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Individualized treatment planning in chronic back pain patients by advanced imaging and multi-parametric biomechanical models

Fact Sheet

Reporting

Results

Objective

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.

Programme(s)

H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)

Topic(s)

ERC-StG-2014 - ERC Starting Grant

Call for proposal

ERC-2014-STG

See other projects for this call

Funding Scheme

ERC-STG - Starting Grant

Leaflet | Map data © OpenStreetMap contributors, Credit: EC-GISCO, © EuroGeographics for the administrative boundaries

Host institution

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Address

Ismaninger Strasse 22
81675 Muenchen

Germany

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 1 229 616

Website

Contact the organisation

Beneficiaries (2)

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KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Germany

EU Contribution

€ 1 229 616

TECHNISCHE UNIVERSITAET MUENCHEN

Germany

EU Contribution

€ 263 876

Project information

iBack

Grant agreement ID: 637164

Project website

Status

Ongoing project

Start date

1 June 2015
End date

31 May 2020

Funded under:

H2020-EU.1.1.

Overall budget:

€ 1 493 492
EU contribution

€ 1 493 492

Hosted by:

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Germany

Periodic Reporting for period 2 - iBack (Individualized treatment planning in chronic back pain patients by advanced imaging and multi-parametric biomechanical models)

Reporting period: 2016-12-01 to 2018-05-31

Summary of the context and overall objectives of the project

Chronic back pain is a major burden and source of disability worldwide. It is primarily attributed to biomechanical factors, but may include a neuropathic component. In elderly patients, osteoporosis complicates the determination of the source of the pain. 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. Recent clinical trials demonstrated that surgery is not beneficial in patients with unspecific chronic lower back pain [1]. This caused a dramatic decrease in those operations, also at our institution. However, many patients with chronic lower back pain remain, where spinal fusion is still indicated due to other conditions like spondylolisthesis, spinal canal stenosis, fractures or tumors [2]. The objective of iBack is to break new ground in individualized therapy planning in these patients based on novel in-vivo imaging and image post processing. We already improved in-vivo imaging in CT using different iterative reconstruction algorithms and in MR imaging, allowing to quantify tissue properties of spinal muscles, bone marrow and intervertebral disks. We are currently developing individualized biomechanical models that will allow personalized treatment planning and outcome prediction. With these techniques we recently started to establish objective, image-based criteria for surgery outcome prediction. Using calibrated opportunistic quantitative CTs we were able to predict surgery outcome in different surgical techniques. This directly influences the surgical approach at our institution. Additionally, we currently establish a machine-learning based model to predict vertebral fractures.

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1. Mannion, A.F. J.I. Brox, and J.C. Fairbank, Comparison of spinal fusion and nonoperative treatment in patients with chronic low back pain: long-term follow-up of three randomized controlled trials. Spine J, 2013. 13(11): p. 1438-48.
2. in Low Back Pain and Sciatica in Over 16s: Assessment and Management. 2016: London.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Comparison of different DTI sequences to assess back muscles

Automatic evaluation of vertebral geometry

Calculated stresses for a complex vertebral-screw-interaction

Project information

iBack

Grant agreement ID: 637164

Project website

Status

Ongoing project

Start date

1 June 2015
End date

31 May 2020

Funded under:

H2020-EU.1.1.

Overall budget:

€ 1 493 492
EU contribution

€ 1 493 492

Hosted by:

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Deliverables

Deliverables not available

Publications

Peer reviewed articles (14)

Robust and parallel scalable iterative solutions for large-scale finite cell analyses

Author(s): J.N. Jomo, F. de Prenter, M. Elhaddad, D. D'Angella, C.V. Verhoosel, S. Kollmannsberger, J.S. Kirschke, V. Nübel, E.H. van Brummelen, E. Rank

Published in: Finite Elements in Analysis and Design, Issue 163, 2019, Page(s) 14-30, ISSN 0168-874X

DOI: 10.1016/j.finel.2019.01.009

Effects of dose reduction on bone strength prediction using finite element analysis

Author(s): D. Anitha, Karupppasamy Subburaj, Kai Mei, Felix K. Kopp, Peter Foehr, Peter B. Noel, Jan S. Kirschke, Thomas Baum

Published in: Scientific Reports, Issue 6, 2016, Page(s) 38441, ISSN 2045-2322

DOI: 10.1038/srep38441

Bone mineral density measurements in vertebral specimens and phantoms using dual-layer spectral computed tomography

Author(s): Kai Mei, Benedikt J. Schwaiger, Felix K. Kopp, Sebastian Ehn, Alexandra S. Gersing, Jan S. Kirschke, Daniela Muenzel, Alexander A. Fingerle, Ernst J. Rummeny, Franz Pfeiffer, Thomas Baum, Peter B. Noël

Published in: Scientific Reports, Issue 7/1, 2017, ISSN 2045-2322

DOI: 10.1038/s41598-017-17855-4

Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment

Author(s): Felix K. Kopp, Konstantin Holzapfel, Thomas Baum, Radin A. Nasirudin, Kai Mei, Eduardo G. Garcia, Rainer Burgkart, Ernst J. Rummeny, Jan S. Kirschke, Peter B. Noël

Published in: PLOS ONE, Issue 11/7, 2016, Page(s) e0159903, ISSN 1932-6203

DOI: 10.1371/journal.pone.0159903

Anatomical Variation of Age-Related Changes in Vertebral Bone Marrow Composition Using Chemical Shift Encoding-Based Water–Fat Magnetic Resonance Imaging

Author(s): Thomas Baum, Alexander Rohrmeier, Jan Syväri, Maximilian N. Diefenbach, Daniela Franz, Michael Dieckmeyer, Andreas Scharr, Hans Hauner, Stefan Ruschke, Jan S. Kirschke, Dimitrios C. Karampinos

Published in: Frontiers in Endocrinology, Issue 9, 2018, ISSN 1664-2392

DOI: 10.3389/fendo.2018.00141

B1-insensitive T2 mapping of healthy thigh muscles using a T2-prepared 3D TSE sequence

Author(s): Elisabeth Klupp, Dominik Weidlich, Sarah Schlaeger, Thomas Baum, Barbara Cervantes, Marcus Deschauer, Hendrik Kooijman, Ernst J. Rummeny, Claus Zimmer, Jan S. Kirschke, Dimitrios C. Karampinos

Published in: PLOS ONE, Issue 12/2, 2017, Page(s) e0171337, ISSN 1932-6203

DOI: 10.1371/journal.pone.0171337

Isotropic resolution diffusion tensor imaging of lumbosacral and sciatic nerves using a phase-corrected diffusion-prepared 3D turbo spin echo

Author(s): Barbara Cervantes, Anh T. Van, Dominik Weidlich, Hendrick Kooijman, Andreas Hock, Ernst J. Rummeny, Alexandra Gersing, Jan S. Kirschke, Dimitrios C. Karampinos

Published in: Magnetic Resonance in Medicine, Issue 80/2, 2018, Page(s) 609-618, ISSN 0740-3194

DOI: 10.1002/mrm.27072

Multi-level h p -finite cell method for embedded interface problems with application in biomechanics

Author(s): Mohamed Elhaddad, Nils Zander, Tino Bog, László Kudela, Stefan Kollmannsberger, Jan S. Kirschke, Thomas Baum, Martin Ruess, Ernst Rank

Published in: International Journal for Numerical Methods in Biomedical Engineering, 2018, ISSN 2040-7939

DOI: 10.1002/cnm.2951

Diagnostic Value of CT Arthrography for Evaluation of Osteochondral Lesions at the Ankle

Author(s): Thomas Baum; Christian Holwein; Christoph Schaeffeler; Klaus Woertler; Imhoff, Andreas B; Kirschke, Jan S.; Ernst J Rummeny; Jungmann, Pia M.; Sepp Braun

Published in: BioMed Research International, Vol 2016 (2016), Issue 1, 2017, ISSN 2314-6141

DOI: 10.1155/2016/3594253

Is multidetector CT-based bone mineral density and quantitative bone microstructure assessment at the spine still feasible using ultra-low tube current and sparse sampling?

Author(s): Kai Mei, Felix K. Kopp, Rolf Bippus, Thomas Köhler, Benedikt J. Schwaiger, Alexandra S. Gersing, Andreas Fehringer, Andreas Sauter, Daniela Münzel, Franz Pfeiffer, Ernst J. Rummeny, Jan S. Kirschke, Peter B. Noël, Thomas Baum

Published in: European Radiology, Issue 27/12, 2017, Page(s) 5261-5271, ISSN 0938-7994

DOI: 10.1007/s00330-017-4904-y

MR-based assessment of body fat distribution and characteristics

Author(s): Thomas Baum, Christian Cordes, Michael Dieckmeyer, Stefan Ruschke, Daniela Franz, Hans Hauner, Jan S. Kirschke, Dimitrios C. Karampinos

Published in: European Journal of Radiology, Issue 85/8, 2016, Page(s) 1512-1518, ISSN 0720-048X

DOI: 10.1016/j.ejrad.2016.02.013

Bone Mineral Density Estimations From Routine Multidetector Computed Tomography

Author(s): Johannes Kaesmacher, Hans Liebl, Thomas Baum, Jan Stefan Kirschke

Published in: Journal of Computer Assisted Tomography, 2016, Page(s) 1, ISSN 0363-8715

DOI: 10.1097/RCT.0000000000000518

Association of Quadriceps Muscle Fat With Isometric Strength Measurements in Healthy Males Using Chemical Shift Encoding-Based Water-Fat Magnetic Resonance Imaging

Author(s): Thomas Baum, Stephanie Inhuber, Michael Dieckmeyer, Christian Cordes, Stefan Ruschke, Elisabeth Klupp, Pia M. Jungmann, Rosanna Farlock, Holger Eggers, Hendrik Kooijman, Ernst J. Rummeny, Ansgar Schwirtz, Jan S. Kirschke, Dimitrios C. Karampinos

Published in: Journal of Computer Assisted Tomography, Issue 40/3, 2016, Page(s) 447-451, ISSN 0363-8715

DOI: 10.1097/RCT.0000000000000374

Phase-field boundary conditions for the voxel finite cell method: Surface-free stress analysis of CT-based bone structures

Author(s): Lam Nguyen, Stein Stoter, Thomas Baum, Jan Kirschke, Martin Ruess, Zohar Yosibash, Dominik Schillinger

Published in: International Journal for Numerical Methods in Biomedical Engineering, Issue 33/12, 2017, Page(s) e2880, ISSN 2040-7939

DOI: 10.1002/cnm.2880

Project information

iBack

Grant agreement ID: 637164

Project website

Status

Ongoing project

Start date

1 June 2015
End date

31 May 2020

Funded under:

H2020-EU.1.1.

Overall budget:

€ 1 493 492
EU contribution

€ 1 493 492

Hosted by:

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

Project information

iBack

Grant agreement ID: 637164

Project website

Status

Ongoing project

Start date

1 June 2015
End date

31 May 2020

Funded under:

H2020-EU.1.1.

Overall budget:

€ 1 493 492
EU contribution

€ 1 493 492

Hosted by:

KLINIKUM RECHTS DER ISAR DER TECHNISCHEN UNIVERSITAT MUNCHEN

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Last update: 17 November 2016

Record number: 196763

CORDIS

Objective

Host institution

Beneficiaries (2)

Project information

Periodic Reporting for period 2 - iBack (Individualized treatment planning in chronic back pain patients by advanced imaging and multi-parametric biomechanical models)

Project information

Deliverables

Publications

Project information

Project information

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