Automated ASPECTS calculation may equal the performance of experienced clinicians: a machine learning study based on a large cohort.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS) is a semi-quantitative method to evaluate the severity of early ischemic change on non-contrast computed tomography (NCCT) in patients with acute ischemic stroke (AIS). In this work, we propose an automated ASPECTS method based on large cohort of data and machine learning. METHODS: For this study, we collected 3626 NCCT cases from multiple centers and annotated directly on this dataset by neurologists. Based on image analysis and machine learning methods, we constructed a two-stage machine learning model. The validity and reliability of this automated ASPECTS method were tested on an independent external validation set of 300 cases. Statistical analyses on the total ASPECTS, dichotomized ASPECTS, and region-level ASPECTS were presented. RESULTS: On an independent external validation set of 300 cases, for the total ASPECTS results, the intraclass correlation coefficient between automated ASPECTS and expert-rated was 0.842. The agreement between ASPECTS threshold of ≥ 6 versus < 6 using a dichotomized method was moderate (κ = 0.438, 0.391-0.477), and the detection rate (sensitivity) was 86.5% for patients with ASPECTS threshold of ≥ 6. Compared with the results of previous studies, our method achieved a slight lead in sensitivity (67.8%) and AUC (0.845), with comparable accuracy (78.9%) and specificity (81.2%). CONCLUSION: The proposed automated ASPECTS method driven by a large cohort of NCCT images performed equally well compared with expert-rated ASPECTS. This work further demonstrates the validity and reliability of automated ASPECTS evaluation method. CLINICAL RELEVANCE STATEMENT: The automated ASPECTS method proposed by this study may help AIS patients to receive rapid intervention, but should not be used as a stand-alone diagnostic basis. KEY POINTS: NCCT-based manual ASPECTS scores were poorly consistent. Machine learning can automate the ASPECTS scoring process. Machine learning model design based on large cohort data can effectively improve the consistency of ASPECTS scores.

PCSK9 expression in fibrous cap possesses a marker for rupture in advanced plaque.

BACKGROUND: To date, PCSK9 inhibitors are well known for eliminating cardiac and cerebral artery ischemia events by lowering the serum lipid level. However, the pathophysiological value of in-plaque PCSK9 expression is still unclear. METHODS: Advanced plaques removed by carotid endarterectomy were sectioned and stained to identify the PCSK9 expression pattern and its co-expression with rupture-relevant markers. To investigate the correlation of PCSK9 expression with regional blood shear flow, hemodynamic characteristics were analyzed using computational fluid dynamics, and representative parameters were compared between PCSK9 positive and negative staining plaques. To explore this phenomenon in vitro, human aortic vascular smooth muscle cells were used to overexpress and knock down PCSK9. The impacts of PCSK9 modulations on mechanical sensor activity were testified by western blot and immunofluorescence. Real-time polymerase chain reaction was used to evaluate the transcription levels of downstream rupture-prone effectors. RESULTS: PCSK9 distribution in plaque preferred cap and shoulder regions, residing predominantly in smooth muscle actin-positive cells. Cap PCSK9 expression correlated with fibrous cap thickness negatively and co-expressed with MMP-9, both pointing to the direction of plaque rupture. A hemodynamic profile indicated a rupture-prone feature of cap PCSK9 expression. In vitro, overexpression and knockdown of PCSK9 in human aortic vascular smooth muscle cells has positive modulation on mechanical sensor Yes-associated protein 1 (YAP) activity and transcription levels of its downstream rupture-prone effectors. Serial section staining verified in situ colocalization among PCSK9, YAP, and downstream effectors. CONCLUSIONS: Cap PCSK9 possesses a biomarker for rupture risk, and its modulation may lead to a novel biomechanical angle for plaque interventions.

Angiography-based Fractional Flow Reserve for the Prediction of Clinical Outcomes After Drug-coated Balloon or Plain Old Balloon Angioplasty.

BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: AccuFFRangio measured immediately after balloon angioplasty is a promising predictor of unfavorable clinical outcomes.

Hemodynamic alterations of flow diverters on aneurysms at the fetal posterior communicating artery: A simulation study using CFD to compare the surpass streamline, pipeline flex, and tubridge devices.

PURPOSE: Traditional flow diverters (FDs) for treating aneurysms at the fetal posterior communicating artery are unsatisfactory. Surpass Streamline is a novel FD with different mesh characteristics; however, the outcomes for such aneurysms remain unclear. This study aimed to compare hemodynamic alterations induced by Surpass Streamline, Pipeline Flex, and Tubridge devices and explore possible strategies for aneurysms at the fetal posterior communicating artery. METHODS: Two simulated aneurysms (Case 1, Case 2) were constructed from digital subtraction angiography (DSA). The three FDs were virtually deployed, and hemodynamic analysis based on computational fluid dynamics was performed. Hemodynamic parameters, including the sac-averaged velocity magnitude (Velocity), high-flow volume (HFV), and wall shear stress (WSS), were compared between each FD and the untreated model (control). Surpass Streamline was performed in real life for two aneurysms and the clinical outcomes were collected for analysis. RESULTS: Compared to the control, the Surpass resulted in the most significant reduction in flow. In Case 1, the Velocity, HFV, and WSS were reduced by 51.6%, 78.1%, and 64.3%, respectively. In Case 2, the Velocity, HFV, and WSS were reduced by 48.0%, 81.1%, and 65.3%, respectively. Tubridge showed slightly larger changes in hemodynamic parameters than Pipeline. In addition, our analysis suggested that metal coverage was correlated with the WSS, Velocity, and HFV. The postoperative DSA showed that the aneurysm was nearly occluded in Case 1 and decreased in Case 2. CONCLUSION: Compared to that with the Pipeline and Tubridge, the Surpass resulted in the greatest reduction in hemodynamic parameters and might be effective for aneurysms at the fetal posterior communicating artery. Virtual FD deployment and computational fluid dynamics analysis may be used to predict the treatment outcomes.

Comparison of deep learning-based image segmentation methods for intravascular ultrasound on retrospective and large image cohort study.

OBJECTIVES: The aim of this study was to investigate the generalization performance of deep learning segmentation models on a large cohort intravascular ultrasound (IVUS) image dataset over the lumen and external elastic membrane (EEM), and to assess the consistency and accuracy of automated IVUS quantitative measurement parameters. METHODS: A total of 11,070 IVUS images from 113 patients and pullbacks were collected and annotated by cardiologists to train and test deep learning segmentation models. A comparison of five state of the art medical image segmentation models was performed by evaluating the segmentation of the lumen and EEM. Dice similarity coefficient (DSC), intersection over union (IoU) and Hausdorff distance (HD) were calculated for the overall and for subsets of different IVUS image categories. Further, the agreement between the IVUS quantitative measurement parameters calculated by automatic segmentation and those calculated by manual segmentation was evaluated. Finally, the segmentation performance of our model was also compared with previous studies. RESULTS: CENet achieved the best performance in DSC (0.958 for lumen, 0.921 for EEM) and IoU (0.975 for lumen, 0.951 for EEM) among all models, while Res-UNet was the best performer in HD (0.219 for lumen, 0.178 for EEM). The mean intraclass correlation coefficient (ICC) and Bland-Altman plot demonstrated the extremely strong agreement (0.855, 95% CI 0.822-0.887) between model's automatic prediction and manual measurements. CONCLUSIONS: Deep learning models based on large cohort image datasets were capable of achieving state of the art (SOTA) results in lumen and EEM segmentation. It can be used for IVUS clinical evaluation and achieve excellent agreement with clinicians on quantitative parameter measurements.

Accuracy of intravascular ultrasound-derived virtual fractional flow reserve (FFR) and FFR derived from computed tomography for functional assessment of coronary artery disease.

BACKGROUND: Coronary computed tomography-derived fractional flow reserve (CT-FFR) and intravascular ultrasound-derived fractional flow reserve (IVUS-FFR) are two functional assessment methods for coronary stenoses. However, the calculation algorithms for these methods differ significantly. This study aimed to compare the diagnostic performance of CT-FFR and IVUS-FFR using invasive fractional flow reserve (FFR) as the reference standard. METHODS: Six hundred and seventy patients (698 lesions) with known or suspected coronary artery disease were screened for this retrospective analysis between January 2020 and July 2021. A total of 40 patients (41 lesions) underwent intravascular ultrasound (IVUS) and FFR evaluations within six months after completing coronary CT angiography were included. Two novel CFD-based models (AccuFFRct and AccuFFRivus) were used to compute the CT-FFR and IVUS-FFR values, respectively. The invasive FFR ≤ 0.80 was used as the reference standard for evaluating the diagnostic performance of CT-FFR and IVUS-FFR. RESULTS: Both AccuFFRivus and AccuFFRct demonstrated a strong correlation with invasive FFR (R = 0.7913, P < 0.0001; and R = 0.6296, P < 0.0001), and both methods showed good agreement with FFR. The area under the receiver operating characteristic curve was 0.960 (P < 0.001) for AccuFFRivus and 0.897 (P < 0.001) for AccuFFRct in predicting FFR ≤ 0.80. FFR ≤ 0.80 were predicted with high sensitivity (96.6%), specificity (85.7%), and the Youden index (0.823) using the same cutoff value of 0.80 for AccuFFRivus. A good diagnostic performance (sensitivity 89.7%, specificity 85.7%, and Youden index 0.754) was also demonstrated by AccuFFRct. CONCLUSIONS: AccuFFRivus, computed from IVUS images, exhibited a high diagnostic performance for detecting myocardial ischemia. It demonstrated better diagnostic power than AccuFFRct, and could serve as an accurate computational tool for ischemia diagnosis and assist in clinical decision-making.

Diagnostic performance of deep learning and computational fluid dynamics-based instantaneous wave-free ratio derived from computed tomography angiography.

BACKGROUND AND OBJECTIVES: Both fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) are widely used to evaluate ischemia-causing coronary lesions. A new method of CT-iFR, namely AccuiFRct, for calculating iFR based on deep learning and computational fluid dynamics (CFD) using coronary computed tomography angiography (CCTA) has been proposed. In this study, the diagnostic performance of AccuiFRct was thoroughly assessed using iFR as the reference standard. METHODS: Data of a total of 36 consecutive patients with 36 vessels from a single-center who underwent CCTA, invasive FFR, and iFR were retrospectively analyzed. The CT-derived iFR values were computed using a novel deep learning and CFD-based model. RESULTS: Mean values of FFR and iFR were 0.80 ± 0.10 and 0.91 ± 0.06, respectively. AccuiFRct was well correlated with FFR and iFR (correlation coefficients, 0.67 and 0.68, respectively). The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of AccuiFRct ≤ 0.89 for predicting FFR ≤ 0.80 were 78%, 73%, 81%, 73%, and 81%, respectively. Those of AccuiFRct ≤ 0.89 for predicting iFR ≤ 0.89 were 81%, 73%, 86%, 79%, and 82%, respectively. AccuiFRct showed a similar discriminant function when FFR or iFR were used as reference standards. CONCLUSION: AccuiFRct could be a promising noninvasive tool for detection of ischemia-causing coronary stenosis, as well as facilitating in making reliable clinical decisions.

Diagnostic accuracy of coronary computed tomography angiography-derived fractional flow reserve.

BACKGROUND: Fractional flow reserve (FFR) is a widely used gold standard to evaluate ischemia-causing lesions. A new method of non-invasive approach, termed as AccuFFRct, for calculating FFR based on coronary computed tomography angiography (CCTA) and computational fluid dynamics (CFD) has been proposed. However, its diagnostic accuracy has not been validated. OBJECTIVES: This study sought to present a novel approach for non-invasive computation of FFR and evaluate its diagnostic performance in patients with coronary stenosis. METHODS: A total of 54 consecutive patients with 78 vessels from a single center who underwent CCTA and invasive FFR measurement were retrospectively analyzed. The CT-derived FFR values were computed using a novel CFD-based model (AccuFFRct, ArteryFlow Technology Co., Ltd., Hangzhou, China). Diagnostic performance of AccuFFRct and CCTA in detecting hemodynamically significant coronary artery disease (CAD) was evaluated using the invasive FFR as a reference standard. RESULTS: Diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for AccuFFRct in detecting FFR ≤ 0.8 on per-patient basis were 90.7, 89.5, 91.4, 85.0 and 94.1%, respectively, while those of CCTA were 38.9, 100.0, 5.71, 36.5 and 100.0%, respectively. The correlation between AccuFFRct and FFR was good (r = 0.76 and r = 0.65 on per-patient and per-vessel basis, respectively, both p < 0.0001). Area under the curve (AUC) values of AccuFFRct for identifying ischemia per-patient and per-vessel basis were 0.945 and 0.925, respectively. There was much higher accuracy, specificity and AUC for AccuFFRct compared with CCTA. CONCLUSIONS: AccuFFRct computed from CCTA images alone demonstrated high diagnostic performance for detecting lesion-specific ischemia, it showed superior diagnostic power than CCTA and eliminated the risk of invasive tests, which could be an accurate and time-efficient computational tool for diagnosing ischemia and assisting clinical decision-making.

Automatic segmentation of coronary lumen and external elastic membrane in intravascular ultrasound images using 8-layer U-Net.

BACKGROUND: Intravascular ultrasound (IVUS) is the golden standard in accessing the coronary lesions, stenosis, and atherosclerosis plaques. In this paper, a fully automatic approach by an 8-layer U-Net is developed to segment the coronary artery lumen and the area bounded by external elastic membrane (EEM), i.e., cross-sectional area (EEM-CSA). The database comprises single-vendor and single-frequency IVUS data. Particularly, the proposed data augmentation of MeshGrid combined with flip and rotation operations is implemented, improving the model performance without pre- or post-processing of the raw IVUS images. RESULTS: The mean intersection of union (MIoU) of 0.937 and 0.804 for the lumen and EEM-CSA, respectively, were achieved, which exceeded the manual labeling accuracy of the clinician. CONCLUSION: The accuracy shown by the proposed method is sufficient for subsequent reconstruction of 3D-IVUS images, which is essential for doctors' diagnosis in the tissue characterization of coronary artery walls and plaque compositions, qualitatively and quantitatively.

Are hemodynamics of irregular small carotid-ophthalmic aneurysms different from those of regular ones and large aneurysms based on numerical simulation?

PURPOSE: The purpose of this study is to investigate whether hemodynamics of unruptured, irregular small intracranial aneurysms (SIAs) are different from those of regular ones and large intracranial aneurysms (LIAs) in ophthalmic artery segment of internal carotid artery (ICA). METHODS: Between April 2015 and June 2018, 106 carotid-ophthalmic artery aneurysms were retrospectively analyzed using 3D angiographic images and computational fluid dynamics (CFD). Three categories were stratified: regular SIAs, irregular SIAs and LIAs. Statistical comparisons of the differences in clinical, morphological and hemodynamic parameters among regular SIA, irregular SIA and LIA groups were performed by one-way analysis of variance (ANOVA) or Kruskal-Wallis Test. RESULTS: The median maximal height of regular SIA, irregular SIA and LIA were 3.03 (interquartile range: 2.49-4.22) mm, 4.59 (interquartile range: 3.86-5.32) mm and 11.06 (interquartile range: 9.28-13.69) mm, all P < 0.05). Low shear-stress area percentage (LSA%) and oscillatory shear index (OSI) of irregular SIAs and LIAs were not significantly different (P = 0.72, P = 0.27 respectively), and were significantly higher than those of regular SIAs (all P < 0.01). Wall shear stress (WSS) and normalized wall shear stress (NWSS) of irregular SIAs were significantly higher than those of LIAs (P < 0.01, P < 0.01 respectively), but lower than those of regular SIAs (P < 0.01, P < 0.01 respectively). CONCLUSIONS: Special unruptured irregular SIAs share a similarity of hemodynamic characteristics with LIAs in high LSA% and high OSI, and are different from regular SIAs in hemodynamics.

Numerical simulation of patient-specific endovascular stenting and coiling for intracranial aneurysm surgical planning.

BACKGROUND: In this study, we develop reliable and practical virtual coiling and stenting methods for intracranial aneurysm surgical planning. Since the purpose of deploying coils and stents is to provide device geometries for subsequent accurate post-treatment computational fluid dynamics analysis, we do not need to accurately capture all the details such as the stress and force distribution for the devices and vessel walls. Our philosophy for developing these methods is to balance accuracy and practicality. METHODS: We consider the mechanical properties of the devices and recapitulate the clinical practice using a finite element method (FEM) approach. At the same time, we apply some simplifications for FEM modeling to make our methods efficient. For the virtual coiling, the coils are modeled as 3D Euler-Bernoulli beam elements, which is computationally efficient and provides good geometry representation. During the stent deployment process, the stent-catheter system is transformed according to the centerline of the parent vessel since the final configuration of the stent is not dependent of the deployment history. The aneurysm and vessel walls are assumed to be rigid and are fully constrained during the simulation. All stent-catheter system and coil-catheter system are prepared and packaged as a library which contains all types of stents, coils and catheters, which improves the efficiency of surgical planning process. RESULTS: The stent was delivered to the suitable position during the clinical treatment, achieving good expansion and apposition of the stent to the arterial wall. The coil was deployed into the aneurysm sac and deformed to different shapes because of the stored strain energy during coil package process and the direction of the microcatheter. CONCLUSIONS: The method which we develop here could become surgical planning for intracranial aneurysm treatment in the clinical workflow.

AneuGuide™ software-assisted vs. manual measurements in sizing for pipeline embolization device: An agreement study.

Sizing of flow diverters (FDs) is a challenging task in the treatment of intracranial aneurysms due to their foreshortening behavior. The purpose of this study is to evaluate the difference between the sizing results from the AneuGuide™ software and from conventional 2D measurement. Ninety-eight consecutive patients undergoing pipeline embolization device (PED) treatment between October 2018 and April 2023 in the First Medical Center of Chinese PLA General Hospital (Beijing, China) were retrospectively analyzed. For all cases, the optimal PED dimensions were both manually determined through 2D measurements on pre-treatment 3D-DSA and computed by AneuGuide™ software. The inter-rater reliability between the two sets of sizing results for each methodology was analyzed using intraclass correlation coefficient (ICC). The degree of agreement between manual sizing and software sizing were analyzed with the Bland-Altman plot and Pearson's test. Differences between two methodologies were analyzed with Wilcoxon signed rank test. Statistical significance was defined as p < 0.05. There was better inter-rater reliability between AneuGuide™ measurements both for diameter (ICC 0.92, 95%CI 0.88-0.95) and length (ICC 0.93, 95%CI 0.89-0.96). Bland-Altman plots showed a good agreement for diameter selection between two methodologies. However, the median length proposed by software group was significantly shorter (16 mm versus 20 mm, p < 0.001). No difference was found for median diameter (4.25 mm versus 4.25 mm). We demonstrated that the AneuGuide™ software provides highly reliable results of PED sizing compared with manual measurement, with a shorter stent length. AneuGuide™ may aid neurointerventionalists in selecting optimal dimensions for FD treatment.

Differences and Correlations of Morphological and Hemodynamic Parameters between Anterior Circulation Bifurcation and Side-wall Aneurysms.

OBJECTIVE: The objective of this research was to explore the difference and correlation of the morphological and hemodynamic features between sidewall and bifurcation aneurysms in anterior circulation arteries, utilizing computational fluid dynamics as a tool for analysis. METHODS: In line with the designated inclusion criteria, this study covered 160 aneurysms identified in 131 patients who received treatment at Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, China, from January 2021 to September 2022. Utilizing follow-up digital subtraction angiography (DSA) data, these cases were classified into two distinct groups: the sidewall aneurysm group and the bifurcation aneurysm group. Morphological and hemodynamic parameters in the immediate preoperative period were meticulously calculated and examined in both groups using a three-dimensional DSA reconstruction model. RESULTS: No significant differences were found in the morphological or hemodynamic parameters of bifurcation aneurysms at varied locations within the anterior circulation. However, pronounced differences were identified between sidewall and bifurcation aneurysms in terms of morphological parameters such as the diameter of the parent vessel (Dvessel), inflow angle (θF), and size ratio (SR), as well as the hemodynamic parameter of inflow concentration index (ICI) (P<0.001). Notably, only the SR exhibited a significant correlation with multiple hemodynamic parameters (P<0.001), while the ICI was closely related to several morphological parameters (R>0.5, P<0.001). CONCLUSIONS: The significant differences in certain morphological and hemodynamic parameters between sidewall and bifurcation aneurysms emphasize the importance to contemplate variances in threshold values for these parameters when evaluating the risk of rupture in anterior circulation aneurysms. Whether it is a bifurcation or sidewall aneurysm, these disparities should be considered. The morphological parameter SR has the potential to be a valuable clinical tool for promptly distinguishing the distinct rupture risks associated with sidewall and bifurcation aneurysms.

A multidimensional pre-operative planning method of unruptured vertebral artery dissecting aneurysms using three-dimensional AWE mapping and hemodynamic simulation.

OBJECTIVE: High-resolution magnetic resonance imaging (HR-MRI) can provide valuable insights into the evaluation of vascular pathological conditions, and 3D digital subtraction angiography (3D-DSA) offers clear visualization of the vascular morphology and hemodynamics. This study aimed to investigate the potential of a multimodal method to treat unruptured vertebral artery dissection aneurysms (u-VADAs) by fusing image data from HR-MRI and 3D-DSA. METHODS: This observational study enrolled 5 patients diagnosed with u-VADAs, who were scheduled for interventional treatment. The image data of HR-MRI and 3D-DSA were merged by geometry software, resulting in a multimodal model. Quantified values of aneurysm wall enhancement (AWE), wall shear stress (WSS), neck velocity, inflow volume, intra-stent flow velocity (ISvelocity), and intra-aneurysmal velocity (IAvelocity) were calculated from the multimodal method. RESULTS: We found the actual lengths of u-VADAs in the multimodal model were longer than the 3D-DSA model. We formulated surgical plannings based on the WSS, IA velocity, and neck velocity. The post-operative value of IAvelocity, neck velocity, and follow-up quantified values of AWE were decreased compared with the pre-operative condition. After that, u-VADAs were complete occlusion in four patients and near-complete occlusion in one patient during the 6th-month follow-up after surgery. CONCLUSION: The multidimensional method combining HR-MRI with 3D-DSA may provide more valuable information for treating VADAs, with the potential to develop effective surgical planning.

Agreement of ejection fraction measured by coronary computed tomography (CT) and cardiac ultrasound in evaluating patients with chronic heart failure: an observational comparative study.

Background: Cardiac ultrasound is one of the most important examinations in cardiovascular medicine, but the technical requirements for the operator are relatively high, which to some extent affects the scope of its use. This study was dedicated to investigating the agreement of ejection fraction between coronary computed tomography (CT) and cardiac ultrasound and diagnostic performance in evaluating the clinical diagnosis of patients with chronic heart failure. Methods: We conducted a single-center-based retrospective study including 343 consecutive patients enrolled between January 2019 to April 2020, all of whom presented with suspected symptoms of heart failure within one month. All enrolled cases performed cardiac ultrasound and coronary CT scans. The CT images were analyzed using accurate left ventricle (AccuLV) artificial intelligence (AI) software to calculate the ejection fraction-computed tomography (EF-CT) and it was compared with the ejection fraction (EF) obtained based on ultrasound. Cardiac insufficiency was determined if the EF measured by ultrasound was below 50%. Diagnostic performance analysis, correlation analysis and Bland-Altman plot were used to compare agreement between EF-CT and CT. Results: Of the 319 successfully performed patients, 220 (69%) were identified as cardiac insufficiency. Quantitative consistency analysis showed a good correlation between EF-CT and EF values in all cases (R square =0.704, r=0.837). Bland-Altman analysis showed mean bias of 6.6%, mean percentage error of 27.5% and 95% limit of agreement of -17% to 30% between EF and EF-CT. The results of the qualitative diagnostic study showed that the sensitivity and specificity of EF measured by coronary CT reached a high level of 91% [95% confidence interval (CI): 86-94%], and the positive diagnostic value was up to 96% (95% CI: 92-98%). Conclusions: The EF-CT and EF have excellent agreement, and AccuLV-based AI left ventricular function analysis software perhaps can be used as a clinical diagnostic reference.

Hemodynamic assessment for intracranial atherosclerosis from angiographic images: a clinical validation study.

BACKGROUND: Intracranial atherosclerotic stenosis (ICAS) is one of the leading causes of ischemic stroke. Conventional anatomical analysis by CT angiography, MRI, or digital subtraction angiography can provide valuable information on the anatomical changes of stenosis; however, they are not sufficient to accurately evaluate the hemodynamic severity of ICAS. The goal of this study was to assess the diagnostic performance of the pressure ratio across intracranial stenoses (termed as fractional flow (FF)) derived from cerebral angiography for the diagnosis of hemodynamically significant ICAS defined by pressure wire-derived FF. METHODS: This retrospective study represents a feasible and reliable method for calculating the FF from cerebral angiography (AccuFFicas). Patients (n=121) who had undergone wire-based measurement of FF and cerebral angiography were recruited. The accuracy of the computed pressure ratio was evaluated using wire-based FF as the reference standard. RESULTS: The mean value of wire-based FF was 0.78±0.19, while the computed AccuFFicas had an average value of 0.79±0.18. Good correlation (Pearson's correlation coefficient r=0.92, P<0.001) between AccuFFicas and FF was observed. Bland-Altman analysis showed that the mean difference between AccuFFicas and FF was -0.01±0.07, indicating good agreement. The area under the curve (AUC) of AccuFFicas in predicting FF≤0.70, FF≤0.75, and FF≤0.80 was 0.984, 0.986, and 0.962, respectively. CONCLUSION: Angiography-based FF computed from cerebral angiographic images could be an effective computational tool for evaluating the hemodynamic significance of ICAS.

Intravascular Ultrasound-Based Fractional Flow Reserve for Predicting Prognosis after Percutaneous Coronary Intervention.

AccuFFRivus is an alternative to fractional flow reserve (FFR) based on intravascular ultrasound (IVUS) images for functional assessment of coronary stenosis. However, its prognostic impact in patients undergoing percutaneous coronary intervention (PCI) is still unclear. This retrospective study aimed to investigate the capability of AccuFFRivus in predicting prognosis. AccuFFRivus was calculated based on postoperative angiographic and IVUS images. Vessel-oriented clinical events (VOCE) at 2 years were recorded and analyzed. A total of 131 participants with 131 vessels were included in the study. VOCE occurred in 15 patients during 2-year follow-up. AccuFFRivus after PCI (post-AccuFFRivus) was significantly higher in the non-VOCE group than in the VOCE group (0.95 ± 0.03 vs. 0.91 ± 0.02, p < 0.001). Multivariate Cox regression showed that AccuFFRivus ≤ 0.94 was a strong independent predictor of VOCE during 2-year follow-up (hazard ratio 23.76, 95% confidence interval: 3.04-185.81, p < 0.001). The left panel displays the Receiver operating characteristics (ROC) curves of postoperative parameters (post-AccuFFRivus and post-MLA) versus vessel-oriented clinical events (VOCE) occurrence within 2-year follow-up. The right panel demonstrates Kaplan-Meier curves of VOCE stratified by the optimal cut-off of post-AccuFFRivus.

Predicting flow diverter sizing using the AneuGuideTM software: a validation study.

BACKGROUND: Stent sizing remains a challenging task for flow diverter implantation because of stent foreshortening. In this study, we aimed to quantify the change in length after implantation and assess the error in length prediction using AneuGuideTM software. METHODS: In a retrospective cohort of 101 patients with 102 aneurysms undergoing treatment with a pipeline embolization device (PED; Covidien, Irvine, California, USA), we used AneuGuideTM software to obtain measured lengths (ML) and calculated lengths (CL) after stent implantation. Stent elongation was defined as the ratio of ML-LL to the labeled length (LL). Simulation error was defined as the ratio of the absolute value of CL-ML to ML. The correlation and consistency between ML and LL and between ML and CL were analyzed using Pearson's correlation test and the Bland-Altman plot. Statistical significance was set at p<0.05. RESULTS: The mean elongation of ML was 32.6% (range 26.3-109.2%). Moderate consistency was observed between LL and ML (ρ=0.74, p<0.001). With the AneuGuideTM software, the mean simulation error was 6.6% (range 0.32-21.2%). Pearson's correlation test and the Bland-Altman plot showed a high correlation and consistency between ML and CL (ρ=0.96, p<0.001). CONCLUSION: Labeled length provides only a low reference value for predicting the actual length of the flow diverter after implantation. The high consistency between ML and CL obtained from AneuGuideTM software shows its great potential for the optimization of the flow diverter sizing process.

Computational fluid dynamics (CFD) analysis in a ruptured vertebral artery dissecting aneurysm implanted by Pipeline when recurrent after LVIS-assisted coiling treatment: Case report and review of the literatures.

BACKGROUNDS: Hemodynamics plays an important role in the natural history of the process of rupture and recurrence of intracranial aneurysms. This study aimed to investigate the role of hemodynamics for recurrence in a vertebral artery dissecting aneurysm (VADA). METHODS: A patient with a ruptured VADA firstly treated by low-profile visualized intraluminal support (LVIS)-assisted coiling, and was implanted with a Pipeline Embolization Device (PED) after aneurysm recurrence. Finite element analysis and computational fluid dynamics simulations were conducted in 6 serial imaging procedures, and the calculated hemodynamics was correlated with aneurysm recurrence. RESULTS: Wall shear stress (WSS) was not effectively suppressed, resulting in aneurysm recurrence with initial entry tear to occur above the protuberance after 7 months of LVIS stent-assisted coiling. With the implantation of PED, WSS, inflow stream and velocity at the aneurysm neck significantly decreased. During the 3-month follow-up after PED deployment, there was significant shrinkage of the sac and the blood flow in the sac was reduced considerably. The 27-month follow-up after PED deployment indicated the aneurysm was stable. CONCLUSIONS: The present case study suggests that insufficient suppression of high WSS and high inflow velocity at the neck of the parent artery, especially near the posterior inferior cerebellar artery, might be associated with aneurysm recurrence.

How to perform intra-aneurysmal coil embolization after Pipeline deployment: a study from a hemodynamic viewpoint.

BACKGROUND: Pipeline embolization device (PED) deployment combined with coil therapy for large complex intracranial aneurysms is effective and considered superior to PED deployment alone. However, the optimal strategy for use of coils remains unclear. We used patient-specific aneurysm models and finite element analysis to determine the ideal packing density of coils after PED placement. METHODS: Finite element analysis was used to provide a higher-fidelity model for accurate post-treatment computational fluid dynamics analysis to simulate the real therapeutic process of PED and all coils. We then calculated and analyzed the reduction ratio of velocity to identify the hemodynamic change during PED deployment and each coil embolization. RESULTS: Sixteen consecutive patients underwent PED plus coil procedures to treat internal carotid artery intracranial aneurysms. After PED deployment, the intra-aneurysmal flow velocity significantly decreased (15.3 vs 10.0 cm/s; p<0.001). When the first coil was inserted, the flow velocity in the aneurysm further decreased and the reduction was significant (10.0 vs 5.3 cm/s; p<0.001). Analysis of covariance showed that the effect of the reduction ratio of velocity of the second coil was significantly lower than that of the first coil (p<0.001)-that is, when the packing density increased to 7.06%, the addition of coils produced no further hemodynamic effect. CONCLUSION: Adjunct coiling could improve the post-PED hemodynamic environment in treated intracranial aneurysms. However, dense packing is not necessary because the intra-aneurysmal hemodynamics tend to stabilize as the packing density reaches an average of 7.06% or after insertion of the second coil.