Purpose: To develop a technique based on image noise distribution for automated endocardial border detection from cardiac magnetic resonance (CMR) images throughout the cardiac cycle, validate it, and test its clinical utility.
Materials and Methods:Images obtained in 36 patients were analyzed using custom software to obtain left ventricular (LV) volume throughout the cardiac cycle, end-systolic and end-diastolic LV volumes, and ejection fraction (EF). Validation against manually-traced endocardial boundaries included intertechnique comparisons of LV volumes, slice areas, and border positions. Then, the clinical feasibility of the dynamic automated analysis of LV function was tested in 14 patients with normal LV function, 12 patients with systolic dysfunction, and 10 patients with diastolic dysfunction.Results: Analysis time for one cardiac cycle was Ͻ15 minutes. Intertechnique comparisons resulted in high correlation (r Ͼ 0.96), small biases (volumes: -6 mL; EF: 4.6%) and narrow limits of agreement (volumes: 17.6 mL; EF: 9.2%). We found significant intergroup differences in multiple quantitative indices of systolic and diastolic function.
Conclusion:Fast, automated, dynamic detection of LV endocardial boundaries is feasible and allows accurate quantification of LV size and function, which is potentially clinically useful for objective assessment of systolic and diastolic dysfunction. CARDIAC MAGNETIC RESONANCE (CMR) is a noninvasive imaging modality with excellent spatial and contrast resolution that has become the standard reference in the assessment of left ventricular (LV) size and function (1,2), against which other techniques are frequently validated (3-12). However, this technique relies on the detection of endocardial boundaries, which requires frame-by-frame manual tracing on multiple slices, and is thus of limited value in clinical practice. Moreover, continuous measurement of LV volume requires slice-by-slice, phase-by-phase detection of the endocardial boundaries, which with the commercially available analysis software packages, based on the analysis of image intensity gradients, requires manual corrections in most patients and thus remains semiautomated at best, time consuming, and subjective. Thus, the dynamic nature of CMR imaging is largely unutilized in the clinical assessment of LV function, which is commonly reduced to visually identifying in a small number of slices the end-systolic (ES) and end-diastolic (ED) frames as those that depict the smallest and largest cross-sectional LV cavity areas, respectively. These frames are then traced slice-by-slice and used to obtain ES and ED volumes (ESV and EDV) and calculate the ejection fraction (EF). This practical solution can be challenging in patients with severely reduced systolic function, when volume changes are minimal, and inaccurate in hearts, wherein ventricular contraction is uneven and dyssynchronized so that minimum and maximum cross-sectional areas may appear in different slices at different times. Availability of a reliable technique f...