Towards in silico prognosis using big data
Refereed conference paper presented and published in conference proceedings


Full Text

Other information
AbstractClinical diagnosis and prognosis usually rely on few or even single measurements despite clinical big data being available. This limits the exploration of complex diseases such as adolescent idiopathic scoliosis (AIS) where the associated low bone mass remains unexplained. Observed low physical activity and increased RANKL/OPG, however, both indicate a mechanobiological cause. To deepen disease understanding, we propose an in silico prognosis approach using clinical big data, i.e. medical images, serum markers, questionnaires and live style data from mobile monitoring devices and explore the role of inadequate physical activity in a first AIS prototype. It employs a cellular automaton (CA) to represent the medical image, micro-finite element analysis to calculate loading, and a Boolean network to integrate the other biomarkers. Medical images of the distal tibia, physical activity scores, and vitamin D and PTH levels were integrated as measured clinically while the time development of bone density and RANKL/OPG was observed. Simulation of an AIS patient with normal physical activity and patient-specific vitamin D and PTH levels showed minor changes in bone density whereas the simulation of the same AIS patient but with reduced physical activity led to low density. Both showed unchanged RANKL/OPG and considerable cortical resorption. We conclude that our integrative in silico approach allows to account for a variety of clinical big data to study complex diseases.
All Author(s) ListOhs, N., Keller, F., Blank, O. , Lee, W. Y. W. , Cheng, J. C. Y. , Arbenz. P., Muller, R., Christen, P.
Name of ConferenceBMT 2016 "Dreiländertagung" Swiss, Austrian and German Societies of Biomedical Engineering
Start Date of Conference04/10/2016
End Date of Conference06/10/2016
Place of ConferenceBasel, Switzerland
Country/Region of ConferenceSwitzerland
Proceedings TitleCurrent Directions in Biomedical Engineering
Year2016
Volume Number2
Issue Number1
PublisherDe Gruyter
Pages57 - 60
eISSN2364-5504
LanguagesEnglish-United Kingdom
Keywordsadolescent idiopathic scoliosis, Boolean network, cellular automaton, clinical big data, micro-finite element analysis.

Last updated on 2021-17-02 at 19:33