Computational modelling of the scoliotic spine: A literature review

Gould, Samuele L; Cristofolini, Luca; Davico, Giorgio; Viceconti, Marco

doi:10.1002/cnm.3503

Cited by 13 publications

(7 citation statements)

References 155 publications

(675 reference statements)

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“…Additionally, there is a need for standardized outcome measures and diagnostic criteria across studies to facilitate meaningful comparisons and meta-analyses [111]. Incorporating advanced imaging modalities and computational modeling techniques can enhance the precision of scoliosis studies [112,113]. However, accessibility to these technologies, especially in resource-constrained settings, remains limited.…”

Section: Limitations Of Studiesmentioning

confidence: 99%

The Pathophysiology of Scoliosis Across the Spectrum of Human Physiological Systems

Kerna,

Carsrud,

Zhao

et al. 2024

ejmhr

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Scoliosis is a medical condition characterized by an abnormal lateral curvature of the spine. It can lead to various health issues, affecting mobility, respiratory function, and overall quality of life. There are several types of scoliosis, including idiopathic, congenital, neuromuscular, degenerative, and functional. The severity of scoliosis is measured by the degree of spinal curvature, typically expressed in degrees through a system known as the Cobb angle. Early detection and intervention are fundamental in managing scoliosis, as more severe forms may necessitate bracing or surgical intervention. Healthcare professionals must understand the different types of scoliosis and their unique characteristics to tailor appropriate treatment plans.Scoliosis can significantly impact various physiological systems, including the circulatory, digestive, endocrine, integumentary, lymphatic, muscular, nervous, and respiratory systems. In the circulatory system, scoliosis can cause hemodynamic changes, impaired venous return, cardiac strain, and pulmonary complications. In the digestive system, scoliosis can lead to gastric displacement, impaired intra-abdominal pressure, gastroesophageal reflux, and nutritional implications. The endocrine system can be affected by scoliosis, leading to neuroendocrine dysregulation, growth hormone abnormalities, cortisol dysregulation, and impact on thyroid function. Scoliosis can also affect the integumentary system, leading to pressure ulcers, altered skin sensation, and hygiene challenges. In the lymphatic system, scoliosis can cause lymphatic obstruction, impaired immune response, altered inflammatory responses, fibrosis, and secondary lymphedema. Scoliosis can affect the muscular system, leading to muscle imbalance, myofascial pain, respiratory muscle weakness, and mobility issues. The nervous system can also be impacted by scoliosis, leading to neural compression, central nervous system impact, neurological dysfunction, and coordination challenges. In the respiratory system, scoliosis can cause thoracic deformities, reduced lung compliance, ventilation-perfusion mismatch, respiratory muscle weakness, increased work of breathing (WOB), and an increased risk of respiratory infections.Recognizing and addressing the interplay between scoliosis and these physiological systems is integral for healthcare professionals to provide comprehensive care to individuals with scoliosis.Current research on scoliosis has made progress in diagnostic tools and techniques, including the use of imaging methods like MRI and X-ray, wearable sensors, and 3D reconstruction techniques for better evaluation of spinal motion and function, along with treatment strategies like Schroth exercises and braces, and management measures for respiratory and circulatory problems. However, there are limitations to current studies, such as the heterogeneity of scoliosis, compartmentalized approaches, limited longitudinal studies, reliance on retrospective data, and the need for standardized measures and diagnostic criteria. Future research prospects include advancements in genetic research, biomechanics, artificial intelligence and machine learning, longitudinal studies, non-invasive treatments, and multidisciplinary collaborations among researchers, clinicians, and technologists.

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Section: Limitations Of Studiesmentioning

confidence: 99%

The Pathophysiology of Scoliosis Across the Spectrum of Human Physiological Systems

Kerna,

Carsrud,

Zhao

et al. 2024

ejmhr

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“…Further, MSK models allow for sensitivity analyses, such as the effect of intervertebral joint (IVJ) location and soft tissue properties on the compressive loads that the vertebrae experience ( Senteler et al, 2016 ; Byrne et al, 2020 ). They, therefore, have the potential to reduce the risk of spinal injuries and improve spinal surgery outcomes ( Beaucage-Gauvreau et al, 2019 ; Gould et al, 2021 ; Dall’Ara et al, 2022 ), and so reduce the cost to individuals and society.…”

Section: Introductionmentioning

confidence: 99%

“…MSK models of the spine often simplify the IVJ to three rotational degrees of freedom (DoF) with a fixed centre of rotation ( Petit et al, 2004 ; Han et al, 2012 ), although more recent studies have included translational DoF ( Meng et al, 2015 ; Ignasiak et al, 2016 ; Arshad et al, 2017 ). The mechanical properties of the IVJs are not included in all models and if present are simplified to a lumped parameter spring-damper model, commonly referred to as a bushing force ( Silvestros et al, 2019 ; Wang et al, 2019 ; 2021 ; Alizadeh et al, 2020 ; Gould et al, 2021 ). Parameters for the bushing force are taken from the literature ( Han et al, 2012 ; Christophy et al, 2013 ; Ignasiak et al, 2016 ; Senteler et al, 2016 ; Arshad et al, 2017 ; Zhang et al, 2020 ; Remus et al, 2021 ; Lerchl et al, 2022 ) and applied in each DoF ( Silvestros et al, 2019 ; Wang et al, 2019 ; 2021 ; Alizadeh et al, 2020 ; Gould et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

“…The mechanical properties of the IVJs are not included in all models and if present are simplified to a lumped parameter spring-damper model, commonly referred to as a bushing force ( Silvestros et al, 2019 ; Wang et al, 2019 ; 2021 ; Alizadeh et al, 2020 ; Gould et al, 2021 ). Parameters for the bushing force are taken from the literature ( Han et al, 2012 ; Christophy et al, 2013 ; Ignasiak et al, 2016 ; Senteler et al, 2016 ; Arshad et al, 2017 ; Zhang et al, 2020 ; Remus et al, 2021 ; Lerchl et al, 2022 ) and applied in each DoF ( Silvestros et al, 2019 ; Wang et al, 2019 ; 2021 ; Alizadeh et al, 2020 ; Gould et al, 2021 ). Despite these simplifications, representing the IVJ with a bushing force is complex due to the interaction between joint pose and stiffness which influences the predicted joint loads and muscle forces ( Byrne et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

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Variability of intervertebral joint stiffness between specimens and spine levels

Gould,

Davico,

Liebsch

et al. 2024

Front. Bioeng. Biotechnol.

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Introduction: Musculoskeletal multibody models of the spine can be used to investigate the biomechanical behaviour of the spine. In this context, a correct characterisation of the passive mechanical properties of the intervertebral joint is crucial. The intervertebral joint stiffness, in particular, is typically derived from the literature, and the differences between individuals and spine levels are often disregarded.Methods: This study tested if an optimisation method of personalising the intervertebral joint stiffnesses was able to capture expected stiffness variation between specimens and between spine levels and if the variation between spine levels could be accurately captured using a generic scaling ratio. Multibody models of six T12 to sacrum spine specimens were created from computed tomography data. For each specimen, two models were created: one with uniform stiffnesses across spine levels, and one accounting for level dependency. Three loading conditions were simulated. The initial stiffness values were optimised to minimize the kinematic error.Results: There was a range of optimised stiffnesses across the specimens and the models with level dependent stiffnesses were less accurate than the models without. Using an optimised stiffness substantially reduced prediction errors.Discussion: The optimisation captured the expected variation between specimens, and the prediction errors demonstrated the importance of accounting for level dependency. The inaccuracy of the predicted kinematics for the level-dependent models indicated that a generic scaling ratio is not a suitable method to account for the level dependency. The variation in the optimised stiffnesses for the different loading conditions indicates personalised stiffnesses should also be considered load-specific.

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“… Le Navéaux et al (2016) developed biomechanical models to analyze the effects of implant density and distribution on curve correction and the resulting forces on the vertebrae. Gould et al (2021) published a literature review of computational modeling of the spine, focusing on both modeling approaches and healthy and scoliotic patients.…”

Section: Introductionmentioning

confidence: 99%

Biomechanical Morphing for Personalized Fitting of Scoliotic Torso Skeleton Models

Koutras

Shayestehpour

Pérez

et al. 2022

Front. Bioeng. Biotechnol.

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The use of patient-specific biomechanical models offers many opportunities in the treatment of adolescent idiopathic scoliosis, such as the design of personalized braces. The first step in the development of these patient-specific models is to fit the geometry of the torso skeleton to the patient’s anatomy. However, existing methods rely on high-quality imaging data. The exposure to radiation of these methods limits their applicability for regular monitoring of patients. We present a method to fit personalized models of the torso skeleton that takes as input biplanar low-dose radiographs. The method morphs a template to fit annotated points on visible portions of the spine, and it relies on a default biomechanical model of the torso for regularization and robust fitting of hardly visible parts of the torso skeleton, such as the rib cage. The proposed method provides an accurate and robust solution to obtain personalized models of the torso skeleton, which can be adopted as part of regular management of scoliosis patients. We have evaluated the method on ten young patients who participated in our study. We have analyzed and compared clinical metrics on the spine and the full torso skeleton, and we have found that the accuracy of the method is at least comparable to other methods that require more demanding imaging methods, while it offers superior robustness to artifacts such as interpenetration of ribs. Normal-dose X-rays were available for one of the patients, and for the other nine we acquired low-dose X-rays, allowing us to validate that the accuracy of the method persisted under less invasive imaging modalities.

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Computational modelling of the scoliotic spine: A literature review

Cited by 13 publications

References 155 publications

The Pathophysiology of Scoliosis Across the Spectrum of Human Physiological Systems

The Pathophysiology of Scoliosis Across the Spectrum of Human Physiological Systems

Variability of intervertebral joint stiffness between specimens and spine levels

Biomechanical Morphing for Personalized Fitting of Scoliotic Torso Skeleton Models

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