Patient‐specific 17‐segment myocardial modeling on a bull's‐eye map

Abstract

The purpose of this study was to develop and validate cardiac computed tomography (CT) quantitative analysis software with a patient‐specific, 17‐segment myocardial model that uses electrocardiogram (ECG)‐gated cardiac CT images to differentiate between normal controls and severe aortic stenosis (AS) patients. ECG‐gated cardiac CT images from 35 normal controls and 144 AS patients were semiautomatically segmented to create a patient‐specific, 17‐segment myocardial model. Two experts then manually determined the anterior and posterior interventricular grooves to be boundaries between the 1st and 2nd segments and between the 3rd and 4th segments, respectively, to correct the model. Each segment was automatically identified as follows. The outer angle of two boundaries was divided to differentiate the 1st, 4th, 5th, and 6th segments in the basal plane, whereas the inner angle divided the 2nd and 3rd segments. The segments of the midplane were similarly divided. Segmental area distributions were quantitatively evaluated on the bull's‐eye map on the basis of the morphological boundaries by measuring the area of each segment. Segmental areas of severe AS patients and normal controls were significantly different (t‐test, all p‐values<0.011) in the proposed model because the septal regions of the severe AS patients were smaller than those of normal controls and the difference was enough to divide the two groups. The capabilities of the 2D segmental areas (p<0.011) may be equivalent to those of 3D segmental analysis (all p‐values<0.001) for differentiating the two groups (t‐test, all p‐values<0.001). The proposed method is superior to the conventional 17‐segment in relation to reflection of patient‐specific morphological variation and allows to obtain a more precise mapping between segments and the AHA recommended nomenclature. It can be used to differentiate severer AS patients and normal controls and also helps to understand the left ventricular morphology at a glance.PACS number(s): 87.57.N‐, 87.57.R‐, 87.57.qp

Impact of Aortic Stenosis on Myofiber Stress: Translational Application of Left Ventricle-Aortic Coupling Simulation

“…Examining how this ventricular stress profile may vary among patients, or shift as disease progresses, can offer a unique biomechanical profile for each patient. For example, Jung et al classified cardiac computed tomography images of normal control patients and those with severe AS by physical parameters associated with the 17 segments (Jung et al, 2016). Two and three-dimensional parameters were found to discriminate between the two patient groups, with the severe AS group having greater LV wall thickness, segment mass, and surface area.…”

Human iPS cell-derived cardiac tissue sheets for functional restoration of infarcted porcine hearts

“…For speckle tracking strain echocardiography, we obtained echocardiographic images in 2 levels of short axis (base / mid) of the left ventricle (LV) and analyzed the data using QLAB Ultrasound Cardiac Analysis software (Philips) with the electrocardiogram-gated mode. The images were tagged as 17-segments (American Heart Association) [ 11 ] and the circumference strain of each segment was automatically measured.…”

A Novel Method using Long Axis Cardiac MRI Measurements can Improve in vivo Myocardial Infarct Quantification

“…LGE sequences on MRI or other advanced imaging to assess ventricular abnormalities, such as echocardiogram or nuclear myocardial perfusion imaging. The 17-segment model is a wellaccepted model to assess location and size of infarcted myocardium although lacks accuracy when quantifying the percentage of infarcted tissue given that the summation of segments can overestimate infract volume since partial segments are seen as being completely affected [7].…”

“…While the precision of infarct-sizing continues to advance with emerging imaging techniques [4,5], the clinical standard for communicating MI size and location continues to use the methods proposed by the 17-segment model provided by American Heart Association (AHA) [1]. The 17-segment model has continued to be a readily accessible technique for rapid qualitative analysis of infarct size and location; however, this method has shown shortcoming when attempting to provide definitive quantitative analysis of myocardial infarct size [6,7,8].…”