Automated 4-dimensional Regional Myocardial Strain Evaluation using Cardiac Computed Tomography

Introduction: Evaluation of myocardial regional function is generally performed by visual "eyeballing" which is highly subjective. A robust quantifiable parameter of regional function is required to provide an objective, repeatable and comparable measure of myocardial performance. We aimed to evaluate novel software especially developed in our laboratory, to automatically derive regional myocardial strains from gated 4D computed tomography (CT) datasets.

Methods: 106 consecutive patients who had undergone retrospectively gated cardiac CT were evaluated by the software, which utilises a finite element based tracking algorithm through the cardiac cycle. The tracking algorithm utilizes the trabeculae and papillary muscle texture in the framework of a functional model of the left ventricle that accounts for the elasticity and incompressibility of the myocardium and the rapid contraction of the blood pool. Circumferential (CS), longitudinal (LS) and radial (RS) strains were calculated for each of 16 myocardial segments and compared to a visual assessment, carried out by an experienced cardiologist on cine movies of standard "echo" views derived from the CT data.

Results: The automated software performed successfully in 96/106 cases, with minimal human interaction. Peak CS, LS and RS all differentiated well between normal, hypokinetic and akinetic segments (p<0.0001, see table). Peak strains for akinetic segments were generally postsystolic, peaking at 50±17% of the RR interval compared to 43±9% for normokinetic segments. Using ROC analysis to test the ability to differentiate between normal and abnormal segments, the area under the curve was 0.81±0.02 for CS, 0.78±0.02 for RS and 0.67±0.02 for LS.

Conclusion: Automated 4D regional strain analysis of CT datasets shows a good correspondence to visual analysis and successfully differentiates between normal and abnormal segments.