By linking video, CT scans, computer models, specially developed computer software and other technologies, Dr. Fregly and his colleagues expect to enhance understanding of the causes for failure of artificial and natural knee joints as well as improve surgical procedures and create longer-lasting artificial knees. They also are working to develop tools that will shed light on the causes of arthritis in the knee and improve the success of a surgical approach to correct damage from the disease. Seventy million adults, or about one in three Americans, suffer from some form of arthritis, according to the Centers for Disease Control and Prevention in Atlanta.
Problems related to wear typically limit the life span of knee implants to 15 or 20 years, possibly less for more active patients. As younger patients are diagnosed with knee joint problems, the restricted life span and functional limitations of artificial knees are becoming an increasing concern. "We want knee implant recipients to be able to resume all their favorite activities, such as playing a game of tennis or going on long walks, without limitations or fear of wearing out their new knees prematurely", explained Dr. Fregly. "With this research, we are not just hoping to prolong the life span of artificial knees; we are hoping to prolong the patient's enjoyment of life."
One problem, according to Dr. Fregly, is the current technology to test new implant designs is ineffective. Simulators designed to highlight the places in which artificial knees will develop wear require up to three months and cost as much as $40.000 for an assessment, yet the results do not consistently equate to what occurs in patients. As a result, Dr. Fregly's team is developing a better way to test new implant designs. The researchers' key innovation is to combine motion data recorded from artificial knees with computer simulations of walking using physiological loads and speeds to create the first-ever computational wear models for knees, or models that make quantifiable predictions of deterioration of artificial knees.
Dr. Fregly, whose previous work has been published in the Journal of Biomechanics and the Journal of Biomechanical Engineering, leads a group of researchers who are evaluating and testing artificial knee designs by simulating a real world environment specific to individual patients. His team begins the process by placing reflective markers on the patient's skin and clothing during treadmill walking and stair-rise activities. The patient's motion data is captured by LCD devices and stored in a computer database.
Dr. Scott Banks of the Biomotion Foundation in West Palm Beach, Florida, augments the motion capture data with a dynamic x-ray procedure called fluoroscopy. Fluoroscopy accurately measures knee joint motion for natural or artificial knees. When studying artificial knees, Dr. Banks obtains computer-aided design (CAD) models of the implant components from the manufacturer. He then uses custom software to match the 3D CAD models to each 2D fluoroscopic image as though he were orienting an object to a photograph of its shadow. The image-matched components are used to quantify the 3D motion of the patient's knee under real life loading conditions, such as walking and climbing stairs.
The process for studying natural knees is more difficult, since CAD models of the bones are not readily available. To create models of natural knees, Dr. Fregly's team uses CT scans, which produce static 2D image slices of a patient's leg. The CT data are imported into sliceOmatic image-processing software from TomoVision, where the 2D slices are stacked to create a 3D model. The range of data in this 3D model is collected in co-ordinates known as "point clouds".
Researchers then use Geomagic Studio software from Raindrop Geomagic to automatically generate accurate 3D computer models from the point cloud data. The team uses polygon models from Geomagic Studio for shape-related tasks such as image matching. The polygonal models are then converted into highly accurate mathematical surface models for contact stress analysis.
Once the researchers have developed contact stress predictions from the movement data, the final comprehensive wear model is created with help from Dr. Greg Sawyer, a University of Florida friction and wear specialist. Combining accurate knee motion data with contact stress predictions creates a wear model that pinpoints the exact places where an artificial knee is likely to fail.
Scott Delp, an associate professor of biomechanical engineering at Stanford University, noted that Dr. Fregly's research offers a unique solution to a complex problem. "It is not possible to simulate the motions and functions of knee implants without the advanced software tools like Professor Fregly has developed. His technology offers an entirely new paradigm for simulation-based design and evaluation of knee surgery."
Eventually, Dr. Fregly and Dr. Rafi Hafka, an optimisation specialist in the Mechanical and Aerospace Engineering department, will be able to fine-tune a full-body model to reproduce movement data collected from the patient prior to surgery. The surgeon and research team will then perform the surgery on the computer model to predict which surgical parameters or implant designs will produce the best outcome for a particular patient. Patients will be followed long-term and re-measured in the movement lab following surgery to assess the model's predictions.
By developing a better understanding of how and where stress and movement produce wear, Drs. Fregly, Banks, Sawyer, and Haftka hope advances can be made to extend the life span and functionality of artificial knees. An early version of Dr. Fegly's system came within a few tenths of a millimeter of predicting the wear in an artificial knee that was recovered after a patient died and accurately predicted the locations of the worst wear.
Dr. Fregly's group also is seeking to improve the success of a surgical procedure called tibial osteotomy, which involves realigning one of the lower leg bones to redistribute loads on the knees of patients suffering from arthritis. The problem is the procedure is successful only in some cases. "Many doctors today feel that the variability is so large that the operation is not worth it", Dr. Fregly stated.
As part of the procedure, surgeons essentially have to make an educated guess about how much to rotate the lower leg bone. By recording how patients walk normally and with heel wedges that approximate the effects of the surgery, Dr. Fregly and fellow researchers are creating a computer model that could predict more accurately the correct rotation. Now, in the second of a three-year project funded with a $240.000 grant from the Whitaker Foundation, the research eventually could make the surgery more effective.
Dr. Fregly's third project probes the causes of knee arthritis itself, an area that has long proven mysterious because it is so difficult to determine what is happening inside the knee as a person walks. The team is seeking to predict inner forces on the knee using computer models, CT scans and reverse-engineering software produced by Research Triangle Park-based Raindrop Geomagic. One result of the three-year project, funded with a $210.000 grant from the National Institutes of Health, may be a better understanding of how to guard against developing arthritis.