High resolution 7T and 9.4T-MRI of human cerebral arterial casts enables accurate estimations of the cerebrovascular morphometry.
Jasper H G HelthuisAlbert van der ZwanTristan P C van DoormaalRonald L A W BleysAnita A HarteveldAnnette van der ToornMariana BroziciJeroen HendrikseJaco J M ZwanenburgPublished in: Scientific reports (2018)
Quantitative data on the morphology of the cerebral arterial tree could aid in modelling and understanding cerebrovascular diseases, but is scarce in the range between 200 micrometres and 1 mm diameter arteries. Traditional manual measurements are difficult and time consuming. 7T-MRI and 9.4T-MRI of human cerebral arterial plastic casts could proof feasible for acquiring detailed morphological data of the cerebral arterial tree in a time efficient method. One cast of the complete human cerebral arterial circulation embedded in gadolinium-containing gelatine gel was scanned at 7T-MRI (0.1 mm isotropic resolution). A small section of another cast was scanned at 9.4T-MRI (30 µm isotropic resolution). Subsequent 3D-reconstruction was performed using a semi-automatic approach. Validation of 7T-MRI was performed by comparing the radius calculated using MRI to manual measurements on the same cast. As manual measurement of the small section was not feasible, 9.4T-MRI was validated by scanning the small section both at 7T-MRI and 9.4T MRI and comparing the diameters of arterial segments. Linear regression slopes were 0.97 (R-squared 0.94) and 1.0 (R-squared 0.90) for 7T-MRI and 9.4T-MRI. This data shows that 7T-MRI and 9.4T-MRI and subsequent 3D reconstruction of plastic casts is feasible, and allows for characterization of human cerebral arterial tree morphology.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- diffusion weighted imaging
- high resolution
- endothelial cells
- subarachnoid hemorrhage
- computed tomography
- magnetic resonance
- machine learning
- deep learning
- electronic health record
- mass spectrometry
- brain injury
- big data
- induced pluripotent stem cells
- clinical evaluation