Surgical management of dysphagia due to diffuse idiopathic skeletal hyperostosis: the role of barium swallow fluoroscopy-a case report.

Background: Diffuse idiopathic skeletal hyperostosis (DISH) is a systemic condition that might lead to dysphagia because of massive osteophytes that may be present at multiple levels. Confirming the symptomatic level to guide surgical management and avoid extensive surgery is important, however, there is no globally accepted consensus on the topic.

Case Description: We report the case of a 51-year-old man, with no specific past medical history, who has been complaining of a 3-months pain in the left side of the tongue base with sensation of a lump in the throat and dysphagia.

Machine learning can predict surgical indication: new clustering model from a large adult spine deformity database.

Purpose: The choice of the best management for Adult Spine Deformity (ASD) is challenging. Health-related quality of life (HRQoL), comorbidities, symptoms and spine geometry, along with surgical risk and potential residual disability play a role, and a definite algorithm for patient management is lacking. Machine learning allows to analyse complex settings more efficiently than other available statistical tools.

Offset sublaminar hook is an efficient tool for the prevention of distal junctional failure after kyphotic deformity correction.

Purpose: To assess the radiological outcomes and complications focusing on distal junctional failure (DJF) of adult spinal deformity patients who underwent thoracolumbar fixation with the use of offset sublaminar hooks (OSH) distally.

Methods: Retrospective review of a prospective, multicenter adult spinal deformity database (2 sites). Inclusion criteria were age of at least 18 years, presence of a spinal deformity with thoraco-lumbar instrumentation ending distally with OSH (pelvis excluded), with minimum 2 years of follow-up.

Assessment of submicron bone tissue composition in plastic-embedded samples using optical photothermal infrared (O-PTIR) spectral imaging and machine learning.

Understanding the composition of bone tissue at the submicron level is crucial to elucidate factors contributing to bone disease and fragility. Here, we introduce a novel approach utilizing optical photothermal infrared (O-PTIR) spectroscopy and imaging coupled with machine learning analysis to assess bone tissue composition at 500 nm spatial resolution. This approach was used to evaluate thick bone samples embedded in typical poly(methyl methacrylate) (PMMA) blocks, eliminating the need for cumbersome thin sectioning.