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Objective@#To quantitatively analyze the cardiac magnetic resonance imaging (CMR) characteristics of chemotherapy-related cardiac dysfunction (CTRCD) and explore their prognostic value for major adverse cardiovascular events (MACE). @*Materials and Methods@#A total of 145 patients (male:female = 76:69, mean age = 63.0 years) with cancer and heart failure who underwent CMR between January 2015 and January 2021 were included. CMR was performed using a 3T scanner (Siemens). Biventricular functions, native T1 T2, extracellular volume fraction (ECV) values, and late gadolinium enhancement (LGE) of the left ventricle (LV) were compared between those with and without CTRCD. These were compared between patients with mild-to-moderate CTRCD and those with severe CTRCD. Cox proportional hazard regression analysis was used to evaluate the association between the CMR parameters and MACE occurrence during follow-up in the CTRCD patients. @*Results@#Among 145 patients, 61 had CTRCD and 84 did not have CTRCD. Native T1, ECV, and T2 were significantly higher in the CTRCD group (1336.9 ms, 32.5%, and 44.7 ms, respectively) than those in the non-CTRCD group (1303.4 ms, 30.5%, and 42.0 ms, respectively; P = 0.013, 0.010, and < 0.001, respectively). They were not significantly different between patients with mild-to-moderate and severe CTRCD. Indexed LV mass was significantly smaller in the CTRCD group (65.0 g/m2 vs. 78.9 g/m2 ; P < 0.001). According to the multivariable Cox regression analysis, T2 (hazard ratio [HR]: 1.14, 95% confidence interval [CI]: 1.01–1.27; P = 0.028) and quantified LGE (HR: 1.07, 95% CI: 1.01–1.13; P = 0.021) were independently associated with MACE in the CTRCD patients. @*Conclusion@#Quantitative parameters from CMR have the potential to evaluate myocardial changes in CTRCD. Increased T2 with reduced LV mass was demonstrated in CTRCD patients even before the development of severe cardiac dysfunction. T2 and quantified LGE may be independent prognostic factors for MACE in patients with CTRCD.
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Objective@#We aimed to evaluate the ostium of right coronary artery of anomalous origin from the left coronary sinus (AORL) with an interarterial course throughout the cardiac cycle on CT and analyze the clinical significance of the ostial findings. @*Materials and Methods@#From January 2011 to December 2015, 68 patients (41 male, 57.3 ± 12.1 years) with AORL with an interarterial course and retrospective cardiac CT data were included. AORL was classified as high or low ostial location based on the pulmonary annulus in the diastolic and systolic phases on cardiac CT. In addition, the height, width, height/width ratio, area, and angle of the ostium were measured in both cardiac phases. After cardiac CT, patients were followed until December 31, 2020 for major adverse cardiac events (MACE). Clinical and CT characteristics associated with MACE were explored using Cox regression analysis. @*Results@#During a median follow-up period of 2071 days (interquartile range, 1180.5–2747.3 days), 13 patients experienced MACE (19.1%, 13/68). Seven (10.3%, 7/68) had the ostial location change from high in the diastolic phase to low in the systolic phase. In the univariable analysis, younger age (hazard ratio [HR] = 0.918, p < 0.001), high ostial location (HR = 4.008, p = 0.036), larger height/width ratio (HR = 5.621, p = 0.049), and smaller ostial angle (HR = 0.846, p = 0.048) in the systolic phase were significant predictors of MACE. In multivariable cox regression analysis, younger age (adjusted HR = 0.917, p = 0.002) and high ostial location in the systolic phase (adjusted HR = 4.345, p = 0.026) were independent predictors of MACE. @*Conclusion@#The ostial location of AORL with an interarterial course can change during the cardiac cycle, and high ostial location in the systolic phase was an independent predictor of MACE.
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Purpose@#This study aimed to assess the factors influencing aortic unfolding (AU) defined by aortic width on coronary artery calcium (CAC) scan and determine the normal limits for AU. @*Materials and Methods@#In this retrospective study, we measured AU in 924 asymptomatic subjects who underwent CAC scanning during routine health screening from June 2015 to June 2018. Multivariate regression analysis was used to evaluate the factors influencing AU. After the exclusion of subjects with risk factors associated with AU, 283 subjects were included in the analysis of normal values of AU. Mean AU, standard deviation, and upper normal limit were calculated. @*Results@#Sex, age, CAC score, body mass index, body surface area, hypertension, left ventricular hypertrophy, plasma creatinine, and smoking were significantly associated with AU. The mean AU was 102.2 ± 12.8 mm for men and 93.1 ± 10.7 mm for women. AU increased with advancing age (9.6 mm per decade). @*Conclusion@#AU determined from a single measurement on CAC scans was associated with cardiovascular risk factors. The normal limits of AU were defined by age, sex, and body surface area in low-risk subjects in this study.
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Objective@#This study aimed to investigate the regional amyloid burden and myocardial deformation using T1 mapping and strain values in patients with cardiac amyloidosis (CA) according to late gadolinium enhancement (LGE) patterns. @*Materials and Methods@#Forty patients with CA were divided into 2 groups per LGE pattern, and 15 healthy subjects were enrolled. Global and regional native T1 and T2 mapping, extracellular volume (ECV), and cardiac magnetic resonance (CMR)-feature tracking strain values were compared in an intergroup and interregional manner. @*Results@#Of the patients with CA, 32 had diffuse global LGE (group 2), and 8 had focal patchy or no LGE (group 1). Global native T1, T2, and ECV were significantly higher in groups 1 and 2 than in the control group (native T1: 1384.4 ms vs. 1466.8 ms vs. 1230.5 ms; T2: 53.8 ms vs. 54.2 ms vs. 48.9 ms; and ECV: 36.9% vs. 51.4% vs. 26.0%, respectively; all, p < 0.001). Basal ECV (53.7%) was significantly higher than the mid and apical ECVs (50.1% and 50.0%, respectively; p < 0.001) in group 2. Basal and mid peak radial strains (PRSs) and peak circumferential strains (PCSs) were significantly lower than the apical PRS and PCS, respectively (PRS, 15.6% vs. 16.7% vs. 26.9%; and PCS, -9.7% vs. -10.9% vs. -15.0%; all, p < 0.001). Basal ECV and basal strain (2-dimensional PRS) in group 2 showed a significant negative correlation (r = -0.623, p < 0.001). Group 1 showed no regional ECV differences (basal, 37.0%; mid, 35.9%; and apical, 38.3%; p = 0.184). @*Conclusion@#Quantitative T1 mapping parameters such as native T1 and ECV may help diagnose early CA. ECV, in particular, can reflect regional differences in the amyloid deposition in patients with advanced CA, and increased basal ECV is related to decreased basal strain. Therefore, quantitative CMR parameters may help diagnose CA and determine its severity in patients with or without LGE.
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Objective@#The purpose of this meta-analysis was to investigate the pooled agreements of the coronary artery calcium (CAC) severities assessed by electrocardiogram (ECG)-gated and non-ECG-gated CT and evaluate the impact of the scan parameters. @*Materials and Methods@#PubMed, EMBASE, and the Cochrane library were systematically searched. A modified Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the studies. Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and the correlation coefficient of the CAC scores or the weighted kappa for the categorization of the CAC severities detected by the two modalities. The heterogeneity among the studies was also assessed. Subgroup analyses were performed based on factors that could affect the measurement of the CAC score and severity: slice thickness, reconstruction kernel, and radiation dose for non-ECG-gated CT. @*Results@#A total of 4000 patients from 16 studies were included. The pooled bias was 62.60, 95% LOA were -36.19 to 161.40, and the pooled correlation coefficient was 0.94 (95% confidence interval [CI] = 0.89–0.97) for the CAC score. The pooled weighted kappa of the CAC severity was 0.85 (95% CI = 0.79–0.91). Heterogeneity was observed in the studies (I2 > 50%, p < 0.1). In the subgroup analysis, the agreement between the CAC categorizations was better when the two CT examinations had reconstructions based on the same slice thickness and kernel. @*Conclusion@#The pooled agreement of the CAC severities assessed by the ECG-gated and non-ECG-gated CT was excellent; however, it was significantly affected by scan parameters, such as slice thickness and the reconstruction kernel.
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Purpose@#To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). @*Materials and Methods@#A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions.Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. @*Results@#The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. @*Conclusion@#The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS.
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Purpose@#To construct a standard dataset of contrast-enhanced CT images of liver tumors to test the performance and safety of artificial intelligence (AI)-based algorithms for clinical decision support systems (CDSSs). @*Materials and Methods@#A consensus group of medical experts in gastrointestinal radiology from four national tertiary institutions discussed the conditions to be included in a standard dataset. Seventy-five cases of hepatocellular carcinoma, 75 cases of metastasis, and 30–50 cases of benign lesions were retrieved from each institution, and the final dataset consisted of 300 cases of hepatocellular carcinoma, 300 cases of metastasis, and 183 cases of benign lesions.Only pathologically confirmed cases of hepatocellular carcinomas and metastases were enrolled. The medical experts retrieved the medical records of the patients and manually labeled the CT images. The CT images were saved as Digital Imaging and Communications in Medicine (DICOM) files. @*Results@#The medical experts in gastrointestinal radiology constructed the standard dataset of contrast-enhanced CT images for 783 cases of liver tumors. The performance and safety of the AI algorithm can be evaluated by calculating the sensitivity and specificity for detecting and characterizing the lesions. @*Conclusion@#The constructed standard dataset can be utilized for evaluating the machine-learningbased AI algorithm for CDSS.
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Objective@#We aimed to develop a prediction model for diagnosing severe aortic stenosis (AS) using computed tomography (CT) radiomics features of aortic valve calcium (AVC) and machine learning (ML) algorithms. @*Materials and Methods@#We retrospectively enrolled 408 patients who underwent cardiac CT between March 2010 and August 2017 and had echocardiographic examinations (240 patients with severe AS on echocardiography [the severe AS group] and 168 patients without severe AS [the non-severe AS group]). Data were divided into a training set (312 patients) and a validation set (96 patients). Using non-contrast-enhanced cardiac CT scans, AVC was segmented, and 128 radiomics features for AVC were extracted. After feature selection was performed with three ML algorithms (least absolute shrinkage and selection operator [LASSO], random forests [RFs], and eXtreme Gradient Boosting [XGBoost]), model classifiers for diagnosing severe AS on echocardiography were developed in combination with three different model classifier methods (logistic regression, RF, and XGBoost). The performance (c-index) of each radiomics prediction model was compared with predictions based on AVC volume and score. @*Results@#The radiomics scores derived from LASSO were significantly different between the severe AS and non-severe AS groups in the validation set (median, 1.563 vs. 0.197, respectively, p 0.05 for all). @*Conclusion@#Models based on the radiomics features of AVC and ML algorithms may perform well for diagnosing severe AS, but the added value compared to AVC volume and score should be investigated further.
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Objective@#This study aimed to investigate the regional amyloid burden and myocardial deformation using T1 mapping and strain values in patients with cardiac amyloidosis (CA) according to late gadolinium enhancement (LGE) patterns. @*Materials and Methods@#Forty patients with CA were divided into 2 groups per LGE pattern, and 15 healthy subjects were enrolled. Global and regional native T1 and T2 mapping, extracellular volume (ECV), and cardiac magnetic resonance (CMR)-feature tracking strain values were compared in an intergroup and interregional manner. @*Results@#Of the patients with CA, 32 had diffuse global LGE (group 2), and 8 had focal patchy or no LGE (group 1). Global native T1, T2, and ECV were significantly higher in groups 1 and 2 than in the control group (native T1: 1384.4 ms vs. 1466.8 ms vs. 1230.5 ms; T2: 53.8 ms vs. 54.2 ms vs. 48.9 ms; and ECV: 36.9% vs. 51.4% vs. 26.0%, respectively; all, p < 0.001). Basal ECV (53.7%) was significantly higher than the mid and apical ECVs (50.1% and 50.0%, respectively; p < 0.001) in group 2. Basal and mid peak radial strains (PRSs) and peak circumferential strains (PCSs) were significantly lower than the apical PRS and PCS, respectively (PRS, 15.6% vs. 16.7% vs. 26.9%; and PCS, -9.7% vs. -10.9% vs. -15.0%; all, p < 0.001). Basal ECV and basal strain (2-dimensional PRS) in group 2 showed a significant negative correlation (r = -0.623, p < 0.001). Group 1 showed no regional ECV differences (basal, 37.0%; mid, 35.9%; and apical, 38.3%; p = 0.184). @*Conclusion@#Quantitative T1 mapping parameters such as native T1 and ECV may help diagnose early CA. ECV, in particular, can reflect regional differences in the amyloid deposition in patients with advanced CA, and increased basal ECV is related to decreased basal strain. Therefore, quantitative CMR parameters may help diagnose CA and determine its severity in patients with or without LGE.
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Objective@#The purpose of this meta-analysis was to investigate the pooled agreements of the coronary artery calcium (CAC) severities assessed by electrocardiogram (ECG)-gated and non-ECG-gated CT and evaluate the impact of the scan parameters. @*Materials and Methods@#PubMed, EMBASE, and the Cochrane library were systematically searched. A modified Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the studies. Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and the correlation coefficient of the CAC scores or the weighted kappa for the categorization of the CAC severities detected by the two modalities. The heterogeneity among the studies was also assessed. Subgroup analyses were performed based on factors that could affect the measurement of the CAC score and severity: slice thickness, reconstruction kernel, and radiation dose for non-ECG-gated CT. @*Results@#A total of 4000 patients from 16 studies were included. The pooled bias was 62.60, 95% LOA were -36.19 to 161.40, and the pooled correlation coefficient was 0.94 (95% confidence interval [CI] = 0.89–0.97) for the CAC score. The pooled weighted kappa of the CAC severity was 0.85 (95% CI = 0.79–0.91). Heterogeneity was observed in the studies (I2 > 50%, p < 0.1). In the subgroup analysis, the agreement between the CAC categorizations was better when the two CT examinations had reconstructions based on the same slice thickness and kernel. @*Conclusion@#The pooled agreement of the CAC severities assessed by the ECG-gated and non-ECG-gated CT was excellent; however, it was significantly affected by scan parameters, such as slice thickness and the reconstruction kernel.
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Purpose@#Myocardial T1 and T2 relaxation times are affected by technical factors such as cardiovascular magnetic resonance platform/vendor. We aimed to validate T1 and T2 mapping sequences using a phantom; establish reference T1, T2, and extracellular volume (ECV) measurements using two sequences at 3T in normal Koreans; and compare the protocols and evaluate the differences from previously reported measurements. @*Materials and Methods@#Eleven healthy subjects underwent cardiac magnetic resonance imaging (MRI) using 3T MRI equipment (Verio, Siemens, Erlangen, Germany). We did phantom validation before volunteer scanning: T1 mapping with modified look locker inversion recovery (MOLLI) with 5(3)3 and 4(1)3(1)2 sequences, and T2 mapping with gradient echo (GRE) and TrueFISP sequences. We did T1 and T2 mappings on the volunteers with the same sequences. ECV was also calculated with both sequences after gadolinium enhancement. @*Results@#The phantom study showed no significant differences from the gold standard T1 and T2 values in either sequence. Pre-contrast T1 relaxation times of the 4(1)3(1)2 protocol was 1142.27 ± 36.64 ms and of the 5(3)3 was 1266.03 ± 32.86 ms on the volunteer study. T2 relaxation times of GRE were 40.09 ± 2.45 ms and T2 relaxation times of TrueFISP were 38.20 ± 1.64 ms in each. ECV calculation was 24.42% ± 2.41% and 26.11% ± 2.39% in the 4(1)3(1)2 and 5(3)3 protocols, respectively, and showed no differences at any segment or slice between the sequences. We also calculated ECV from the pre-enhancement T1 relaxation time of MOLLI 5(3)3 and the postenhancement T1 relaxation time of MOLLI 4(1)3(1)2, with no significant differences between the combinations. @*Conclusion@#Using phantom-validated sequences, we reported the normal myocardial T1, T2, and ECV reference values of healthy Koreans at 3T. There were no statistically significant differences between the sequences, although it has limited statistical value due to the small number of subjects studied. ECV showed no significant differences between calculations based on various pre- and post-mapping combinations.
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Objective@#The present study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parametersoffer an incremental risk stratification benefit over the CT ventricular diameter ratio in patients with acute pulmonary embolism(PE) by using propensity score analysis. @*Materials and Methods@#This study was conducted on 480 patients with acute PE who underwent CT pulmonary angiography(CTPA) or DECT pulmonary angiography (DE CT-PA). This propensity-matched study population included 240 patients with acutePE each in the CTPA and DECT groups. Altogether, 260 (54.1%) patients were men, and the mean age was 64.9 years (64.9 ±13.5 years). The primary endpoint was all-cause death within 30 days. The Cox proportional hazards regression model was usedto identify associations between CT parameters and outcomes and to identify potential predictors. Concordance (C) statisticswere used to compare the prognoses between the two groups. @*Results@#In both CTPA and DECT groups, right to left ventricle diameter ratio ≥ 1 was associated with an increased risk of allcausedeath within 30 days (hazard ratio: 3.707, p< 0.001 and 5.573, p< 0.001, respectively). However, C-statisticsshowed no statistically significant difference between the CTPA and DECT groups for predicting death within 30 days(C-statistics: 0.759 vs. 0.819, p= 0.117). @*Conclusion@#Quantitative measurement of lung perfusion defect volume by DECT had no added benefit over CT ventriculardiameter ratio for predicting all-cause death within 30 days.
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OBJECTIVE: We performed a meta-analysis to evaluate the agreement of cardiac computed tomography (CT) with cardiac magnetic resonance imaging (CMRI) in the assessment of right ventricle (RV) volume and functional parameters.MATERIALS AND METHODS: PubMed, EMBASE, and Cochrane library were systematically searched for studies that compared CT with CMRI as the reference standard for measurement of the following RV parameters: end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), or ejection fraction (EF). Meta-analytic methods were utilized to determine the pooled weighted bias, limits of agreement (LOA), and correlation coefficient (r) between CT and CMRI. Heterogeneity was also assessed. Subgroup analyses were performed based on the probable factors affecting measurement of RV volume: CT contrast protocol, number of CT slices, CT reconstruction interval, CT volumetry, and segmentation methods.RESULTS: A total of 766 patients from 20 studies were included. Pooled bias and LOA were 3.1 mL (−5.7 to 11.8 mL), 3.6 mL (−4.0 to 11.2 mL), −0.4 mL (5.7 to 5.0 mL), and −1.8% (−5.7 to 2.2%) for EDV, ESV, SV, and EF, respectively. Pooled correlation coefficients were very strong for the RV parameters (r = 0.87–0.93). Heterogeneity was observed in the studies (I2 > 50%, p < 0.1). In the subgroup analysis, an RV-dedicated contrast protocol, ≥ 64 CT slices, CT volumetry with the Simpson's method, and inclusion of the papillary muscle and trabeculation had a lower pooled bias and narrower LOA.CONCLUSION: Cardiac CT accurately measures RV volume and function, with an acceptable range of bias and LOA and strong correlation with CMRI findings. The RV-dedicated CT contrast protocol, ≥ 64 CT slices, and use of the same CT volumetry method as CMRI can improve agreement with CMRI.
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BACKGROUND AND OBJECTIVES: Decreased left atrial appendage (LAA) emptying velocity in transesophageal echocardiography (TEE) is related with higher incidence of thrombus and increased risk of stroke. Patients with valve disease are at higher risk of thrombus formation before and after surgery. The aim of this study was to investigate the role of 4-dimensional cardiac computed tomography (4DCT) to predict the risk of thrombus formation. METHODS: Between March 2010 to March 2015, total of 62 patients (mean 60±15 years old, male: 53.2%) who underwent 4DCT and TEE for cardiac valve evaluation before surgery were retrospectively included in the current study. Fractional area change in TEE view and emptying velocity at left atrial appendage in TEE view (VeTEE) were measured. Ejection fraction (EF) of left atrial appendage in computed tomography (EFCT) was calculated by 4DCT with full volume analysis. The best cut-off value of EFCT predicting presence of spontaneous echo contrast (SEC) or thrombus was evaluated, and correlation between the parameters were also estimated. RESULTS: SEC or thrombus was observed in 45.2%. EFCT and VeTEE were significantly correlated (r=0.452, p < 0.001). However, fractional area change measured by TEE showed no correlation with VeTEE (r=0.085, p=0.512). EFCT < 37.5% best predicted SEC or thrombus in the patients with valve disease who underwent 4DCT and TEE (area under the curve, 0.654; p=0.038). CONCLUSIONS: In the patients who underwent 4DCT for cardiac valve evaluation before surgery, EFCT by volume analysis might have additional role to evaluate LAA function and estimate the risk of thrombus.
Subject(s)
Humans , Male , Atrial Appendage , Echocardiography, Transesophageal , Four-Dimensional Computed Tomography , Heart Valve Diseases , Heart Valves , Incidence , Retrospective Studies , Stroke , ThrombosisABSTRACT
PURPOSE: We investigate biases in the assessments of left ventricular function (LVF), by compressed sensing (CS)-cine magnetic resonance imaging (MRI). MATERIALS AND METHODS: Cardiovascular cine images with short axis view, were obtained for 8 volunteers without CS. LVFs were assessed with subsampled data, with compression factors (CF) of 2, 3, 4, and 8. A semi-automatic segmentation program was used, for the assessment. The assessments by 3 CS methods (ITSC, FOCUSS, and view sharing (VS)), were compared to those without CS. Bland-Altman analysis and paired t-test were used, for comparison. In addition, real-time CS-cine imaging was also performed, with CF of 2, 3, 4, and 8 for the same volunteers. Assessments of LVF were similarly made, for CS data. A fixed compensation technique is suggested, to reduce the bias. RESULTS: The assessment of LVF by CS-cine, includes bias and random noise. Bias appeared much larger than random noise. Median of end-diastolic volume (EDV) with CS-cine (ITSC or FOCUSS) appeared −1.4% to −7.1% smaller, compared to that of standard cine, depending on CF from (2 to 8). End-systolic volume (ESV) appeared +1.6% to +14.3% larger, stroke volume (SV), −2.4% to −16.4% smaller, and ejection fraction (EF), −1.1% to −9.2% smaller, with P < 0.05. Bias was reduced from −5.6% to −1.8% for EF, by compensation applied to real-time CS-cine (CF = 8). CONCLUSION: Loss of temporal resolution by adopting missing data from nearby cardiac frames, causes an underestimation for EDV, and an overestimation for ESV, resulting in underestimations for SV and EF. The bias is not random. Thus it should be removed or reduced for better diagnosis. A fixed compensation is suggested, to reduce bias in the assessment of LVF.
Subject(s)
Bias , Compensation and Redress , Diagnosis , Magnetic Resonance Imaging , Magnetic Resonance Imaging, Cine , Noise , Stroke Volume , Ventricular Function, Left , VolunteersABSTRACT
OBJECTIVE: We aimed to investigate the diagnostic accuracy of cardiac computed tomography (CT) for the detection of mitral valve (MV) prolapse in mitral regurgitation (MR) with surgical findings as the standard reference, and to assess the predictability of MV replacement based on morphologic CT findings. MATERIALS AND METHODS: A total of 156 patients who had undergone preoperative cardiac CT and subsequently received MV surgery due to severe MR were retrospectively enrolled. Non-repairable MV was defined when at least one of the following conditions was met: 1) anterior leaflet prolapse, 2) bi-leaflet prolapse, or 3) valve morphology (leaflet thickening, calcification, or mitral annular calcification [MAC]). Diagnostic performance of CT for the detection of the prolapsed segment was assessed with surgical findings as the standard reference. Logistic regression analysis was performed to evaluate the value of CT findings to predict actual valve replacement. RESULTS: During surgery, MV prolapse was identified in 72.1%. The sensitivity, specificity, and diagnostic accuracy for the detection of MV prolapse were 99.1%, 81.4%, and 94.2%, respectively, per patient. One-hundred eighteen patients (75.6%) underwent MV repair and the remaining 38 patients received MV replacement. Bi-leaflet prolapse and valve morphology were independent predictors of valve replacement after adjusting for clinical variables (adjusted odds ratio, [OR] 8.63 for bi-leaflet prolapse; OR, 4.14 for leaflet thickening; and OR, 5.37 for leaflet calcium score > 5.6; p < 0.05). CONCLUSION: Cardiac CT can have high diagnostic performance for detecting the prolapsed segment of the MV and predictability of valve replacement before surgery. Bi-leaflet prolapse and valve morphology, such as leaflet thickening, or calcification or MAC, are the most important predictors of valve replacement.
Subject(s)
Humans , Calcium , Logistic Models , Mitral Valve Insufficiency , Mitral Valve Prolapse , Mitral Valve , Odds Ratio , Prolapse , Retrospective Studies , Sensitivity and SpecificityABSTRACT
BACKGROUND AND OBJECTIVES@#Decreased left atrial appendage (LAA) emptying velocity in transesophageal echocardiography (TEE) is related with higher incidence of thrombus and increased risk of stroke. Patients with valve disease are at higher risk of thrombus formation before and after surgery. The aim of this study was to investigate the role of 4-dimensional cardiac computed tomography (4DCT) to predict the risk of thrombus formation.@*METHODS@#Between March 2010 to March 2015, total of 62 patients (mean 60±15 years old, male: 53.2%) who underwent 4DCT and TEE for cardiac valve evaluation before surgery were retrospectively included in the current study. Fractional area change in TEE view and emptying velocity at left atrial appendage in TEE view (VeTEE) were measured. Ejection fraction (EF) of left atrial appendage in computed tomography (EFCT) was calculated by 4DCT with full volume analysis. The best cut-off value of EFCT predicting presence of spontaneous echo contrast (SEC) or thrombus was evaluated, and correlation between the parameters were also estimated.@*RESULTS@#SEC or thrombus was observed in 45.2%. EFCT and VeTEE were significantly correlated (r=0.452, p < 0.001). However, fractional area change measured by TEE showed no correlation with VeTEE (r=0.085, p=0.512). EFCT < 37.5% best predicted SEC or thrombus in the patients with valve disease who underwent 4DCT and TEE (area under the curve, 0.654; p=0.038).@*CONCLUSIONS@#In the patients who underwent 4DCT for cardiac valve evaluation before surgery, EFCT by volume analysis might have additional role to evaluate LAA function and estimate the risk of thrombus.
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Due to rapid developments in the deep learning model, artificial intelligence (AI) models are expected to enhance clinical diagnostic ability and work efficiency by assisting physicians. Therefore, many hospitals and private companies are competing to develop AI-based automatic diagnostic systems using medical images. In the near future, many deep learning-based automatic diagnostic systems would be used clinically. However, the possibility of adversarial attacks exploiting certain vulnerabilities of the deep learning algorithm is a major obstacle to deploying deep learning-based systems in clinical practice. In this paper, we will examine in detail the kinds of principles and methods of adversarial attacks that can be made to deep learning models dealing with medical images, the problems that can arise, and the preventive measures that can be taken against them.
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PURPOSE: The present study investigated the diagnostic accuracy and clinical implications of moderate stenosis (50–69%, Coronary Artery Disease Reporting and Data System, grade 3) on coronary computed tomography angiography (CCTA), compared with invasive coronary angiography (ICA). MATERIALS AND METHODS: Two hundred and seventy-six patients who underwent ICA due to moderate stenosis alone on CCTA were selected from our prospective registry cohort. RESULTS: Diagnostic concordance between CCTA and ICA was found in only 50 (18%) patients. Among the 396 vessels and 508 segments with moderate stenosis, diagnostic concordance was found in 132 vessels (33%) and 127 segments (25%). Segments with calcified plaque had lower diagnostic concordance than those with mixed or non-calcified plaque (22% vs. 28% vs. 27%, respectively, p=0.001). While calcified plaque burden did not have an influence on severe stenosis (≥70%) on ICA, higher burden of non-calcified plaque was correlated with a greater incidence of ICA-based severe stenosis, which was more frequent in patients with ≥3 segments of non-calcified plaque (75%) than those without non-calcified plaque (22%, p < 0.001). Typical angina and mixed or non-calcified plaque were correlated with a higher incidence of under-diagnosis, while the use of next-generation computed tomography scanners reduced the incidence of under-diagnosis. Increased body weight, left circumflex artery involvement, and calcified plaque were independent factors that increased the risk of over-diagnosis of CCTA. CONCLUSION: The diagnosis of moderate stenosis by CCTA may be limited in estimating the exact degree of ICA-based anatomical stenosis. Unlike calcific burden, non-calcific burden was positively correlated with the presence of severe stenosis on ICA.
Subject(s)
Humans , Angina, Stable , Angiography , Arteries , Body Weight , Cohort Studies , Constriction, Pathologic , Coronary Angiography , Coronary Artery Disease , Coronary Stenosis , Diagnosis , Incidence , Information Systems , Prospective StudiesABSTRACT
Cardiac magnetic resonance (CMR) imaging is widely used in various medical fields related to cardiovascular diseases. Rapid technological innovations in magnetic resonance imaging in recent times have resulted in the development of new techniques for CMR imaging. T1 and T2 image mapping sequences enable the direct quantification of T1, T2, and extracellular volume fraction (ECV) values of the myocardium, leading to the progressive integration of these sequences into routine CMR settings. Currently, T1, T2, and ECV values are being recognized as not only robust biomarkers for diagnosis of cardiomyopathies, but also predictive factors for treatment monitoring and prognosis. In this study, we have reviewed various T1 and T2 mapping sequence techniques and their clinical applications.