Search results for "Cervical myelopathy"
showing 4 items of 4 documents
Cervical Spondylotic Myelopathy: When and Why the Cervical Corpectomy?
2020
Background: Cervical spondylotic myelopathy (CSM) is a degenerative disease that represents the most common spinal cord disorder in adults. The best treatment option has remained controversial. We performed a prospective study to evaluate the clinical, radiographic, and neurophysiologic outcomes for anterior cervical corpectomy in the treatment of CSM. Methods: From January 2011 to January 2017, 60 patients with CSM were prospectively enrolled in the present study. The patients were divided according to the modified Japanese Orthopaedic Association scale (mJOA) score into 2 groups: group A, patients with mild to moderate CSM (mJOA score ≥13); and group B, patients with severe myelopathy (mJ…
A cervical myelopathy with a Hirayama disease-like phenotype
2008
A 21-year-old man with a muscular atrophy of the left distal upper extremity is presented. The disorder had been progressive over a few years, showing an exacerbation of the hand's weakness when the patient worked in a chilled environment (i.e., in a cold room). The patient's diagnostic work-up was extensive and the MRI documented the presence of a cervical myelopathy, associated to an inversion of the physiological lordosis at the C5-C6 level, with a phenotype highly resembling Hirayama disease. This case indirectly supports the debated hypothesis that juvenile amyotrophy of the upper limb (Hirayama disease) is actually a type of cervical myelopathy, with a likely ischaemic pathogenesis of…
Use of Machine Learning and Artificial Intelligence to Drive Personalized Medicine Approaches for Spine Care
2020
Personalized medicine is a new paradigm of healthcare in which interventions are based on individual patient characteristics rather than on “one-size-fits-all” guidelines. As epidemiological datasets continue to burgeon in size and complexity, powerful methods such as statistical machine learning and artificial intelligence (AI) become necessary to interpret and develop prognostic models from underlying data. Through such analysis, machine learning can be used to facilitate personalized medicine via its precise predictions. Additionally, other AI tools, such as natural language processing and computer vision, can play an instrumental part in personalizing the care provided to patients with …
Diagnostic potential of the diffusion tensor tractography with fractional anisotropy in the diagnosis and treatment of cervical spondylotic and postt…
2016
Background: Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI)-based methodology widely used for the evaluation of microstructural integrity of the central nervous system (CNS), particularly of brain white matter fibers and bundles. Methods: The most common parameters evaluated in a DTI study are the fractional anisotropy (FA) and mean diffusivity (MD). Combining FA and MD analyses is commonly used in the evaluation of various types of brain pathologies, such as brain tumors, where a combined analysis allows an accurate tumor characterization. Results: Recent studies have shown that FA and MD could be of value in non-oncologic spinal pathology. In this regard, it has been …