BACKGROUND: The hemodynamic evaluation of cerebral arteriovenous malformations (AVMs) using DSA has not been validated against true flow measurements. OBJECTIVE: To validate AVM hemodynamics assessed by DSA using quantitative magnetic resonance angiography (QMRA). MATERIALS AND METHODS: Patients seen at our institution between 2007 and 2016 with a supratentorial AVM and DSA and QMRA obtained before any treatment were retrospectively reviewed. DSA assessment of AVM flow comprised AVM arterial-to-venous time (A-Vt) and iFlow transit time. A-Vt was defined as the difference between peak contrast intensity in the cavernous internal carotid artery and peak contrast intensity in the draining vein. iFlow transit times were determined using syngo iFlow software. A-Vt and iFlow transit times were correlated with total AVM flow measured using QMRA and AVM angioarchitectural and clinical features. RESULTS: 33 patients (mean age 33 years) were included. Nine patients presented with hemorrhage. Mean AVM volume was 9.8 mL (range 0.3-57.7 mL). Both A-Vt (r=-0.47, p=0.01) and iFlow (r=-0.44, p=0.01) correlated significantly with total AVM flow. iFlow transit time was significantly shorter in patients who presented with seizure but A-Vt and iFlow did not vary with other AVM angioarchitectural features such as venous stenosis or hemorrhagic presentation. CONCLUSIONS: A-Vt and iFlow transit times on DSA correlate with cerebral AVM flow measured using QMRA. Thus, these parameters may be used to indirectly estimate AVM flow before and after embolization during angiography in real time. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
BACKGROUND: The hemodynamic evaluation of cerebral arteriovenous malformations (AVMs) using DSA has not been validated against true flow measurements. OBJECTIVE: To validate AVM hemodynamics assessed by DSA using quantitative magnetic resonance angiography (QMRA). MATERIALS AND METHODS:Patients seen at our institution between 2007 and 2016 with a supratentorial AVM and DSA and QMRA obtained before any treatment were retrospectively reviewed. DSA assessment of AVM flow comprised AVM arterial-to-venous time (A-Vt) and iFlow transit time. A-Vt was defined as the difference between peak contrast intensity in the cavernous internal carotid artery and peak contrast intensity in the draining vein. iFlow transit times were determined using syngo iFlow software. A-Vt and iFlow transit times were correlated with total AVM flow measured using QMRA and AVM angioarchitectural and clinical features. RESULTS: 33 patients (mean age 33 years) were included. Nine patients presented with hemorrhage. Mean AVM volume was 9.8 mL (range 0.3-57.7 mL). Both A-Vt (r=-0.47, p=0.01) and iFlow (r=-0.44, p=0.01) correlated significantly with total AVM flow. iFlow transit time was significantly shorter in patients who presented with seizure but A-Vt and iFlow did not vary with other AVM angioarchitectural features such as venous stenosis or hemorrhagic presentation. CONCLUSIONS: A-Vt and iFlow transit times on DSA correlate with cerebral AVM flow measured using QMRA. Thus, these parameters may be used to indirectly estimate AVM flow before and after embolization during angiography in real time. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Entities:
Keywords:
Angiography; Arteriovenous Malformation; Blood Flow; Magnetic Resonance Angiography
Authors: Ahmed E Hussein; Meghana Shownkeen; Andre Thomas; Christopher Stapleton; Denise Brunozzi; Jessica Nelson; John Naumgart; Andreas Linninger; Gursant Atwal; Ali Alaraj Journal: Interv Neuroradiol Date: 2020-02-26 Impact factor: 1.610
Authors: Mahsa Ghaffari; Kevin Tangen; Ali Alaraj; Xinjian Du; Fady T Charbel; Andreas A Linninger Journal: Comput Biol Med Date: 2017-10-24 Impact factor: 4.589
Authors: Grace M Y Ma; Adam A Dmytriw; Premal A Patel; Nicholas Shkumat; Timo Krings; Manohar M Shroff; Prakash Muthusami Journal: Childs Nerv Syst Date: 2019-07-06 Impact factor: 1.475
Authors: Murad Alqadi; Denise Brunozzi; Andreas Linninger; Sepideh Amin-Hanjani; Fady T Charbel; Ali Alaraj Journal: Med Hypotheses Date: 2019-01-07 Impact factor: 1.538