Für den Inhalt der Angaben zeichnet die Projektleitung verantwortlich.
Dieses von der Gebert Rüf Stiftung geförderte Projekt wird von folgenden weiteren Projektpartnern mitgetragen: Institute for Surgical Technology and Biomechanics, University of Bern; Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern; Osteoporosis Clinic, Inselspital, Bern; University Hospital and University of Bern; University of Erlangen, Germany
Förderbeitrag: CHF 150000
Dauer: 09.2015 - 06.2017
Pilotprojekte, 1998 - 2018
Do you have back pain? If you are over 50 years of age, you might be suffering from osteoporosis - literally «porous bone»- just as half of the western population. The disease slowly reduces the resistance of your bones, mainly at the spine and hip, and numerous patients discover their condition too late: when fracture occurs. If you are younger, you are also concerned: detected early enough, osteoporosis can be cured by the potent drugs available on the market.
Due to the aging of the population and a sedentary lifestyle, osteoporosis constitutes a major threat for the healthcare system. Yet, surprisingly, mass screening is not recommended by the health authorities. How will we help millions of new patients in 10 years, when less than 20% of the population at risk is being diagnosed today? Better screening procedures need to be developed quickly. We have a solution. It relies on the latest progress of in silico medicine and on the re-use of dormant Computed Tomography (CT) images.
Through collaborations with clinical partners, our objective is to turn our research in biomechanics into a software solution adapted to clinical practice. Accurate computer models of bones can be built from CT data with minimal user interaction. A patient’s vertebra is then virtually crushed and its resistance to failure is automatically computed based on the body weight of the patient and a selected type of activity. This information can be used by the clinician to discriminate patients at risk. The program will deal with most acquisition protocols and be embedded in the hospital’s network as a new standard for the extended screening of osteoporosis.
Was ist das Besondere an diesem Projekt?
Tomorrow’s tool for the diagnosis of osteoporosis...
Our computer models ensure better identification of the fragile individuals than the current techniques by evaluating the resistance of their bone
before fracture actually happens.
Based on a full-proof technology...
The finite element technology, used for decades in the orthopaedic industry for implant design, was thoroughly validated for bone health diagnosis.
To improve the detection of the disease…
Re-using existing CT data already covered by insurances is an attractive solution to diagnose individuals who might not have been screened otherwise
...while optimizing the hospital’s resources
Each abdominal CT becomes 2-in-1: two diagnoses for the radiation dose and cost of one. The existing resources of the hospital can be optimised and allow for timely initiation of therapy if necessary.
Fracture occurs when the load is larger than the bone strength..., but which load? Typically, your bone will break differently whether you fall from a chair or pick your grandchild up. This information is not part of the current screening methods. We thus propose to conduct mechanical testing on your bones to determine their risk of fracture. Obviously, we only do this «virtually» via computer models. Such analysis is non-invasive and can be seen as a virtual crash test for your bones. An example can be seen on our website
Virtual testing has been introduced in orthopaedic research already 40 years ago. Since then, it has been thoroughly validated against experiments for the major sites at risk of fracture (wrist, spine, and hip) and pharmaceutical companies use it to evaluate the efficacy of the osteoporosis drug therapies you may receive. We have even shown that virtual testing could predict the impact of osteoplasty (bone surgery). Its clearance by the U.S. Food and Drug Administration for clinical use confirmed that virtual testing is the method of the future.
Yet, the model generation can prove tricky. In the usual procedure, every structure except the bone of interest (let us say the femur) is erased: this is the segmentation. The contour of the bone is then used as a basis for creating the shape of the computer model. In our method, however, a single template model is deformed to fit one’s anatomy. It has several advantages. First, the segmentation is no longer necessary. Second, since the same model is being used every time, comparing patients or visits is much easier. The usual evaluation for fracture risk is conducted using DXA images, not CT. We thus simulate DXA from CT data to provide your clinician with an image he is used to. Yet, we also used the pairs of simulated DXAs and the corresponding CT to test a new approach for reconstructing 3D images from 2D ones. In a near future, we will perform virtual testing on DXA images as already done on a CT scans.
Maquer, G., Bürki, A., Nuss, K., Zysset, P. K., & Tannast, M. (2016). Head-neck osteoplasty has minor effect on the strength of an ovine Cam-FAI model: in vitro and finite element analyses
. Clinical Orthopaedics and Related Research, 474(12), 2633-2640;
Daszkiewicz, K., Maquer, G., & Zysset, P. K. (2016). The effective elastic properties of human trabecular bone may be approximated using micro-finite element analyses of embedded volume elements
. Biomechanics and Modeling in Mechanobiology, 1-12;
Musy, S. N., Maquer, G., Panyasantisuk, J., Wandel, J., & Zysset, P. K. (2017). Not only stiffness, but also yield strength of the trabecular structure determined by non-linear µFE is best predicted by bone volume fraction and fabric tensor
. Journal of the mechanical behavior of biomedical materials, 65, 808-813;
Hosseini, H. S., Maquer, G., & Zysset, P. K. (2017). CT-based trabecular anisotropy can be reproducibly computed from HR-pQCT scans using the triangulated bone surface
. Bone, 97, 114-120;
Chandran V, Maquer G, Gerig T, Zysset P, Reyes M. Supervised learning for bone shape and cortical thickness estimation from clinical CT images for finite element analysis. Submitted to Medical Image Analysis in Jan 2017;
Wili P, Maquer G, Panyasantisuk J, Zysset P. Estimation of the effective yield properties of human trabecular bone using nonlinear micro finite element analyses. Submitted to Biomechanics and Modeling in Mechanobiology in Feb 2017.
Am Projekt beteiligte Personen
Institute for Surgical Technology and Biomechanics, University of Bern, SwitzerlandDr. Ghislain MaquerProf. Philippe ZyssetDr. Guoyan Zheng
Department of Diagnostic, Interventional and Paediatric Radiology of the Inselspital, SwitzerlandProf. Johannes HeverhagenJasmin Troger
Department of Osteoporosis of the Inselspital, SwitzerlandProf. Kurt Lippuner (firstname.lastname@example.org@email@example.comDr. Albrecht Popp Dr. Sandra Bras
Institute for Risks and Extremes, Bern University of Applied Science, SwitzerlandDr. Jasmin Wandel
Institute for Forensic Medicine, University of Bern, Switzerland
Prof. Christian JackowskiNicole Schwendener
Institute of Medical Physics, University of Erlangen, Germany Prof. Klaus Engelke
Radiology Institute, Erlangen University Hospital, GermanyDr. Peter Dankerl
Department of Medicine, University of Cambridge, UK
Letzte Aktualisierung dieser Projektdarstellung 17.10.2018