| Radiology Room |
| Ultrasound Room |
| Surgery Room |
| Laboratory Room |
| Comprehensive Room |
| Pediatrics Room |
| Dental Room |
| Medical operation instruments |
| Hospital Furniture |
| Medical supplies |
News Center
New Model Reveals Optimal Positioning of Orthopedic Screws in Fractures
Surgical screws are critical tools in orthopedic procedures, used to stabilize fractured bones and hold them together during healing. However, under everyday physical stress, these screws can loosen or fail—posing significant risks to patient recovery. Until now, predicting which screws are at risk has been a challenge, largely due to the inability to simulate real bodily stress before implantation. Researchers have now developed a new method that uses high-resolution micro-CT imaging and mechanical testing to accurately predict screw stability before surgery, potentially reducing complications and improving surgical outcomes.
The method was developed by researchers at the Karl Landsteiner University of Health Sciences (Krems an der Donau, Austria) by combining advanced imaging techniques with mechanical stress simulations to study how bone structure affects screw stability, aiming to offer a predictive tool that could guide surgeons in planning more secure implant placements. Using micro-computed tomography (micro-CT), the team analyzed 100 bone samples taken from pigs, whose bone structure closely resembles that of humans. These samples were scanned to map detailed bone structures around planned implant sites. After implanting the screws, the team subjected them to ten different loading scenarios, including axial, shear, and mixed stress conditions that mimic routine physical activities such as walking or lifting.
Six bone parameters were measured, with bone volume (BV) and bone volume fraction (BV/TV) emerging as the strongest indicators of how much force the screws could withstand before failure. With this data, the researchers developed two statistical models to predict screw stability. One model used bone volume alone, while the other combined multiple bone parameters in a stepwise regression. Both demonstrated strong predictive power, explaining between 70–90% of the variation in screw failure across samples.
The outcomes, published in the journal J Mech Behav Biomed Mater, confirm the models’ ability to assess the risk of failure in advance, offering a reliable way to guide orthopedic planning and avoid complications like screw loosening or fracture. The study paves the way for more personalized orthopedic care, especially for vulnerable groups such as elderly individuals or those with osteoporosis. By identifying the most stable screw positions based on patient-specific bone structure, surgeons could make better-informed decisions, potentially improving healing outcomes and reducing the need for repeat surgeries.
http://www.comcn021.com/en/index.asp
