• Journal of the Korean Society of Radiology
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• v.5 no.5
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• pp.289-294
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• 2011

The aim of this study is to evaluate the differences of ejection fraction of left ventricle through the quantitative analysis of diastolic and systolic volumes according to slices selected using cardiac MR imaging. A total of 12 volunteers (7 normal, 1 myocardium bridge, and 4 arrhythmia) underwent cardiac MRI on a MR scanner(Magnetom Trio, Siemens, Germany). Ejection fractions for quantitative analysis were calculated at single slice of center of left ventricle, 3, 5, and 6-7 slices extending from the center of left ventricle. Average values were analyzed for evaluating differences of ejection fraction according to the number of slices selected. Mean value of normal person of ejection fraction were 67.14% at single slice of center of left ventricle, 66.24% at 3 slices, 65.63% at 5 slices, and 65.29% at 6-7 slices. While ejection fraction obtained from a patient with 61.74% at single slice of center of left ventricle, 60.92% at 3 slices, 60.89% at 5 slices, and 61.89% at 6-7 slices. There was no significant differences by the number of slices selected. This study demonstrates that ejection fraction obtained from single slice of center of left ventricle may represent a optimum parameter for cardiac function, instead of the value calculated on the variable slices selected.

• The Korean Journal of Nuclear Medicine
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• v.25 no.2
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• pp.186-191
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• 1991

Radionuclide cardiac studies lend themselves exceptionally well to functional imaging. This is especially true for gated blood pool scan (GBP). Making functional images is also possible in radionuclide angiocardiography (RNAC). In this study we tried to validate the functional images obtained from RNAC by comparing it with GBP. Twenty three patients (16 patients with coronary artery diseases, 5 with hypertensive heart diseases, and 2 with nonspecific chest pains) underwent simultaneous RNAC and GBP at the same position (LAO $45^{\circ}$). From both studies, global ejection fraction, regional ejection fraction, phase image, amplitude image, stroke image, paradox image, maximum ejection and maximum filling rates were obtained. Global ejection fraction are almost same in both studies. Regional ejection fractions of apex and inferior portion of left ventricle calculated from RNAC are well correlated with those of GBP. Phase and paradox image, maximum ejection and maximum filling rates were obtained. Global ejection fraction are almost same in both studies. Regional ejection fractions of apex and inferior portion of left ventricle calculated from RNAC are well correlated with those of GBP. Phase and paradox images of RNAC are very similar to those of GBP. However, amplitude and stroke images are different. Regional ejection fractions of the left ventricular base, maximum ejection and maximum filling rates obtained from RNAC are significantly different from those of GBP. In conclusion, albeit all of functional images of RNAC is not same as GBP, regional walt motions and global left ventricular function are expected to be successfully analyzed by phase and paradox image and ejection fraction.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.177-188
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• 1987

Detection of left ventricular boundary for the functional analysis of LV(left ventricle) is obtained using automatic boundary detection algorithm based on dynamic program ming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge detection methods. The left ventricular diastolic volume and systolic volume were computed after this automatic boundary detection, and these volume data were applied to analyze LV ejection fraction.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.437-444
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• 2021

The aim of this study was to compare the cardiac CT and cardiac MRI in calculating and correcting the left ventricle ejection fraction by analyzing the physical and temporal resolution for reducing the misdiagnosis rate. One hundred thirty-eight patients with aortic value regurgitation who underwent both cardiac CT and cardiac MRI were analyzed. Left ventricle ejection fractions calculated from each exam were corrected based on the physical and temporal resolution differences and the reliability test evaluated whether the misdiagnosis rate of cardiac CT was improved after the correction. As a result of the study, the misdiagnosis rate of cardiac CT ejection fraction before correcting the difference in physical and temporal resolution was 38.4%(53 persons). In addition, it can be seen that the corrected cardiac CT ejection fraction confirmed in the Bland-Altman plot was highly consistent with the ejection fraction of cardiac MRI. In conclusion, as the cardiac CT is less well suited for measuring ejection fraction, physical characteristics and the time resolution correction using cardiac MRI is needed and the misdiagnosis rate after correction decreased to 14.5%(20 persons). Therefore, this study appears more appropriate for better prediction of ejection fraction and clinical utility.

• Investigative Magnetic Resonance Imaging
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• v.22 no.1
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• pp.26-36
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• 2018

Purpose: Children born with single ventricle physiology demonstrate poor growth rate and suffer from malnutrition, which lead to increased morbidity and mortality in this population. We assume that an anabolic steroid, oxandrolone, will promote growth in these infants by improving myocardial energy utilization. The purpose of this paper is to study the efficacy of oxandrolone on myocardial energy consumption in these infants. Materials and Methods: We modeled single ventricle physiology in a lamb by prenatally shunting the aorta to the pulmonary artery and then postnatally, we monitored cardiac energy utilization by quantitatively measuring the first order reaction rate constant, $k_f$ of the creatine-kinase reaction in the heart using magnetization transfer $^{31}P$ magnetic resonance spectroscopy, home built $^1H/^{31}P$ transmit/receive double tuned coil, and transmit/receive switch. We also performed cine MRI to study the structure and dynamic function of the myocardium and the left ventricular chamber. The spectroscopy data were processed using home-developed python software, while cine data were analyzed using Argus software. Results: We quantitatively measured both the first order reaction rate constant and ejection fraction in the control, shunted, and the oxandrolone-treated lambs. Both $k_f$ and ejection fraction were found to be more significantly reduced in the shunted lambs compared to the control lambs, and they are increased in oxandrolone-treated lambs. Conclusion: Some improvement was observed in both the first order reaction rate constant and ejection fraction for the lamb treated with oxandrolone in our preliminary study.

• Journal of Chest Surgery
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• v.21 no.2
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• pp.223-230
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• 1988

Emax, end-systolic pressure-volume relationship, has been established as a new concept which can be representative of ventricular contractility itself since 1970s. Comparing to ejection fraction[EF], Emax is independent of preload and afterload. However Emax has not been proved precisely in non-thoracotomized condition because current methods have limitation in measuring ventricular chamber volume accurately in in viva state. The Dynamic Spatial Reconstructor[DSR], high speed computerized tomography, can measure ventricular chamber volume accurately throughout cardiac cycle in non-thoracotomized state. So Emax and EF of the left ventricle was tried to measure precisely in in vivo condition with DSR. Emax was compared to EF to estimate its ability to evaluate ventricular contractility. 5 mongrel dogs, weighing 15-16kg, were used for measuring Emax and EF of the left ventricle in 3 or 4 different loading conditions using DSR. Emax value in 5 dogs was from 2.62 to 10.49. Each dog has one Emax value regardless of loading conditions. However EF in 5 dogs varies depending on loading conditions. The conclusions are that Emax is useful in in viva state and EF varies depending on loading conditions. So Emax should be tried to use in clinical situation rather than EF because it is always representative of contractility itself regardless loading conditions in in viva state.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.570-574
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• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.151-158
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• 2022

The Cardiac Gated Blood Pool (GBP) scintigram, a nuclear medicine imaging, calculates the left ventricular Ejection Fraction (EF) by segmenting the left ventricle from the heart. However, in order to accurately segment the substructure of the heart, specialized knowledge of cardiac anatomy is required, and depending on the expert's processing, there may be a problem in which the left ventricular EF is calculated differently. In this study, using the DeepLabV3 architecture, GBP images were trained on 93 training data with a ResNet-50 backbone. Afterwards, the trained model was applied to 23 separate test sets of GBP to evaluate the reproducibility of the region of interest and left ventricular EF. Pixel accuracy, dice coefficient, and IoU for the region of interest were 99.32±0.20, 94.65±1.45, 89.89±2.62(%) at the diastolic phase, and 99.26±0.34, 90.16±4.19, and 82.33±6.69(%) at the systolic phase, respectively. Left ventricular EF was calculated to be an average of 60.37±7.32% in the ROI set by humans and 58.68±7.22% in the ROI set by the deep learning segmentation model. (p<0.05) The automated segmentation method using deep learning presented in this study similarly predicts the average human-set ROI and left ventricular EF when a random GBP image is an input. If the automatic segmentation method is developed and applied to the functional examination method that needs to set ROI in the field of cardiac scintigram in nuclear medicine in the future, it is expected to greatly contribute to improving the efficiency and accuracy of processing and analysis by nuclear medicine specialists.

• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.57-66
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• 2011

To prevent cardiac diseases, quantifying cardiac function is important in routine clinical practice by analyzing blood volume and ejection fraction. These works have been manually performed and hence it requires computational costs and varies depending on the operator. In this paper, an automatic left ventricle segmentation algorithm is presented to segment left ventricle on cardiac magnetic resonance images. After coil sensitivity of MRI images is compensated, a K-mean clustering scheme is applied to segment blood area. A graph searching scheme is employed to correct the segmentation error from coil distortions and noises. Using cardiac MRI images from 38 subjects, the presented algorithm is performed to calculate blood volume and ejection fraction and compared with those of manual contouring by experts and GE MASS software. Based on the results, the presented algorithm achieves the average accuracy of 6.2mL${\pm}$5.6, 2.9mL${\pm}$3.0 and 2.1%${\pm}$1.5 in diastolic phase, systolic phase and ejection fraction, respectively. Moreover, the presented algorithm minimizes user intervention rates which was critical to automatize algorithms in previous researches.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.250-257
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• 2010

This study was to analysis what factors could affect left ventricle ejection fraction(LVEF) using 64-slice multidetector CT. 164 patients(84 men, 80 women) had a cardiac CT in this study, and their blood pressure, body mass index(BMI), heart rate(HR) measured. LVEF was 52.00${\pm}$18.95% in below 25kg/$m^2$, 59.50${\pm}$16.05% in above 25kg/$m^2$ of BMI. LVEF was 57.26${\pm}$17.84% in normal blood pressure group(NBPG), 49.95${\pm}$17.63 in hypertension group(HG). LVEF was 60.76${\pm}$17.26 in below 60 beats/min, 54.14${\pm}$16.56 in 60-70 beats/min, 50.83${\pm}$20.56 in above 70 beats/min of HR. LVEF was negatively correlated with age, HR(r=-0.283 p<0.05, r=-0.231 p<0.05. respectively). And LVEF was positively correlated with BMI(r=0.228 p<0.05). A measurement of LVEF at cardiac CT by using MDCT may be considered to age, blood pressure, heart rate and BMI.