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BackgroundDiabetes mellitus (DM) and coronary microvascular dysfunction (CMD) increase the risk of adverse cardiac events in patients with non-ST-segment elevation myocardial infarction (NSTEMI). This study aimed to evaluate the combined risk estimates of DM and CMD, assessed by the angiography-derived index of microcirculatory resistance (angio-IMR), in patients with NSTEMI.MethodsA total of 2212 patients with NSTEMI who underwent successful percutaneous coronary intervention (PCI) were retrospectively enrolled from three centers. The primary outcome was a composite of cardiac death or readmission for heart failure at a 2-year follow-up.ResultsPost-PCI angio-IMR did not significantly differ between the DM group and the non-DM group (20.13 [17.91–22.70] vs. 20.19 [18.14–22.77], P = 0.530). DM patients exhibited a notably higher risk of cardiac death or readmission for heart failure at 2 years compared to non-DM patients (9.5% vs. 5.4%, P < 0.001). NSTEMI patients with both DM and CMD experienced the highest cumulative incidence of cardiac death or readmission for heart failure at 2 years (24.0%, P < 0.001). The combination of DM and CMD in NSTEMI patients were identified as the most powerful independent predictor for cardiac death or readmission for heart failure at 2 years (adjusted HR: 7.894, [95% CI, 4.251–14.659], p < 0.001).ConclusionsIn patients with NSTEMI, the combination of DM and CMD is an independent predictor of cardiac death or readmission for heart failure. Angio-IMR could be used as an additional evaluation tool for the management of NSTEMI patients with DM.Trial registrationURL: https://www.clinicaltrials.gov; Unique identifier: NCT05696379.Graphical

BackgroundIntracranial atherosclerotic stenosis (ICAS) stands as a prominent contributor to ischemic strokes. Although a large number of ICAS-related hemodynamic assessment studies have been performed, their methods had limitations, such as high requirements for image quality and simulations with complex assumption. Therefore, there is an urgent need for a method to conveniently and efficiently conduct hemodynamic assessment for ICAS but remain high accuracy.ObjectiveThe purpose of this study is to explore the feasibility of calculating fractional flow (FF) from angiographic image with a single projection and verify its accuracy through the FF measured by pressure wires.MethodIn this retrospective study, ICAS patients (n=135) who underwent pressure wire measurement and DSA evaluation were recruited. A computational fluid dynamics-based FF was calculated by AccuICAD using angiographic images (AccuICAD-FF). The accuracy the computed FF was validated by the wire-based FF as a baseline standard (wire-FF).ResultsThe mean value of wire-FF was 0.77±0.18, while AccuICAD-FF had an average value of 0.78±0.19. Good correlation (Pearson’s correlation coefficient r=0.90, P<0.001) between AccuICAD-FF and wire-FF was observed. Bland-Altman analysis showed that the mean difference between AccuICAD-FF and wire-FF was -0.01±0.08, indicating good agreement. The area under the curve (AUC) of AccuICAD-FF and diameter stenosis in predicting wire-FF≤0.70, wire-FF≤0.75, and wire-FF≤0.80 were 0.982 vs 0.788, 0.968 vs 0.780, and 0.943 vs 0.806, respectively.ConclusionThe physiological index AccuICAD-FF calculated from a single DSA projection showed good correlation and agreement with wire-based FF. The FF calculation method based on angiographic images with a single projection exhibits superior efficiency and less imaging acquisition. AccuICAD could be an efficient and valid tool without the need of invasive pressure-wire measurement for the evaluation of intracranial stenosis. Figure 1 This is a typical case of MCA stenosis. The left image is the original DSA image with the pressure-wire measurement (proximal pressure (Pa) =61 mmHg, distal pressure (Pd)=38 mmHg, wire-FF=0.62). The right image is the result of AccuICAD imported into a single DSA projection to calculate FF (AccuICAD-FF=0.64). P-015 Figure 1DisclosuresM. Wang: 1; C; Medical Health Science and Technology Project of Zhejiang Provincial Health Commission (WKJ-ZJ-2340). P. Yang: None. J. Wang: None. C. Rong: 5; C; ArteryFlow Technology Co., Ltd. Y. Hu: 5; C; ArteryFlow Technology Co., Ltd. R. Zou: 5; C; ArteryFlow Technology Co., Ltd. X. Leng: 5; C; ArteryFlow Technology Co., Ltd. L. Zhang: None. J. Fiehler: None. A. Siddiqui: None. J. Xiang: 1; C; Zhejiang Provincial Key Research and Development Plan (No. 2024C03095), Hangzhou Leading Innovation and Entrepreneurship Team Project (No.TD2022007). 5; C; ArteryFlow Technology Co., Ltd. J. Liu: None. S. Wan: 1; C; Key Research and Development Project of Zhejiang Provincial Department of Science and Technology (2021C03105), Special Support Program for High Level Talents of Zhejiang Province (2022R52038).

AccuFFRangio is a novel method for fast computation of fractional flow reserve (FFR) based on coronary angiography and computational fluid dynamics. The association between the AccuFFRangio and clinical outcomes after drug-coated balloon (DCB) or plain old balloon angioplasty (POBA) remains to be investigated. This study included consecutive patients who underwent balloon angioplasty from December 2016 to October 2020. AccuFFRangio was calculated retrospectively based on the post-procedural angiography obtained immediately after angioplasty. The primary endpoint was major adverse cardiac events (MACE), defined as a composite of all-cause death, vessel-related myocardial infarction, and repeat target vessel revascularization. A total of 169 patients were retrospectively analyzed in this study. Post-procedural AccuFFRangio (hazard ratio [HR] per 0.1 increase 0.33, 95% confidence interval [CI] 0.22-0.48, p < 0.001) was an independent predictor for MACE at 2-year follow-up. Post-procedural AccuFFRangio ≤ 0.87 was determined as the optimal cutoff value to predict MACE with an area under the curve (AUC) of 0.872 (95% CI 0.813-0.919, p < 0.001). AccuFFRangio measured immediately after balloon angioplasty is a promising predictor of unfavorable clinical outcomes.

Background and PurposeThe objective of this study was to identify the morphological and hemodynamic factors associated with the rupture of multiple intracranial aneurysms regardless of patient-related factors and establish a statistical model for aneurysm rupture risk assessment.MethodsThe digital subtraction angiography (DSA) data of 104 mirror intracranial aneurysms in 52 consecutive patients were retrospectively analyzed in this study. 21 morphological parameters and hemodynamic parameters were calculated by 3-dimensional reconstruction and computational fluid dynamics (CFD) simulation. Significant differences (p < 0.05) between the two groups were subsequently tested with the multivariate logistic regression to identify the independent risk factors. A prediction model was established based on the independent risk factors. The receiver operating characteristics (ROCs) were generated to estimate the prediction performance. A cohort of patients with multiple intracranial aneurysms admitted in our institute from January 2021 to October 2021 was introduced to verify the value of the model.ResultsSignificant differences between the ruptured and unruptured aneurysms were found in 15 out of 19 parameters. Bleb formation, neck width, and size ratio were independent factors in the multivariate logistic regression. A prediction model based on the three independent risk factors was established: Odds = −1.495 – 0.707 × (Neckwidth) + 3.061 × (Blebformation) + 2.1 × (SR) (bleb formation: Yes = 1, No = 0). The area under the curve (AUC) value of the model was 0.901. In the validation cohort, the prediction model showed satisfying performance in assessing multiple aneurysm rupture risk with a sensitivity of 100% and specificity of 88.46%.ConclusionBleb formation, neck width, and size ratio were independently associated with aneurysm rupture status. The prediction model may help in identifying the aneurysm with high rupture risk.

Some investigators have proposed models for large-scale Discrete Element Method (DEM) simulations since the numder of particles is restricted by the limit of computer memories In these models the particle-to-particle contact force was not evaluated accurately. This is due to the fact that the models were developed for fluidized beds where the fluid drag force is dominant. In the present study, Advanced Representative Particle Model (ARPM) is developed to evaluate the contact force accurately in the large-scale DEM simulations. In the ARPM, the original small-size particles are represented by a large-size ARPM particle. The translational and rotational energies are the same for the ARPM particles and the original small-size particles in the interaction. In this study, the ARPM is verfied by numerical examplas. It is clarified that the behavior of the original small-size particles is successfully simulated by using the large-size ARPM particles.