Diagnostic Accuracy of a Novel On-site Virtual Fractional Flow Reserve Parallel Computing System

PURPOSE: To evaluate the diagnostic accuracy of a novel on-site virtual fractional flow reserve (vFFR) derived from coronary computed tomography angiography (CTA). MATERIALS AND METHODS: We analyzed 100 vessels from 57 patients who had undergone CTA followed by invasive FFR during coronary angiography. Coronary lumen segmentation and three-dimensional reconstruction were conducted using a completely automated algorithm, and parallel computing based vFFR prediction was performed. Lesion-specific ischemia based on FFR was defined as significant at ≤0.8, as well as ≤0.75, and obstructive CTA stenosis was defined that ≥50%. The diagnostic performance of vFFR was compared to invasive FFR at both ≤0.8 and ≤0.75. RESULTS: The average computation time was 12 minutes per patient. The correlation coefficient (r) between vFFR and invasive FFR was 0.75 [95% confidence interval (CI) 0.65 to 0.83], and Bland-Altman analysis showed a mean bias of 0.005 (95% CI -0.011 to 0.021) with 95% limits of agreement of -0.16 to 0.17 between vFFR and FFR. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 78.0%, 87.1%, 72.5%, 58.7%, and 92.6%, respectively, using the FFR cutoff of 0.80. They were 87.0%, 95.0%, 80.0%, 54.3%, and 98.5%, respectively, with the FFR cutoff of 0.75. The area under the receiver-operating characteristics curve of vFFR versus obstructive CTA stenosis was 0.88 versus 0.61 for the FFR cutoff of 0.80, respectively; it was 0.94 versus 0.62 for the FFR cutoff of 0.75. CONCLUSION: Our novel, fully automated, on-site vFFR technology showed excellent diagnostic performance for the detection of lesion-specific ischemia.ope

Longitudinal quantitative assessment of coronary atherosclerosis related to normal systolic blood pressure maintenance in the absence of established cardiovascular disease

ope

Quantitative measurement of lipid rich plaque by coronary computed tomography angiography: A correlation of histology in sudden cardiac death

BACKGROUND AND AIMS: Recent advancements in coronary computed tomography angiography (CCTA) have allowed for the quantitative measurement of high-risk lipid rich plaque. Determination of the optimal threshold for Hounsfield units (HU) by CCTA for identifying lipid rich plaque remains unknown. We aimed to validate reliable cut-points of HU for quantitative assessment of lipid rich plaque. METHODS: 8 post-mortem sudden coronary death hearts were evaluated with CCTA and histologic analysis. Quantitative plaque analysis was performed in histopathology images and lipid rich plaque area was defined as intra-plaque necrotic core area. CCTA images were analyzed for quantitative plaque measurement. Low attenuation plaque (LAP) was defined as any pixel < 30, 45, 60, 75, and 90 HU cut-offs within a coronary plaque. The area of LAP was calculated in each cross-section. RESULTS: Among 105 cross-sections, 37 (35.2%) cross-sectional histology images contained lipid rich plaque. Although the highest specificity for identifying lipid rich plaque was shown with <30 HU cut-off (88.2%), sensitivity (e.g. 55.6% for <75 HU, 16.2% for <30 HU) and negative predictive value (e.g. 75.9% for <75 HU, 65.9% for <30 HU) tended to increase with higher HU cut-offs. For quantitative measurement, <75 HU showed the highest correlation coefficient (0.292, p = 0.003) and no significant differences were observed between lipid rich plaque area and LAP area between histology and CT analysis (Histology: 0.34 ± 0.73 mm2, QCT: 0.37 ± 0.71 mm2, p = 0.701). CONCLUSIONS: LAP area by CCTA using a <75 HU cut-off value demonstrated high sensitivity and quantitative agreement with lipid rich plaque area by histology analysis.restrictio

Fully automated quantification of cardiac chamber and function assessment in 2-D echocardiography: clinical feasibility of deep learning-based algorithms

We aimed to compare the segmentation performance of the current prominent deep learning (DL) algorithms with ground-truth segmentations and to validate the reproducibility of the manually created 2D echocardiographic four cardiac chamber ground-truth annotation. Recently emerged DL based fully-automated chamber segmentation and function assessment methods have shown great potential for future application in aiding image acquisition, quantification, and suggestion for diagnosis. However, the performance of current DL algorithms have not previously been compared with each other. In addition, the reproducibility of ground-truth annotations which are the basis of these algorithms have not yet been fully validated. We retrospectively enrolled 500 consecutive patients who underwent transthoracic echocardiogram (TTE) from December 2019 to December 2020. Simple U-net, Res-U-net, and Dense-U-net algorithms were compared for the segmentation performances and clinical indices such as left atrial volume (LAV), left ventricular end diastolic volume (LVEDV), left ventricular end systolic volume (LVESV), LV mass, and ejection fraction (EF) were evaluated. The inter- and intra-observer variability analysis was performed by two expert sonographers for a randomly selected echocardiographic view in 100 patients (apical 2-chamber, apical 4-chamber, and parasternal short axis views). The overall performance of all DL methods was excellent [average dice similarity coefficient (DSC) 0.91 to 0.95 and average Intersection over union (IOU) 0.83 to 0.90], with the exception of LV wall area on PSAX view (average DSC of 0.83, IOU 0.72). In addition, there were no significant difference in clinical indices between ground truth and automated DL measurements. For inter- and intra-observer variability analysis, the overall intra observer reproducibility was excellent: LAV (ICC = 0.995), LVEDV (ICC = 0.996), LVESV (ICC = 0.997), LV mass (ICC = 0.991) and EF (ICC = 0.984). The inter-observer reproducibility was slightly lower as compared to intraobserver agreement: LAV (ICC = 0.976), LVEDV (ICC = 0.982), LVESV (ICC = 0.970), LV mass (ICC = 0.971), and EF (ICC = 0.899). The three current prominent DL-based fully automated methods are able to reliably perform four-chamber segmentation and quantification of clinical indices. Furthermore, we were able to validate the four cardiac chamber ground-truth annotation and demonstrate an overall excellent reproducibility, but still with some degree of inter-observer variability.restrictio

Atherosclerotic plaque characteristics by CT angiography identify coronary lesions that cause ischemia: a direct comparison to fractional flow reserve

OBJECTIVES: This study evaluated the association between atherosclerotic plaque characteristics (APCs) by coronary computed tomographic angiography (CTA), and lesion ischemia by fractional flow reserve (FFR). BACKGROUND: FFR is the gold standard for determining lesion ischemia. Although APCs by CTA-including aggregate plaque volume % (%APV), positive remodeling (PR), low attenuation plaque (LAP), and spotty calcification (SC)-are associated with future coronary syndromes, their relationship to lesion ischemia is unclear. METHODS: 252 patients (17 centers, 5 countries; mean age 63 years; 71% males) underwent coronary CTA, with FFR performed for 407 coronary lesions. Coronary CTA was interpreted for 1.10; 2) LAP, any voxel <30 Hounsfield units; and 3) SC, nodular calcified plaque <3 mm. Odds ratios (OR) and net reclassification improvement of APCs for lesion ischemia, defined by FFR ≤0.8, were analyzed. RESULTS: By FFR, ischemia was present in 151 lesions (37%). %APV was associated with a 50% increased risk of ischemia per 5% additional APV. PR, LAP, and SC were associated with ischemia, with a 3 to 5 times higher prevalence than in nonischemic lesions. In multivariable analyses, a stepwise increased risk of ischemia was observed for 1 (OR: 4.0, p < 0.001) and ≥2 (OR: 12.1, p < 0.001) APCs. These findings were APC dependent, with PR (OR: 5.3, p < 0.001) and LAP (OR: 2.1, p = 0.038) associated with ischemia, but not SC. When examined by stenosis severity, PR remained a predictor of ischemia for all lesions, whereas %APV and LAP were associated with ischemia for only ≥50%, but not for <50%, stenosis. CONCLUSIONS: %APV and APCs by coronary CTA improve identification of coronary lesions that cause ischemia. PR is associated with all ischemia-causing lesions, whereas %APV and LAP are only associated with ischemia-causing lesions ≥50%. (Determination of Fractional Flow Reserve by Anatomic Computed Tomographic Angiography; NCT01233518).ope

Effects of Statins on Coronary Atherosclerotic Plaques: The PARADIGM Study

OBJECTIVES: This study sought to describe the impact of statins on individual coronary atherosclerotic plaques. BACKGROUND: Although statins reduce the risk of major adverse cardiovascular events, their long-term effects on coronary atherosclerosis remain unclear. METHODS: We performed a prospective, multinational study consisting of a registry of consecutive patients without history of coronary artery disease who underwent serial coronary computed tomography angiography at an interscan interval of ≥2 years. Atherosclerotic plaques were quantitatively analyzed for percent diameter stenosis (%DS), percent atheroma volume (PAV), plaque composition, and presence of high-risk plaque (HRP), defined by the presence of ≥2 features of low-attenuation plaque, positive arterial remodeling, or spotty calcifications. RESULTS: Among 1,255 patients (60 ± 9 years of age; 57% men), 1,079 coronary artery lesions were evaluated in statin-naive patients (n = 474), and 2,496 coronary artery lesions were evaluated in statin-taking patients (n = 781). Compared with lesions in statin-naive patients, those in statin-taking patients displayed a slower rate of overall PAV progression (1.76 ± 2.40% per year vs. 2.04 ± 2.37% per year, respectively; p = 0.002) but more rapid progression of calcified PAV (1.27 ± 1.54% per year vs. 0.98 ± 1.27% per year, respectively; p 50% DS were not different (1.0% vs. 1.4%, respectively; p > 0.05). Statins were associated with a 21% reduction in annualized total PAV progression above the median and 35% reduction in HRP development. CONCLUSIONS: Statins were associated with slower progression of overall coronary atherosclerosis volume, with increased plaque calcification and reduction of high-risk plaque features. Statins did not affect the progression of percentage of stenosis severity of coronary artery lesions but induced phenotypic plaque transformation. (Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography Imaging [PARADIGM]; NCT02803411).restrictio

Atherogenic index of plasma and the risk of rapid progression of coronary atherosclerosis beyond traditional risk factors

Background and aims: The atherogenic index of plasma (AIP) has been suggested as a marker of plasma athe-rogenicity. This study aimed to assess the association between AIP and the rapid progression of coronary atherosclerosis using serial coronary computed tomography angiography (CCTA). Methods: A total of 1488 adults (60.9 +/- 9.2 years, 58.9% male) who underwent serial CCTA with a median inter-scan period of 3.4 years were included. AIP was defined as the base 10 logarithm of the ratio of the concen-trations of triglyceride to high-density lipoprotein cholesterol. Rapid plaque progression (RPP) was defined as the change of percentage atheroma volume (PAV) &gt;1.0%/year. All participants were divided into three groups based on AIP tertiles. Results: Baseline total PAV (median [interquartile range (IQR)]) (%) (group I [lowest]: 1.91 [0.00, 6.21] vs. group II: 2.82 [0.27, 8.83] vs. group III [highest]: 2.70 [0.41, 7.50]), the annual change of total PAV (median [IQR]) (%/year) (group I: 0.27 [0.00, 0.81] vs. group II: 0.37 [0.04, 1.11] vs. group III: 0.45 [0.06, 1.25]), and the incidence of RPP (group I: 19.7% vs. group II: 27.3% vs. group III: 31.4%) were significantly different among AIP tertiles (all p &lt; 0.05). In multiple logistic regression analysis, the risk of RPP was increased in group III (odds ratio: 1.52, 95% confidence interval: 1.02-2.26; p = 0.042) compared to group I after adjusting for clinical factors and baseline total PAV. Conclusions: Based on serial CCTA findings, AIP is an independent predictive marker for RPP beyond traditional risk factors