We have a great interest in the article in Journal of Atherosclerosis and Thrombosis by Suzuki et al. titled Complex Aortic Arch Atherosclerosis in Acute Ischemic Stroke Patients with Non-Valvular ...Atrial Fibrillation. The authors demonstrated that 38.7% transesophageal echocardiography-derived complex aortic arch plaques (CAPs) among 106 patients with acute ischemic strokes with atrial fibrillation (AF), suggesting that patients with acute ischemic stroke and AF often had CAPs. The atheromatous lesions at the aortic arch are one of the causes of ischemic strokes. The cause of acute ischemic strokes in patients with AF could not only be cardiogenic embolisms due to AF but also aortogenic embolisms due to CAPs. The possibility of concomitant CAPs should be considered for stroke patients with AF. Non-obstructive general angioscopy has the possibility to detect aortic plaques in the aortic arch more accurately than TEE and might help to diagnose atheromatous plaques and embolic materials in the aortic arch. Further studies are needed to elucidate the causes of ischemic strokes and are expected to improve the outcomes for acute ischemic strokes in patients with AF.
Recent studies reported that a convolutional neural network (CNN; a deep learning model) can detect elevated pulmonary artery wedge pressure (PAWP) from chest radiographs, the diagnostic images most ...commonly used for assessing pulmonary congestion in heart failure. However, no method has been published for quantitatively estimating PAWP from such radiographs. We hypothesized that a regression CNN, an alternative type of deep learning, could be a useful tool for quantitatively estimating PAWP in cardiovascular diseases. We retrospectively enrolled 936 patients with cardiovascular diseases who had undergone right heart catheterization (RHC) and chest radiography and estimated PAWP by constructing a regression CNN based on the VGG16 model. We randomly categorized 80% of the data as training data (training group,
n
= 748) and 20% as test data (test group,
n
= 188). Moreover, we tuned the learning rate—one of the model parameters—by 5-hold cross-validation of the training group. Correlations between PAWP measured by RHC ground truth (GT) PAWP and PAWP derived from the regression CNN (estimated PAWP) were tested. To visualize how the regression CNN assessed the images, we created a regression activation map (RAM), a visualization technique for regression CNN. Estimated PAWP correlated significantly with GT PAWP in both the training (
r
= 0.76,
P
< 0.001) and test group (
r
= 0.62,
P
< 0.001). Bland–Altman plots found a mean (SEM) difference between GT and estimated PAWP of − 0.23 (0.16) mm Hg in the training and − 0.05 (0.41) mm Hg in the test group. The RAM showed that our regression CNN model estimated high PAWP by focusing on the cardiomegaly and pulmonary congestion. In the test group, the area under the curve (AUC) for detecting elevated PAWP (≥ 18 mm Hg) produced by the regression CNN model was similar to the AUC of an experienced cardiologist (0.86 vs 0.83, respectively;
P
= 0.24). This proof-of-concept study shows that regression CNN can quantitatively estimate PAWP from standard chest radiographs in cardiovascular diseases.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Aims: Smaller low-density lipoprotein (LDL) particle size has been suggested to result in the development of endothelial dysfunction, atherosclerosis, and in-stent restenosis (ISR); however, little ...is known regarding the impact of the LDL particle size on the neointima formation leading to ISR after everolimus-eluting stent (EES) implantation. Methods: In this study, we have included 100 patients to examine the relationship between an LDL-C/apolipoprotein B (Apo B) ≤ 1.2, reportedly representing the LDL particle size, and the neointimal characteristics using optical coherence tomography (OCT) and coronary angioscopy (CAS) during the follow-up coronary angiography (CAG) period (8.8±2.5 months) after EES implantation. We divided them into two groups: LDL-C/Apo B ≤ 1.2 group (low LDL-C/Apo B group, n=53) and LDL-C/Apo B ＞1.2 group (high LDL-C/Apo B group, n=47). Results: The low LDL-C/Apo B group had a significantly larger neointimal volume (12.8±5.3 vs. 10.3±4.9 mm3, p=0.021) and lower incidence of a neointimal homogeneous pattern (71 vs. 89 %), higher incidence of a neointimal heterogeneous pattern (25 vs. 9 %) (p=0.006) and higher prevalence of macrophage accumulation (9 vs. 2 %) (p=0.030) as assessed via OCT, and, as per the CAS findings, a higher prevalence of yellow grade ≥ 2 (grade 2; adjusted residual: 2.94, grade 3; adjusted residual: 2.00, p=0.017) than the high LDL-C/Apo B group. Conclusions: A low LDL-C/Apo B ratio was found to be strongly associated with neointimal proliferation and neointimal instability evidenced chronically by OCT and CAS. An LDL-C/Apo B ≤ 1.2 will be of aid in terms of identifying high-risk patients after EES implantation.
Objective Radwisp™ is a fluoroscopic video analysis workstation recently developed to evaluate pulmonary circulation, thereby obviating the need for contrast medium or breath-holding. This study ...validated Radwisp as a diagnostic tool for acute pulmonary embolism (APE) and evaluated its potential utility in patients with symptoms of suspected APE. Methods The study included 10 patients (mean age, 69±16 years old) who were admitted to our hospital for suspected APE based on symptoms and physical examination findings between January 2020 and April 2021. Contrast-enhanced computed tomography (CT) and cineradiography, based on standard radiographs for the creation of a Radwisp image, were performed on the same day. Of the 10 cases of suspected APE, 7 were definitively diagnosed by CT with APE, and 3 were definitively diagnosed as not having APE. Fifty physicians (25 cardiologists and 25 residents) were blinded to patient information and CT images and asked to diagnose the presence of APE based solely on the Radwisp images. Results A total of 250 diagnoses were made by cardiologists and 250 by residents. Among the cardiologists, the sensitivity and specificity of the Radwisp-based analysis were 91% and 48%, respectively, and the positive and negative predictive values were 80% and 69%, respectively. Among the residents, the sensitivity and specificity were 88% and 35%, respectively, and the positive and negative predictive values were 76% and 55%, respectively. Conclusion This study showed an initial validation of Radwisp for diagnosing APE, revealing a high sensitivity but not yet achieving a high specificity. Further studies with a larger number of cases are needed to thoroughly evaluate the diagnostic performance.
This study aimed to investigate the relationship between ocular vascular resistance parameters, evaluated by laser speckle flowgraphy (LSFG), and systemic atherosclerosis, renal parameters and ...cardiac function in acute coronary syndrome (ACS) patients. We evaluated 53 ACS patients between April 2019 and September 2020. LSFG measured the mean blur rate (MBR) and ocular blowout time (BOT) and resistivity index (RI). 110 consequent patients without a history of coronary artery disease who visited ophthalmology as a control group. Significant positive correlations were observed between ocular RI and systemic parameters in ACS patients, including intima-media thickness (r = 0.34, P = 0.015), brachial-ankle pulse-wave velocity (r = 0.41, P = 0.002), cystatin C (r = 0.32, P = 0.020), and E/e' (r = 0.34, P = 0.013). Ocular RI was significantly higher in the ACS group than in the control group in male in their 40 s (0.37 ± 0.02 vs. 0.29 ± 0.01, P < 0.001) and 50 s (0.36 ± 0.02 vs. 0.30 ± 0.01, P = 0.01). We found that the ocular RI was associated with systemic atherosclerosis, early renal dysfunction, and diastolic cardiac dysfunction in ACS patients, suggesting that it could be a useful non-invasive comprehensive arteriosclerotic marker.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Low wall shear stress (WSS) is associated with plaque formation. However, the relationship between WSS and coronary plaque vulnerability remains unclear. Therefore, this study aimed to clarify the in ...vivo relationship between luminal WSS derived from three-dimensional (3D) computed tomography (CT) and plaque vulnerability within the coronary artery. Forty-three consecutive patients with ischemic heart disease and coronary stenotic lesions were enrolled and underwent coronary angiography and color-coded intravascular ultrasonography (iMap™) followed by multi-slice coronary CT angiography. CT-derived high-risk plaque was defined by specific CT characteristics, including low CT intensity (< 30 HU) and positive remodeling. The Student’s
t
test, Mann–Whitney
U
test,
χ
2
test, repeated measures analysis of variance, and logistic and multiple regression were used for statistical analyses. CT-derived high-risk plaque (
n
= 15) had higher values of maximum and average shear stress than CT-derived stable plaque (474 ± 453 vs. 158 ± 138 Pa,
p
= 0.018; 4.2 ± 3.1 vs. 1.6 ± 1.2 Pa,
p
= 0.007, respectively). Compared with patients with CT-derived stable plaque, those with CT-derived high-risk plaque had a higher prevalence of necrotic and lipidic characteristics (44 ± 13 vs. 31 ± 11%,
p
= 0.001) based on iMap™. Multivariate logistic regression analysis showed that the average WSS and necrotic plus lipidic content were independent determinants of CT-derived high-risk plaque (average WSS: odds ratio 2.996,
p
= 0.014; necrotic plus lipidic content: odds ratio 1.306,
p
= 0.036). Our findings suggested that CT-derived high-risk plaque may coexist with high shear stress on the plaque surface.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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