Quantitative vertebral morphometry based on parametric modeling of vertebral bodies in 3D

Pediatric Solid-State 3D Models of Lumbar Vertebrae and Spine

Introduction While various 3D vertebral models have been utilized in numerous studies, there is a notable gap in the representation of pediatric lumbar vertebrae and spine. This study aimed to describe the changing shapes of lumbar vertebrae and spine with age and to develop precise 3D models. Materials and methods Solid-state 3D models of pediatric lumbar vertebrae and spine were created using SOLIDWORKS® Simulation software for five age groups: newborns, infants (ages 0-1), toddlers (ages 1-3), middle childhood (ages 4-7), and preadolescents (ages 8-12). Models were composed of components with varying biomechanical characteristics. Results Created 3D models replicate variations in the dimensions and configurations of vertebrae, taking into account osteometric analyses conducted on actual vertebral specimens. These models also include elements made of cartilage, representing various phases of vertebral growth during ontogeny. Additionally, through 3D parametric design, we developed comprehensive lumbar spine models, incorporating both the vertebrae and intervertebral disks. Conclusion Created pediatric solid-state vertebral 3D models can be utilized in developing virtual or augmented reality applications and for medical research. Users can interact with models, allowing virtual exploration and manipulation, enhancing learning experiences and facilitating a better understanding of spatial relationships. These solid-state 3D models allow finite element analysis and can be used for further research to calculate internal relative deformations and stress distribution under different conditions.

A deep learning framework for vertebral morphometry and Cobb angle measurement with external validation

PURPOSE

To propose a fully automated deep learning (DL) framework for the vertebral morphometry and Cobb angle measurement from three-dimensional (3D) computed tomography (CT) images of the spine, and validate the proposed framework on an external database.

METHODS

The vertebrae were first localized and segmented in each 3D CT image using a DL architecture based on an ensemble of U-Nets, and then automated vertebral morphometry in the form of vertebral body (VB) and intervertebral disk (IVD) heights, and spinal curvature measurements in the form of coronal and sagittal Cobb angles (thoracic kyphosis and lumbar lordosis) were performed using dedicated machine learning techniques. The framework was trained on 1725 vertebrae from 160 CT images and validated on an external database of 157 vertebrae from 15 CT images.

RESULTS

The resulting mean absolute errors (± standard deviation) between the obtained DL and corresponding manual measurements were 1.17 ± 0.40 mm for VB heights, 0.54 ± 0.21 mm for IVD heights, and 3.42 ± 1.36° for coronal and sagittal Cobb angles, with respective maximal absolute errors of 2.51 mm, 1.64 mm, and 5.52°. Linear regression revealed excellent agreement, with Pearson's correlation coefficient of 0.943, 0.928, and 0.996, respectively.

CONCLUSION

The obtained results are within the range of values, obtained by existing DL approaches without external validation. The results therefore confirm the scalability of the proposed DL framework from the perspective of application to external data, and time and computational resource consumption required for framework training.

Reconstruction of three-dimensional lumbar vertebrae from biplanar x-rays

Objective. Vertebrae models from computer tomographic (CT) imaging are extensively used in image-guided surgical systems to deliver percutaneous orthopaedic operations with minimum risks, but patients may be exposed to excess radiation from the pre-operative CT scans. Generating vertebrae models from intra-operative x-rays for image-guided systems can reduce radiation exposure to the patient, and the surgeons can acquire the vertebrae's relative positions during the operation; therefore, we proposed a lumbar vertebrae reconstruction method from biplanar x-rays.Approach. Non-stereo-corresponding vertebral landmarks on x-rays were identified as targets for deforming a set of template vertebrae; the deformation was formulated as a minimisation problem, and was solved using the augmented Lagrangian method. Mean surface errors between the models reconstructed using the proposed method and CT scans were measured to evaluate the reconstruction accuracy.Main results. The evaluation yielded mean errors of 1.27 mm and 1.50 mm inin vitroexperiments on normal vertebrae and pathological vertebrae, respectively; the outcomes were comparable to other template-based methods.Significance. The proposed method is a viable alternative to provide digital lumbar to be used in image-guided systems, where the models can be used as a visual reference in surgical planning and image-guided applications in operations where the reconstruction error is within the allowable surgical error.

Vertebral Fractures Associated with Spinal Sagittal Imbalance and Quality of Life in Acromegaly: A Radiographic Study with EOS 2D/3D Technology

INTRODUCTION

Acromegaly is commonly complicated by arthropathy and skeletal fragility with high risk of vertebral fractures (VFs).

OBJECTIVE

This study aimed to assess whether VFs may be associated with sagittal spine deformities, arthropathy, impaired quality of life (QoL), pain, and disability.

METHODS

Thirty-eight patients with acromegaly (median age: 55 years, 20 males) and 38 matched control subjects were evaluated by a low-dose sagittal and coronal planes, X-ray imaging system (EOS®-2D/3D) for morphometric VFs, radiological signs of spine arthropathy, and spine deformities (Cobb thoracic index ≥40°, pelvic incidence minus lumbar lordosis ≥10°, pelvic tilt >20°, and sagittal vertical axis ≥4 cm) determining sagittal spine imbalance. Acromegalic patients were also evaluated by questionnaires for QoL (Acromegaly QoL Questionnaire [AcroQoL] and Short Form-36 [SF-36]) and pain and disability (Western Ontario and McMaster University [WOMAC]).

RESULTS

Acromegalic patients showed higher prevalence of thoracic hyperkyphosis (i.e., Cobb thoracic index ≥40°; p = 0.04) and pelvic tilt >20° (p = 0.02) than control subjects. VFs were found in 34.2% of acromegalic patients (p = 0.003 vs. control subjects), in relationship with higher prevalence of hyperkyphosis (p = 0.03), pelvic tilt >20° (p = 0.04), sagittal vertical axis ≥4 cm (p = 0.03), and moderate/severe subchondral degeneration (p = 0.01). Moreover, patients with VFs had lower AcroQoL general health (p = 0.007) and SF-36 general health (p = 0.002) scores and higher WOMAC pain (p = 0.003) and global (p = 0.009) scores than patients who did not fracture.

CONCLUSIONS

In acromegaly, VFs may be associated with spine deformities and sagittal imbalance, spine arthropathy, impaired QoL, and disability.

Vertebral Morphometry

There is as yet no agreement about the criteria by which to arrive at an imaging diagnosis of a vertebral fracture. Because high-grade fractures result in alterations in vertebral shape, 1 possible avenue of diagnosis has been to quantitate changes in vertebral shape. The result has been a variety of methods for the relative and absolute measurements of vertebral dimensions. Such measurements have also lent themselves to automated computed analysis. The number of techniques reflects the absence of any consensus about the best. The semiquantitative technique proposed by Genant has become the most widely used and has served the field well for comparative purposes. Its use in higher grade fractures has been widely endorsed, if some concepts (e.g., short vertebral height-vertebrae) are at variance with lower grades of fracturing. Vertebral morphometry may be the only recourse in high volume epidemiological and interventional studies.