Hélène Raoult1, Elise Bannier2, Pierre Maurel2, Clément Neyton2, Jean-Christophe Ferré2, Peter Schmitt2, Christian Barillot2, Jean-Yves Gauvrit2. 1. From the CHU Rennes, Department of Neuroradiology, Rennes, France (H.R., J.-C.F., J.-Y.G.); Unité VISAGES U746 INSERM-INRIA, IRISA UMR CNRS 6074, University of Rennes, Rennes, France (H.R., E.B., P.M., C.N., J.-C.F., C.B., J.-Y.G); and MR Application & Workflow Development, Siemens AG, Healthcare Sector, Erlangen, Germany (P.S.). helene.raoult@chu-rennes.fr. 2. From the CHU Rennes, Department of Neuroradiology, Rennes, France (H.R., J.-C.F., J.-Y.G.); Unité VISAGES U746 INSERM-INRIA, IRISA UMR CNRS 6074, University of Rennes, Rennes, France (H.R., E.B., P.M., C.N., J.-C.F., C.B., J.-Y.G); and MR Application & Workflow Development, Siemens AG, Healthcare Sector, Erlangen, Germany (P.S.).
Abstract
BACKGROUND AND PURPOSE: Unenhanced time-resolved spin-labeled magnetic resonance angiography enables hemodynamic quantification in arteriovenous malformations (AVMs). Our purpose was to identify quantitative parameters that discriminate among different AVM components and to relate hemodynamic patterns with rupture risk. METHODS: Sixteen patients presenting with AVMs (7 women, 9 men; mean age 37.1±15.9 years) were assigned to the high rupture risk or low rupture risk group according to anatomic AVM characteristics and rupture history. High temporal resolution (<70 ms) unenhanced time-resolved spin-labeled magnetic resonance angiography was performed on a 3-T MR system. After dedicated image processing, hemodynamic quantitative parameters were computed. T tests were used to compare quantitative parameters among AVM components, between the high rupture risk and low rupture risk groups, and between the hemorrhagic and nonhemorrhagic groups. RESULTS: Among the quantitative parameters, time-to-peak (P<0.001) and maximum outflow gradient (P=0.01) allowed discriminating various intranidal flow patterns with significantly different values between feeding arteries and draining veins. With 9 AVMs classified into the high rupture risk group (whose 6 were hemorrhagic) and 7 into the low rupture risk group, the observed venous-to-arterial time-to-peak ratio was significantly lower in the high rupture risk (P=0.003) and hemorrhagic (P=0.001) groups. CONCLUSIONS: Unenhanced time-resolved spin-labeled magnetic resonance angiography allows AVM-specific combined anatomic and quantitative analysis of AVM hemodynamics.
BACKGROUND AND PURPOSE: Unenhanced time-resolved spin-labeled magnetic resonance angiography enables hemodynamic quantification in arteriovenous malformations (AVMs). Our purpose was to identify quantitative parameters that discriminate among different AVM components and to relate hemodynamic patterns with rupture risk. METHODS: Sixteen patients presenting with AVMs (7 women, 9 men; mean age 37.1±15.9 years) were assigned to the high rupture risk or low rupture risk group according to anatomic AVM characteristics and rupture history. High temporal resolution (<70 ms) unenhanced time-resolved spin-labeled magnetic resonance angiography was performed on a 3-T MR system. After dedicated image processing, hemodynamic quantitative parameters were computed. T tests were used to compare quantitative parameters among AVM components, between the high rupture risk and low rupture risk groups, and between the hemorrhagic and nonhemorrhagic groups. RESULTS: Among the quantitative parameters, time-to-peak (P<0.001) and maximum outflow gradient (P=0.01) allowed discriminating various intranidal flow patterns with significantly different values between feeding arteries and draining veins. With 9 AVMs classified into the high rupture risk group (whose 6 were hemorrhagic) and 7 into the low rupture risk group, the observed venous-to-arterial time-to-peak ratio was significantly lower in the high rupture risk (P=0.003) and hemorrhagic (P=0.001) groups. CONCLUSIONS: Unenhanced time-resolved spin-labeled magnetic resonance angiography allows AVM-specific combined anatomic and quantitative analysis of AVM hemodynamics.
Authors: W Chang; Y Wu; K Johnson; M Loecher; O Wieben; M Edjlali; C Oppenheim; P Roca; J Hald; B Aagaard-Kienitz; D Niemann; C Mistretta; P Turski Journal: AJNR Am J Neuroradiol Date: 2015-02-19 Impact factor: 3.825
Authors: Y Takeda; T Kin; T Sekine; H Hasegawa; Y Suzuki; H Uchikawa; T Koike; S Kiyofuji; Y Shinya; M Kawashima; N Saito Journal: AJNR Am J Neuroradiol Date: 2021-10-07 Impact factor: 3.825
Authors: K H Narsinh; K Mueller; J Nelson; J Massachi; D C Murph; A Z Copelan; S W Hetts; V V Halbach; R T Higashida; A A Abla; M R Amans; C F Dowd; H Kim; D L Cooke Journal: AJNR Am J Neuroradiol Date: 2020-10-29 Impact factor: 3.825
Authors: Xiaolin Chen; Daniel L Cooke; David Saloner; Jeffrey Nelson; Hua Su; Michael T Lawton; Christopher Hess; Tarik Tihan; Yuanli Zhao; Helen Kim Journal: Stroke Date: 2017-08-30 Impact factor: 7.914
Authors: Maria Aristova; Alireza Vali; Sameer A Ansari; Ali Shaibani; Tord D Alden; Michael C Hurley; Babak S Jahromi; Matthew B Potts; Michael Markl; Susanne Schnell Journal: J Magn Reson Imaging Date: 2019-05-09 Impact factor: 4.813
Authors: Hyo Jung Seo; Jefferson R Pagsisihan; Jin Chul Paeng; Seung Hong Choi; Gi Jeong Cheon; June-Key Chung; Dong Soo Lee; Keon Wook Kang Journal: Yonsei Med J Date: 2015-11 Impact factor: 2.759