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Abdominal parametric perfusion imaging with respiratory motion-compensation based on contrast-enhanced ultrasound: In-vivo validation.

Authors
  • Wang, Diya1
  • Xiao, Mengnan2
  • Zhang, Yu2
  • Wan, Mingxi3
  • 1 The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China; Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center, Montreal, QC, Canada. , (Canada)
  • 2 The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China. , (China)
  • 3 The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, PR China. Electronic address: [email protected] , (China)
Type
Published Article
Journal
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Publication Date
Apr 01, 2018
Volume
65
Pages
11–21
Identifiers
DOI: 10.1016/j.compmedimag.2017.06.005
PMID: 28666563
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Parametric perfusion imaging (PPI) based on dynamic contrast-enhanced ultrasound (DCEUS) is a multi-parametric functional method that is increasingly used to characterize the hemodynamic features of abdominal tumors. Periodic respiratory kinetics adversely affects the signal-to-clutter ratio (SCR) and accuracy of abdominal PPI. This study proposed respiratory motion-compensation (rMoCo) employing non-negative matrix factorization combined with fast block matching algorithm to effectively remove these disturbances on abdominal PPI, which was validated through in-vivo perfusion experiments. The mean calculation efficiency of rMoCo was improved by 83.6% when the algorithm was accelerated in a unique matching sequence, which was formed from dozens of DCEUS subsequences at the same respiratory phase. The horizontal and vertical displacements induced by respiratory kinetics were estimated to correct the extraction of time-intensity curves and the peak SNR remained at 22.58±2.90dB. Finally, the abdominal PPIs of four perfusion parameters were formed with non-negative rMoCo, and their SCR was improved by 3.99±0.49dB (p<0.05). Compared with the results without rMoCo, the continuity and visualization of abdominal arterioles were clearly enhanced, and their perfusion details were accurately characterized by PPIs with non-negative rMoCo. The proposed method benefits clinicians in providing accurate diagnoses and in developing appropriate therapeutic strategies for abdominal diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

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