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).

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BackgroundFirst pass effect (FPE) in mechanical thrombectomy is thought to be associated with good clinical outcomes.ObjectiveTo determine FPE rates as a function of thrombectomy technique and to compare clinical outcomes between patients with and without FPE.MethodsIn July 2020, a literature search on FPE (defined as modified Thrombolysis in Cerebral Infarction (TICI) 2c–3 after a single pass) and modified FPE (mFPE, defined as TICI 2b–3 after a single pass) and mechanical thrombectomy for stroke was performed. Using a random-effects meta-analysis, we evaluated the following outcomes for both FPE and mFPE: overall rates, rates by thrombectomy technique, rates of good neurologic outcome (modified Rankin Scale score ≤2 at day 90), mortality, and symptomatic intracerebral hemorrhage (sICH) rate.ResultsSixty-seven studies comprising 16 870 patients were included. Overall rates of FPE and mFPE were 28% and 45%, respectively. Thrombectomy techniques shared similar FPE (p=0.17) and mFPE (p=0.20) rates. Higher odds of good neurologic outcome were found when we compared FPE with non-FPE (56% vs 41%, OR=1.78) and mFPE with non-mFPE (57% vs 44%, OR=1.73). FPE had a lower mortality rate (17% vs 25%, OR=0.62) than non-FPE. FPE and mFPE were not associated with lower sICH rate compared with non-FPE and non-mFPE (4% vs 18%, OR=0.41 for FPE; 5% vs 7%, OR=0.98 for mFPE).ConclusionsOur findings suggest that approximately one-third of patients achieve FPE and around half of patients achieve mFPE, with equivalent results throughout thrombectomy techniques. FPE and mFPE are associated with better clinical outcomes.

Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. Following H&E staining, quantification of clot components was performed by two different methods: a pathologist using a reference standard method (Adobe Photoshop CC) and an experienced researcher using Orbit Image Analysis. Following quantification, the clots were categorized into 3 types: RBC dominant (≥60% RBCs), Mixed and Fibrin dominant (≥60% Fibrin). Correlations between clot composition and Hounsfield Units density on Computed Tomography (CT) were assessed. There was a significant correlation between the components of clots as quantified by the Orbit Image Analysis algorithm and the reference standard approach (ρ = 0.944**, p < 0.001, n = 150). A significant relationship was found between clot composition (RBC-Rich, Mixed, Fibrin-Rich) and the presence of a Hyperdense artery sign using the algorithmic method (X2(2) = 6.712, p = 0.035*) but not using the reference standard method (X2(2) = 3.924, p = 0.141). Orbit Image Analysis machine learning software can be used for the histological quantification of AIS clots, reproducibly generating composition analyses similar to current reference standard methods.

BACKGROUND:The natural history of coronary artery disease (CAD) in patients with

Differences in all major outcome measures were markedly better in patients with complete versus incomplete but still 'successful' revascularization using prior thresholds, with ORs in the order of those seen in recent definitive trials comparing EVT to an intravenous tissue plasminogen activator.

Background. Evaluation of resting myocardial computed tomography perfusion (CTP) by coronary CT angiography (CCTA) might serve as a useful addition for determining coronary artery disease. We aimed to evaluate the incremental benefit of resting CTP over coronary stenosis for predicting ischemia using a computational algorithm trained by machine learning methods.Methods. 252 patients underwent CCTA and invasive fractional flow reserve (FFR). CT stenosis was classified as 0%, 1-30%, 31-49%, 50-70%, and >70% maximal stenosis. Significant ischemia was defined as invasive FFR < 0.80. Resting CTP analysis was performed using a gradient boosting classifier for supervised machine learning.Results. On a per-patient basis, accuracy, sensitivity, specificity, positive predictive, and negative predictive values according to resting CTP when added to CT stenosis (>70%) for predicting ischemia were 68.3%, 52.7%, 84.6%, 78.2%, and 63.0%, respectively. Compared with CT stenosis [area under the receiver operating characteristic curve (AUC): 0.68, 95% confidence interval (CI) 0.62-0.74], the addition of resting CTP appeared to improve discrimination (AUC: 0.75, 95% CI 0.69-0.81, P value .001) and reclassification (net reclassification improvement: 0.52, P value < .001) of ischemia.Conclusions. The addition of resting CTP analysis acquired from machine learning techniques may improve the predictive utility of significant ischemia over coronary stenosis. (J Nucl Cardiol 2018;25:223-33.)

BackgroundWall shear stress (WSS) is an established predictor of coronary atherosclerosis progression. Prior studies have reported that high WSS has been associated with high‐risk atherosclerotic plaque characteristics (APCs). WSS and APCs are quantifiable by coronary computed tomography angiography, but the relationship of coronary lesion ischemia—evaluated by fractional flow reserve—to WSS and APCs has not been examined.Methods and Results WSS measures were obtained from 100 evaluable patients who underwent coronary computed tomography angiography and invasive coronary angiography with fractional flow reserve. Patients were categorized according to tertiles of mean WSS values defined as low, intermediate, and high. Coronary ischemia was defined as fractional flow reserve ≤0.80. Stenosis severity was determined by minimal luminal diameter. APCs were defined as positive remodeling, low attenuation plaque, and spotty calcification. The likelihood of having positive remodeling and low‐attenuation plaque was greater in the high WSS group compared with the low WSS group after adjusting for minimal luminal diameter (odds ratio for positive remodeling: 2.54, 95% CI 1.12–5.77; odds ratio for low‐attenuation plaque: 2.68, 95% CI 1.02–7.06; both P<0.05). No significant relationship was observed between WSS and fractional flow reserve when adjusting for either minimal luminal diameter or APCs. WSS displayed no incremental benefit above stenosis severity and APCs for detecting lesions that caused ischemia (area under the curve for stenosis and APCs: 0.87, 95% CI 0.81–0.93; area under the curve for stenosis, APCs, and WSS: 0.88, 95% CI 0.82–0.93; P=0.30 for difference).ConclusionsHigh WSS is associated with APCs independent of stenosis severity. WSS provided no added value beyond stenosis severity and APCs for detecting lesions with significant ischemia.