Assessment of adolescent idiopathic scoliosis from body scanner image by finite element simulations

Measurement of distances and locations of thoracic and lumbar vertebral bodies from CT scans in cases of spinal deformation

BACKGROUND

Spinal deformations, except for acute injuries, are among the most frequent reasons for visiting an orthopaedic specialist and musculoskeletal treatment in adults and adolescents. Data on the morphology and anatomical structures of the spine are therefore of interest to orthopaedics, physicians, and medical scientists alike, in the broad field from diagnosis to therapy and in research.

METHODS

Along the course of developing supplementary methods that do not require the use of ionizing radiation in the assessment of scoliosis, twenty CT scans from females and males with various severity of spinal deformations and body shape have been analysed with respect to the transverse distances between the vertebral body and the spinous process end tip and the skin, respectively, at thoracic and lumbar vertebral levels. Further, the locations of the vertebral bodies have been analysed in relation to the patient's individual body shape and shown together with those from other patients by normalization to the area encompassed by the transverse body contour.

RESULTS

While the transverse distance from the vertebral body to the skin varies between patients, the distances from the vertebral body to the spinous processes end tips tend to be rather similar across different patients of the same gender. Tables list the arithmetic mean distances for all thoracic and lumbar vertebral levels and for different regions upon grouping into mild, medium, and strong spinal deformation and according to the range of spinal deformation.

CONCLUSIONS

The distances, the clustering of the locations of the vertebral bodies as a function of the vertebral level, and the trends therein could in the future be used in context with biomechanical modeling of a patient's individual spinal deformation in scoliosis assessment using 3D body scanner images during follow-up examinations.

Asymmetric Load Transmission Induces Facet Joint Subchondral Sclerosis and Hypertrophy in Patients with Idiopathic Adolescent Scoliosis: Evaluation Using Finite Element Model and Surgical Specimen

Adolescent idiopathic scoliosis (AIS) with thoracic curvature primarily progresses from the thoracolumbar region, causing abnormal twisting and rotation of the spinal column. This results in unbalanced, asymmetric loads on each vertebrae and increased demands on the thoracic facet joints to withstand rotational stress from adjacent vertebrae. However, no studies have focused on the stress distribution on the facet joints of the thoracic spine in patients with AIS. This study aimed to investigate the mechanical loading and its distribution on the thoracic facet joints of AIS patients using finite element (FE) analysis and surgical specimens. FE models of the thoracic spine were created from a total of 13 female AIS patients (Lenke type 1, n = 4; Lenke type 2, n = 4; Lenke type 3, n = 5). A load of 200 N on the T3 vertebrae and 30 N each on the bilateral superior articular processes were applied vertically to quantify the contact force on the facet joints from T3 to T11. In addition, morphological and histological analyses were performed on the inferior articular processes obtained during surgery. FE analysis demonstrated that contact forces of the facet joint progressively increased from the mid to lower thoracic spine of the concave side, reaching a maximum around the apex. More than 91% of the load was transmitted by the facet joints at the concave side, resulting in facet joint subchondral sclerosis and hypertrophy. The apical facet joint in AIS helps counteract rotational stress between vertebrae and transfers most stress through the concave side. In conclusion, this study found that asymmetric load transfer in the facet joints leads to subchondral sclerosis and hypertrophy. These findings can enhance our understanding of the stress loading on facet joints and the resulting biological changes and help clarify the mechanisms involved in scoliosis progression. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Current models to understand the onset and progression of scoliotic deformities in adolescent idiopathic scoliosis: a systematic review

PURPOSE

To create an updated and comprehensive overview of the modeling studies that have been done to understand the mechanics underlying deformities of adolescent idiopathic scoliosis (AIS), to predict the risk of curve progression and thereby substantiate etiopathogenetic theories.

METHODS

In this systematic review, an online search in Scopus and PubMed together with an analysis in secondary references was done, which yielded 86 studies. The modeling types were extracted and the studies were categorized accordingly.

RESULTS

Animal modeling, together with machine learning modeling, forms the category of black box models. This category is perceived as the most clinically relevant. While animal models provide a tangible idea of the biomechanical effects in scoliotic deformities, machine learning modeling was found to be the best curve-progression predictor. The second category, that of artificial models, has, just as animal modeling, a tangible model as a result, but focusses more on the biomechanical process of the scoliotic deformity. The third category is formed by computational models, which are very popular in etiopathogenetic parameter-based studies. They are also the best in calculating stresses and strains on vertebrae, intervertebral discs, and other surrounding tissues.

CONCLUSION

This study presents a comprehensive overview of the current modeling techniques to understand the mechanics of the scoliotic deformities, predict the risk of curve progression in AIS and thereby substantiate etiopathogenetic theories. Although AIS remains to be seen as a complex and multifactorial problem, the progression of its deformity can be predicted with good accuracy. Modeling of AIS develops rapidly and may lead to the identification of risk factors and mitigation strategies in the near future. The overview presented provides a basis to follow this development.

Reliability of a three-dimensional spinal proprioception assessment for patients with adolescent idiopathic scoliosis

PURPOSE

Although it is evident that some patients with adolescent idiopathic scoliosis (AIS) have proprioceptive deficit in peripheral joints, knowledge on the proprioceptive function of the deformed spine is limited. Nonetheless, spinal proprioception in AIS may be affected three-dimensionally, prior studies only focussed on evaluating peripheral proprioception in single plane. Therefore, this study aimed to develop a novel spinal proprioception assessment using three-dimensional motion analysis in patients with AIS.

METHODS

Participants were included if they had a primary diagnosis of AIS who did not receive or failed conservative treatments. Three trunk repositioning tests involving flexion-extension, lateral-flexion, and axial-rotation were conducted. A three-dimensional kinematics of the trunk was used as the outcome measures. The proprioceptive acuity was quantified by the repositioning error. The intra-examiner and test-retest reliability were analysed by the intraclass correlation coefficient (ICC).

RESULTS

Fifty-nine patients with AIS were recruited. Regarding the trunk flexion-extension test, the single measure ICC showed moderate reliability (0.46) and the average measures ICC demonstrated good reliability (0.72). As for the trunk lateral-flexion test, the reliability of single measure and average measures ICC was moderate (0.44) and good (0.70) reliability, respectively. For the trunk axial-rotation test, the single measure ICC indicated fair reliability (0.32), while the average measures ICC showed moderate reliability (0.59).

CONCLUSION

This is the first study to evaluate the reliability of novel three-dimensional spinal proprioception assessments in patients with AIS. The trunk flexion-extension repositioning test may be preferable clinical test given its highest reliability.

Scoliosis assessment tools to reduce follow-up X-rays

Purpose

Clinical examinations of scoliosis often includes X-rays. Regular clinical monitoring is recommended in particular at young age, because of the high risk of progression during periods of rapid growth. Supplementary methods free of ionizing radiation thus could help to reduce the potential risk of ionizing radiation related health problems.

Methods

Twelve 3D scan images from female and male patients with different types and severities of spinal deformations were analysed using body scanner image analysis tools. The scan images were captured with a 3D body scanner, which used an infrared sensor and a video camera. To calculate and compare with the patient's specific spinal deformations, simulations based on finite elements methods were performed on biomechanical models of ribcage and spinal column.

Results

The methods and parameters presented here are in good agreement with corresponding X-rays, used for comparison. High correlation coefficients of ‖ρ _s ‖ ≥ 0.87 between Cobb angle and lateral deviation, as well as between Cobb angle and rotation of the vertebrae, indicate that the parameters could provide supplementary informations in the assessment of spinal deformations. So-called apex angles, in addition introduced to relate the results of the present method with Cobb angles, show strong correlations of ‖ρ _s ‖ ≥ 0.68 and thus could be used for comparison in later follow-up examinations.

Conclusion

The user-friendly 3D body scanner image analysis tools enable orthopaedic specialists to simulate, visualize and inspect patient's specific spinal deformations. The method is intended to provide supplementary information in complement to the Cobb angle for the assessment of spinal deformations in clinical daily routine and might have the potential to reduce X-rays in follow-up examinations.

The Translational Potential of this article

The study presents a new method, based on 3D body scanner images and biomechanical modelling, that has the potential to reduce X-rays when monitoring scoliosis especially in young patients.

A non-invasive method for scoliosis assessment—A new mathematical concept using polar angle

Scoliosis is one of the most common pediatric spinal diseases that leads to a three-dimensional deformity of the spine and has a high risk of progression during growth. Regular clinical monitoring and follow-up X-rays are needed to providing proper treatment at that time. Repetitive X-rays can results in an increased risk of radiation related health problems. We present a non-invasive, ionizing radiation-free method for assessing scoliosis and its progression from the 3D images of the body torso, captured by a body scanner. A new concept is introduced based on a mathematical method in polar coordinate system to quantify and characterize the deformities in the torso from 2D transverse cross-sections of the 3D torso images at example cases for a healthy individual and for two patients with scoliosis. To capture quantitatively the characteristics of scoliosis, and to verify them at the example cases two asymmetry parameters and a linear fitting parameter are calculated: a) back side area asymmetry, b) left right area asymmetry, and c) coefficient of determination (R²). Within the analyzed patients, both the area asymmetries are maximum at the apex of scoliosis, and increase with the severity of scoliosis. R² values are smaller in the case of patients compared with the healthy. Furthermore, the parameters show a trend when compared with the Cobb angle from the X-ray and the findings match with clinical examination. Therefore, the quantities are able to capture, certain characteristics associated with scoliosis. These quantities can be compared as a measure of deformities of torso, during the follow-up examinations in the future, without ionizing radiations.

Model-Based Radiation-Free Assessment of Scoliosis: A Principle Validation Study

Purpose

Adolescent scoliosis is one of the common pediatric spinal diseases which has a high risk of progression due to the rapid growth of the skeleton during the growing stage therefore needs regular clinical monitoring including X-rays. Because X-rays could lead to ionizing radiation-related health problems, an ionizing radiation-free, non-invasive method is presented here to estimate the degree of scoliosis and to potentially support the medical assessment.

Methods

The radiation-free body scanner provides a 3D surface scan of the torso. A basic 3D structure of the human ribcage and vertebral column was modeled and simulated with computer-aided design software and finite element method calculation. For comparison with X-rays, courses of vertebral columns derived from 3D torso images and 3D models were analyzed with respect to their apex positions and angles.

Results

The methods show good results in the estimation of the apex positions of scoliosis. Strong correlations (R = 0.8924) were found between the apex and Cobb angle from X-rays. Similar correlations (R = 0.8087) was obtained between the apex angles extracted from X-rays and the combination of torso scan images with 3D model simulations. Promising agreement was obtained between the spinal trajectories extracted from X-ray and 3D torso images.

Conclusions

Very strong correlations suggest that the apex angle could potentially be used for scoliosis assessment in follow-up examinations in complement to the Cobb angle. However, further improvements of the methods and tests on a larger number of data set are necessary before their introduction into the clinical application.

Supervised and unsupervised learning to classify scoliosis and healthy subjects based on non-invasive rasterstereography analysis

The aim of our study was to classify scoliosis compared to to healthy patients using non-invasive surface acquisition via Video-raster-stereography, without prior knowledge of radiographic data. Data acquisitions were made using Rasterstereography; unsupervised learning was adopted for clustering and supervised learning was used for prediction model Support Vector Machine and Deep Network architectures were compared. A M-fold cross validation procedure was performed to evaluate the results. The accuracy and balanced accuracy of the best supervised model were close to 85%. Classification rates by class were measured using the confusion matrix, giving a low percentage of unclassified patients. Rasterstereography has turned out to be a good tool to distinguish subject with scoliosis from healthy patients limiting the exposure to unnecessary radiations.