VPHOP

Nearly four million osteoporotic bone fractures cost the European health system more than 30 billion Euro per year. This figure could double by 2050. After the first fracture, the chances of having another one increase by 86%. We need to prevent osteoporotic fractures. The first step is an accurate prediction of the patient-specific risk of fracture that considers not only the skeletal determinants but also the neuromuscular condition.

The aim of VPHOP is to develop a multiscale modelling technology based on conventional diagnostic imaging methods that makes it possible, in a clinical setting, to predict for each patient the strength of his/her bones, how this strength is likely to change over time, and the probability that the he/she will overload his/her bones during daily life. With these three predictions, the evaluation of the absolute risk of bone fracture will be much more accurate than any prediction based on external and indirect determinants, as it is current clinical practice.

These predictions will be used to:

  • improve the diagnostic accuracy of the current clinical standards;
  • to provide the basis for an evidence-based prognosis with respect to the natural evolution of the disease, to pharmacological treatments, and/or to preventive interventional treatments aimed to selectively strengthen particularly weak regions of the skeleton.

For patients at high risk of fracture, and for which the pharmacological treatment appears insufficient, the VPHOP system will also assist the interventional radiologist in planning the augmentation procedure. The various modelling technologies developed during the project will be validated not only in vitro, on animal models, or against retrospective clinical outcomes, but will also be assessed in term of clinical impact and safety on small cohorts of patients enrolled at four different clinical institutions, providing the factual basis for effective clinical and industrial exploitations.

For further information, please visit:
http://www.vphop.eu

Project co-ordinator:
Istituto Ortopedico Rizzoli

Partners:

  • SCS SRL
  • Société d’Etudes et de Recherches de l’Ecole Nationale Supérieure d’Arts et Métiers
  • Universität Bern
  • Biospace Med SA
  • University of Bedfordshire
  • Technische Universiteit Eindhoven
  • Philips Medical Systems Nederland BV
  • empirica Gesellschaft für Kommunikations- und Technologieforschung mbH
  • Université de Genève (UNIGE)
  • Sylvia Lawry Centre for Multiple Sclerosis Research e.V.
  • ANSYS France SAS
  • Háskóli Íslands
  • Institut National de la Santé et de la Recherche Médicale (INSERM)
  • Uppsala universitet
  • Charité - Universitätsmedizin Berlin
  • Eidgenössische Technische Hochschule Zürich (ETHZ)
  • BrainLAB AG
  • Katholieke Universiteit Leuven

Timetable: from 08/2008 – to 08/2012

Total cost: € 12.073.349

EC funding: € 8.989.363

Programme Acronym: FP7-ICT

Subprogramme Area: Virtual physiological human

Contract type: Collaborative project (generic)

Related news articles::

Most Popular Now

Researchers Invent AI Model to Design Ne…

Researchers at McMaster University and Stanford University have invented a new generative artificial intelligence (AI) model which can design billions of new antibiotic molecules that are inexpensive and easy to...

Two Artificial Intelligences Talk to Eac…

Performing a new task based solely on verbal or written instructions, and then describing it to others so that they can reproduce it, is a cornerstone of human communication that...

Powerful New AI can Predict People'…

A powerful new tool in artificial intelligence is able to predict whether someone is willing to be vaccinated against COVID-19. The predictive system uses a small set of data from demographics...

Greater Manchester Reaches New Milestone…

Radiologists and radiographers at Northern Care Alliance NHS Foundation Trust have become the first in Greater Manchester to use the Sectra picture archiving and communication system (PACS) to report on...

AI-Based App can Help Physicians Find Sk…

A mobile app that uses artificial intelligence, AI, to analyse images of suspected skin lesions can diagnose melanoma with very high precision. This is shown in a study led from...

Alcidion and Novari Health Forge Strateg…

Alcidion Group Limited, a leading provider of FHIR-native patient flow solutions for healthcare, and Novari Health, a market leader in waitlist management and referral management technologies, have joined forces to...

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Advancing Drug Discovery with AI: Introd…

A transformative study published in Health Data Science, a Science Partner Journal, introduces a groundbreaking end-to-end deep learning framework, known as Knowledge-Empowered Drug Discovery (KEDD), aimed at revolutionizing the field...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Wanted: Young Talents. DMEA Sparks Bring…

9 - 11 April 2024, Berlin, Germany. The digital health industry urgently needs skilled workers, which is why DMEA sparks focuses on careers, jobs and supporting young people. Against the backdrop of...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...