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Related Experiment Video

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Automatic Respiratory Gating Hepatic DCEUS-based Dual-phase Multi-parametric Functional Perfusion Imaging using a

Diya Wang1,2, Guy Cloutier2,3, Yan Fan4

  • 1Department of Biomedical Engineering, School of Life Science and Technology, Xi' an Jiaotong University, Xi' an, P. R. China.

Theranostics
|September 20, 2019
PubMed
Summary

This study introduces a new dual-phase multi-parametric functional perfusion imaging (DM-FPI) technique using respiratory gating to improve liver cancer imaging accuracy. The method effectively reduces motion artifacts, enhancing the characterization of liver tumor hemodynamics.

Keywords:
contrast-enhanced ultrasoundfunctional perfusion imagingmachine learningprincipal component analysisrespiratory motion

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Area of Science:

  • Medical Imaging
  • Ultrasound Technology
  • Oncology

Background:

  • Liver cancer angiogenesis can be assessed using dynamic contrast-enhanced ultrasound (DCEUS) for functional perfusion imaging (FPI).
  • Breathing motion causes out-of-plane artifacts in DCEUS, limiting FPI accuracy.
  • Existing FPI methods lack artifact correction and accuracy evaluation.

Purpose of the Study:

  • To develop and validate a hepatic DCEUS-based dual-phase multi-parametric FPI (DM-FPI) scheme.
  • To overcome limitations caused by respiratory motion artifacts in liver FPI.
  • To improve the accuracy and robustness of liver tumor hemodynamic characterization.

Main Methods:

  • A novel derivative principal component analysis (PCA) respiratory gating technique was employed.
  • Accuracy was validated using *in vitro* DCEUS experiments in a hepatic vein flow model.
  • Feasibility was demonstrated *in vivo* using DCEUS in rabbit livers and human liver tumors (hemangioma, hepatocellular carcinoma).
  • Dual-phase microbubble kinetics were identified using derivative PCA zero-crossing detection.
  • Six dual-phase hemodynamic parameters were estimated to reconstruct DM-FPI for 2.5D angiogenic hemodynamic distribution.

Main Results:

  • The DM-FPI scheme significantly reduced mean square error (1893.9 ± 965.4) and noise coefficients (17.5 ± 7.1) compared to non-gated methods (p < 0.05).
  • Correlation coefficients improved by 0.4 ± 0.2 (p < 0.01), indicating enhanced accuracy.
  • DM-FPI effectively removed respiratory motion artifacts, improving *in vitro* and *in vivo* imaging accuracy and robustness.
  • Heterogeneous angiogenic hemodynamics, including perfusion volume, blood flow, and flow rate, were precisely characterized in normal livers and tumors.

Conclusions:

  • The proposed DM-FPI scheme accurately characterizes heterogeneous angiogenic hemodynamics in normal liver and hepatic tumors.
  • This DCEUS-based DM-FPI method offers a potential tool for clinicians in diagnosing and guiding therapies for liver tumors.
  • The technique demonstrates improved accuracy and robustness in quantifying liver perfusion parameters.