Characterization of spine and torso stiffness via differentiable biomechanics

We present a methodology to personalize the stiffness response of a biomechanical model of the torso and the spine. In high contrast to previous work, the proposed methodology uses controlled force-deformation data that mimic the conditions of spinal bracing for scoliosis, which leads to personalized biomechanical models that are suitable for computational brace design. The novel methodology relies on several technical contributions. First, a prototype system that includes controlled force measurement and low-dose radiographs, with low-encumbrance for its implementation in the clinical protocol. Second, a model of differentiable biomechanics of the torso and the spine, which becomes the key building block for robust parameter estimation. And third, an optimization procedure for parameter estimation from force-deformation data, which relies on differentiability of the biomechanics and the image generation process. We demonstrate the application of the methodology to a cohort of 7 subjects who underwent scoliosis check-ups, and we show quantitative validation of the estimated personalized parameters and the improvement over default parameters from the bibliography.

Authors

Institutions

Publication Details

Journal
Medical Image Analysis
Published
2025-04-19
DOI
https://doi.org/10.1016/j.media.2025.103573
Citations
1
Primary Topic
Scoliosis diagnosis and treatment
Type
article
Field-Weighted Citation Impact
2.01

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Characterization of spine and torso stiffness via differentiable biomechanics

John Rasmussen, Hamed Shayestehpour, Christian Wong, Christos Koutras et al.
1 citations
Medical Image Analysis
Scoliosis diagnosis and treatment
2.01
article

Characterization of spine and torso stiffness via differentiable biomechanics

John Rasmussen, Hamed Shayestehpour, Christian Wong, Christos Koutras, Miguel Á. Otaduy, Jesús Pérez
article en
1 citations

Abstract

We present a methodology to personalize the stiffness response of a biomechanical model of the torso and the spine. In high contrast to previous work, the proposed methodology uses controlled force-deformation data that mimic the conditions of spinal bracing for scoliosis, which leads to personalized biomechanical models that are suitable for computational brace design. The novel methodology relies on several technical contributions. First, a prototype system that includes controlled force measurement and low-dose radiographs, with low-encumbrance for its implementation in the clinical protocol. Second, a model of differentiable biomechanics of the torso and the spine, which becomes the key building block for robust parameter estimation. And third, an optimization procedure for parameter estimation from force-deformation data, which relies on differentiability of the biomechanics and the image generation process. We demonstrate the application of the methodology to a cohort of 7 subjects who underwent scoliosis check-ups, and we show quantitative validation of the estimated personalized parameters and the improvement over default parameters from the bibliography.

Medical Image AnalysisVol. 103
Universidad Rey Juan Carlos (ES), Hvidovre Hospital (DK), Aalborg University (DK)
European Commission, Universidad Rey Juan Carlos, Horizon 2020 Framework Programme, Research Executive Agency, H2020 Marie Skłodowska-Curie Actions
Openalex Percentile: Top 17%
Scoliosis diagnosis and treatment
2.01
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Characterization of spine and torso stiffness via differentiable biomechanics — John Rasmussen, Hamed Shayestehpour, et al. · Medical Image Analysis (2025) | TGRS Research Map | TGRS