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The data collection was approved of by the ethical commit-tee (CPP 6001 Ile de France V), and patients and their parents signed an informed consent. Bracing is the most common treatment to stop the progression of adolescent idiopathic scoliosis. Finite element modeling could help improve brace design, but model validation is still a challenge. In this work, the clinical relevance of a predictive and subject-specific model for bracing was evaluated in forty-six AIS patients. The model reproduces brace action and the patient’s spinopelvic adjustments to keep balance. The model simulated 70% or more patients with geometrical parameters within a preselected tolerance level. Although the model simulation of the sagittal plane could be improved, the approach is promising for a realistic and predictive simulation of brace action. The authors are grateful to the ParisTech BiomecAM chair program on subject-specific musculoskeletal modelling (with the support of ParisTech and Yves Cotrel Foundations, Proteor, Société Génerale and Covea). We are also thankful to David Barrie Colridge for his support.

International audience; 3D reconstruction from low-dose Bi-Planar X-Rays (BPXR) is a rising practice in clinical routine.However, this process is time consuming and highly depends on the user. This study aims topartially automate the process for the femur, thus decreasing reconstruction time and increasingrobustness. As a training set, 50 femurs are segmented from CT scans together with 120 BPXRreconstructions. From this dataset, an initial solution for the bony contours is defined throughGaussian Process Regression (GPR), using eight digitized landmarks. This initial solution is projectedon both x-rays and automatically adjusted using an adapted Minimal Path Algorithm (MPA). Toevaluate this method, CT-scans were acquired from 20 cadaveric femurs. For each sample, the CTbasedreconstruction is compared to the one automatically generated from the digitally reconstructedradiographs. Euclidean distances between femur reconstructions and the segmented CTdata are on average 1.0 mm with a Root Mean Square Error (RMSE) of 0.8 mm. Femoral torsionerrors are assessed: the bias is lower than 0.1° with a 95% confidence interval of 4.8°. The proposedmethod substantially improves 3D reconstructions from BPXR, as it enables a fast and reliablereconstruction, without the need for manual adjustments, which is essential in clinical routine.

Quantitative measurements of spine shape parameters on planar X-ray images is critical for clinical applications but remains tedious and with no fully-automated solution demonstrated on the whole spine. This study aims to limit manual input, while demonstrating precise vertebrae corners positioning and shape parameter measurements from sagittal radiographs of the cervical and lumbar regions, exploiting novel dedicated visual features and specialized classifiers. A database of manually annotated X-ray images is used to train specialized Random Forest classifiers for each spine regions and corner types. An original combination of local gradient characteristics, Haar-like features, and contextual features based on patch intensity and contrast is used as visual features. The proposed method is evaluated on 49 sagittal X-rays of asymptomatic and pathological subjects, from multiple imaging sites, and with a large age range (6 – 69 years old). Performance is first evaluated for positioning a 2D spine shape model, where precisely detected corners enable to adjust the model via an original multilinear statistical regression. Root-mean square errors (RMSE) of corners localization and vertebra orientations are reported, demonstrating state-of-the-art precision compared to existing methods, but with minimal manual input. The method is then evaluated for the extraction of additional vertebrae shape characteristics, such as centre positioning, endplate centres positioning and endplate length measures, rarely studied in previous literature. The proposed method enables, with minimal initialization, fast and precise individual vertebrae delineations on sagittal radiographs on normal and pathological cases, with a level of precision and robustness required for objective support for diagnosis and therapy decision making. BiomecAM chair program

International audience; Several Finite Element (FE) models of the pelvis have been developed to comprehensively assess the onset of pathologies and for clinical and industrial applications. However, because of the difficulties associated with the creation of subject-specific FE mesh from CT scan and MR images, most of the existing models rely on the data of one given individual. Moreover, although several fast and robust methods have been developed for automatically generating tetrahedral meshes of arbitrary geometries, hexahedral meshes are still preferred today because of their distinct advantages but their generation remains an open challenge. Recently, approaches have been proposed for fast 3D reconstruction of bones based on X-ray imaging. In this study, we adapted such an approach for the fast and automatic generation of all-hexahedral subject-specific FE models of the pelvis based on the elastic registration of a generic mesh to the subject-specific target in conjunction with element regularity and quality correction. The technique was successfully tested on a database of 120 3D reconstructions of pelvises from biplanar X-ray images. For each patient, a full hexahedral subject-specific FE mesh was generated with an accurate surface representation.

Although the use of pedicle screws is considered safe, mechanical issues still often occur. Commonly reported issues are screw loosening, screw bending and screw fracture. The aim of this study was to develop a Finite Element (FE) model for the study of pedicle screw biomechanics and for the prediction of the intraoperative pullout strength. The model includes both a parameterized screw model and a patient-specific vertebra model. Pullout experiments were performed on 30 human cadaveric vertebrae from ten donors. The experimental force-displacement data served to evaluate the FE model performance. μCT images were taken before and after screw insertion, allowing the creation of an accurate 3D-model and a precise representation of the mechanical properties of the bone. The experimental results revealed a significant positive correlation between bone mineral density (BMD) and pullout strength (Spearman ρ= 0.59, p

Rib cage 3D reconstruction is an important prerequisite for thoracic spine modelling, particularly for studies of the deformed thorax in adolescent idiopathic scoliosis. This study proposes a new method for rib cage 3D reconstruction from biplanar radiographs, using a statistical parametric model approach. Simplified parametric models were defined at the hierarchical levels of rib cage surface, rib midline and rib surface, and applied on a database of 86 trunks. The resulting parameter database served to statistical models learning which were used to quickly provide a first estimate of the reconstruction from identifications on both radiographs. This solution was then refined by manual adjustments in order to improve the matching between model and image. Accuracy was assessed by comparison with 29 rib cages from CT scans in terms of geometrical parameter differences and in terms of line-to-line error distance between the rib midlines. Intra and inter-observer reproducibility were determined regarding 20 scoliotic patients. The first estimate (mean reconstruction time of 2’30) was sufficient to extract the main rib cage global parameters with a 95% confidence interval lower than 7%, 8%, 2% and 4° for rib cage volume, antero-posterior and lateral maximal diameters and maximal rib hump, respectively. The mean error distance was 5.4 mm (max 35mm) down to 3.6 mm (max 24 mm) after the manual adjustment step (+3’30). The proposed method will improve developments of rib cage finite element modeling and evaluation of clinical outcomes. This work was funded by Paris Tech BiomecAM chair on subject specific muscular skeletal modeling, and we express our acknowledgments to the chair founders: Cotrel foundation, Société générale, Protéor Company and COVEA consortium. We extend your acknowledgements to Alina Badina for medical imaging data, Alexandre Journé for his advices, and Thomas Joubert for his technical support.

Version éditeur : http://www.tandfonline.com/toc/gcmb20/13/6 In order to improve the reliability of children’s models, the aim of this study was to determine the subject-specific masses and 3D locations of the centres of mass (CoM) of body segments using biplanar X-rays. Previous methods, validated on upper leg segments, were applied to the whole body. Six children and six adults were studied. The low-dose X-ray system EOS was used to simultaneously get head-to-foot biplanar X-rays in the upright position. Specific methods were used to get 3D reconstructions of bones and body shape. The densities from the literature were used to define the masses. To assess the accuracy of the reconstructions, a force plate was used to compare the mass and the projection of the CoM. A mean distance of 4.5mm between the measured and the calculated projections of the CoM was found. The mean error between the estimated and the actual body mass was 2.6%. Such a method will be useful in obtaining the body segment parameters in children, hard to obtain using direct measurement techniques. ANR (SECUR_ENFANT_06_0385)