01 Jan 24. Featured Paper

Detectability and accuracy of computational measurements of in-silico and physical representations of enlarged perivascular spaces from magnetic resonance images

Link to paper at Pub Med

Authors

Roberto Duarte Coello  Maria Del C Valdés Hernández,  Jaco J M Zwanenburg, Moniek van der Velden, Hugo J Kuijf, Alberto De Luca, José Bernal Moyano, Lucia Ballerini, Francesca M Chappell, Rosalind Brown, Geert Jan Biessels, Joanna M Wardlaw

Abstract

Background

Magnetic Resonance Imaging (MRI) visible perivascular spaces (PVS) have been associated with age, decline in cognitive abilities, interrupted sleep, and markers of small vessel disease. But the limits of validity of their quantification have not been established

New method

We use a purpose-built digital reference object to construct an in-silico phantom for addressing this need, and validate it using a physical phantom. We use cylinders of different sizes as models for PVS. We also evaluate the influence of 'PVS' orientation, and different sets of parameters of the two vesselness filters that have been used for enhancing tubular structures, namely Frangi and RORPO filters, in the measurements' accuracy.

Results

PVS measurements in MRI are only a proxy of their true dimensions, as the boundaries of their representation are consistently overestimated. The success in the use of the Frangi filter relies on a careful tuning of several parameters. Alpha= 0.5, beta= 0.5 and c= 500 yielded the best results. RORPO does not have these requirements and allows detecting smaller cylinders in their entirety more consistently in the absence of noise and confounding artefacts. The Frangi filter seems to be best suited for voxel sizes equal or larger than 0.4 mm-isotropic and cylinders larger than 1 mm diameter and 2 mm length. 'PVS' orientation did not affect measurements in data with isotropic voxels.

Conclusions

The in-silico and physical phantoms presented are useful for establishing the validity of quantification methods of tubular small structures.

Keywords

• MRI phantom
• Perivascular spaces
• Virchow-Robin spaces