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iBack

Financiado

Cerrado

Individualized treatment planning in chronic back pain patients by advanced imag...

Individualized treatment planning in chronic back pain patients by advanced imaging and multi parametric biomechanical models Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to biomechanical factors. In elderly patients, osteoporosis complicates the biomechanical scenario. Surgery is often required to tr... ver más

30/11/2020

TUM-MED

1M€

Presupuesto del proyecto: 1M€

Líder del proyecto

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIV... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 3 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-11-30

ERC-StG-2014: ERC Starting Grant

I+D

Cerrada hace 10 años

0% 100% 100%

Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

TUM-MED

1.23M€ | Lider

INDUSTRIAS LOTU

302.73K€ | Participante

TUM

263.88K€ | Participante

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Duración del proyecto: 66 meses Fecha Inicio: 2015-05-13
Fecha Fin: 2020-11-30

Líder del proyecto

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIV... No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 1M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to biomechanical factors. In elderly patients, osteoporosis complicates the biomechanical scenario. Surgery is often required to treat instability-related pain and to restore the balance of the spine. However, when and how to perform surgery remains a highly subjective decision based on the surgeon’s experience, with 2/3 of patients experiencing prolonged pain. We recently established objective, image-based criteria for surgery outcome prediction. As an example, we were able to develop tools for routine density and fracture assessment and demonstrate that screw loosening occurs in >85% of patients with bone mineral density <92 mg/ccm. This directly influences the surgical approach in all spine surgery patients at our institution. Additionally, we improved the prediction of bone strength by advanced image post processing such as scaling indices, finite element and finite cell models. The high-level objective of iBack is to individualize therapy planning in back pain patients. We will improve in-vivo imaging and image analysis to compute individualized biomechanical models that reveal the underlying pathophysiologic process and allow personalized treatment planning and outcome prediction after spine surgery or conservative treatment. The main objectives of iBack are: (1) improving computed tomography (CT) and magnetic resonance imaging (MRI) of the spine; (2) combining sagittal balance radiographs, CT and MRI of the spine in one biomechanical multi-body simulation (MBS); (3) creating a statistical model that includes both clinical and biomechanical information to reveal interactions between the two and to predict individual treatment success probability. The results of iBack will help to better understand instability-related pain and develop personalized surgical strategies which will have major impacts on patients.

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