BACKGROUND AND PURPOSE: Hemodynamic properties of brain arteriovenous malformations (AVMs) with risk factors for a future hemorrhage are essentially unknown. We hypothesized that AVMs with anatomic properties, which are associated with an increased rupture risk, exhibit different hemodynamic characteristics than those without these properties. METHODS: Seventy-two consecutive patients with AVMs diagnosed by conventional angiography underwent MRI examination, including time-resolved 3-dimensional MR angiography. Signal-intensity curves derived from the time-resolved 3-dimensional MR angiography datasets were used to calculate relative blood flow transit times through the AVM nidus based on the time-to-peak parameter. For identification of characteristics associated with altered transit times, a multiple normal regression model was fitted with stepwise selection of the following regressors: intracranial hemorrhage, deep nidus location, infratentorial location, deep drainage, associated aneurysm, nidus size, draining venous stenosis, and number of draining veins. RESULTS: A previous intracranial hemorrhage is the only characteristic that was associated with a significant alteration of the relative transit time, leading to an increase of 2.4 seconds (95% CI, 1.2-3.6 seconds;, P<0.001) without adjustment and 2.1 seconds (95% CI, 0.6-3.6 seconds; P=0.007) with adjustment for all other regressors considered. The association was independent of the bleeding age. CONCLUSIONS: Hemodynamic parameters do not seem useful for risk assessment of an AVM-related hemorrhage because only a previous AVM rupture leads to a significant and permanent alteration of the hemodynamic situation.
BACKGROUND AND PURPOSE: Hemodynamic properties of brain arteriovenous malformations (AVMs) with risk factors for a future hemorrhage are essentially unknown. We hypothesized that AVMs with anatomic properties, which are associated with an increased rupture risk, exhibit different hemodynamic characteristics than those without these properties. METHODS: Seventy-two consecutive patients with AVMs diagnosed by conventional angiography underwent MRI examination, including time-resolved 3-dimensional MR angiography. Signal-intensity curves derived from the time-resolved 3-dimensional MR angiography datasets were used to calculate relative blood flow transit times through the AVM nidus based on the time-to-peak parameter. For identification of characteristics associated with altered transit times, a multiple normal regression model was fitted with stepwise selection of the following regressors: intracranial hemorrhage, deep nidus location, infratentorial location, deep drainage, associated aneurysm, nidus size, draining venous stenosis, and number of draining veins. RESULTS: A previous intracranial hemorrhage is the only characteristic that was associated with a significant alteration of the relative transit time, leading to an increase of 2.4 seconds (95% CI, 1.2-3.6 seconds;, P<0.001) without adjustment and 2.1 seconds (95% CI, 0.6-3.6 seconds; P=0.007) with adjustment for all other regressors considered. The association was independent of the bleeding age. CONCLUSIONS: Hemodynamic parameters do not seem useful for risk assessment of an AVM-related hemorrhage because only a previous AVM rupture leads to a significant and permanent alteration of the hemodynamic situation.
Authors: C Wu; S A Ansari; A R Honarmand; P Vakil; M C Hurley; B R Bendok; J Carr; T J Carroll; M Markl Journal: AJNR Am J Neuroradiol Date: 2015-02-26 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: Nils Daniel Forkert; Till Illies; Einar Goebell; Jens Fiehler; Dennis Säring; Heinz Handels Journal: Int J Comput Assist Radiol Surg Date: 2013-03-07 Impact factor: 2.924