The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data.Ģ.2 Image Analysis: Cardiac function quantificationĪn in-house plugin was developed in Paraview (Kitware, Inc., Clifton Park, NY) to compute a signed Hausdorff distance (HD) between consecutive cardiac phases, at uniformly spaced surface points on the segmented endocardial surfaces. The unique features provided by cardiac magnetic resonance (CMR) imaging allow for evaluation of regional systolic and diastolic myocardial function in 3D at each cardiac phase. Accurate and timely quantification of regional pathological function (hypokinesia / akinesia / dyskinesia) could be vital for early clinical risk assessment and patient management of ischemic heart disease (IHD), and evaluation of therapeutic efficacy prior to when significant changes occur to global function parameters. RMS-P2PD, when contrasted against a collective normal reference, is a promising biomarker to investigate further in its utility for identifying quantitative signs of pathological endocardial function which may boost standard image makers as precursors of declining cardiac performance.Ībnormal / discoordinated regional wall motion during left ventricular (LV) contraction is a precursor to poor systolic performance evidenced by diminished global function parameters viz. This improved to 91.9% with inclusion of the RMS-P2PD biomarker and was congruent with improvements in both sensitivity for classifying patients and specificity for identifying asymptomatic controls from 82.6% up to 95.7%. BRL accurately classified 83.8% of patients correctly from the patient and control populations, with leave-one-out cross validation, using standard indices of LV ejection fraction (LV-EF) and LV end-systolic volume index (LV-ESVI). The RMS-P2PD biomarker indices were significantly different for the symptomatic patient and asymptomatic control cohorts (p<0.001). The novel RMS-P2PD marker was tested as a cardiac function based feature for automatic patient classification using a Bayesian Rule Learning (BRL) framework. A novel biomarker of RMS error between mean patient-specific characteristic P2PD over the cardiac cycle for each individual patient and the cumulative P2PD characteristic of a cohort of asymptomatic patients was established as the RMS-P2PD marker. Average and standard deviation in P2PD over the cardiac cycle was used to prepare characteristic curves for the asymptomatic and IHD cohort. An LV-averaged index of phase-to-phase endocardial displacement (P2PD) time-histories was computed at each tracked point, using the HD computed between consecutive cardiac phases. The LV endocardium was segmented and a signed phase-to-phase Hausdorff distance (HD) was computed at 3D uniformly spaced points tracked on segmented endocardial surface contours, over the cardiac cycle. The purpose of this study is to characterize LV function through a systematic analysis of 4D (3D + time) endocardial motion over the cardiac cycle in an effort to define objective, clinically useful metrics of pathological remodeling and declining cardiac performance, using standard cardiac MRI data for two distinct patient cohorts accessed from : a) MESA – a cohort of asymptomatic patients and b) DETERMINE – a cohort of symptomatic patients with a history of ischemic heart disease (IHD) or myocardial infarction.
Characterization of regional left ventricular (LV) function may have application in prognosticating timely response and informing choice therapy in patients with ischemic cardiomyopathy.
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