Three dimensional model-based analysis of the lenticulostriate arteries and identification of the vessels correlated to the infarct area: preliminary results

Authors

  • Chang-Ki Kang,

    1. Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea
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  • Stefan Wörz,

    1. Department of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Heidelberg, Germany
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  • Wei Liao,

    1. Department of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Heidelberg, Germany
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  • Chan-A Park,

    1. Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea
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  • Young-Bo Kim,

    1. Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea
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  • Cheol-Wan Park,

    1. Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea
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  • Young-Bae Lee,

    1. Department of Neurology, Gil Medical Center, Gachon University of Medicine and Science, Incheon, Korea
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  • Karl Rohr,

    Corresponding author
    1. Department of Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, BIOQUANT, IPMB, and German Cancer Research Center (DKFZ), Heidelberg, Germany
      Zang-Hee Cho*, Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Republic of Korea, 1198 Kuwol-dong, Namdong-gu, Incheon 405-760, Republic of Korea. E-mail: zcho@gachon.ac.kr, or Co-correspondence: Karl Rohr*, k.rohr@dkfz-heidelberg.de
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  • Zang-Hee Cho

    Corresponding author
    1. Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea
      Zang-Hee Cho*, Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Republic of Korea, 1198 Kuwol-dong, Namdong-gu, Incheon 405-760, Republic of Korea. E-mail: zcho@gachon.ac.kr, or Co-correspondence: Karl Rohr*, k.rohr@dkfz-heidelberg.de
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  • Conflict of interest: None declared.

  • Funding: This work was supported in part by a Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (20100002134), Republic of Korea and also by the Deutsche Forschungsgemeinschaft (DFG) within the project QuantVessel (RO 2471/6), Germany.

Zang-Hee Cho*, Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Republic of Korea, 1198 Kuwol-dong, Namdong-gu, Incheon 405-760, Republic of Korea. E-mail: zcho@gachon.ac.kr, or Co-correspondence: Karl Rohr*, k.rohr@dkfz-heidelberg.de

Abstract

Background Small vessel diseases have been studied noninvasively with magnetic resonance imaging. Direct observation or visualization of the connected microvessel to the infarct, however, was not possible due to the limited resolution. Hence, one could not determine whether vessel occlusion or abnormal narrowing is the cause of an infarct.

Methods In this report, we demonstrate that the small vessel related to the infarct can be detected using ultra-high-field (7 T) magnetic resonance imaging and a three dimensional image analysis and modeling technique for microvessels, which thereby enables us to quantify the vessel morphology directly, that is, visualize the vessel that is related to the infarct. We compared vessels of selected stroke patients, who had recovered from stroke, with vessels from typical stroke patients, who had after effects like motor weakness, and age-matched healthy subjects to demonstrate the potential of the technique.

Results The experimental results show that typical stroke patients had overall degradation or loss of small vessels, compared with the selected patients as well as healthy subjects. The selected patients, however, had only minimal loss of vessels, except for one vessel located close to the infarct area.

Conclusions These preliminary results demonstrated that 7 T magnetic resonance imaging together with a three dimensional image analysis and modeling technique could provide information for detection of the vessel related to the infarct. In addition, three dimensional image analysis and modeling of vessels could further provide quantitative information on the microvessel structures comprising diameter, length and tortuosity.

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