Subvoxel vessel wall thickness measurements of the intracranial arteries using a convolutional neural network

Vessel wall thickening of the intracranial arteries has been associated with cerebrovascular disease and atherosclerotic plaque development. Visualization of the vessel wall has been enabled by recent advancements in vessel wall MRI. However, quantifying early wall thickening from these MR images is difficult and prone to severe overestimation, because the voxel size of clinically used acquisitions exceeds the wall thickness of the intracranial arteries. In this study, we aimed for accurate and precise subvoxel vessel wall thickness measurements. A convolutional neural network was trained on MR images of 34 ex vivo circle of Willis specimens, acquired with a clinically used protocol (isotropic acquired voxel size: 0.8 mm). Ground truth measurements were performed on images acquired with an ultra-high-resolution protocol (isotropic acquired voxel size: 0.11 mm) and were used for evaluation. Additionally, we determined the robustness of our method by applying Monte Carlo dropout and test time augmentation. Lastly, we applied our method on in vivo images of three intracranial aneurysms to measure their wall thickness. Our method shows resolvability of different vessel wall thicknesses, well below the acquired voxel size. The method described may facilitate quantitative measurements on MRI data for a wider range of clinical applications.

Update on retinal vessel structure measurement with spectral-domain optical coherence tomography

This study was conducted to demonstrate a new scan method for retinal vessel structure measurement in a specific region of fundus (zone B) using spectral-domain optical coherence tomography (SD-OCT), and to assess its reliability. One temporal superior retinal vessel pair passing through a concentric ring (zone B), which was defined between half and one disc distance from the optic disc border, was chosen for the measurement using a volume scan in SD-OCT. On the SD-OCT image, retinal arteriolar outer diameter (RAOD), retinal arteriolar lumen diameter (RALD), retinal venular outer diameter (RVOD) and retinal venular lumen diameter (RVLD) were measured. Retinal vessel diameters on color fundus photographs were also analyzed. Fifty-five healthy individuals were recruited to evaluate intraobserver and interobserver reproducibility between the two examiners. The intraobserver intraclass correlation coefficient (ICC) ranged from 0.972 to 0.981, and the interobserver ICC ranged from 0.968 to 0.980. In the Bland-Altman plot, the 95% limits of interobserver agreement for the RAOD, RALD, RVOD and RVLD were -5.60 to 4.84μm, -5.78 to 5.05μm, -7.52 to 5.62μm and -7.10 to 5.63μm, respectively. The retinal arteriolar and venular lumen diameters on the SD-OCT image were close to the mean arteriolar and venular diameters obtained from the color fundus photographs. Volume scan method produced better images of retinal vessels showing the fine structures of the vessel wall, and provided reliable retinal vessel structure measurement in zone B with good repeatability and reproducibility.