyperplasia (BPH) is a frequent cause of lower urinary tract symptoms in aging men and often requires invasive procedures or prolonged recovery. With prevalence expected to rise as populations... Read more
Continuous Monitoring with Wearables Enhances Postoperative Patient Safety
Postoperative hypoxemia on general surgical wards is common and often missed by intermittent vital sign checks. Undetected low oxygen levels can delay recovery and raise the risk of complications that... Read more
Patient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read more
Health IT
view channel
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read more
Business
view channel
GE HealthCare Leads Major European Initiative to Advance Cardio-Oncology Care
Cardiovascular complications are increasingly recognized among people undergoing or recovering from cancer treatment, driven by pre‑existing disease and the cardiotoxic effects of chemotherapy, radiotherapy,... Read more
