Details

The study uses semi-automated detection of anatomical metrics (morphometric parameters) and DCC with Spinal Cord Toolbox (SCT). This method have been proven more reliable than expert's manual rating, the introduction of the automated method will be utilized in the future multi-centre and longitudinal studies. Routine anatomical morphometric parameters such as compressive ratio (CR) and cross-sectional area (CSA) will be acquired along with microstructural and metabolic metrics obtained with validated dMRI and MRS methods, remote cervical cord atrophy from voxel-based MRI volumetry, T2* white matter/gray matter (WM/GM) signal-intensity ratio, and also metrics obtained with novel Intravoxel Incoherent Motion (IVIM) method will predict progression of NMDCC into symptomatic DCM. "Natural course" (i.e., speed of progression) of the severity of DCC assessed with anatomical and advanced MRI/MRS metrics is not known but may play a role in the progression from NMDCC to symptomatic DCM. Aims of this project are: To determine independent predictors of unfavourable outcome - progression into symptomatic degenerative cervical myelopathy (DCM) - among quantitative MRI parameters and compare them with already defined clinical and electrophysiological predictors. To evaluate the "natural course" of MRI descriptors of compression and its severity, and the correlation between progression and development of symptomatic DCM. To implement automated detection of cervical cord compression using Spinal Cord Toolbox based on automatically computed morphometric parameters.