Myocardial strain assessment by cine cardiac magnetic resonance imaging using non-rigid registration

被引:12
|
作者
Tsadok, Yossi [1 ]
Friedman, Zvi [2 ]
Haluska, Brian A. [3 ]
Hoffmann, Rainer [4 ]
Adam, Dan [1 ]
机构
[1] Technion Israel Inst Technol, Fac Biomed Engn, IL-32000 Haifa, Israel
[2] Gen Elect Healthcare, Ultrasound, Tirat Karmel, Israel
[3] Univ Queensland, Cardiovasc Imaging Res Ctr, Brisbane, Qld, Australia
[4] Univ Hosp RWTH Aachen, Med Clin 1, Aachen, Germany
关键词
Cardiac magnetic resonance; Strain analysis; Tagged magnetic resonance imaging; Speckle tracking echocardiography; LEFT-VENTRICULAR FUNCTION; VESSEL SIZE MEASUREMENTS; CANINE LEFT-VENTRICLE; QUANTITATIVE ASSESSMENT; 2-DIMENSIONAL STRAIN; PIXEL TRACKING; WALL-MOTION; INFARCTION; DEFORMATION; MRI;
D O I
10.1016/j.mri.2015.12.035
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Aims: To evaluate a novel post-processing method for assessment of longitudinal mid-myocardial strain in standard cine cardiac magnetic resonance (CMR) imaging sequences. Methods and results: Cine CMR imaging and tagged cardiac magnetic resonance imaging (TMRI) were performed in 15 patients with acute myocardial infarction (AMI) and 15 healthy volunteers served as control group. A second group of 37 post-AMI patients underwent both cine CMR and late gadolinium enhancement (LGE) CMR exams. Speckle tracking echocardiography (STE) was performed in 36 of these patients. Cine CMR, TMRI and STE were analyzed to obtain longitudinal strain. LGE-CMR datasets were analyzed to evaluate scar extent. Comparison of peak systolic strain (PSS) measured from CMR and TMRI yielded a strong correlation (r = 0.86, p < 0.001). PSS measured from CMR and STE correlated well (r = 0.75, p < 0.001). A cutoff longitudinal PSS value of -13.14% differentiated non-infarction from any infarcted myocardium, with a sensitivity of 93% and a specificity of 89% (area under curve (AUC) 0.95). PSS value of -9.39% differentiated non-transmural from transmural infarcted myocardium, with a sensitivity of 75% and a specificity of 67% (AUC 0.78). Conclusion: The present study showed a novel off-line post-processing method for segmental longitudinal strain analysis in mid-myocardium layer based on cine CMR data. The method was found to be highly correlated with strain measurements obtained by TMRI and STE. This tool allows accurate discrimination between different transmurality states of myocardial infarction. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:381 / 390
页数:10
相关论文
共 50 条
  • [31] Non-rigid registration using distance functions
    Paragios, N
    Rousson, M
    Ramesh, V
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2003, 89 (2-3) : 142 - 165
  • [32] In vivo assessment of cardiac remodeling after myocardial infarction in rats by cine-magnetic resonance imaging
    Nahrendorf, M
    Wiesmann, F
    Hiller, KH
    Han, H
    Hu, K
    Waller, C
    Ruff, J
    Haase, A
    Ertl, G
    Bauer, WR
    JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE, 2000, 2 (03) : 171 - 180
  • [33] Reproducibility study on myocardial strain assessment using fast-SENC cardiac magnetic resonance imaging
    Giusca, Sorin
    Korosoglou, Grigorios
    Zieschang, Victoria
    Stoiber, Lukas
    Schnackenburg, Bernhard
    Stehning, Christian
    Gebker, Rolf
    Pieske, Burkert
    Schuster, Andreas
    Backhaus, Soeren
    Pieske-Kraigher, Elisabeth
    Patel, Amit
    Kawaji, Keigo
    Steen, Henning
    Lapinskas, Tomas
    Kelle, Sebastian
    SCIENTIFIC REPORTS, 2018, 8
  • [34] Reproducibility study on myocardial strain assessment using fast-SENC cardiac magnetic resonance imaging
    Sorin Giusca
    Grigorios Korosoglou
    Victoria Zieschang
    Lukas Stoiber
    Bernhard Schnackenburg
    Christian Stehning
    Rolf Gebker
    Burkert Pieske
    Andreas Schuster
    Sören Backhaus
    Elisabeth Pieske-Kraigher
    Amit Patel
    Keigo Kawaji
    Henning Steen
    Tomas Lapinskas
    Sebastian Kelle
    Scientific Reports, 8
  • [35] A brain nuclear magnetic resonance image segmentation algorithm based on non-rigid registration
    Peng, Lei
    TRAITEMENT DU SIGNAL, 2018, 35 (3-4) : 317 - 330
  • [36] Balanced multi-image demons for non-rigid registration of magnetic resonance images
    Mesin, Luca
    MAGNETIC RESONANCE IMAGING, 2020, 74 : 128 - 138
  • [37] Validation of non-rigid registration between functional and anatomical magnetic resonance brain images
    Gholipour, Ali
    Kehtarnavaz, Nasser
    Briggs, Richard W.
    Gopinath, Kaundinya S.
    Ringe, Wendy
    Whittemore, Anthony
    Cheshkov, Sergey
    Bakhadirov, Khamid
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2008, 55 (02) : 563 - 571
  • [38] Construction of a cardiac motion atlas from MR using non-rigid registration
    Rao, A
    Sanchez-Ortiz, GI
    Chandrashekara, R
    Lorenzo-Valdés, M
    Mohiaddin, R
    Rueckert, D
    FUNCTIONAL IMAGING AND MODELING OF THE HEART, PROCEEDINGS, 2003, 2674 : 141 - 150
  • [39] Non-rigid magnetic resonance image registration for cervical cancer radiation therapy evaluation using hybrid features
    Zhi, L.
    Zhang, S.
    Xin, J.
    Ma, J.
    Zhu, R.
    INTERNATIONAL JOURNAL OF RADIATION RESEARCH, 2020, 18 (01): : 13 - 22
  • [40] Strain imaging using cardiac magnetic resonance
    A. Scatteia
    A. Baritussio
    C. Bucciarelli-Ducci
    Heart Failure Reviews, 2017, 22 : 465 - 476