European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
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Vertebral Body Tethering (VBT), an alternative treatment for adolescent idiopathic scoliosis, shows satisfactory post-operative results. However, the biomechanical quantities and consequences after VBT surgery remain largely unknown. Therefore, the aim of this study is to analyze the spinal biomechanics during different motions using a multibody simulation approach. ⋯ The biomechanical data provide a first impression of the forces that occur along the spine during various physiological movements and are consistent with published clinical data. Forces are not evenly distributed along the spine, with higher lumbar forces. The tether forces reach values during lateral bending that can potentially destroy the tether´s integrity and thus may explain the common post-operative complication, namely tether breakage. The results of the model can therefore have an impact on future directions for improved surgical VBT treatment.
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To compare the mechanical properties of human annulus fibrosus obtained by forceps versus bistoury and observe whether the measurement could be affected by forceps sampling method. ⋯ The results indicate that the forceps sampling method has a substantial negative effect on the micromechanical properties of the ECM of the annulus fibrosus. Bistoury sampling method is recommended as the experimental subject for exploring the micromechanics mechanisms of cervical degenerative disease.
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The Cobb angle is a standard measurement to qualify and track the progression of scoliosis. However, the Cobb angle has high inter- and intra-observer variability. Consequently, its measurement varies with vertebrae and may even differ when the same vertebra is measured. Therefore, it is not constant and differs with measurements. This study aimed to develop a deep learning model that automatically measures the Cobb angle. The deep learning model for identifying vertebrae on spine radiographs was developed. ⋯ The authors believe the model will be useful in clinical practice by relieving clinicians of the burden of having to manually compute the Cobb angle. Further studies are needed to enhance the accuracy and versatility of this deep learning model.