Advances In Neuroradiology
Magnetic resonance imaging (MRI) is well-established in neuroimaging due to its relative abundance, non-invasive, and free from ionising radiation ability. MRI can detect both brain perfusion and metabolic activity and hence plays a vital role in neuro imaging. It can help in identifying both congenital and degenerative disease processes in the brain. The advances in neuroradiology are constantly evolving from sequence modifications and inventions to data analysis. It can enable various neuro-imaging technologies such as anatomical images and functional and quantitative data for diffusion-weighted imaging (DWI), spectroscopy, blood oxygenation level-dependent functional MRI, and T1/T2 mapping dynamic contrast-enhanced imaging.
A few recent trends in medical imaging have been elaborated on here.
Volumetric MRI
T1-weighted MR imaging has increased sensitivity to assess epileptogenic lesions. The Hallmark of Temporal lobe epilepsy (TLE) is hippocampal volume loss, signal changes ad loss of internal architecture. There may be artificial smoothing during the initial processing of 3T MRI, which can be more accurately assessed by increasing the spatial resolution to 7T imaging. [1] Volumetric MRI in Huntington’s disease is characterised by a reduction in regional brain volume that correlates to disease characteristics. Even before the onset of motor symptoms volume loss is seen in the caudate and putamen, whereas loss in cortical regions is more widespread and may be seen after clinical motor diagnosis.
Diffusion-weighted imaging
Diffusion-weighted MRI (DW-MRI) deploys a magnetic field that sensitises MRI signals to characterise cell sizes, density, and morphology. The diffusion tensor imaging (DTI) signal model is sensitive to macro and microstructural tissue. The diffusion kurtosis imaging (DKI) signal model provides more sensitive and accurate information about tissue microstructure when compared to DTI. The Composite hindered and restricted model of diffusion (CHARMED) is a multi-compartment model that is helpful to know the axonal density and extra-axonal diffusion tensor. The orientation dispersion index, neurite density index, and isotropic volume fraction can be known by neurite orientation dispersion and density imaging (NODDI). Microstructural measures and more sensitive than DTI indices as they provide additional information and more accurate and powerful biomarkers of tissue disease burden in multiple sclerosis. NODDI metrics are found to be associated with cognition in Alzheimer disease in the early stages. DKI can enable distinguishing gliomas from other intra-axial brain tumors. It can differentiate between high and low-grade gliomas with a sensitivity of 0.87. Read more here about Neuro Radiology
