9 research outputs found

    Figure 1

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    <p>A–B. Scout cardiovascular magnetic resonance image of thoracic aorta demonstrating the planning of a transverse section through proximal descending aorta at the level of the right pulmonary artery. <b>C.</b> Arterial stiffness equations. Area(s) = systolic area, area(d) = diastolic area, ΔP = SBP-DBP, ρ = blood density (1059 kg.m<sup>−3</sup>).</p

    Additional file 1 of Precision measurement of cardiac structure and function in cardiovascular magnetic resonance using machine learning

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    Additional file 1: Table S1. Technical details of each neural network model (U-net) used. Table S2. Demographics and descriptive analysis of the generalizability cohort with a total of 1,277 patients. BMI = body mass index; LVEDV = left ventricle end diastolic volume; LVEF = left ventricle ejection fraction; LVESV = left ventricle end systolic volume; LGE = late gadolinium enhancement; LVM = left ventricle mass. Table S3. Comparison of Mean values (standard deviation in brackets) for LV metrics computed using three different methods in the Precision dataset. LVEDV: left ventricular end-diastolic volume; LVESV: left ventricular end-systolic volume; LVEF: left ventricular ejection fraction; LVM: LVM: left ventricular mass; LVSV: left ventricular stroke volume. Table S4. Comparison of scan-rescan precision metrics between human, machine and cvi42. LVEDV: left ventricular end diastolic volume; LVESV: left ventricular end systolic volume; LVEF: left ventricular ejection fraction; LVM: left ventricular mass; LVSV: left ventricular troke Volume Table S5. Sample size calculation based on Precision dataset. sd = standardized difference. Table S6. Pilot Study for Normal reference range showing mean (95% confidence interval in bracket) for each LV metric for machine-derived CMR volumes from a set of 98 healthy subjects. The combined reference range is presented as well as sex- and age-stratified ranges. Table S7. Breakdown of segmentation error by type and location on the validation (precision) dataset, which contains a total of 5058 images
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