Optimal Medical Therapy Following Deep Venous Interventions: Proceedings from the Society of Interventional Radiology Foundation Research Consensus Panel.

The optimal medical management of patients following endovascular deep venous interventions remains ill-defined. As such, the Society of Interventional Radiology Foundation (SIRF) convened a multidisciplinary group of experts in a virtual Research Consensus Panel (RCP) to develop a prioritized research agenda regarding antithrombotic therapy following deep venous interventions. The panelists presented the gaps in knowledge followed by discussion and ranking of research priorities based on clinical relevance, overall impact, and technical feasibility. The following research topics were identified as high priority: 1) characterization of biological processes leading to in-stent stenosis/rethrombosis; 2) identification and validation of methods to assess venous flow dynamics and their effect on stent failure; 3) elucidation of the role of inflammation and anti-inflammatory therapies; and 4) clinical studies to compare antithrombotic strategies and improve venous outcome assessment. Collaborative, multicenter research is necessary to answer these questions and thereby enhance the care of patients with venous disease.

Antithrombotic Therapy After Venous Interventions: AJR Expert Panel Narrative Review.

Interventions for thrombotic and nonthrombotic venous disorders have increased with technical advances and more trained venous specialists. Antithrombotic therapy is essential to clinical and procedural success; however, postprocedural therapeutic regimens exhibit significant heterogeneity due to limited prospective randomized data and incomplete mechanistic understanding of the critical factors driving long-term patency. Postinterventional antithrombotic therapy for thrombotic venous disorders should adhere to existing venous thromboembolism management guidelines, which include 3-6 months of therapeutic anticoagulation at minimum and consideration of extended therapy in patients with higher risk of thrombosis because of procedural or patient factors. The added benefit of antiplatelet agents in the acute and intermediate period is unknown, having shown improved long-term stent patency in some retrospective studies. Dual- and/or triple-agent therapy should be limited based on individual risks of thrombosis and bleeding. The treatment of nonthrombotic disorders is more heterogeneous, though patients with limited flow, extensive stent material, or underlying prothrombotic states such as malignancy or chronic inflammation may benefit from single-agent or multiagent antithrombotic therapy. However, the agent, dose, and duration of therapy remain indeterminate. Future prospective studies are warranted to improve patient risk stratification and standardize postprocedural anti-thrombotic therapy in patients receiving venous interventions.

Mechanical aspiration thrombectomy for the treatment of pulmonary embolism: A systematic review and meta-analysis.

INTRODUCTION: There are no randomized trials studying the outcomes of mechanical aspiration thrombectomy (MAT) for management of pulmonary embolism (PE). METHODS: We performed a systematic review and meta-analysis of existing literature to evaluate the safety and efficacy of MAT in the setting of PE. Inclusion criteria were as follows: studies reporting more than five patients, study involved MAT, and reported clinical outcomes and pulmonary artery pressures. Studies were excluded if they failed to separate thrombectomy data from catheter-directed thrombolysis data. Databases searched include PubMed, EMBASE, Web of Science until April, 2021. RESULTS: Fourteen case series were identified, consisting of 516 total patients (mean age 58.4 ± 13.6 years). Three studies had only high-risk PE, two studies had only intermediate-risk PE, and the remaining nine studies had a combination of both high-risk and intermediate-risk PE. Six studies used the Inari FlowTriever device, five studies used the Indigo Aspiration system, and the remaining three studies used the Rotarex or Aspirex suction thrombectomy system. Four total studies employed thrombolytics in a patient-specific manner, with seven receiving local lysis and 17 receiving systemic lysis, and 40 receiving both. A random-effects meta-analyses of proportions of in-hospital mortality, major bleeding, technical success, and clinical success were calculated, which yielded estimate pooled percentages [95% CI] of 3.6% [0.7%, 7.9%], 0.5% [0.0%, 1.8%], 97.1% [94.8%, 98.4%], and 90.7% [85.5%, 94.3%]. CONCLUSION: There is significant heterogeneity in clinical, physiologic, and angiographic data in the currently available data on MAT. RCTs with consistent parameters and outcomes measures are still needed.

Cardiovascular disease detection using machine learning and carotid/femoral arterial imaging frameworks in rheumatoid arthritis patients.

The study proposes a novel machine learning (ML) paradigm for cardiovascular disease (CVD) detection in individuals at medium to high cardiovascular risk using data from a Greek cohort of 542 individuals with rheumatoid arthritis, or diabetes mellitus, and/or arterial hypertension, using conventional or office-based, laboratory-based blood biomarkers and carotid/femoral ultrasound image-based phenotypes. Two kinds of data (CVD risk factors and presence of CVD-defined as stroke, or myocardial infarction, or coronary artery syndrome, or peripheral artery disease, or coronary heart disease) as ground truth, were collected at two-time points: (i) at visit 1 and (ii) at visit 2 after 3 years. The CVD risk factors were divided into three clusters (conventional or office-based, laboratory-based blood biomarkers, carotid ultrasound image-based phenotypes) to study their effect on the ML classifiers. Three kinds of ML classifiers (Random Forest, Support Vector Machine, and Linear Discriminant Analysis) were applied in a two-fold cross-validation framework using the data augmented by synthetic minority over-sampling technique (SMOTE) strategy. The performance of the ML classifiers was recorded. In this cohort with overall 46 CVD risk factors (covariates) implemented in an online cardiovascular framework, that requires calculation time less than 1 s per patient, a mean accuracy and area-under-the-curve (AUC) of 98.40% and 0.98 (p < 0.0001) for CVD presence detection at visit 1, and 98.39% and 0.98 (p < 0.0001) at visit 2, respectively. The performance of the cardiovascular framework was significantly better than the classical CVD risk score. The ML paradigm proved to be powerful for CVD prediction in individuals at medium to high cardiovascular risk.

Adoption of a dedicated multidisciplinary team is associated with improved survival in acute pulmonary embolism.

BACKGROUND: Acute pulmonary embolism remains a significant cause of mortality and morbidity worldwide. Benefit of recently developed multidisciplinary PE response teams (PERT) with higher utilization of advanced therapies has not been established. METHODS: To evaluate patient-centered outcomes and cost-effectiveness of a multidisciplinary PERT we performed a retrospective analysis of 554 patients with acute PE at the university of Virginia between July 2014 and June 2015 (pre-PERT era) and between April 2017 through October 2018 (PERT era). Six-month survival, hospital length-of-stay (LOS), type of PE therapy, and in-hospital bleeding were assessed upon collected data. RESULTS: 317 consecutive patients were treated for acute PE during an 18-month period following institution of a multidisciplinary PE program; for 120 patients PERT was activated (PA), the remaining 197 patients with acute PE were considered as a separate, contemporary group (NPA). The historical, comparator cohort (PP) was composed of 237 patients. These 3 groups were similar in terms of baseline demographics, comorbidities and risk, as assessed by the Pulmonary Embolism Severity Index (PESI). Patients in the historical cohort demonstrated worsened survival when compared with patients treated during the PERT era. During the PERT era no statistically significant difference in survival was observed in the PA group when compared to the NPA group despite significantly higher severity of illness among PA patients. Hospital LOS was not different in the PA group when compared to either the NPA or PP group. Hospital costs did not differ among the 3 cohorts. 30-day re-admission rates were significantly lower during the PERT era. Rates of advanced therapies were significantly higher during the PERT era (9.1% vs. 2%) and were concentrated in the PA group (21.7% vs. 1.5%) without any significant rise in in-hospital bleeding complications. CONCLUSIONS: At our institution, all-cause mortality in patients with acute PE has significantly and durably decreased with the adoption of a PERT program without incurring additional hospital costs or protracting hospital LOS. Our data suggest that the adoption of a multidisciplinary approach at some institutions may provide benefit to select patients with acute PE.

Interpretation of peripheral arterial and venous Doppler waveforms: A consensus statement from the Society for Vascular Medicine and Society for Vascular Ultrasound.

This expert consensus statement on the interpretation of peripheral arterial and venous spectral Doppler waveforms was jointly commissioned by the Society for Vascular Medicine (SVM) and the Society for Vascular Ultrasound (SVU). The consensus statement proposes a standardized nomenclature for arterial and venous spectral Doppler waveforms using a framework of key major descriptors and additional modifier terms. These key major descriptors and additional modifier terms are presented alongside representative Doppler waveforms, and nomenclature tables provide context by listing previous alternate terms to be replaced by the new major descriptors and modifiers. Finally, the document reviews Doppler waveform alterations with physiologic changes and disease states, provides optimization techniques for waveform acquisition and display, and provides practical guidance for incorporating the proposed nomenclature into the final interpretation report.

Cardiovascular risk assessment in patients with rheumatoid arthritis using carotid ultrasound B-mode imaging.

Rheumatoid arthritis (RA) is a systemic chronic inflammatory disease that affects synovial joints and has various extra-articular manifestations, including atherosclerotic cardiovascular disease (CVD). Patients with RA experience a higher risk of CVD, leading to increased morbidity and mortality. Inflammation is a common phenomenon in RA and CVD. The pathophysiological association between these diseases is still not clear, and, thus, the risk assessment and detection of CVD in such patients is of clinical importance. Recently, artificial intelligence (AI) has gained prominence in advancing healthcare and, therefore, may further help to investigate the RA-CVD association. There are three aims of this review: (1) to summarize the three pathophysiological pathways that link RA to CVD; (2) to identify several traditional and carotid ultrasound image-based CVD risk calculators useful for RA patients, and (3) to understand the role of artificial intelligence in CVD risk assessment in RA patients. Our search strategy involves extensively searches in PubMed and Web of Science databases using search terms associated with CVD risk assessment in RA patients. A total of 120 peer-reviewed articles were screened for this review. We conclude that (a) two of the three pathways directly affect the atherosclerotic process, leading to heart injury, (b) carotid ultrasound image-based calculators have shown superior performance compared with conventional calculators, and (c) AI-based technologies in CVD risk assessment in RA patients are aggressively being adapted for routine practice of RA patients.

Low-Cost Office-Based Cardiovascular Risk Stratification Using Machine Learning and Focused Carotid Ultrasound in an Asian-Indian Cohort.

This study developed an office-based cardiovascular risk calculator using a machine learning (ML) algorithm that utilized a focused carotid ultrasound. The design of this study was divided into three steps. The first step involved collecting 18 office-based biomarkers consisting of six clinical risk factors (age, sex, body mass index, systolic blood pressure, diastolic blood pressure, and smoking) and 12 carotid ultrasound image-based phenotypes. The second step consisted of the design of an ML-based cardiovascular risk calculator-called "AtheroEdge Composite Risk Score 2.0" (AECRS2.0ML) for risk stratification, considering chronic kidney disease (CKD) as the surrogate endpoint of cardiovascular disease. The last step consisted of comparing AECRS2.0ML against the currently utilized office-based CVD calculators, namely the Framingham risk score (FRS) and the World Health Organization (WHO) risk scores. A cohort of 379 Asian-Indian patients with type-2 diabetes mellitus, hypertension, and chronic kidney disease (stage 1 to 5) were recruited for this cross-sectional study. From this retrospective cohort, 758 ultrasound scan images were acquired from the far walls of the left and right common carotid arteries [mean age = 55 ± 10.8 years, 67.28% males, 91.82% diabetic, 86.54% hypertensive, and 83.11% with CKD]. The mean office-based cardiovascular risk estimates using FRS and WHO calculators were 26% and 19%, respectively. AECRS2.0ML demonstrated a better risk stratification ability having a higher area-under-the-curve against FRS and WHO by ~30% (0.871 vs. 0.669) and ~ 20% (0.871 vs. 0.727), respectively. The office-based machine-learning cardiovascular risk-stratification tool (AECRS2.0ML) shows superior performance compared to currently available conventional cardiovascular risk calculators.

Portal vein thrombosis: When to treat and how?

Portal vein thrombosis is an unusual thrombotic condition not frequently seen in the general population; however, it has a higher prevalence in special circumstances such as in liver cirrhosis and hepatic or pancreatic malignancy. It also can be associated with significant morbidity and mortality. In this review, we discuss the current data available to guide therapy in the setting of different associated co-morbidities, hypercoagulable states, and associated thrombosis of the remaining splanchnic circulation. We discuss indications for anticoagulation, including the choice of anticoagulants, as well as the role of conservative 'wait and watch' and invasive therapies, such as thrombolysis, thrombectomy, and transjugular intrahepatic portosystemic shunt.

Endothelial interleukin-21 receptor up-regulation in peripheral artery disease.

In most patients with symptomatic peripheral artery disease (PAD), severe stenosis in or occlusion of the major blood vessels that supply the legs make the amount of distal blood flow dependent on the capacity to induce angiogenesis and collateral vessel formation. Currently, there are no medications that improve perfusion to the ischemic limb, and thus directly treat the primary problem of PAD. A recent report from our group in a pre-clinical mouse PAD model showed that interleukin-21 receptor (IL-21R) is up-regulated in the endothelial cells from ischemic hindlimb muscle. We further showed that loss of IL-21R resulted in impaired perfusion recovery in this model. In our study, we sought to determine whether IL-21R is present in the endothelium from ischemic muscle of patients with PAD. Using human gastrocnemius muscle biopsies, we found increased levels of IL-21R in the skeletal muscle endothelial cells of patients with PAD compared to control individuals. Interestingly, PAD patients had approximately 1.7-fold higher levels of circulating IL-21. These data provide direct evidence that the IL-21R pathway is indeed up-regulated in patients with PAD. This pathway may serve as a therapeutic target for modulation.

Carotid inter-adventitial diameter is more strongly related to plaque score than lumen diameter: An automated tool for stroke analysis.

PURPOSE: To compare the strength of correlation between automatically measured carotid lumen diameter (LD) and interadventitial diameter (IAD) with plaque score (PS). METHODS: Retrospective study on a database of 404 common carotid artery B-mode sonographic images from 202 diabetic patients. LD and IAD were computed automatically using an advanced computerized edge detection method and compared with two distinct manual measurements. PS was computed by adding the maximal thickness in millimeters of plaques in segments taken from the internal carotid artery, bulb, and common carotid artery on both sides. RESULTS: The coefficient of correlation was 0.19 (p < 0.007) between LD and PS, and 0.25 (p < 0.0006) between IAD and PS. After excluding 10 outliers, coefficient of correlation was 0.25 (p < 0.0001) between LD and PS, and 0.38 (p < 0.0001) between IAD and PS. The precision of merit of automated versus the two manual measurements was 96.6% and 97.2% for LD, and 97.7% and 98.1%, for IAD, respectively. CONCLUSIONS: Our automated measurement system gave satisfying results in comparison with manual measurements. Carotid IAD was more strongly correlated to PS than carotid LD in this population sample of Japanese diabetic patients.

Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches.

The degree of stenosis in the carotid artery can be predicted using automated carotid lumen diameter (LD) measured from B-mode ultrasound images. Systolic velocity-based methods for measurement of LD are subjective. With the advancement of high resolution imaging, image-based methods have started to emerge. However, they require robust image analysis for accurate LD measurement. This paper presents two different algorithms for automated segmentation of the lumen borders in carotid ultrasound images. Both algorithms are modeled as a two stage process. Stage one consists of a global-based model using scale-space framework for the extraction of the region of interest. This stage is common to both algorithms. Stage two is modeled using a local-based strategy that extracts the lumen interfaces. At this stage, the algorithm-1 is modeled as a region-based strategy using a classification framework, whereas the algorithm-2 is modeled as a boundary-based approach that uses the level set framework. Two sets of databases (DB), Japan DB (JDB) (202 patients, 404 images) and Hong Kong DB (HKDB) (50 patients, 300 images) were used in this study. Two trained neuroradiologists performed manual LD tracings. The mean automated LD measured was 6.35 ± 0.95 mm for JDB and 6.20 ± 1.35 mm for HKDB. The precision-of-merit was: 97.4 % and 98.0 % w.r.t to two manual tracings for JDB and 99.7 % and 97.9 % w.r.t to two manual tracings for HKDB. Statistical tests such as ANOVA, Chi-Squared, T-test, and Mann-Whitney test were conducted to show the stability and reliability of the automated techniques.

A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework.

Cardiovascular diseases (including stroke and heart attack) are identified as the leading cause of death in today's world. However, very little is understood about the arterial mechanics of plaque buildup, arterial fibrous cap rupture, and the role of abnormalities of the vasa vasorum. Recently, ultrasonic echogenicity characteristics and morphological characterization of carotid plaque types have been shown to have clinical utility in classification of stroke risks. Furthermore, this characterization supports aggressive and intensive medical therapy as well as procedures, including endarterectomy and stenting. This is the first state-of-the-art review to provide a comprehensive understanding of the field of ultrasonic vascular morphology tissue characterization. This paper presents fundamental and advanced ultrasonic tissue characterization and feature extraction methods for analyzing plaque. Additionally, the paper shows how the risk stratification is achieved using machine learning paradigms. More advanced methods need to be developed which can segment the carotid artery walls into multiple regions such as the bulb region and areas both proximal and distal to the bulb. Furthermore, multimodality imaging is needed for validation of such advanced methods for stroke and cardiovascular risk stratification.

Outcomes of Hypertensive Patients with Renal Fibromuscular Dysplasia Compared with Patients with Concomitant Atherosclerotic Renal Artery Stenosis following Endovascular Therapy.

PURPOSE: To examine if the outcomes after endovascular treatment in hypertensive patients with renal artery fibromuscular dysplasia (FMD) and incidental atherosclerotic renal artery stenosis (ARAS) differ from the outcomes in patients with FMD alone. MATERIALS AND METHODS: All cases of patients with renal artery FMD undergoing percutaneous transluminal angioplasty during the period 2002-2012 were reviewed. The patients with complete data before and after the procedure were identified (N = 84). Based on the procedural reports, these patients were separated into two cohorts: patients with isolated FMD (n = 59) and patients with concomitant atherosclerotic renal artery stenosis and FMD (ARAS-FMD) (n = 25). The medical record of each patient was reviewed for baseline blood pressure, antihypertensive medication use, and renal function data and the same data after the procedure. Procedural details including the angiographic findings, the number of stents placed, the average number of revascularization procedures, and the number of patients requiring more than one revascularization procedure were noted. RESULTS: The study population included 68 patients (FMD, n = 46; ARAS-FMD, n = 22). Patients in the FMD and ARAS-FMD cohorts experienced comparable significant decreases in systolic and mean arterial pressures after endovascular intervention. There was no change in the number of antihypertensive medications after the procedure within or between groups. Patients in the ARAS-FMD cohort had lower baseline estimated glomerular filtration rates (P = .007); however, renal function stabilized in both groups after endovascular therapy. CONCLUSIONS: Patients with ARAS-FMD respond to endovascular therapy with outcomes similar to patients with isolated renal artery FMD.

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.

Vasculitis: When to Consider this Diagnosis?

Vasculitis is a diverse group of disorders involving inflammation of the blood vessels. Approaching the diagnosis of vasculitis can be challenging, given the differing clinical presentation and organ manifestations. Often vasculitis is a diagnosis that is considered too late, given the heterogeneous presentation and various mimics. This article aims to provide physicians with a diagnostic approach to vasculitis.

Cardiovascular disease/stroke risk stratification in deep learning framework: a review.

The global mortality rate is known to be the highest due to cardiovascular disease (CVD). Thus, preventive, and early CVD risk identification in a non-invasive manner is vital as healthcare cost is increasing day by day. Conventional methods for risk prediction of CVD lack robustness due to the non-linear relationship between risk factors and cardiovascular events in multi-ethnic cohorts. Few recently proposed machine learning-based risk stratification reviews without deep learning (DL) integration. The proposed study focuses on CVD risk stratification by the use of techniques mainly solo deep learning (SDL) and hybrid deep learning (HDL). Using a PRISMA model, 286 DL-based CVD studies were selected and analyzed. The databases included were Science Direct, IEEE Xplore, PubMed, and Google Scholar. This review is focused on different SDL and HDL architectures, their characteristics, applications, scientific and clinical validation, along with plaque tissue characterization for CVD/stroke risk stratification. Since signal processing methods are also crucial, the study further briefly presented Electrocardiogram (ECG)-based solutions. Finally, the study presented the risk due to bias in AI systems. The risk of bias tools used were (I) ranking method (RBS), (II) region-based map (RBM), (III) radial bias area (RBA), (IV) prediction model risk of bias assessment tool (PROBAST), and (V) risk of bias in non-randomized studies-of interventions (ROBINS-I). The surrogate carotid ultrasound image was mostly used in the UNet-based DL framework for arterial wall segmentation. Ground truth (GT) selection is vital for reducing the risk of bias (RoB) for CVD risk stratification. It was observed that the convolutional neural network (CNN) algorithms were widely used since the feature extraction process was automated. The ensemble-based DL techniques for risk stratification in CVD are likely to supersede the SDL and HDL paradigms. Due to the reliability, high accuracy, and faster execution on dedicated hardware, these DL methods for CVD risk assessment are powerful and promising. The risk of bias in DL methods can be best reduced by considering multicentre data collection and clinical evaluation.

ACR Appropriateness Criteria® Sudden Onset of Cold, Painful Leg: 2023 Update.

Acute onset of a cold, painful leg, also known as acute limb ischemia, describes the sudden loss of perfusion to the lower extremity and carries significant risk of morbidity and mortality. Acute limb ischemia requires rapid identification and the management of suspected vascular compromise and is inherently driven by clinical considerations. The objectives of initial imaging include confirmation of diagnosis, identifying the location and extent of vascular occlusion, and preprocedural/presurgical planning. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.