• Investigative Magnetic Resonance Imaging
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• v.24 no.1
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• pp.1-20
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• 2020

This document is the third part of the guidelines for the interpretation and post-processing of cardiac magnetic resonance (CMR) studies. These consensus recommendations have been developed by a Consensus Committee of the Korean Society of Cardiovascular Imaging (KOSCI) to standardize the requirements for image interpretation and post-processing of CMR. This third part of the recommendations describes tissue characterization modules, including perfusion, late gadolinium enhancement, and T1- and T2 mapping. Additionally, this document provides guidance for visual and quantitative assessment, consisting of "What-to-See," "How-To," and common pitfalls for the analysis of each module. The Consensus Committee hopes that this document will contribute to the standardization of image interpretation and post-processing of CMR studies.

• Journal of Chest Surgery
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• v.29 no.2
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• pp.136-146
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• 1996

Studies on normal human embryos and on malformed human hearts have been two main sources of the information on the developmental cardiology, Recent advances in the biological technology has opened a new era and descriptive embryology is being shifted into dynamic developmental biology. In this review, we discuss the current understanding on the cardiac embryology relevant to clinical practices of pediatric cardiology. Classical cardiac embryology starts with understanding on five segments of a straight heart tube : the sinus venosus, the primitive atria, the embryonic left ventricle, the embryonic right ventricle and the truncus arteriosus. Key steps in the normal morphogenetic process are the complex spiral septation of ventriculoarterial junction and two jumping connections : between the embryonic right atrium and embryonic right ventricle, and between the embryonic left ventricle and the aorta. Only after these two steps are successfully completed, the third fetal stage tak s place, when myocardial growth and remodeling take place There are two outstanding progresses on the cardiac embryology during recent five-year period. One is immunohistochemical mapping of the conduction system in the developing heart and the other is the understanding on the neural crest cell migration followed by molecular detection of the microdeletion of chromosome 22. A balanced progress of classical morphological studies, modern biological technics and advanced clinical medicine is an urgent task for doctors and scientists dealing with children with sick hearts.

• Journal of Cardiovascular Imaging
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• v.30 no.4
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• pp.263-275
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• 2022

BACKGROUND: Cardiac allograft vasculopathy (CAV) is a complication beyond the first-year post-heart transplantation (HTx). We aimed to test the utility of cardiac magnetic resonance (CMR) to detect functional/structural changes in HTx recipients with CAV. METHODS: Seventy-seven prospectively recruited HTx recipients beyond the first-year post-HTx and 18 healthy controls underwent CMR, including cine imaging of ventricular function and T1- and T2-mapping to assess myocardial tissue changes. Data analysis included quantification of global cardiac function and regional T2, T1 and extracellular volume based on the 16-segment model. International Society for Heart and Lung Transplantation criteria was used to adjudicate CAV grade (0-3) based on coronary angiography. RESULTS: The majority of HTx recipients (73%) presented with CAV (1: n = 42, 2/3: n = 14, 0: n = 21). Global and segmental T2 (49.5 ± 3.4 ms vs 50.6 ± 3.4 ms, p < 0.001;16/16 segments) were significantly elevated in CAV-0 compared to controls. When comparing CAV-2/3 to CAV-1, global and segmental T2 were significantly increased (53.6 ± 3.2 ms vs. 50.6 ± 2.9 ms, p < 0.001; 16/16 segments) and left ventricular ejection fraction was significantly decreased (54 ± 9% vs. 59 ± 9%, p < 0.05). No global, structural, or functional differences were seen between CAV-0 and CAV-1. CONCLUSIONS: Transplanted hearts display functional and structural alteration compared to native hearts, even in those without evidence of macrovasculopathy (CAV-0). In addition, CMR tissue parameters were sensitive to changes in CAV-1 vs. 2/3 (mild vs. moderate/severe). Further studies are warranted to evaluate the diagnostic value of CMR for the detection and classification of CAV.

• Korean Journal of Radiology
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• v.22 no.4
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• pp.535-546
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• 2021

Objective: To evaluate the feasibility of texture analysis on non-contrast-enhanced T1 maps of cardiac magnetic resonance (CMR) imaging for the diagnosis of myocardial injury in acute myocardial infarction (MI). Materials and Methods: This study included 68 patients (57 males and 11 females; mean age, 55.7 ± 10.5 years) with acute ST-segment-elevation MI who had undergone 3T CMR after a percutaneous coronary intervention. Forty patients of them also underwent a 6-month follow-up CMR. The CMR protocol included T2-weighted imaging, T1 mapping, rest first-pass perfusion, and late gadolinium enhancement. Radiomics features were extracted from the T1 maps using open-source software. Radiomics signatures were constructed with the selected strongest features to evaluate the myocardial injury severity and predict the recovery of left ventricular (LV) longitudinal systolic myocardial contractility. Results: A total of 1088 segments of the acute CMR images were analyzed; 103 (9.5%) segments showed microvascular obstruction (MVO), and 557 (51.2%) segments showed MI. A total of 640 segments were included in the 6-month follow-up analysis, of which 160 (25.0%) segments showed favorable recovery of LV longitudinal systolic myocardial contractility. Combined radiomics signature and T1 values resulted in a higher diagnostic performance for MVO compared to T1 values alone (area under the curve [AUC] in the training set; 0.88, 0.72, p = 0.031: AUC in the test set; 0.86, 0.71, p = 0.002). Combined radiomics signature and T1 values also provided a higher predictive value for LV longitudinal systolic myocardial contractility recovery compared to T1 values (AUC in the training set; 0.76, 0.55, p < 0.001: AUC in the test set; 0.77, 0.60, p < 0.001). Conclusion: The combination of radiomics of non-contrast-enhanced T1 mapping and T1 values could provide higher diagnostic accuracy for MVO. Radiomics also provides incremental value in the prediction of LV longitudinal systolic myocardial contractility at six months.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1294-1304
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• 2020

Objective: To determine whether T1 mapping could monitor the dynamic changes of injury in myocardial infarction (MI) and be histologically validated. Materials and Methods: In 22 pigs, MI was induced by ligating the left anterior descending artery and they underwent serial cardiovascular magnetic resonance examinations with modified Look-Locker inversion T1 mapping and extracellular volume (ECV) computation in acute (within 24 hours, n = 22), subacute (7 days, n = 13), and chronic (3 months, n = 7) phases of MI. Masson's trichrome staining was performed for histological ECV calculation. Myocardial native T1 and ECV were obtained by region of interest measurement in infarcted, peri-infarct, and remote myocardium. Results: Native T1 and ECV in peri-infarct myocardium differed from remote myocardium in acute (1181 ± 62 ms vs. 1113 ± 64 ms, p = 0.002; 24 ± 4% vs. 19 ± 4%, p = 0.031) and subacute phases (1264 ± 41 ms vs. 1171 ± 56 ms, p < 0.001; 27 ± 4% vs. 22 ± 2%, p = 0.009) but not in chronic phase (1157 ± 57 ms vs. 1120 ± 54 ms, p = 0.934; 23 ± 2% vs. 20 ± 1%, p = 0.109). From acute to chronic MI, infarcted native T1 peaked in subacute phase (1275 ± 63 ms vs. 1637 ± 123 ms vs. 1471 ± 98 ms, p < 0.001), while ECV progressively increased with time (35 ± 7% vs. 46 ± 6% vs. 52 ± 4%, p < 0.001). Native T1 correlated well with histological findings (R² = 0.65 to 0.89, all p < 0.001) so did ECV (R² = 0.73 to 0.94, all p < 0.001). Conclusion: T1 mapping allows the quantitative assessment of injury in MI and the noninvasive monitoring of tissue injury evolution, which correlates well with histological findings.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1276-1279
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• 1987

Cardiac arrhythmias are associated with electrical Instability and, hence, with abnormal mechanical activity of the heart in many cases, arrhythmias can be treated with drugs or electric shock to control and/or stop them. Hence fast arrhythmia detection is very important. In this paper RR interval, QRS width, and morphology are used for diagnosis and QRS complex is detected by hardware system. hence diagnosing time is shorten. Moreover doctors or nurses who have little knowledge of computer manipulation can get the Information of Patient's ECG by showing characteristics of abnormal waveform and by mapping graphs of RR interval .vs. QRS width and RR interval .vs. morphology on screen.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• Korean Journal of Radiology
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• v.22 no.10
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• pp.1619-1627
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• 2021

Objective: This study used cardiac magnetic resonance imaging (MRI) to compare the characteristics of left ventricular remodeling in patients with primary aldosteronism (PA) with those of patients with essential hypertension (EH) and healthy controls (HCs). Materials and Methods: This prospective study enrolled 35 patients with PA, in addition to 35 age- and sex-matched patients with EH, and 35 age- and sex-matched HCs, all of whom underwent comprehensive clinical and cardiac MRI examinations. The analysis of variance was used to detect the differences in the characteristics of left ventricular remodeling among the three groups. Univariable and multivariable linear regression analyses were used to determine the relationships between left ventricular remodeling and the physiological variables. Results: The left ventricular end-diastolic volume index (EDVi) (mean ± standard deviation [SD]: 85.1 ± 13.0 mL/m² for PA, 75.9 ± 14.3 mL/m² for EH, and 77.3 ± 12.8 mL/m² for HC; p = 0.010), left ventricular end-systolic volume index (ESVi) (mean ± SD: 35.2 ± 9.8 mL/m² for PA, 30.7 ± 8.1 mL/m² for EH, and 29.5 ± 7.0 mL/m² for HC; p = 0.013), left ventricular mass index (mean ± SD: 65.8 ± 16.5 g/m² for PA, 56.9 ± 12.1 g/m² for EH, and 44.1 ± 8.9 g/m² for HC; p < 0.001), and native T1 (mean ± SD: 1224 ± 39 ms for PA, 1201 ± 47 ms for EH, and 1200 ± 44 ms for HC; p = 0.041) values were higher in the PA group compared to the EH and HC groups. Multivariable linear regression demonstrated that log (plasma aldosterone-to-renin ratio) was independently correlated with EDVi and ESVi. Plasma aldosterone was independently correlated with native T1. Conclusion: Patients with PA showed a greater degree of ventricular hypertrophy and enlargement, as well as myocardial fibrosis, compared to those with EH. Cardiac MRI T1 mapping can detect left ventricular myocardial fibrosis in patients with PA.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1251-1259
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• 2022

Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

• Journal of Sensor Science and Technology
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• v.22 no.1
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• pp.38-43
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• 2013

In this study, the artery's compliance model and the pulsation waveform model was proposed to estimate blood pressure without applying HPF (High Pass Filter) on signal measured by the oscillometric method. The method proposed in the study considered two ways of estimating blood pressure. The first method of estimating blood pressure is by comparing and analyzing changes in pulsation waveform's dicrotic notch region during each cardiac period. The second method is by comparing and analyzing morphological changes in the pulsation waveform during each cardiac period, which occur in response to the change in pressure applied on the cuff. To implement these methods, we proposed the compliance model and the pulsation waveform model of the artery based on hemodynamic theory, and then conducted various simulations. The artery model presented in this study only took artery's compliance into account. Then, a pulsation waveform model was suggested, which uses characteristic changes in the pulsation waveform to estimate blood pressure. In addition, characteristic changes were observed in arterial volume by applying artery's pulsation waveform to the compliance model. The pulsation waveform model was suggested to estimate blood pressure using characteristic changes of the pulsation waveform in the arteries. This model was composed of the sum of sine waves and a Fourier's series in combination form up to 10th harmonics components of the sinusoidal waveform. Then characteristic of arterial volume change was observed by inputting pulsation waveform into the compliance model. The characteristic changes were also observed in the pulsation waveform by mapping the arterial volume change in accordance with applied cuff's pressure change to the pulsation waveform's change according to applied pressure changes by cuff. The systolic and diastolic blood pressures were estimated by applying positional change of pulsation waveform's dicrotic notch region.