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DOI 10.1111/jon.12853

Медицинская библиотека · Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2021

Conventional and advanced MRI evaluation of brain vascular malformations.

Martín-Noguerol Teodoro, Concepción-Aramendia Luis, Lim Cc Tchoyoson, Santos-Armentia Eloísa, Cabrera-Zubizarreta Alberto, Luna Antonio

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Аннотация

Vascular malformations (VMs) of the central nervous system (CNS) include a wide range of pathological conditions related to intra and extracranial vessel abnormalities. Although some VMs show typical neuroimaging features, other VMs share and overlap pathological and neuroimaging features that hinder an accurate differentiation between them. Hence, it is not uncommon to misclassify different types of VMs under the general heading of arteriovenous malformations. Thorough knowledge of the imaging findings of each type of VM is mandatory to avoid these inaccuracies. Conventional MRI sequences, including MR angiography, have allowed the evaluation of CNS VMs without using ionizing radiation. Newer MRI techniques, such as susceptibility-weighted imaging, black blood sequences, arterial spin labeling, and 4D flow imaging, have an added value of providing physiopathological data in real time regarding the hemodynamics of VMs. Beyond MR images, new insights using 3D printed models are being incorporated as part of the armamentarium for a noninvasive evaluation of VMs. In this paper, we briefly review the pathophysiology of CNS VMs, focusing on the MRI findings that may be helpful to differentiate them. We discuss the role of each conventional and advanced MRI sequence for VMs assessment and provide some insights about the value of structured reports of 3D printing to evaluate VMs.

Для цитирования: Martín-Noguerol Teodoro, Concepción-Aramendia Luis, Lim Cc Tchoyoson, Santos-Armentia Eloísa, Cabrera-Zubizarreta Alberto, Luna Antonio. Conventional and advanced MRI evaluation of brain vascular malformations.. Journal of neuroimaging : official journal of the American Society of Neuroimaging. 2021. DOI: 10.1111/jon.12853.

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