Acute anterior myocardial infarction seen on conventional iodine-contrast CT.
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ABSTRACT:
SUBMITTER: Hagdrup C
PROVIDER: S-EPMC5552012 | biostudies-other | 2017 Sep
REPOSITORIES: biostudies-other
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Project description:BackgroundTo assess the recovery and prognostic values of myocardial strain using cardiac magnetic resonance (CMR)- feature tracking (FT) in acute anterior and non-anterior wall myocardial infarction.Methods103 reperfused patients after STEMI who underwent CMR at about 4 days (baseline) and 4 months (follow-up) were included, including 48 and 55 patients with anterior wall myocardial infarction (AWMI) and non-anterior wall myocardial infarction(NAWMI). CMR-FT analysis was performed using cine images to measure LV global radial, circumferential, and longitudinal peak strains (GRS, GCS, and GLS, respectively). Infarct size (IS) and microvascular obstruction (MVO) were estimated by late-gadolinium enhancement imaging. The primary clinical endpoint was the occurrence of major adverse cardiac events (MACE) after infarction.ResultsPatients with AWMI had higher IS, higher MVO, lower ejection fraction, and more significantly impaired CMR-FT strain values than patients with NAWMI (all p<0.05). Global strain significantly improved at 4 months (all p<0.01), especial in NAWMI. GLS was an independent predictor (odds ratio = 2.08, 95% confidence interval = 1.032-4.227, p = 0.04] even after adjustment for IS and MVO. The optimal cutoff of GLS was -7.9%, with sensitivity and specificity were 73.3% and 75.0%, respectively. In receiver operating characteristic analysis, IS remained the strongest predictor (area under the curve [AUC] = 0.83, p<0.01), followed by MVO (AUC = 0.81, p<0.01) and GLS (AUC = 0.78, p<0.01).ConclusionCMR-FT-derived global myocardial strains significantly improved over time, especial in NAWMI. GLS measurement independently predicted the occurrence of medium-term MACE.
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Project description:To investigate the feasibility and accuracy of texture analysis to distinguish through objective and quantitative image information between healthy and infarcted myocardium with computed tomography (CT).Twenty patients (5 females; mean age 56±10years) with proven acute myocardial infarction (MI) and 20 patients (8 females; mean age 42±15years) with no cardiac abnormalities (hereafter termed controls) underwent contrast-enhanced cardiac CT. Short axis CT images of the left ventricle (LV) were reconstructed at the slice thicknesses 1mm, 2mm, and 5mm. Two independent, blinded readers segmented the LV in controls and patients. Texture analysis was performed yielding first-level features based on the histogram (variance, skewness, kurtosis, entropy), second-level features based on the gray-level co-occurrence matrix (GLCM) (contrast, correlation, energy and homogeneity), and third-level features based on the gray-level run-length matrix (GLRLM).Inter-and intrareader agreement was good to excellent for all histogram (intraclass correlation coefficient (ICC):0.70-0.93) and for all GLCM features (ICC:0.66-0.99), and was variable for the GLRLM features (ICC:-0.12-0.99). Univariate analysis showed significant differences between patients and controls for 2/4 histogram features, 3/4 GLCM and for 6/11 GLRLM features and all assessed slice thicknesses (all,p<0.05). In a multivariate logistic regression model, the single best variable from each level, determined by ROC analysis, was included stepwise. The best model included kurtosis (OR 0.08, 95%CI:0.01-0.65,P = 0.018) and short run high gray-level emphasis (SRHGE, OR 0.97, 95%CI:0.94-0.99,P = 0.007), with an area-under-the-curve (AUC) of 0.90 (95%CI:0.80-0.99). The best results for kurtosis and SRHGE (AUC = 0.78) were obtained at a 5mm slice thickness. A cut-off value of 14.4 for kurtosis+0.013*SRHGE predicted acute MI with a sensitivity of 95% (specificity 55%).Our study illustrates the feasibility of texture analysis for distinguishing healthy from acutely infarcted myocardium with cardiac CT using objective, quantitative features, with most reproducible and accurate results at a short axis slice thickness of 5mm.
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Project description:Objective: To develop predictive models for contrast induced acute kidney injury (CI-AKI) among acute myocardial infarction (AMI) patients treated invasively. Methods: Patients with AMI who underwent angiography therapy were enrolled and randomly divided into training cohort (75%) and validation cohort (25%). Machine learning algorithms were used to construct predictive models for CI-AKI. The predictive models were tested in a validation cohort. Results: A total of 1,495 patients with AMI were included. Of all the patients, 226 (15.1%) cases developed CI-AKI. In the validation cohort, Random Forest (RF) model with top 15 variables reached an area under the curve (AUC) of 0.82 (95% CI: 0.76-0.87), while the best logistic model had an AUC of 0.69 (95% CI: 0.62-0.76). ACEF (age, creatinine, and ejection fraction) model reached an AUC of 0.62 (95% CI: 0.53-0.71). RF model with top 15 variables achieved a high recall rate of 71.9% and an accuracy of 73.5% in the validation group. Random Forest model significantly outperformed logistic regression in every comparison. Conclusions: Machine learning algorithms especially Random Forest algorithm improves the accuracy of risk stratifying patients with AMI and should be used to accurately identify the risk of CI-AKI in AMI patients.
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Project description:BackgroundComputed tomography (CT) imaging has been widely used for the diagnosis and surveillance of diseases. Although CT is attracting attention due to its reasonable price, short scan time, and excellent diagnostic ability, there are severe drawbacks of conventional CT contrast agents, such as low sensitivity, serious toxicity, and complicated synthesis process. Herein, we describe iodine-doped carbon dots (IDC) for enhancing the abilities of CT contrast agents.MethodIDC was synthesized by one-pot hydrothermal synthesis for 4 h at 180 ℃ and analysis of its structure and size distribution with UV-Vis, XPS, FT-IR, NMR, TEM, and DLS. Furthermore, the CT values of IDC were calculated and compared with those of conventional CT contrast agents (Iohexol), and the in vitro and in vivo toxicities of IDC were determined to prove their safety.ResultsIDC showed improved CT contrast enhancement compared to iohexol. The biocompatibility of the IDC was verified via cytotoxicity tests, hemolysis assays, chemical analysis, and histological analysis. The osmotic pressure of IDC was lower than that of iohexol, resulting in no dilution-induced contrast decrease in plasma.ConclusionBased on these results, the remarkable CT contrast enhancement and biocompatibility of IDC can be used as an effective CT contrast agent for the diagnosis of various diseases compared with conventional CT contrast agents.
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Project description:Preclinical data suggest that an acute inflammatory response following myocardial infarction (MI) accelerates systemic atherosclerosis. Using combined positron emission and computed tomography, we investigated whether this phenomenon occurs in humans.Overall, 40 patients with MI and 40 with stable angina underwent thoracic 18F-fluorodeoxyglucose combined positron emission and computed tomography scan. Radiotracer uptake was measured in aortic atheroma and nonvascular tissue (paraspinal muscle). In 1003 patients enrolled in the Global Registry of Acute Coronary Events, we assessed whether infarct size predicted early (?30 days) and late (>30 days) recurrent coronary events. Compared with patients with stable angina, patients with MI had higher aortic 18F-fluorodeoxyglucose uptake (tissue-to-background ratio 2.15±0.30 versus 1.84±0.18, P<0.0001) and plasma C-reactive protein concentrations (6.50 [2.00 to 12.75] versus 2.00 [0.50 to 4.00] mg/dL, P=0.0005) despite having similar aortic (P=0.12) and less coronary (P=0.006) atherosclerotic burden and similar paraspinal muscular 18F-fluorodeoxyglucose uptake (P=0.52). Patients with ST-segment elevation MI had larger infarcts (peak plasma troponin 32 300 [10 200 to >50 000] versus 3800 [1000 to 9200] ng/L, P<0.0001) and greater aortic 18F-fluorodeoxyglucose uptake (2.24±0.32 versus 2.02±0.21, P=0.03) than those with non-ST-segment elevation MI. Peak plasma troponin concentrations correlated with aortic 18F-fluorodeoxyglucose uptake (r=0.43, P=0.01) and, on multivariate analysis, independently predicted early (tertile 3 versus tertile 1: relative risk 4.40 [95% CI 1.90 to 10.19], P=0.001), but not late, recurrent MI.The presence and extent of MI is associated with increased aortic atherosclerotic inflammation and early recurrent MI. This finding supports the hypothesis that acute MI exacerbates systemic atherosclerotic inflammation and remote plaque destabilization: MI begets MI.URL: https://www.clinicaltrials.gov. Unique identifier: NCT01749254.
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