Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT

Objective: To evaluate the feasibility of dual-energy CT (DECT)-based iodine quantification to estimate myocardial extracellular volume (ECV) fraction in patients with and without cardiomyopathy (CM), as well as to assess its ability to distinguish healthy myocardial tissue from cardiomyopathic, with the goal of defining a threshold ECV value for disease detection. Methods: Ten subjects free of heart disease and 60 patients with CM (mean age 66.4 ± 9.4; 59 males and 11 females; 40 ischemic and 20 non-ischemic CM) underwent late iodine enhanced DECT imaging. Myocardial iodine maps were obtained using 3-material decomposition. ECV of the left ventricle was estimated from hematocrit levels and the iodine maps using the AHA 16-segment model. Receiver operating characteristic curve analysis was performed, with corresponding area under the curve, along with Youden's index assessment, to establish a threshold for CM detection. Results: The median ECV for healthy myocardium, non-ischemic CM, and ischemic CM were 25.4% (22.9–27.3), 38.3% (33.7–43.0), and 36.9% (32.4–41.1), respectively. Healthy myocardium showed significantly lower ECV values compared to ischemic and non-ischemic CM (p 29.5% would indicate the presence of CM in the myocardium (sensitivity = 90.3; specificity = 90.3); the AUC for this criterion was 0.950 (p < 0.001). Conclusion: The findings of this study resulted in a statistically significant distinction between healthy myocardium and CM ECVs. This led to the establishment of a promising threshold ECV value that could facilitate the differentiation between healthy and diseased myocardium, and highlights the potential of this DECT methodology to detect cardiomyopathic tissue

Predictive Value of Cardiac CTA, Cardiac MRI, and Transthoracic Echocardiography for Cardioembolic Stroke Recurrence

Background: Transthoracic echocardiography (TTE) is the standard of care for initial evaluation of patients with suspected cardioembolic stroke. While TTE is useful for assessing certain sources of cardiac emboli, its diagnostic capability is limited in the detection of other sources, including left atrial thrombus and aortic plaques. Objectives: To investigate sensitivity, specificity and predictive value of cardiac CT angigography (cCTA), cardiac MRI (CMR), and TTE for recurrence in patients with suspected cardioembolic stroke. Methods: We retrospectively included 151 patients with suspected cardioembolic stroke who underwent TTE and either CMR (n=75) or cCTA (n=76) between January 2013 and May 2017. We evaluated for presence of left atrial thrombus, left ventricular thrombus, vulnerable aortic plaque, cardiac tumors, and valvular vegetation as causes of cardioembolic stroke. The end-point was stroke recurrence. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for recurrent stroke were calculated; the diagnostic accuracy of CMR, cCTA, and TTE was compared between and within groups using area under the curves (AUCs). Results: Twelve and 14 recurrent strokes occurred in the cCTA and CMR groups, respectively. Sensitivity, specificity, PPV and NPV were: 33.3%, 93.7%, 50.0%, and 88.2% for cCTA; 14.3%, 80.3%, 14.3%, and 80.3% for CMR; 14.3%, 83.6%, 16.7%, 80.9% for TTE in the CMR group, and 8.3%, 93.7%, 20.0% and 84.5% for TTE in the cCTA group. Accuracy was not different (p&gt;0.05) between cCTA (0.63, 95% CI [0.49, 0.77]), CMR (0.53, [0.42, 0.63]), TTE in CMR group (0.51, [0.40, 0.61], and TTE in cCTA group (0.51, [0.42, 0.59]). In cCTA group, atrial and ventricular thrombus were detected by cCTA in 3 patients and TTE in 1 patient; in CMR group, thrombus was detected by CMR in 1 patient and TTE in 2 patients. Conclusion: cCTA, CMR, and TTE showed comparably high specificity and NPV for cardioembolic stroke recurrence. cCTA and CMR may be valid alternatives to TTE. cCTA may be preferred given potentially better detection of atrial and ventricular thrombus. Clinical impact: cCTA and CMR have similar clinical performance as TTE for predicting cardioembolic stroke recurrence. This observation may be especially important when TTE provides equivocal findings

Extracellular volume quantitation using dual-energy CT in patients with heart failure: Comparison with 3T cardiac MR

Backgrounds: Cardiac magnetic resonance (CMR) T1 mapping and the extracellular volume (ECV) have been developed to quantitative analysis of diffusely abnormal myocardial fibrosis (MF). However, dual-energy CT (DECT) has a potential for calculation of ECV. The aim of this study is to evaluate the feasibility and accuracy of DECT technique in determining the ECV in patients with heart failure, with 3T CMR as the reference. Methods: Thirty-five patients with various reasons of heart failure were enrolled in this study. Both DECT and CMR exams were completed within 24 h. ECVs were calculated, and the relationship between DECT-ECV, CMR-ECV, and other heart function parameters, including left ventricular end systolic and diastolic volume, cardiac output and ejection fraction(LVESV, LVEDV, CO, LVEF), Brain natriuretic peptide (BNP) was determined. All participants gave informed consent, and the study was approved by the institutional review board. Results: The median ECVs on DECT and CMR were 33% (95%CI: 32%–36%) and 30% (95%CI: 30% - 32%), respectively. A good correlation between myocardial ECV at DECT and that at CMR (r = 0.945, P < 0.001) was observed. Bland-Altman analysis between DECT and CMR showed a small bias (2.6%), with 95% limits of agreement of −0.4% and 5.6%. Interobserver agreement for ECV at DECT was excellent (ICC = 0.907). Both ECVs, for DECT and CMR, were inversely associated with LVEF and CO. Conclusion: DECT-based ECV could be an alternative non-invasive imaging tool for myocardial tissue characterization. However, overestimation of the extent of diffuse MF is observed with use of DECT

Comparison of Artificial Intelligence-Based Fully Automatic Chest CT Emphysema Quantification to Pulmonary Function Testing

OBJECTIVE. The purpose of this study was to evaluate an artificial intelligence (AI)based prototype algorithm for fully automated quantification of emphysema on chest CT compared with pulmonary function testing (spirometry). MATERIALS AND METHODS. A total of 141 patients (72 women, mean age +/- SD of 66.46 +/- 9.7 years [range, 23-86 years]; 69 men, mean age of 66.72 +/- 11.4 years [range, 27-91 years]) who underwent both chest CT acquisition and spirometry within 6 months were retrospectively included. The spirometry-based Tiffeneau index (TI; calculated as the ratio of forced expiratory volume in the first second to forced vital capacity) was used to measure emphysema severity; a value less than 0.7 was considered to indicate airway obstruction. Segmentation of the lung based on two different reconstruction methods was carried out by using a deep convolution image-to-image network. This multilayer convolutional neural network was combined with multilevel feature chaining and depth monitoring. To discriminate the output of the network from ground truth, an adversarial network was used during training. Emphysema was quantified using spatial filtering and attenuation-based thresholds. Emphysema quantification and TI were compared using the Spearman correlation coefficient. RESULTS. The mean TI for all patients was 0.57 +/- 0.13. The mean percentages of emphysema using reconstruction methods 1 and 2 were 9.96% +/- 11.87% and 8.04% +/- 10.32%, respectively. AI-based emphysema quantification showed very strong correlation with TI (reconstruction method 1, rho = -0.86; reconstruction method 2, rho = -0.85; both p <0.0001), indicating that AI-based emphysema quantification meaningfully reflects clinical pulmonary physiology. CONCLUSION. AI-based, fully automated emphysema quantification shows good correlation with TI, potentially contributing to an image-based diagnosis and quantification of emphysema severity

Feasibility of extracellular volume quantification using dual-energy CT

ObjectiveTo assess the feasibility of dual energy CT (DECT) to derive myocardial extracellular volume (ECV) and detect myocardial ECV differences without a non-contrast acquisition, compared to single energy CT (SECT). MethodsSubjects (n = 35) with focal fibrosis (n = 17), diffuse fibrosis (n = 10), and controls (n = 9) underwent non-contrast and delayed acquisitions to calculate SECT-ECV. DECT-ECV was calculated using the delayed acquisition and the derived virtual non-contrast images. In the control and diffuse fibrotic groups, the entire myocardium of the left ventricle was used to calculate ECV. Two ROIs were placed in the focal fibrotic group, one in normal and one in fibrotic myocardium. ResultsMedian ECV was 33.4% (IQR, 30.1-37.4) using SECT and 34.9% (IQR, 31.2-39.2) using DECT (p = 0.401). For both techniques, focal and diffuse fibrosis had significantly higher ECV values (all p <0.021) than normal myocardium. There was no systematic bias between DECT and SECT (p = 0.348). SECT had a higher radiation dose (1.1 mSv difference) than DECT (p <0.001). ConclusionECV can be measured using a DECT approach with only a delayed acquisition. The DECT approach provides similar results at a lower radiation dose compared to SECT

Nonbinary Quantification Technique Accounting for Myocardial Infarct Heterogeneity: Feasibility of Applying Percent Infarct Mapping in Patients

Background: Binary threshold-based quantification techniques ignore myocardial infarct (MI) heterogeneity, yielding substantial misquantification of MI. Purpose: To assess the technical feasibility of MI quantification using percent infarct mapping (PIM), a prototype nonbinary algorithm, in patients with suspected MI. Study Type: Prospective cohort Population: Patients (n5171) with suspected MI referred for cardiac MRI. Field Strength/Sequence: Inversion recovery balanced steady-state free-precession for late gadolinium enhancement (LGE) and modified Look-Locker inversion recovery (MOLLI) T1-mapping on a 1.5T system. Assessment: Infarct volume (IV) and infarct fraction (IF) were quantified by two observers based on manual delineation, binary approaches (2-5 standard deviations [ SD] and full-width at half-maximum [ FWHM] thresholds) in LGE images, and by applying the PIM algorithm in T1 and LGE images (PIMT1; PIMLGE). Statistical Test: IV and IF were analyzed using repeated measures analysis of variance (ANOVA). Agreement between the approaches was determined with Bland-Altman analysis. Interobserver agreement was assessed by intraclass correlation coefficient (ICC) analysis. Results: MI was observed in 89 (54.9%) patients, and 185 (38%) short-axis slices. IF with 2, 3, 4, 5SDs and FWHM techniques were 15.766.6, 13.465.6, 11.665.0, 10.865.2, and 10.065.2%, respectively. The 5SD and FWHM techniques had the best agreement with manual IF (9.964.8%) determination (bias 1.0 and 0.2%; P50.1426 and P50.8094, respectively). The 2SD and 3SD algorithms significantly overestimated manual IF (9.964.8%; both P<0.0001). PIMLGE measured significantly lower IF (7.863.7%) compared to manual values (P<0.0001). PIMLGE, however, showed the best agreement with the PIMT1 reference (7.663.6%, P50.3156). Interobserver agreement was rated good to excellent for IV (ICCs between 0.727-0.820) and fair to good for IF (0.589-0.736)