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      Cerebral Venous Thrombosis: MR Black-Blood Thrombus Imaging with Enhanced Blood Signal Suppression

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          Abstract

          Twenty-six participants underwent conventional imaging methods followed by 2 randomized black-blood thrombus imaging scans, with a preoptimized DANTE preparation switched on and off, respectively. The signal intensity of residual blood, thrombus, brain parenchyma, normal lumen, and noise on black-blood thrombus images were measured. The thrombus volume, SNR of residual blood, and contrast-to-noise ratio for residual blood versus normal lumen, thrombus versus residual blood, and brain parenchyma versus normal lumen were compared between the 2 black-blood thrombus imaging techniques. The new black-blood thrombus imaging technique provided higher thrombus-to-residual blood contrast-to-noise ratio, significantly lower thrombus volume, and substantially improved diagnostic specificity and agreement with conventional imaging methods.

          Abstract

          BACKGROUND AND PURPOSE:

          The residual blood flow artifact is a critical confounder for MR black-blood thrombus imaging of cerebral venous sinus thrombosis. This study aimed to conduct a validation of a new MR black-blood thrombus imaging technique with enhanced blood signal suppression.

          MATERIALS AND METHODS:

          Twenty-six participants (13 volunteers and 13 patients) underwent conventional imaging methods followed by 2 randomized black-blood thrombus imaging scans, with a preoptimized delay alternating with nutation for tailored excitation (DANTE) preparation switched on and off, respectively. The signal intensity of residual blood, thrombus, brain parenchyma, normal lumen, and noise on black-blood thrombus images were measured. The thrombus volume, SNR of residual blood, and contrast-to-noise ratio for residual blood versus normal lumen, thrombus versus residual blood, and brain parenchyma versus normal lumen were compared between the 2 black-blood thrombus imaging techniques. Segmental diagnosis of venous sinus thrombosis was evaluated for each black-blood thrombus imaging technique using a combination of conventional imaging techniques as a reference.

          RESULTS:

          In the volunteer group, the SNR of residual blood (11.3 ± 2.9 versus 54.0 ± 23.4, P < .001) and residual blood-to-normal lumen contrast-to-noise ratio (7.5 ± 3.4 versus 49.2 ± 23.3, P < .001) were significantly reduced using the DANTE preparation. In the patient group, the SNR of residual blood (16.4 ± 8.0 versus 75.0 ± 35.1, P = .002) and residual blood-to-normal lumen contrast-to-noise ratio (12.4 ± 7.8 versus 68.8 ± 35.4, P = .002) were also significantly lower on DANTE-prepared black-blood thrombus imaging. The new black-blood thrombus imaging technique provided higher thrombus-to-residual blood contrast-to-noise ratio, significantly lower thrombus volume, and substantially improved diagnostic specificity and agreement with conventional imaging methods.

          CONCLUSIONS:

          DANTE-prepared black-blood thrombus imaging is a reliable MR imaging technique for diagnosing cerebral venous sinus thrombosis.

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          Author and article information

          Journal
          AJNR Am J Neuroradiol
          AJNR Am J Neuroradiol
          ajnr
          ajnr
          AJNR
          AJNR: American Journal of Neuroradiology
          American Society of Neuroradiology
          0195-6108
          1936-959X
          October 2019
          : 40
          : 10
          : 1725-1730
          Affiliations
          [1]From the Department of Biomedical Sciences (G.W., N.Z., Y.X., D.L., Q.Y., Z.F.), Biomedical Imaging Research Institute
          [2] bDepartment of Imaging (M.M.M.), Cedars-Sinai Medical Center, Los Angeles, California
          [3] cDepartment of Radiology (G.W.), The First Affiliated Hospital of China Medical University, Shenyang, China
          [4] dDepartments of Emergency (J.D., X.J.)
          [5] eRadiology (X.Y., Q.Y.) Xuanwu Hospital, Capital Medical University, Beijing, China
          [6] fPaul C. Lauterbur Research Center for Biomedical Imaging (N.Z.), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
          [7] gMR R&D (X.B., D.L.), Siemens Healthineers, Los Angeles, California
          [8] hDepartments of Medicine (D.L., Z.F.)
          [9] iBioengineering (Z.F.), University of California, Los Angeles, California.
          Author notes

          G. Wang and X. Yang have contributed equally to this work.

          Please address correspondence to Zhaoyang Fan, PhD and Qi Yang, MD, PhD, 8700 Beverly Blvd, Pacific Theatres Suite 400, Los Angeles, CA 90048, e-mail: Zhaoyang.Fan@ 123456csmc.edu ; yangyangqiqi@ 123456gmail.com
          Author information
          https://orcid.org/0000-0001-8626-5824
          https://orcid.org/0000-0001-5078-8180
          https://orcid.org/0000-0002-8849-2120
          https://orcid.org/0000-0001-9510-4520
          https://orcid.org/0000-0001-8236-7671
          https://orcid.org/0000-0002-0333-567X
          https://orcid.org/0000-0001-6286-9172
          https://orcid.org/0000-0002-0527-2852
          https://orcid.org/0000-0001-8560-8231
          https://orcid.org/0000-0002-5773-0456
          https://orcid.org/0000-0002-2693-0260
          Article
          PMC6785400 PMC6785400 6785400 19-00519
          10.3174/ajnr.A6212
          6785400
          31558501
          484f2666-454a-4aa5-a068-6dd1e9dd227d
          © 2019 by American Journal of Neuroradiology

          Indicates open access to non-subscribers at www.ajnr.org

          History
          : 10 May 2019
          : 29 July 2019
          Funding
          Funded by: Foundation for the National Institutes of Health https://doi.org/10.13039/100000009
          Award ID: 1 R01 HL147355
          Funded by: National Natural Science Foundation of China https://doi.org/10.13039/501100001809
          Award ID: 81830056
          Award ID: 91749127
          Funded by: Natural Science Foundation of Beijing Municipality https://doi.org/10.13039/501100004826
          Award ID: 17L20253
          Award ID: ZYLX201706
          Categories
          Adult Brain
          Fellows' Journal Club

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