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An Outline of Cardiovascular Structure and Function
Published in Joseph D. Bronzino, Donald R. Peterson, Biomedical Engineering Fundamentals, 2019
During the 480 ms or so lling phase-diastole-of the average 750 ms cardiac cycle, the inlet valves of the two ventricles (3.8-cm-diameter tricuspid valve from the right atrium to the right ventricle, 3.1-cm-diameter bicuspid or mitral valve from the le atrium to the le ventricle) are open, and the outlet valves (2.4-cm-diameter pulmonary valve and 2.25-cm-diameter aortic semilunar valve, respectively) are closed-the heart ultimately expanding to its end-diastolic volume (EDV), which is on the order of 140 mL of blood for the le ventricle. During the 270 ms emptying phase-systole-an electrically induced vigorous contraction of the cardiac muscle drives the intraventricular pressure up, forcing the one-way inlet valves to close and the unidirectional outlet valves to open as the heart contracts to its end-systolic volume (ESV), which is typically on the order of 70 mL of blood for the le ventricle. us, the ventricles normally empty about half their contained volume with each heartbeat, the remainder being termed the cardiac reserve volume. More generally, the dierence between the actual EDV and the actual ESV, called the stroke volume (SV), is the volume of blood expelled from the heart during each systolic interval, and the ratio of SV to EDV is called the cardiac ejection fraction, or ejection ratio (0.5-0.75 is normal, 0.4-0.5 signies mild cardiac damage, 0.25-0.40 implies moderate heart damage, and <0.25 warns of severe damage to the heart’s pumping ability). If the SV is multiplied by the number of systolic intervals per minute, or heart rate (HR), one obtains the total CO:
Cardiovascular System:
Published in Michel R. Labrosse, Cardiovascular Mechanics, 2018
The left ventricle ejects approximately 70 mL during each beat (this is known as the stroke volume) and about 5 L per minute (known as the cardiac output). Cardiac output is the product of stroke volume and heart rate. Stroke volume is dependent on the contractile ability of the heart muscle, as well as the amount of blood in the ventricles at the end of filling (the end-diastolic volume, or EDV). Commonly, the EDV in the left ventricle will be in the range of 110–120 mL. After contraction, the end-systolic volume (or ESV) ranges from 40 to 50 mL. The difference between the EDV and the ESV is the stroke volume. Clinically, the term ejection fraction is often used, which represents the stroke volume as a percentage of the EDV. Normal ejection fractions are approximately 66%–68%.
Images in Radiology: Concepts of Image Acquisition and the Nature of Images
Published in Mitul Kumar Ahirwal, Narendra D. Londhe, Anil Kumar, Artificial Intelligence Applications for Health Care, 2022
One should understand certain terms here, such as systole – contraction and diastole – relaxation. The images through the complete cardiac or ECG cycle are loaded on a dedicated software available with the MRI scanners on an attached workstation. The system detects the images in diastole and systole and then allows for certain calculations from the clinical point of view. Thus, it enables the radiologist to calculate the ventricular function in the following parameters:End-diastolic volume (EDV): The volume of the ventricular cavity at the end of the diastole (just before the start of the systole) expressed as milliliters.End-systolic volume (ESV): Ventricular cavity volume at the end of the systolic phase (just before the ventricle starts relaxing) expressed as milliliters.Stroke volume (SV): The volume of the blood that the ventricle ejects out and is essentially the difference of EDV and ESV and also expressed as milliliters.SV=EDV−ESVEjection fraction (EF): The ratio of SV as toEDV and expressed as a percentage.EF=SVEDV×100
A review on right ventricle cardiac MRI segmentation
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2023
An automatic analytic method for cardiovascular magnetic resonance (CMR) imaging was presented by Bai et al. (2018), which was mainly based on a fully convolutional network (FCN). The developed model was trained and evaluated on a large-scale dataset from the UK Biobank, including 4,875 subjects with 93,500 pixel-wise annotated images. The performance of the developed approach was estimated through several technical metrics, such as Dice metric, right ventricle (RV), end-diastolic volume (RVEDV) and end-systolic volume (RVESV), mean contour distance and Hausdorff distance, as well as clinically relevant measures, together with left ventricle (LV) end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM). The demonstrated model exhibited high performance by combining FCN with a large-scale annotated dataset for LV and RV segmentation on short-axis CMR images. After implementing the proposed algorithm, it was reported that the demonstrated method matched human practiced performance on CMR images in terms of segmentation accuracy and clinical measures. The developed method can take only a few seconds to analyse short- and long-axis images. The experimental result showed that the residual network performed similarly to the VGG-16 network. The main drawback of the algorithm was that it was trained on a single dataset and thus failed for other cases. After fine-tuning, the segmentation results improved in some cases.
Cardiac structure and function in resistance-trained and untrained adults: A systematic review and meta-analysis
Published in Journal of Sports Sciences, 2022
Abigail M Saunders, Rebecca L. Jones, Joanna Richards
When examining chamber dimension, RT athletes displayed greater LV internal diameter (LVID) during diastole than the untrained group (ES = −0.45, p = 0.002) with no obvious publication bias (t = −1.46, p = 0.16). There were no significant differences between RT athletes and the untrained group of untrained individuals with regards to LVID during systole with no obvious publication bias. The combined effect sizes for both aortic and LV atrial diameter were non-significant with no publication bias evident for either variable. When investigating the difference in end-systolic volume between RT athletes and untrained individuals, data pooled from five data sets produced a non-significant combined effect size (ES = −0.37, p = 0.32) however RT athletes did demonstrate greater end-diastolic volume than their untrained counterparts when examining the combined effect size from a total of seven data set (ES = −0.95, p = 0.001). There was no evidence of publication bias for any of the six variables above (p > 0.05), but significant heterogeneity was also noted for each (Table 3).
W-Net: Novel Deep Supervision for Deep Learning-based Cardiac Magnetic Resonance Imaging Segmentation
Published in IETE Journal of Research, 2022
Kamal Raj Singh, Ambalika Sharma, Girish Kumar Singh
The percentage of blood flowing out of the ventricles’ during contraction is known as ejection fraction (EF). where EDV (end-diastolic volume) and ESV (end-systolic volume) are defined as volume of blood in ventricle in the end-diastole phase, and end-systole phase respectively. In terms of the Dice similarity coefficient, W-Net yields results comparable to the highest performing methodologies [20,21,39] for right ventricle segmentation, as depicted in Table 4. For other segmentation parameters, W-Net delivers significantly better results, as can be seen in Figures 8 and 9. However, for myocardium segmentation, W-Net segmentation results are comparable with two best-performing methodologies [20,21], and superior to another best-performing method [39] for all segmentation parameters, as seen in Table 5. The W-Net approach seems to have a significant limitation in this regard.