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Computed Tomography-Based Thrombus Imaging for the Prediction of Recanalization after Reperfusion Therapy in Stroke

 Ji Hoe Heo  ;  Kyeonsub Kim  ;  Joonsang Yoo  ;  Young Dae Kim  ;  Hyo Suk Nam  ;  Eung Yeop Kim 
 JOURNAL OF STROKE, Vol.19(1) : 40-49, 2017 
Journal Title
Issue Date
Endovascular procedure ; Imaging ; Therapeutic thrombolysis ; Thrombus ; Tomography ; X-ray computed
The prediction of successful recanalization following thrombolytic or endovascular treatment may be helpful to determine the strategy of recanalization treatment in acute stroke. Thrombus can be detected using noncontrast computed tomography (CT) as a hyperdense artery sign or blooming artifact on a T2*-weighted gradient-recalled image. The detection of thrombus using CT depends on slice thickness. Thrombus burden can be determined in terms of the length, volume, and clot burden score. The thrombus size can be quantitatively measured on thin-section CT or CT angiography/magnetic resonance angiography. The determination of thrombus size may be predictive of successful recanalization/non-recanalization after intravenous thrombolysis and endovascular treatment. However, cut-offs of thrombus size for predicting recanalization/non-recanalization are different among studies, due to different methods of measurements. Thus, a standardized method to measure the thrombus is necessary for thrombus imaging to be useful and reliable in clinical practice. Software-based measurements may provide a reliable and accurate assessment. The measurement should be easy and rapid to be more widely used in practice, which could be achieved by improvement of the user interface. In addition to prediction of recanalization, sequential measurements of thrombus volume before and after the treatment may also be useful to determine the efficacy of new thrombolytic drugs. This manuscript reviews the diagnosis of thrombus, prediction of recanalization using thrombus imaging, and practical considerations for the measurement of thrombus burden and density on CT.
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1. College of Medicine (의과대학) > Dept. of Neurology (신경과학교실) > 1. Journal Papers
Yonsei Authors
Kim, Kyoung Sub(김경섭)
Kim, Young Dae(김영대) ORCID logo https://orcid.org/0000-0001-5750-2616
Nam, Hyo Suk(남효석) ORCID logo https://orcid.org/0000-0002-4415-3995
Yoo, Joon Sang(유준상) ORCID logo https://orcid.org/0000-0003-1169-6798
Heo, Ji Hoe(허지회) ORCID logo https://orcid.org/0000-0001-9898-3321
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