EMORe: Motion-Robust 5D MRI Reconstruction via Expectation-Maximization-Guided Binning Correction and Outlier Rejection

TL;DR

EMORe is an advanced MRI reconstruction method that improves motion robustness in 5D cardiac MRI by integrating adaptive bin correction and outlier rejection within an EM framework, leading to clearer images despite motion artifacts.

Contribution

This paper introduces EMORe, a novel EM-based approach that adaptively corrects motion artifacts and rejects outliers, significantly improving 5D MRI image quality over traditional methods.

Findings

EMORe outperforms standard compressed sensing in simulations.

In vivo tests show improved image sharpness and reduced artifacts.

Robustness to bulk motion is significantly enhanced.

Abstract

We propose EMORe, an adaptive reconstruction method designed to enhance motion robustness in free-running, free-breathing self-gated 5D cardiac magnetic resonance imaging (MRI). Traditional self-gating-based motion binning for 5D MRI often results in residual motion artifacts due to inaccuracies in cardiac and respiratory signal extraction and sporadic bulk motion, compromising clinical utility. EMORe addresses these issues by integrating adaptive inter-bin correction and explicit outlier rejection within an expectation-maximization (EM) framework, whereby the E-step and M-step are executed alternately until convergence. In the E-step, probabilistic (soft) bin assignments are refined by correcting misassignment of valid data and rejecting motion-corrupted data to a dedicated outlier bin. In the M-step, the image estimate is improved using the refined soft bin assignments. Validation in a simulated 5D MRXCAT phantom demonstrated EMORe's superior performance compared to standard compressed sensing reconstruction, showing significant improvements in peak signal-to-noise ratio, structural similarity index, edge sharpness, and bin assignment accuracy across varying levels of simulated bulk motion. In vivo validation in 13 volunteers further confirmed EMORe's robustness, significantly enhancing blood-myocardium edge sharpness and reducing motion artifacts compared to compressed sensing, particularly in scenarios with controlled coughing-induced motion. Although EMORe incurs a modest increase in computational complexity, its adaptability and robust handling of bulk motion artifacts significantly enhance the clinical applicability and diagnostic confidence of 5D cardiac MRI.