Qi Yang1, Jiangang Duan1, Zhaoyang Fan1, Xiaofeng Qu1, Yibin Xie1, Christopher Nguyen1, Xiangying Du1, Xiaoming Bi1, Kuncheng Li1, Xunming Ji2, Debiao Li1. 1. From the Departments of Radiology (Q.Y., X.D., K.L.), Emergency (J.D.), and Neurosurgery (X.J.), Xuanwu Hospital, Capital Medical University, Beijing, China; Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA (Q.Y., Z.F., X.Q., Y.X., C.N., D.L.); and MR Research and Development, Siemens Healthcare, Los Angeles, CA (X.B.). 2. From the Departments of Radiology (Q.Y., X.D., K.L.), Emergency (J.D.), and Neurosurgery (X.J.), Xuanwu Hospital, Capital Medical University, Beijing, China; Biomedical Imaging Research Institute, Cedars Sinai Medical Center, Los Angeles, CA (Q.Y., Z.F., X.Q., Y.X., C.N., D.L.); and MR Research and Development, Siemens Healthcare, Los Angeles, CA (X.B.). xunmingji2006@yeah.net kunchengli@yeah.net.
Abstract
BACKGROUND AND PURPOSE: Early diagnosis of cerebral venous thrombosis (CVT) is currently a major clinical challenge. We proposed a novel magnetic resonance black-blood thrombus imaging technique (MRBTI) for detection and quantification of CVT. METHODS: MRBTI was performed on 23 patients with proven CVT and 24 patients with negative CVT confirmed by conventional imaging techniques. Patients were divided into 2 groups based on the duration of clinical onset: ≤7 days (group 1) and between 7 and 30 days (group 2). Signal/noise ratio was calculated for the detected thrombus, and contrast/noise ratio was measured between thrombus and lumen and also between thrombus and brain tissue. The feasibility of using MRBTI for thrombus volume measurement was explored, and total thrombus volume was calculated for each patient. RESULTS: In 23 patients with proven CVT, MRBTI correctly identified 113 of 116 segments with a sensitivity of 97.4%. Thrombus signal/noise ratio was 153±57 and 261±95 for group 1 (n=10) and group 2 (n=13), respectively (P<0.01). Thrombus to lumen contrast/noise ratio was 149±57 and 256±94 for group 1 and group 2, respectively. Thrombus to brain tissue contrast/noise ratio was 41±36 and 120±63 (P<0.01), respectively. Quantification of thrombus volume was successfully conducted in all patients with CVT, and mean volume of thrombus was 10.5±6.9 mL. CONCLUSIONS: The current findings support that with effectively suppressed blood signal, MRBTI allows selective visualization of thrombus as opposed to indirect detection of venous flow perturbation and can be used as a promising first-line diagnostic imaging tool.
BACKGROUND AND PURPOSE: Early diagnosis of cerebral venous thrombosis (CVT) is currently a major clinical challenge. We proposed a novel magnetic resonance black-blood thrombus imaging technique (MRBTI) for detection and quantification of CVT. METHODS: MRBTI was performed on 23 patients with proven CVT and 24 patients with negative CVT confirmed by conventional imaging techniques. Patients were divided into 2 groups based on the duration of clinical onset: ≤7 days (group 1) and between 7 and 30 days (group 2). Signal/noise ratio was calculated for the detected thrombus, and contrast/noise ratio was measured between thrombus and lumen and also between thrombus and brain tissue. The feasibility of using MRBTI for thrombus volume measurement was explored, and total thrombus volume was calculated for each patient. RESULTS: In 23 patients with proven CVT, MRBTI correctly identified 113 of 116 segments with a sensitivity of 97.4%. Thrombus signal/noise ratio was 153±57 and 261±95 for group 1 (n=10) and group 2 (n=13), respectively (P<0.01). Thrombus to lumen contrast/noise ratio was 149±57 and 256±94 for group 1 and group 2, respectively. Thrombus to brain tissue contrast/noise ratio was 41±36 and 120±63 (P<0.01), respectively. Quantification of thrombus volume was successfully conducted in all patients with CVT, and mean volume of thrombus was 10.5±6.9 mL. CONCLUSIONS: The current findings support that with effectively suppressed blood signal, MRBTI allows selective visualization of thrombus as opposed to indirect detection of venous flow perturbation and can be used as a promising first-line diagnostic imaging tool.
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