BACKGROUND: The Stroke Outcomes and Neuroimaging of Intracranial Atherosclerosis (SONIA) study validated noninvasive imaging tests of intracranial atherosclerosis against catheter angiography in a prospective, blinded, multicenter setting. Critical evaluation of transcranial Doppler (TCD) and magnetic resonance angiography in the SONIA study standardized their performance and interpretation. We performed a similar analysis of computed tomography angiography (CTA) for the detection of intracranial stenosis. METHODS: Multicenter standardization of image acquisition and blinded, central interpretation of CTA performance were conducted in concert with the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial. Measurements of the intracranial arterial diameter were obtained to derive stenosis values. Correlation with catheter angiography was used to assess CTA performance characteristics. RESULTS: CTA measurements of intracranial stenosis were obtained in 120 vessel segments, with angiographic correlation in 52. CTA was performed as a noninvasive study prior to conventional angiography. CTA stenoses of 50-99% or a flow gap were identified in 15 of 52 vessel segments, stenoses of <50% in 5 of 52, and normal arterial diameters in 32 of 52 vessel segments. Based on the digital subtraction angiography (DSA) stenosis defined as 50-99%, the positive predictive value (PPV) of CTA was only 46.7% (95% CI 21.3-73.4) and the negative predictive value (NPV) was 73.0% (95% CI 55.9-86.2). For DSA stenosis defined as 70-99%, the PPV of CTA was 13.3% (95% CI 1.7-40.5) and the NPV was 83.8% (95% CI 68.0-93.8). CONCLUSIONS: CTA can accurately rule out the presence of severe stenosis due to intracranial atherosclerosis and may eliminate the need for angiography in many cases. Further prospective, blinded evaluation of CTA and optimization of cutpoints to predict angiographic disease will facilitate future trials of intracranial atherosclerosis.
BACKGROUND: The Stroke Outcomes and Neuroimaging of Intracranial Atherosclerosis (SONIA) study validated noninvasive imaging tests of intracranial atherosclerosis against catheter angiography in a prospective, blinded, multicenter setting. Critical evaluation of transcranial Doppler (TCD) and magnetic resonance angiography in the SONIA study standardized their performance and interpretation. We performed a similar analysis of computed tomography angiography (CTA) for the detection of intracranial stenosis. METHODS: Multicenter standardization of image acquisition and blinded, central interpretation of CTA performance were conducted in concert with the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) trial. Measurements of the intracranial arterial diameter were obtained to derive stenosis values. Correlation with catheter angiography was used to assess CTA performance characteristics. RESULTS: CTA measurements of intracranial stenosis were obtained in 120 vessel segments, with angiographic correlation in 52. CTA was performed as a noninvasive study prior to conventional angiography. CTA stenoses of 50-99% or a flow gap were identified in 15 of 52 vessel segments, stenoses of <50% in 5 of 52, and normal arterial diameters in 32 of 52 vessel segments. Based on the digital subtraction angiography (DSA) stenosis defined as 50-99%, the positive predictive value (PPV) of CTA was only 46.7% (95% CI 21.3-73.4) and the negative predictive value (NPV) was 73.0% (95% CI 55.9-86.2). For DSA stenosis defined as 70-99%, the PPV of CTA was 13.3% (95% CI 1.7-40.5) and the NPV was 83.8% (95% CI 68.0-93.8). CONCLUSIONS: CTA can accurately rule out the presence of severe stenosis due to intracranial atherosclerosis and may eliminate the need for angiography in many cases. Further prospective, blinded evaluation of CTA and optimization of cutpoints to predict angiographic disease will facilitate future trials of intracranial atherosclerosis.
Authors: Scott E Kasner; Marc I Chimowitz; Michael J Lynn; Harriet Howlett-Smith; Barney J Stern; Vicki S Hertzberg; Michael R Frankel; Steven R Levine; Seemant Chaturvedi; Curtis G Benesch; Cathy A Sila; Tudor G Jovin; Jose G Romano; Harry J Cloft Journal: Circulation Date: 2006-01-23 Impact factor: 29.690
Authors: James K Min; Bon-Kwon Koo; Andrejs Erglis; Joon-Hyung Doh; David V Daniels; Sanda Jegere; Hyo-Soo Kim; Allison M Dunning; Tony Defrance; Alexandra Lansky; Jonathon Leipsic Journal: Am J Cardiol Date: 2012-06-29 Impact factor: 2.778
Authors: Bon-Kwon Koo; Andrejs Erglis; Joon-Hyung Doh; David V Daniels; Sanda Jegere; Hyo-Soo Kim; Allison Dunning; Tony DeFrance; Alexandra Lansky; Jonathan Leipsic; James K Min Journal: J Am Coll Cardiol Date: 2011-11-01 Impact factor: 24.094
Authors: Marc I Chimowitz; Michael J Lynn; Harriet Howlett-Smith; Barney J Stern; Vicki S Hertzberg; Michael R Frankel; Steven R Levine; Seemant Chaturvedi; Scott E Kasner; Curtis G Benesch; Cathy A Sila; Tudor G Jovin; Jose G Romano Journal: N Engl J Med Date: 2005-03-31 Impact factor: 91.245
Authors: E Feldmann; J L Wilterdink; A Kosinski; M Lynn; M I Chimowitz; J Sarafin; H H Smith; F Nichols; J Rogg; H J Cloft; L Wechsler; J Saver; S R Levine; C Tegeler; R Adams; M Sloan Journal: Neurology Date: 2007-04-04 Impact factor: 9.910
Authors: Jun Huang; Andrew J Degnan; Qi Liu; Zhongzhao Teng; Chen Shi Yue; Jonathan H Gillard; Jian Ping Lu Journal: J Neuroradiol Date: 2011-12-23 Impact factor: 3.447
Authors: Pietro Caliandro; Giuseppe Reale; Andrew M Demchuk; Valeria Caso; Anita Arsovska; Chiara Iacovelli; Silvia Giovannini; Paolo Maria Rossini Journal: Neurol Sci Date: 2018-07-09 Impact factor: 3.307
Authors: Ido R van den Wijngaard; Ghislaine Holswilder; Marianne A A van Walderveen; Ale Algra; Marieke J H Wermer; Osama O Zaidat; Jelis Boiten Journal: Brain Behav Date: 2016-08-31 Impact factor: 2.708