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Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

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Physiological Motion Reduction Using Lagrangian Tracking for Electrode Displacement Elastography.

Robert M Pohlman¹, Tomy Varghese¹

¹Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

Ultrasound in Medicine & Biology

|December 7, 2019

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A new Lagrangian deformation tracking (LDT) method improves imaging for microwave ablation (MWA) liver cancer treatment. This technique reduces motion artifacts, enhancing visualization of ablated regions for better patient outcomes.

Area of Science:

Medical Imaging
Oncology
Biomedical Engineering

Background:

Minimally invasive treatments like microwave ablation (MWA) are crucial for liver cancer patients ineligible for surgery.
Electrode displacement elastography (EDE) offers real-time, non-ionizing imaging for MWA, but suffers from motion artifacts.
These artifacts, caused by physiological motion, create speckle variance, hindering accurate visualization of ablated zones.

Purpose of the Study:

To develop and validate a Lagrangian deformation tracking (LDT) approach to mitigate motion artifacts in freehand EDE.
To improve the consistency and accuracy of ablated region visualization during MWA procedures.
To compare the efficacy of LDT with traditional Eulerian methods for analyzing tissue deformation.

Main Methods:

Keywords:

Elastography Electrode displacement elastography Imaging microwave liver ablations Lagrangian description of motion Motion artifact reduction

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A novel Lagrangian deformation tracking (LDT) method was developed for freehand electrode displacement elastography (EDE).

LDT was validated using a spherical inclusion phantom and seven in vivo datasets.

Strain tensor images from LDT were compared against those from a traditional Eulerian approach using identical time-sampled data.

Main Results:

In vivo results demonstrated significantly greater consistency in LDT-derived strain tensor images compared to Eulerian methods.
Segmentation of ablated regions showed standard deviation reductions up to 98% with LDT.
LDT improved Dice coefficients by up to 25% and increased successful ablated region visualization rates from ~50% to nearly 100%.

Conclusions:

The developed Lagrangian deformation tracking (LDT) approach effectively overcomes motion artifacts in freehand EDE.
LDT significantly enhances the consistency and accuracy of visualizing ablated regions during microwave ablation.
This improved imaging modality holds promise for better treatment monitoring and patient outcomes in liver cancer therapy.