Hélène Raoult1, Elise Bannier, Benjamin Robert, Christian Barillot, Peter Schmitt, Jean-Yves Gauvrit. 1. From the Department of Neuroradiology, CHU Rennes, 2 rue Henri Le Guilloux, Rennes 35000, France (H.R., J.Y.G.); Unité VISAGES U746 INSERM-INRIA, IRISA UMR CNRS 6074, University of Rennes, Rennes, France (H.R., E.B., C.B., J.Y.G.); Siemens S.A.S. SWE RC-FR H IM CS AMC, Saint-Denis, France (B.R.); and MR Application & Workflow Development, Siemens AG, Healthcare Sector, Erlangen, Germany (P.S.).
Abstract
PURPOSE: To assess time-resolved spin-labeled (SL) magnetic resonance (MR) angiographic imaging with a large acquisition time window over two cardiac cycles for characterization of cerebral arteriovenous malformations (AVMs). MATERIALS AND METHODS: This study was institutional review board-approved. Sixteen patients presented with an AVM, provided informed consent, and were prospectively included. Time-resolved SL MR angiographic images with acquisition window that covered two cardiac cycles (acquisition time, 10-12 min; temporal resolution, 60 msec) or one cardiac cycle and time-of-flight (TOF) MR angiographic images were acquired with a 3-T MR imager. A diagnostic confidence index was used for image quality evaluation; scores were 0, no diagnosis, to 3, high image quality. AVM characterization consisted of arterial feeder, nidus size, and venous drainage type identification compared with those at digital subtraction angiography (DSA). κ coefficients were computed to determine interobserver and intermodality agreement. RESULTS: Time-resolved SL MR angiographic imaging over two cardiac cycles provided a median diagnostic confidence index of 2.5 for arterial feeders, 3.0 for nidus, and 3.0 for venous drainage. Venous drainage depiction quality was higher with time-resolved SL MR angiography over two cardiac cycles than with time-resolved SL MR angiography over one cardiac cycle (P < .001) and TOF MR angiography (P < .001). For AVM characterization, interobserver agreement was very good to excellent, and agreement with DSA showed κ of 0.85 for arterial feeders, κ of 1.00 for nidus size, and κ of 0.82 for venous drainage. CONCLUSION: Time-resolved SL MR angiographic imaging over two cardiac cycles is a reliable clinical tool for cerebral AVM characterization, which showed very good to excellent agreement with DSA.
PURPOSE: To assess time-resolved spin-labeled (SL) magnetic resonance (MR) angiographic imaging with a large acquisition time window over two cardiac cycles for characterization of cerebral arteriovenous malformations (AVMs). MATERIALS AND METHODS: This study was institutional review board-approved. Sixteen patients presented with an AVM, provided informed consent, and were prospectively included. Time-resolved SL MR angiographic images with acquisition window that covered two cardiac cycles (acquisition time, 10-12 min; temporal resolution, 60 msec) or one cardiac cycle and time-of-flight (TOF) MR angiographic images were acquired with a 3-T MR imager. A diagnostic confidence index was used for image quality evaluation; scores were 0, no diagnosis, to 3, high image quality. AVM characterization consisted of arterial feeder, nidus size, and venous drainage type identification compared with those at digital subtraction angiography (DSA). κ coefficients were computed to determine interobserver and intermodality agreement. RESULTS: Time-resolved SL MR angiographic imaging over two cardiac cycles provided a median diagnostic confidence index of 2.5 for arterial feeders, 3.0 for nidus, and 3.0 for venous drainage. Venous drainage depiction quality was higher with time-resolved SL MR angiography over two cardiac cycles than with time-resolved SL MR angiography over one cardiac cycle (P < .001) and TOF MR angiography (P < .001). For AVM characterization, interobserver agreement was very good to excellent, and agreement with DSA showed κ of 0.85 for arterial feeders, κ of 1.00 for nidus size, and κ of 0.82 for venous drainage. CONCLUSION: Time-resolved SL MR angiographic imaging over two cardiac cycles is a reliable clinical tool for cerebral AVM characterization, which showed very good to excellent agreement with DSA.
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