Promoting patient safety by a novel combination of imaging technologies for biodegradable magnesium implants


Project Title
Promoting patient safety by a novel combination of imaging technologies for biodegradable magnesium implants
 
Funding Code
811226
 
 
Status
Laufend
 
Duration
01-10-2018
-
30-09-2022
 
Funding Organization
 
Funding Program
H2020
 
Abstract
Biomedical imaging has gained a significant technological push and is the mainstay for diag-nosis and therapy monitoring. Still, imaging is yet not optimized for the new class of biode-gradable Mg-based implants. MgSafe addresses this point by training 15 ESRs in both, imag-ing and implant technologies. All ESRs will develop their individual Personal Learning Envi-ronment (PLE) and be trained based on the “T-skills concept” in technologies and transferable skills relevant for their career development and prepared to take over leadership positions in an area of tremendous research promises and clinical relevance where the lack for experts is severe and very well recognized.
The ESRs will quantify the physical impact and suitability of a variety of modalities on Mg implants. Highly sophisticated imaging techniques (nano and µCT, MRT, PET, USPA, IR) will be developed beyond the forefront of medical device production in vivo and with in situ label-ling options to deliver non-invasively data on different time and length scales of the body reac-tion and material behavior during Mg degradation with a precision and plethora of details which is currently not available. Two Mg-alloys and CE-certified Mg-implants will be studied in rats and sheep. Dummy studies will be performed in parallel (following ASTM rules). The ob-tained multimodal imaging data will be combined with molecular biological/biochemical analy-sis, thereby increasing the information about physiological changes without using additional animals. An additional dimension will be added by the analysis of explants to obtain highest resolution chemical and material science data. All relevant biological and chemical in vivo and ex vivo data will be merged by computational 3D methods, simulations and machine learning approaches. The combination of these results will not only allow for an upscaling of the pro-cesses towards humans but will also deliver valuable data in terms of patient safety.
 

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