Motion corrected LV quantification based on 3D modelling for improved functional assessment in cardiac MRI

Abstract

Cine MRI is a clinical reference standard for the quantitative assessment of cardiac function, but reproducibility is confounded by motion artefacts. We explore the feasibility of a motion corrected 3D left ventricle (LV) quantification method, incorporating multislice image registration into the 3D model reconstruction, to improve reproducibility of 3D LV functional quantification. Multi-breath-hold short-axis and radial long-axis images were acquired from 10 patients and 10 healthy subjects. The proposed framework reduced misalignment between slices to subpixel accuracy (2.88 to 1.21 mm), and improved interstudy reproducibility for 5 important clinical functional measures, i.e. end-diastolic volume, end-systolic volume, ejection fraction, myocardial mass and 3D-sphericity index, as reflected in a reduction in the sample size required to detect statistically significant cardiac changes: a reduction of 21-66%. Our investigation on the optimum registration parameters, including both cardiac time frames and number of long-axis (LA) slices, suggested that a single time frame is adequate for motion correction whereas integrating more LA slices can improve registration and model reconstruction accuracy for improved functional quantification especially on datasets with severe motion artefacts.

A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI

“…First, the gap between slices (vertical dimension) in most routine acquisitions is relatively large (around 7-8 mm) and the pixel intensities between the slices cannot be reliably estimated (Petitjean and Dacher, 2011;Tavakoli and Amini, 2013;Petitjean et al, 2015;Queiros et al, 2014). Second, due to motion artifacts in cardiac MRI, misalignment between slices is common (Barajas et al, 2006;Chandler et al, 2008;Lötjönen et al, 2004;Zakkaroff et al;Carminati et al, 2014;Liew et al, 2015). This means that the cavity center is not at the same position in different slices.…”

Left Ventricle Segmentation Using a Combination of Region Growing and Graph Based Method

“…2) Misalignment between slices due to motion artifacts in cardiac MRI (25). This means that the cavity center is not at the same position in different slices.…”

“…The next point is placed in a way such that the lowest cost path between the initial point and the current cursor position will find the object of interest interactively. There are efforts for extending 2-D livewire to 3-D framework (23)(24)(25) in various applications, especially medical applications. Another extended version of live wire is proposed in a study conducted by Poon et al (26), in which the cost function is modified so it can segment vessel images more appropriately.…”

Assessment of infarct-specific cardiac motion dysfunction using modeling and multimodal magnetic resonance merging

“…The REF has been used as a regional function index in several studies to describe the specific contributions of remote and infarct sectors, which could not be measured with the global functional assessment approach . The excellent correlation between α ES and REF demonstrated the feasibility of using regional functional quantification by merging the MRI data of different modalities.…”