Rachel Kleinloog1, Emine Korkmaz, Jaco J M Zwanenburg, Hugo J Kuijf, Fredy Visser, Roos Blankena, Jan A Post, Ynte M Ruigrok, Peter R Luijten, Luca Regli, Gabriel J E Rinkel, Bon H Verweij. 1. *Department of Neurology and Neurosurgery, Brain Center Rudolf Magnus, §Image Sciences Institute, and ¶Department of Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; ‡Biomolecular Imaging, Department of Biology, Science Faculty, Utrecht University, Utrecht, the Netherlands; ‖Philips Healthcare, Best, the Netherlands; #Faculty of Science and Technology, Department of Technical Medicine, University of Twente, Enschede, the Netherlands; **Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland.
Abstract
BACKGROUND: Risk prediction of rupture of intracranial aneurysms is poor and is based mainly on lumen characteristics. However, characteristics of the aneurysm wall may be more informative predictors. The limited resolution of currently available imaging techniques and the thin aneurysm wall make imaging of wall thickness challenging. OBJECTIVE: To introduce a novel protocol for imaging wall thickness variation using ultra--high-resolution 7.0-Tesla (7.0-T) magnetic resonance imaging (MRI). METHODS: We studied 33 unruptured intracranial aneurysms in 24 patients with a T1-weighted 3-dimensional magnetization-prepared inversion-recovery turbo-spin-echo whole-brain sequence with a resolution of 0.8 × 0.8 × 0.8 mm. We performed a validation study with a wedge phantom and with 2 aneurysm wall biopsies obtained during aneurysm treatment using ex vivo MRI and histological examination and correlating variations in MRI signal intensity with variations in actual thickness of the aneurysm wall. RESULTS: In vivo, the aneurysm wall was visible in 28 of the 33 aneurysms. Variation in signal intensity was observed in all visible aneurysm walls. Ex vivo MRI showed variation in signal intensity across the wall of the biopsies, similar to that observed on the in vivo images. Signal intensity and actual thickness in both biopsies had a linear correlation, with Pearson correlation coefficients of 0.85 and 0.86. CONCLUSION: Unruptured intracranial aneurysm wall and its variation in thickness can be visualized with 7.0-T MRI. Aneurysm wall thickness variation can now be further studied as a risk factor for rupture in prospective studies.
BACKGROUND: Risk prediction of rupture of intracranial aneurysms is poor and is based mainly on lumen characteristics. However, characteristics of the aneurysm wall may be more informative predictors. The limited resolution of currently available imaging techniques and the thin aneurysm wall make imaging of wall thickness challenging. OBJECTIVE: To introduce a novel protocol for imaging wall thickness variation using ultra--high-resolution 7.0-Tesla (7.0-T) magnetic resonance imaging (MRI). METHODS: We studied 33 unruptured intracranial aneurysms in 24 patients with a T1-weighted 3-dimensional magnetization-prepared inversion-recovery turbo-spin-echo whole-brain sequence with a resolution of 0.8 × 0.8 × 0.8 mm. We performed a validation study with a wedge phantom and with 2 aneurysm wall biopsies obtained during aneurysm treatment using ex vivo MRI and histological examination and correlating variations in MRI signal intensity with variations in actual thickness of the aneurysm wall. RESULTS: In vivo, the aneurysm wall was visible in 28 of the 33 aneurysms. Variation in signal intensity was observed in all visible aneurysm walls. Ex vivo MRI showed variation in signal intensity across the wall of the biopsies, similar to that observed on the in vivo images. Signal intensity and actual thickness in both biopsies had a linear correlation, with Pearson correlation coefficients of 0.85 and 0.86. CONCLUSION: Unruptured intracranial aneurysm wall and its variation in thickness can be visualized with 7.0-T MRI. Aneurysm wall thickness variation can now be further studied as a risk factor for rupture in prospective studies.
Authors: M D I Vergouwen; D Backes; I C van der Schaaf; J Hendrikse; R Kleinloog; A Algra; G J E Rinkel Journal: AJNR Am J Neuroradiol Date: 2019-06-20 Impact factor: 3.825
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