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Validation of Signal Intensity Gradient from TOF-MRA for Wall Shear Stress by Phase-Contrast MR

  • Chan Hyuk Lee
  • , Sang Hyuk Lee
  • , Hyo Sung Kwak
  • , Yeong Gon Kwak
  • , Robert S. Rosenson
  • , Young I. Cho
  • , Seul Ki Jeong*
  • *Corresponding author for this work
  • University of Ulsan
  • Korea Institute of Machinery and Materials
  • Wonkwang Health Science University
  • Icahn School of Medicine at Mount Sinai
  • Drexel University
  • Seul-Ki Jeong Neurology Clinic

Research output: Contribution to journalJournal articlepeer-review

Abstract

To validate the correlation between the signal intensity gradient (SIG) from time-of-flight magnetic resonance angiography (TOF-MRA) and wall shear stress (WSS) determined by phase contrast magnetic resonance (PC-MR), we conducted both experimental and human studies. In the experimental study, we measured WSS in four tubes of different sizes with variable flow rates using PC-MR and TOF-MRA. The flow rates of water in the experimental study ranged from 0.06 to 12.75 mL/s, resulting in PC-WSS values between 0.1 and 1.6 dyne/cm2. The correlation between PC-WSS and SIG was statistically significant, showing a coefficient of 0.86 (P < 0.001, R2 = 0.75). The line fit provided the conversion equation as Y = 1.6287X − 1.1563 (Y = PC-WSS, X = SIG). For the human study, 28 subjects underwent TOF-MRA and PC-MR examinations of carotid and vertebral arteries. Arterial PC-WSS and SIG were determined in the same segment for each subject. The arterial PC-WSS ranged from 1.9 to 21.0 dyne/cm2. Both carotid and vertebral arteries showed significant correlations between PC-WSS and SIG, with coefficients of 0.85, 0.86, 0.91, and 0.81 in the right and left carotid and vertebral arteries, respectively. Our results show that SIG from TOF-MRA and SIG-WSS derived from the conversion equation provide concurrent in vivo hemodynamic information on arterial shear stress. This study was registered on ClinicalTrials.gov with the identifier NCT04585971 on October 14, 2020.

Original languageEnglish
Pages (from-to)1248-1258
Number of pages11
JournalJournal of Imaging Informatics in Medicine
Volume37
Issue number3
DOIs
StatePublished - 2024.06

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Carotid artery
  • Ischemic stroke
  • Signal intensity gradient
  • Time-of-flight magnetic resonance angiography
  • Wall shear stress

Quacquarelli Symonds(QS) Subject Topics

  • Computer Science & Information Systems
  • Medicine
  • Data Science

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