Improving Prognostication in Pulmonary Hypertension Using AI-quantified Fibrosis and Radiologic Severity Scoring at Baseline CT.

Background There is clinical need to better quantify lung disease severity in pulmonary hypertension (PH), particularly in idiopathic pulmonary arterial hypertension (IPAH) and PH associated with lung disease (PH-LD). Purpose To quantify fibrosis on CT pulmonary angiograms using an artificial intelligence (AI) model and to assess whether this approach can be used in combination with radiologic scoring to predict survival. Materials and Methods This retrospective multicenter study included adult patients with IPAH or PH-LD who underwent incidental CT imaging between February 2007 and January 2019. Patients were divided into training and test cohorts based on the institution of imaging. The test cohort included imaging examinations performed in 37 external hospitals. Fibrosis was quantified using an established AI model and radiologically scored by radiologists. Multivariable Cox regression adjusted for age, sex, World Health Organization functional class, pulmonary vascular resistance, and diffusing capacity of the lungs for carbon monoxide was performed. The performance of predictive models with or without AI-quantified fibrosis was assessed using the concordance index (C index). Results The training and test cohorts included 275 (median age, 68 years [IQR, 60-75 years]; 128 women) and 246 (median age, 65 years [IQR, 51-72 years]; 142 women) patients, respectively. Multivariable analysis showed that AI-quantified percentage of fibrosis was associated with an increased risk of patient mortality in the training cohort (hazard ratio, 1.01 [95% CI: 1.00, 1.02]; P = .04). This finding was validated in the external test cohort (C index, 0.76). The model combining AI-quantified fibrosis and radiologic scoring showed improved performance for predicting patient mortality compared with a model including radiologic scoring alone (C index, 0.67 vs 0.61; P < .001). Conclusion Percentage of lung fibrosis quantified on CT pulmonary angiograms by an AI model was associated with increased risk of mortality and showed improved performance for predicting patient survival when used in combination with radiologic severity scoring compared with radiologic scoring alone. © RSNA, 2024 Supplemental material is available for this article.

Systematic pulmonary embolism follow-up increases diagnostic rates of chronic thromboembolic pulmonary hypertension and identifies less severe disease: results from the ASPIRE Registry.

BACKGROUND: Diagnostic rates and risk factors for the subsequent development of chronic thromboembolic pulmonary hypertension (CTEPH) following pulmonary embolism (PE) are not well defined. METHODS: Over a 10-year period (2010-2020), consecutive patients attending a PE follow-up clinic in Sheffield, UK (population 554 600) and all patients diagnosed with CTEPH at a pulmonary hypertension (PH) referral centre in Sheffield (referral population estimated 15-20 million) were included. RESULTS: Of 1956 patients attending the Sheffield PE clinic 3 months following a diagnosis of acute PE, 41 were diagnosed with CTEPH with a cumulative incidence of 2.10%, with 1.89% diagnosed within 2 years. Of 809 patients presenting with pulmonary hypertension (PH) and diagnosed with CTEPH, 32 were Sheffield residents and 777 were non-Sheffield residents. Patients diagnosed with CTEPH at the PE follow-up clinic had shorter symptom duration (p<0.01), better exercise capacity (p<0.05) and less severe pulmonary haemodynamics (p<0.01) compared with patients referred with suspected PH. Patients with no major transient risk factors present at the time of acute PE had a significantly higher risk of CTEPH compared with patients with major transient risk factors (OR 3.6, 95% CI 1.11-11.91; p=0.03). The presence of three computed tomography (CT) features of PH in combination with two or more out of four features of chronic thromboembolic pulmonary disease at the index PE was found in 19% of patients who developed CTEPH and in 0% of patients who did not. Diagnostic rates and pulmonary endarterectomy (PEA) rates were higher at 13.2 and 3.6 per million per year, respectively, for Sheffield residents compared with 3.9-5.2 and 1.7-2.3 per million per year, respectively, for non-Sheffield residents. CONCLUSIONS: In the real-world setting a dedicated PE follow-up pathway identifies patients with less severe CTEPH and increases population-based CTEPH diagnostic and PEA rates. At the time of acute PE diagnosis the absence of major transient risk factors, CT features of PH and chronic thromboembolism are risk factors for a subsequent diagnosis of CTEPH.

External validation, radiological evaluation, and development of deep learning automatic lung segmentation in contrast-enhanced chest CT.

OBJECTIVES: There is a need for CT pulmonary angiography (CTPA) lung segmentation models. Clinical translation requires radiological evaluation of model outputs, understanding of limitations, and identification of failure points. This multicentre study aims to develop an accurate CTPA lung segmentation model, with evaluation of outputs in two diverse patient cohorts with pulmonary hypertension (PH) and interstitial lung disease (ILD). METHODS: This retrospective study develops an nnU-Net-based segmentation model using data from two specialist centres (UK and USA). Model was trained (n = 37), tested (n = 12), and clinically evaluated (n = 176) on a diverse 'real-world' cohort of 225 PH patients with volumetric CTPAs. Dice score coefficient (DSC) and normalised surface distance (NSD) were used for testing. Clinical evaluation of outputs was performed by two radiologists who assessed clinical significance of errors. External validation was performed on heterogenous contrast and non-contrast scans from 28 ILD patients. RESULTS: A total of 225 PH and 28 ILD patients with diverse demographic and clinical characteristics were evaluated. Mean accuracy, DSC, and NSD scores were 0.998 (95% CI 0.9976, 0.9989), 0.990 (0.9840, 0.9962), and 0.983 (0.9686, 0.9972) respectively. There were no segmentation failures. On radiological review, 82% and 71% of internal and external cases respectively had no errors. Eighteen percent and 25% respectively had clinically insignificant errors. Peripheral atelectasis and consolidation were common causes for suboptimal segmentation. One external case (0.5%) with patulous oesophagus had a clinically significant error. CONCLUSION: State-of-the-art CTPA lung segmentation model provides accurate outputs with minimal clinical errors on evaluation across two diverse cohorts with PH and ILD. CLINICAL RELEVANCE: Clinical translation of artificial intelligence models requires radiological review and understanding of model limitations. This study develops an externally validated state-of-the-art model with robust radiological review. Intended clinical use is in techniques such as lung volume or parenchymal disease quantification. KEY POINTS: • Accurate, externally validated CT pulmonary angiography (CTPA) lung segmentation model tested in two large heterogeneous clinical cohorts (pulmonary hypertension and interstitial lung disease). • No segmentation failures and robust review of model outputs by radiologists found 1 (0.5%) clinically significant segmentation error. • Intended clinical use of this model is a necessary step in techniques such as lung volume, parenchymal disease quantification, or pulmonary vessel analysis.

Non-vitamin-K-antagonist oral anticoagulants (NOACs) after acute myocardial infarction: a network meta-analysis.

BACKGROUND: Balancing the risk of bleeding and thrombosis after acute myocardial infarction (AMI) is challenging, and the optimal antithrombotic therapy remains uncertain. The potential of non-vitamin K antagonist oral anticoagulants (NOACs) to prevent ischaemic cardiovascular events is promising, but the evidence remains limited. OBJECTIVES: To evaluate the efficacy and safety of non-vitamin-K-antagonist oral anticoagulants (NOACs) in addition to background antiplatelet therapy, compared with placebo, antiplatelet therapy, or both, after acute myocardial infarction (AMI) in people without an indication for anticoagulation (i.e. atrial fibrillation or venous thromboembolism). SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, the Conference Proceedings Citation Index - Science, and two clinical trial registers in September 2022 with no language restrictions. We checked the reference lists of included studies for any additional trials. SELECTION CRITERIA: We searched for randomised controlled trials (RCTs) that evaluated NOACs plus antiplatelet therapy versus placebo, antiplatelet therapy, or both, in people without an indication for anticoagulation after an AMI. DATA COLLECTION AND ANALYSIS: Two review authors independently checked the results of searches to identify relevant studies, assessed each included study, and extracted study data. We conducted random-effects pairwise analyses using Review Manager Web, and network meta-analysis using the R package 'netmeta'. We ranked competing treatments by P scores, which are derived from the P values of all pairwise comparisons and allow ranking of treatments on a continuous 0-to-1 scale. MAIN RESULTS: We identified seven eligible RCTs, including an ongoing trial that we could not include in the analysis. Of the six RCTs involving 33,039 participants, three RCTs compared rivaroxaban with placebo, two RCTs compared apixaban with placebo, and one RCT compared dabigatran with placebo. All participants in the six RCTs received concomitant antiplatelet therapy. The available evidence suggests that rivaroxaban compared with placebo reduces the rate of all-cause mortality (risk ratio (RR) 0.82, 95% confidence interval (CI) 0.69 to 0.98; number needed to treat for an additional beneficial outcome (NNTB) 250; 3 studies, 21,870 participants; high certainty) and probably reduces cardiovascular mortality (RR 0.83, 95% CI 0.69 to 1.01; NNTB 250; 3 studies, 21,870 participants; moderate certainty). There is probably little or no difference between apixaban and placebo in all-cause mortality (RR 1.09, 95% CI 0.88 to 1.35; number needed to treat for an additional harmful outcome (NNTH) 334; 2 studies, 8638 participants; moderate certainty) and cardiovascular mortality (RR 0.99, 95% CI 0.77 to 1.27; number needed to treat not applicable; 2 studies, 8638 participants; moderate certainty). Dabigatran may reduce the rate of all-cause mortality compared with placebo (RR 0.57, 95% CI 0.31 to 1.06; NNTB 63; 1 study, 1861 participants; low certainty). Dabigatran compared with placebo may have little or no effect on cardiovascular mortality, although the point estimate suggests benefit (RR 0.72, 95% CI 0.34 to 1.52; NNTB 143; 1 study, 1861 participants; low certainty). Two of the investigated NOACs were associated with an increased risk of major bleeding compared to placebo: apixaban (RR 2.41, 95% CI 1.44 to 4.06; NNTH 143; 2 studies, 8544 participants; high certainty) and rivaroxaban (RR 3.31, 95% CI 1.12 to 9.77; NNTH 125; 3 studies, 21,870 participants; high certainty). There may be little or no difference between dabigatran and placebo in the risk of major bleeding (RR 1.74, 95% CI 0.22 to 14.12; NNTH 500; 1 study, 1861 participants; low certainty). The results of the network meta-analysis were inconclusive between the different NOACs at all individual doses for all primary outcomes. However, low-certainty evidence suggests that apixaban (combined dose) may be less effective than rivaroxaban and dabigatran for preventing all-cause mortality after AMI in people without an indication for anticoagulation. AUTHORS' CONCLUSIONS: Compared with placebo, rivaroxaban reduces all-cause mortality and probably reduces cardiovascular mortality after AMI in people without an indication for anticoagulation. Dabigatran may reduce the rate of all-cause mortality and may have little or no effect on cardiovascular mortality. There is probably no meaningful difference in the rate of all-cause mortality and cardiovascular mortality between apixaban and placebo. Moreover, we found no meaningful benefit in efficacy outcomes for specific therapy doses of any investigated NOACs following AMI in people without an indication for anticoagulation. Evidence from the included studies suggests that rivaroxaban and apixaban increase the risk of major bleeding compared with placebo. There may be little or no difference between dabigatran and placebo in the risk of major bleeding. Network meta-analysis did not show any superiority of one NOAC over another for our prespecified primary outcomes. Although the evidence suggests that NOACs reduce mortality, the effect size or impact is small; moreover, NOACs may increase major bleeding. Head-to-head trials, comparing NOACs against each other, are required to provide more solid evidence.

Establishing minimally important differences for cardiac MRI end-points in pulmonary arterial hypertension.

BACKGROUND: Cardiac magnetic resonance (CMR) is the gold standard technique to assess biventricular volumes and function, and is increasingly being considered as an end-point in clinical studies. Currently, with the exception of right ventricular (RV) stroke volume and RV end-diastolic volume, there is only limited data on minimally important differences (MIDs) reported for CMR metrics. Our study aimed to identify MIDs for CMR metrics based on US Food and Drug Administration recommendations for a clinical outcome measure that should reflect how a patient "feels, functions or survives". METHODS: Consecutive treatment-naïve patients with pulmonary arterial hypertension (PAH) between 2010 and 2022 who had two CMR scans (at baseline prior to treatment and 12 months following treatment) were identified from the ASPIRE registry. All patients were followed up for 1 additional year after the second scan. For both scans, cardiac measurements were obtained from a validated fully automated segmentation tool. The MID in CMR metrics was determined using two distribution-based (0.5sd and minimal detectable change) and two anchor-based (change difference and generalised linear model regression) methods benchmarked to how a patient "feels" (emPHasis-10 quality of life questionnaire), "functions" (incremental shuttle walk test) or "survives" for 1-year mortality to changes in CMR measurements. RESULTS: 254 patients with PAH were included (mean±sd age 53±16 years, 79% female and 66% categorised as intermediate risk based on the 2022 European Society of Cardiology/European Respiratory Society risk score). We identified a 5% absolute increase in RV ejection fraction and a 17 mL decrease in RV end-diastolic or end-systolic volumes as the MIDs for improvement. Conversely, a 5% decrease in RV ejection fraction and a 10 mL increase in RV volumes were associated with worsening. CONCLUSIONS: This study establishes clinically relevant CMR MIDs for how a patient "feels, functions or survives" in response to PAH treatment. These findings provide further support for the use of CMR as a clinically relevant clinical outcome measure and will aid trial size calculations for studies using CMR.

Plain language summaryPulmonary arterial hypertension (PAH) is a disease of the vessels of the lung that causes their narrowing and stiffening. As a result, the heart pumping blood into these diseased lung vessels has to work harder and eventually gets worn out. PAH can affect patients' ability to function in daily activities and impact their quality of life. It also reduces their life expectancy dramatically. Patients are, therefore, often monitored and undergo several investigations to adapt treatment according to their situation. These investigations include a survey of how a patient feels (the emPHasis-10 questionnaire), functions (walking test) and how well the heart is coping with the disease (MRI of the heart). Until now, it is unclear how changes on MRI of the heart reflect changes in how a patient feels and functions. Our study identified patients that had the emPHasis-10 questionnaire, walking test and MRI of the heart at both the time of PAH diagnosis and one year later. This allowed us to compare how the changes in the different tests relate to each other. And because previous research identified thresholds for important changes in the emPHasis-10 questionnaire and the walking tests, we were able to use these tests as a benchmark for changes in the MRI of the heart. Our study identified thresholds for change on heart MRI that might indicate whether a patient has improved or worsened. This finding might have implications for how patients are monitored in clinical practice and future research on PAH treatments.

Automated 4D flow cardiac MRI pipeline to derive peak mitral inflow diastolic velocities using short-axis cine stack: two centre validation study against echocardiographic pulse-wave doppler.

BACKGROUND: Measurement of peak velocities is important in the evaluation of heart failure. This study compared the performance of automated 4D flow cardiac MRI (CMR) with traditional transthoracic Doppler echocardiography (TTE) for the measurement of mitral inflow peak diastolic velocities. METHODS: Patients with Doppler echocardiography and 4D flow cardiac magnetic resonance data were included retrospectively. An established automated technique was used to segment the left ventricular transvalvular flow using short-axis cine stack of images. Peak mitral E-wave and peak mitral A-wave velocities were automatically derived using in-plane velocity maps of transvalvular flow. Additionally, we checked the agreement between peak mitral E-wave velocity derived by 4D flow CMR and Doppler echocardiography in patients with sinus rhythm and atrial fibrillation (AF) separately. RESULTS: Forty-eight patients were included (median age 69 years, IQR 63 to 76; 46% female). Data were split into three groups according to heart rhythm. The median peak E-wave mitral inflow velocity by automated 4D flow CMR was comparable with Doppler echocardiography in all patients (0.90 ± 0.43 m/s vs 0.94 ± 0.48 m/s, P = 0.132), sinus rhythm-only group (0.88 ± 0.35 m/s vs 0.86 ± 0.38 m/s, P = 0.54) and in AF-only group (1.33 ± 0.56 m/s vs 1.18 ± 0.47 m/s, P = 0.06). Peak A-wave mitral inflow velocity results had no significant difference between Doppler TTE and automated 4D flow CMR (0.81 ± 0.44 m/s vs 0.81 ± 0.53 m/s, P = 0.09) in all patients and sinus rhythm-only groups. Automated 4D flow CMR showed a significant correlation with TTE for measurement of peak E-wave in all patients group (r = 0.73, P < 0.001) and peak A-wave velocities (r = 0.88, P < 0.001). Moreover, there was a significant correlation between automated 4D flow CMR and TTE for peak-E wave velocity in sinus rhythm-only patients (r = 0.68, P < 0.001) and AF-only patients (r = 0.81, P = 0.014). Excellent intra-and inter-observer variability was demonstrated for both parameters. CONCLUSION: Automated dynamic peak mitral inflow diastolic velocity tracing using 4D flow CMR is comparable to Doppler echocardiography and has excellent repeatability for clinical use. However, 4D flow CMR can potentially underestimate peak velocity in patients with AF.

An acute increase in Left Atrial volume and left ventricular filling pressure during Adenosine administered myocardial hyperaemia: CMR First-Pass Perfusion Study.

OBJECTIVE: To investigate whether left atrial (LA) volume and left ventricular filling pressure (LVFP) assessed by cardiovascular magnetic resonance (CMR) change during adenosine delivered myocardial hyperaemia as part of a first-pass stress perfusion study. METHODS AND RESULTS: We enrolled 33 patients who had stress CMR. These patients had a baseline four-chamber cine and stress four-chamber cine, which was done at peak myocardial hyperaemic state after administering adenosine. The left and right atria were segmented in the end ventricular diastolic and systolic phases. Short-axis cine stack was segmented for ventricular functional assessment. At peak hyperaemic state, left atrial end ventricular systolic volume just before mitral valve opening increased significantly from baseline in all (91 ± 35ml vs. 81 ± 33ml, P = 0.0002), in males only (99 ± 35ml vs. 88 ± 33ml, P = 0.002) and females only (70 ± 26ml vs. 62 ± 22ml, P = 0.02). The right atrial end ventricular systolic volume increased less significantly from baseline (68 ± 21ml vs. 63 ± 20ml, P = 0.0448). CMR-derived LVFP (equivalent to pulmonary capillary wedge pressure) increased significantly at the peak hyperaemic state in all (15.1 ± 2.9mmHg vs. 14.4 ± 2.8mmHg, P = 0.0002), females only (12.9 ± 2.1mmHg vs. 12.3 ± 1.9mmHg, P = 0.029) and males only (15.9 ± 2.8mmHg vs. 15.2 ± 2.7mmHg, P = 0.002) cohorts. CONCLUSION: Left atrial volume assessment by CMR can measure acute and dynamic changes in preloading conditions on the left ventricle. During adenosine administered first-pass perfusion CMR, left atrial volume and LVFP rise significantly.

Assessment of Right Ventricular Function-a State of the Art.

PURPOSE OF REVIEW: The right ventricle (RV) has a complex geometry and physiology which is distinct from the left. RV dysfunction and failure can be the aftermath of volume- and/or pressure-loading conditions, as well as myocardial and pericardial diseases. RECENT FINDINGS: Echocardiography, magnetic resonance imaging and right heart catheterisation can assess RV function by using several qualitative and quantitative parameters. In pulmonary hypertension (PH) in particular, RV function can be impaired and is related to survival. An accurate assessment of RV function is crucial for the early diagnosis and management of these patients. This review focuses on the different modalities and indices used for the evaluation of RV function with an emphasis on PH.

Cardiac magnetic resonance identifies raised left ventricular filling pressure: prognostic implications.

AIMS: Non-invasive imaging is routinely used to estimate left ventricular (LV) filling pressure (LVFP) in heart failure (HF). Cardiovascular magnetic resonance (CMR) is emerging as an important imaging tool for sub-phenotyping HF. However, currently, LVFP cannot be estimated from CMR. This study sought to investigate (i) if CMR can estimate LVFP in patients with suspected HF and (ii) if CMR-modelled LVFP has prognostic power. METHODS AND RESULTS: Suspected HF patients underwent right heart catheterization (RHC), CMR and transthoracic echocardiography (TTE) (validation cohort only) within 24 h of each other. Right heart catheterization measured pulmonary capillary wedge pressure (PCWP) was used as a reference for LVFP. At follow-up, death was considered as the primary endpoint. We enrolled 835 patients (mean age: 65 ± 13 years, 40% male). In the derivation cohort (n = 708, 85%), two CMR metrics were associated with RHC PCWP:LV mass and left atrial volume. When applied to the validation cohort (n = 127, 15%), the correlation coefficient between RHC PCWP and CMR-modelled PCWP was 0.55 (95% confidence interval: 0.41-0.66, P < 0.0001). Cardiovascular magnetic resonance-modelled PCWP was superior to TTE in classifying patients as normal or raised filling pressures (76 vs. 25%). Cardiovascular magnetic resonance-modelled PCWP was associated with an increased risk of death (hazard ratio: 1.77, P < 0.001). At Kaplan-Meier analysis, CMR-modelled PCWP was comparable to RHC PCWP (≥15 mmHg) to predict survival at 7-year follow-up (35 vs. 37%, χ2 = 0.41, P = 0.52). CONCLUSION: A physiological CMR model can estimate LVFP in patients with suspected HF. In addition, CMR-modelled LVFP has a prognostic role.

Replicating File Segments between Multi-Cloud Nodes in a Smart City: A Machine Learning Approach.

The design and management of smart cities and the IoT is a multidimensional problem. One of those dimensions is cloud and edge computing management. Due to the complexity of the problem, resource sharing is one of the vital and major components that when enhanced, the performance of the whole system is enhanced. Research in data access and storage in multi-clouds and edge servers can broadly be classified to data centers and computational centers. The main aim of data centers is to provide services for accessing, sharing and modifying large databases. On the other hand, the aim of computational centers is to provide services for sharing resources. Present and future distributed applications need to deal with very large multi-petabyte datasets and increasing numbers of associated users and resources. The emergence of IoT-based, multi-cloud systems as a potential solution for large computational and data management problems has initiated significant research activity in the area. Due to the considerable increase in data production and data sharing within scientific communities, the need for improvements in data access and data availability cannot be overlooked. It can be argued that the current approaches of large dataset management do not solve all problems associated with big data and large datasets. The heterogeneity and veracity of big data require careful management. One of the issues for managing big data in a multi-cloud system is the scalability and expendability of the system under consideration. Data replication ensures server load balancing, data availability and improved data access time. The proposed model minimises the cost of data services through minimising a cost function that takes storage cost, host access cost and communication cost into consideration. The relative weights between different components is learned through history and it is different from a cloud to another. The model ensures that data are replicated in a way that increases availability while at the same time decreasing the overall cost of data storage and access time. Using the proposed model avoids the overheads of the traditional full replication techniques. The proposed model is mathematically proven to be sound and valid.

The Left Atrial Area Derived Cardiovascular Magnetic Resonance Left Ventricular Filling Pressure Equation Shows Superiority over Integrated Echocardiography.

Background and objectives: Evaluating left ventricular filling pressure (LVFP) plays a crucial role in diagnosing and managing heart failure (HF). While traditional assessment methods involve multi-parametric transthoracic echocardiography (TTE) or right heart catheterisation (RHC), cardiovascular magnetic resonance (CMR) has emerged as a valuable diagnostic tool in HF. This study aimed to assess a simple CMR-derived model to estimate pulmonary capillary wedge pressure (PCWP) in a cohort of patients with suspected or proven heart failure and to investigate its performance in risk-stratifying patients. Materials and methods: A total of 835 patients with breathlessness were evaluated using RHC and CMR and split into derivation (85%) and validation cohorts (15%). Uni-variate and multi-variate linear regression analyses were used to derive a model for PCWP estimation using CMR. The model's performance was evaluated by comparing CMR-derived PCWP with PCWP obtained from RHC. Results: A CMR-derived PCWP incorporating left ventricular mass and the left atrial area (LAA) demonstrated good diagnostic accuracy. The model correctly reclassified 66% of participants whose TTE was 'indeterminate' or 'incorrect' in identifying raised filling pressures. On survival analysis, the CMR-derived PCWP model was predictive for mortality (HR 1.15, 95% CI 1.04-1.28, p = 0.005), which was not the case for PCWP obtained using RHC or TTE. Conclusions: The simplified CMR-derived PCWP model provides an accurate and practical tool for estimating PCWP in patients with suspected or proven heart failure. Its predictive value for mortality suggests the ability to play a valuable adjunctive role in echocardiography, especially in cases with unclear echocardiographic assessment.

Quantitative CT Evaluation of Small Pulmonary Vessels Has Functional and Prognostic Value in Pulmonary Hypertension.

Background The in vivo relationship between peel pulmonary vessels, small pulmonary vessels, and pulmonary hypertension (PH) is not fully understood. Purpose To quantitatively assess peel pulmonary vessel volumes (PPVVs) and small pulmonary vessel volumes (SPVVs) as estimated from CT pulmonary angiography (CTPA) in different subtypes of PH compared with controls, their relationship to pulmonary function and right heart catheter metrics, and their prognostic value. Materials and Methods In this retrospective single-center study performed from January 2008 to February 2018, quantitative CTPA analysis of total SPVV (TSPVV) (0.4- to 2-mm vessel diameter) and PPVV (within 15, 30, and 45 mm from the lung surface) was performed. Results A total of 1823 patients (mean age, 69 years ± 13 [SD]; 1192 women [65%]) were retrospectively analyzed; 1593 patients with PH (mean pulmonary arterial pressure [mPAP], 43 mmHg ± 13 [SD]) were compared with 230 patient controls (mPAP, 19 mm Hg ± 3). The mean vessel volumes in pulmonary peels at 15-, 30-, and 45-mm depths were higher in pulmonary arterial hypertension (PAH) and PH secondary to lung disease compared with chronic thromboembolic PH (45-mm peel, mean difference: 6.4 mL [95% CI: 1, 11] [P < .001] vs 6.8 mL [95% CI: 1, 12] [P = .01]). Mean small vessel volumes at a diameter of less than 2 mm were lower in PAH and PH associated with left heart disease compared with controls (1.6-mm vessels, mean difference: -4.3 mL [95% CI: -8, -0.1] [P = .03] vs -6.8 mL [95% CI: -11, -2] [P < .001]). In patients with PH, the most significant positive correlation was noted with forced vital capacity percentage predicted (r = 0.30-0.40 [all P < .001] for TSPVVs and r = 0.21-0.25 [all P < .001] for PPVVs). Conclusion The volume of pulmonary small vessels is reduced in pulmonary arterial hypertension and pulmonary hypertension (PH) associated with left heart disease, with similar volume of peel vessels compared with controls. For chronic thromboembolic PH, the volume of peel vessels is reduced. In PH, small pulmonary vessel volume is associated with pulmonary function tests. Clinical trial registration no. NCT02565030 Published under a CC BY 4.0 license Online supplemental material is available for this article.

Validation of Artificial Intelligence Cardiac MRI Measurements: Relationship to Heart Catheterization and Mortality Prediction.

Background Cardiac MRI measurements have diagnostic and prognostic value in the evaluation of cardiopulmonary disease. Artificial intelligence approaches to automate cardiac MRI segmentation are emerging but require clinical testing. Purpose To develop and evaluate a deep learning tool for quantitative evaluation of cardiac MRI functional studies and assess its use for prognosis in patients suspected of having pulmonary hypertension. Materials and Methods A retrospective multicenter and multivendor data set was used to develop a deep learning-based cardiac MRI contouring model using a cohort of patients suspected of having cardiopulmonary disease from multiple pathologic causes. Correlation with same-day right heart catheterization (RHC) and scan-rescan repeatability was assessed in prospectively recruited participants. Prognostic impact was assessed using Cox proportional hazard regression analysis of 3487 patients from the ASPIRE (Assessing the Severity of Pulmonary Hypertension In a Pulmonary Hypertension Referral Centre) registry, including a subset of 920 patients with pulmonary arterial hypertension. The generalizability of the automatic assessment was evaluated in 40 multivendor studies from 32 centers. Results The training data set included 539 patients (mean age, 54 years ± 20 [SD]; 315 women). Automatic cardiac MRI measurements were better correlated with RHC parameters than were manual measurements, including left ventricular stroke volume (r = 0.72 vs 0.68; P = .03). Interstudy repeatability of cardiac MRI measurements was high for all automatic measurements (intraclass correlation coefficient range, 0.79-0.99) and similarly repeatable to manual measurements (all paired t test P > .05). Automated right ventricle and left ventricle cardiac MRI measurements were associated with mortality in patients suspected of having pulmonary hypertension. Conclusion An automatic cardiac MRI measurement approach was developed and tested in a large cohort of patients, including a broad spectrum of right ventricular and left ventricular conditions, with internal and external testing. Fully automatic cardiac MRI assessment correlated strongly with invasive hemodynamics, had prognostic value, were highly repeatable, and showed excellent generalizability. Clinical trial registration no. NCT03841344 Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Ambale-Venkatesh and Lima in this issue. An earlier incorrect version appeared online. This article was corrected on June 27, 2022.

Integrated Cardiopulmonary MRI Assessment of Pulmonary Hypertension.

Pulmonary hypertension (PH) is a heterogeneous condition that can affect the lung parenchyma, pulmonary vasculature, and cardiac chambers. Accurate diagnosis often requires multiple complex assessments of the cardiac and pulmonary systems. MRI is able to comprehensively assess cardiac structure and function, as well as lung parenchymal, pulmonary vascular, and functional lung changes. Therefore, MRI has the potential to provide an integrated functional and structural assessment of the cardiopulmonary system in a single exam. Cardiac MRI is used in the assessment of PH in most large PH centers, whereas lung MRI is an emerging technique in patients with PH. This article reviews the current literature on cardiopulmonary MRI in PH, including cine MRI, black-blood imaging, late gadolinium enhancement, T1 mapping, myocardial strain analysis, contrast-enhanced perfusion imaging and contrast-enhanced MR angiography, and hyperpolarized gas functional lung imaging. This article also highlights recent developments in this field and areas of interest for future research including cardiac MRI-based diagnostic models, machine learning in cardiac MRI, oxygen-enhanced 1 H imaging, contrast-free 1 H perfusion and ventilation imaging, contrast-free angiography and UTE imaging. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

BACKGROUND: Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may allow more reliable measurement of RA areas to improve clinical assessments. The aim of this study was to automate cardiovascular magnetic resonance (CMR) RA area measurements and evaluate the clinical utility by assessing repeatability, correlation with invasive haemodynamics and prognostic value. METHODS: A deep learning RA area CMR contouring model was trained in a multicentre cohort of 365 patients with pulmonary hypertension, left ventricular pathology and healthy subjects. Inter-study repeatability (intraclass correlation coefficient (ICC)) and agreement of contours (DICE similarity coefficient (DSC)) were assessed in a prospective cohort (n = 36). Clinical testing and mortality prediction was performed in n = 400 patients that were not used in the training nor prospective cohort, and the correlation of automatic and manual RA measurements with invasive haemodynamics assessed in n = 212/400. Radiologist quality control (QC) was performed in the ASPIRE registry, n = 3795 patients. The primary QC observer evaluated all the segmentations and recorded them as satisfactory, suboptimal or failure. A second QC observer analysed a random subcohort to assess QC agreement (n = 1018). RESULTS: All deep learning RA measurements showed higher interstudy repeatability (ICC 0.91 to 0.95) compared to manual RA measurements (1st observer ICC 0.82 to 0.88, 2nd observer ICC 0.88 to 0.91). DSC showed high agreement comparing automatic artificial intelligence and manual CMR readers. Maximal RA area mean and standard deviation (SD) DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 is 92.4 ± 3.5 cm2, 91.2 ± 4.5 cm2 and 93.2 ± 3.2 cm2, respectively. Minimal RA area mean and SD DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 was 89.8 ± 3.9 cm2, 87.0 ± 5.8 cm2 and 91.8 ± 4.8 cm2. Automatic RA area measurements all showed moderate correlation with invasive parameters (r = 0.45 to 0.66), manual (r = 0.36 to 0.57). Maximal RA area could accurately predict elevated mean RA pressure low and high-risk thresholds (area under the receiver operating characteristic curve artificial intelligence = 0.82/0.87 vs manual = 0.78/0.83), and predicted mortality similar to manual measurements, both p < 0.01. In the QC evaluation, artificial intelligence segmentations were suboptimal at 108/3795 and a low failure rate of 16/3795. In a subcohort (n = 1018), agreement by two QC observers was excellent, kappa 0.84. CONCLUSION: Automatic artificial intelligence CMR derived RA size and function are accurate, have excellent repeatability, moderate associations with invasive haemodynamics and predict mortality.

RAPT: A Robust Attack Path Tracing Algorithm to Mitigate SYN-Flood DDoS Cyberattacks.

In the recent past, Distributed Denial of Service (DDoS) attacks have become more abundant and present one of the most serious security threats. In a DDoS attack, the attacker controls a botnet of daemons residing in vulnerable hosts that send a significant amount of traffic to flood the victim or the network infrastructure. In this paper, a common type of DDoS attacks known as "TCP SYN-Flood" is studied. This type of attack uses spoofed Internet Protocol (IP) addresses for SYN packets by exploiting the weakness in Transmission Control Protocol (TCP) 3-Way handshake used by the TCP/IP suite of protocols, which make the web servers unreachable for legitimate users or even worse, it might lead to server crash. In this paper, a resilient, efficient, lightweight, and robust IP traceback algorithm is proposed using an IP tracing packet for each attack path. The proposed algorithm suggests that edge routers-where the attack starts from-observe the traffic pattern passing through, and if the observed traffic carries the signature of TCP SYN-Flood DDoS attack and a high percentage of it is destined to a particular web server(s), it starts the tracing process by generating an IP trace packet, which accompanies the attack path recording the routers' IP addresses on the path between the attacker/daemon and the victim, which can extract the path and react properly upon receiving it by discarding any SYN packets originating from that attacker/daemon. To our knowledge, this is the first research that efficiently traces these kinds of attacks while they are running. The proposed solution has low computation and message overhead, efficient detection and tracing time, and converges in near optimal time. The results are validated using extensive simulation runs.

The Role of Artificial Intelligence in Predicting Outcomes by Cardiovascular Magnetic Resonance: A Comprehensive Systematic Review.

Background and Objectives: Interest in artificial intelligence (AI) for outcome prediction has grown substantially in recent years. However, the prognostic role of AI using advanced cardiac magnetic resonance imaging (CMR) remains unclear. This systematic review assesses the existing literature on AI in CMR to predict outcomes in patients with cardiovascular disease. Materials and Methods: Medline and Embase were searched for studies published up to November 2021. Any study assessing outcome prediction using AI in CMR in patients with cardiovascular disease was eligible for inclusion. All studies were assessed for compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Results: A total of 5 studies were included, with a total of 3679 patients, with 225 deaths and 265 major adverse cardiovascular events. Three methods demonstrated high prognostic accuracy: (1) three-dimensional motion assessment model in pulmonary hypertension (hazard ratio (HR) 2.74, 95%CI 1.73−4.34, p < 0.001), (2) automated perfusion quantification in patients with coronary artery disease (HR 2.14, 95%CI 1.58−2.90, p < 0.001), and (3) automated volumetric, functional, and area assessment in patients with myocardial infarction (HR 0.94, 95%CI 0.92−0.96, p < 0.001). Conclusion: There is emerging evidence of the prognostic role of AI in predicting outcomes for three-dimensional motion assessment in pulmonary hypertension, ischaemia assessment by automated perfusion quantification, and automated functional assessment in myocardial infarction.

Repeatability and sensitivity to change of non-invasive end points in PAH: the RESPIRE study.

End points that are repeatable and sensitive to change are important in pulmonary arterial hypertension (PAH) for clinical practice and trials of new therapies. In 42 patients with PAH, test-retest repeatability was assessed using the intraclass correlation coefficient and treatment effect size using Cohen's d statistic. Intraclass correlation coefficients demonstrated excellent repeatability for MRI, 6 min walk test and log to base 10 N-terminal pro-brain natriuretic peptide (log10NT-proBNP). The treatment effect size for MRI-derived right ventricular ejection fraction was large (Cohen's d 0.81), whereas the effect size for the 6 min walk test (Cohen's d 0.22) and log10NT-proBNP (Cohen's d 0.20) were fair. This study supports further evaluation of MRI as a non-invasive end point for clinical assessment and PAH therapy trials.Trial registration number NCT03841344.

Beta-blockers for congestive heart failure in children.

BACKGROUND: Beta-blockers are an essential part of standard therapy in adult congestive heart failure and therefore, are expected to be beneficial in children. However, congestive heart failure in children differs from that in adults in terms of characteristics, aetiology, and drug clearance. Therefore, paediatric needs must be specifically investigated. This is an update of a Cochrane review previously published in 2009. OBJECTIVES: To assess the effect of beta-adrenoceptor-blockers (beta-blockers) in children with congestive heart failure. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library, MEDLINE, EMBASE, and LILACS up to November 2015. Bibliographies of identified studies were checked. No language restrictions were applied. SELECTION CRITERIA: Randomised, controlled, clinical trials investigating the effect of beta-blocker therapy on paediatric congestive heart failure. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted and assessed data from the included trials. MAIN RESULTS: We identified four new studies for the review update; the review now includes seven studies with 420 participants. Four small studies with 20 to 30 children each, and two larger studies of 80 children each, showed an improvement of congestive heart failure with beta-blocker therapy. A larger study with 161 participants showed no evidence of benefit over placebo in a composite measure of heart failure outcomes. The included studies showed no significant difference in mortality or heart transplantation rates between the beta-blocker and control groups. No significant adverse events were reported with beta-blockers, apart from one episode of complete heart block. A meta-analysis of left ventricular ejection fraction (LVEF) and fractional shortening (LVFS) data showed a very small improvement with beta-blockers. However, there were vast differences in the age, age range, and health of the participants (aetiology and severity of heart failure; heterogeneity of diagnoses and co-morbidities); there was a range of treatments across studies (choice of beta-blocker, dosing, duration of treatment); and a lack of standardised methods and outcome measures. Therefore, the primary outcomes could not be pooled in meta-analyses. AUTHORS' CONCLUSIONS: There is not enough evidence to support or discourage the use of beta-blockers in children with congestive heart failure, or to propose a paediatric dosing scheme. However, the sparse data available suggested that children with congestive heart failure might benefit from beta-blocker treatment. Further investigations in clearly defined populations with standardised methodology are required to establish guidelines for therapy. Pharmacokinetic investigations of beta-blockers in children are also required to provide effective dosing in future trials.

Non-vitamin K antagonist oral anticoagulants (NOACs) post-percutaneous coronary intervention: a network meta-analysis.

BACKGROUND: Clinicians must balance the risks of bleeding and thrombosis after percutaneous coronary intervention (PCI) in people with an indication for anticoagulation. The potential of non-vitamin K antagonists (NOACs) to prevent bleeding complications is promising, but evidence remains limited. OBJECTIVES: To review the evidence from randomised controlled trials assessing the efficacy and safety of non-vitamin K antagonist oral anticoagulants (NOACs) compared to vitamin K antagonists post-percutaneous coronary intervention (PCI) in people with an indication for anticoagulation. SEARCH METHODS: We identified studies by searching CENTRAL, MEDLINE, Embase, the Conference Proceedings Citation Index - Science and two clinical trials registers in February 2019. We checked bibliographies of identified studies and applied no language restrictions. SELECTION CRITERIA: We searched for randomised controlled trials (RCT) that compared NOACs and vitamin K antagonists for people with an indication for anticoagulation who underwent PCI. DATA COLLECTION AND ANALYSIS: Two review authors independently checked the results of searches to identify relevant studies, assessed each included study, and extracted study data. We conducted random-effects, pairwise analyses using Review Manager 5 and network meta-analyses (NMA) using the R package 'netmeta'. We ranked competing treatments by P scores, which are derived from the P values of all pairwise comparisons, and allow ranking of treatments on a continuous 0 to 1 scale. MAIN RESULTS: We identified nine RCTs that met the inclusion criteria, but four were ongoing trials, and were not included in this analysis. We included five RCTs, with 8373 participants, in the NMA (two RCTs compared apixaban to a vitamin K antagonist, two RCTs compared rivaroxaban to a vitamin K antagonist, and one RCT compared dabigatran to a vitamin K antagonist). Very low- to moderate-certainty evidence suggests little or no difference between NOACs and vitamin K antagonists in death from cardiovascular causes (not reported in the dabigatran trial), myocardial infarction, stroke, death from any cause, and stent thrombosis. Apixaban (RR 0.85, 95% CI 0.77 to 0.95), high dose rivaroxaban (RR 0.86, 95% CI 0.74 to 1.00), and low dose rivaroxaban (RR 0.80, 95% CI 0.68 to 0.92) probably reduce the risk of recurrent hospitalisation compared with vitamin K antagonists. No studies looked at health-related quality of life. Very low- to moderate-certainty evidence suggests that NOACs may be safer than vitamin K antagonists in terms of bleeding. Both high dose dabigatran (RR 0.53, 95% CI 0.29 to 0.97), and low dose dabigatran (RR 0.38, 95% CI 0.21 to 0.70) may reduce major bleeding more than vitamin K antagonists. High dose dabigatran (RR 0.83, 95% CI 0.72 to 0.96), low dose dabigatran (RR 0.66, 95% CI 0.58 to 0.75), apixaban (RR 0,67 , 95% Cl 0.51 to 0.88), high dose rivaroxaban (RR 0.66, 95% CI 0.52 to 0.83), and low dose rivaroxaban (RR 0.71, 95% CI 0.57 to 0.88) probably reduce non-major bleeding more than vitamin K antagonists. The results from the NMA were inconclusive between the different NOACs for all primary and secondary outcomes. AUTHORS' CONCLUSIONS: Very low- to moderate-certainty evidence suggests no meaningful difference in efficacy outcomes between non-vitamin K antagonist oral anticoagulants (NOAC) and vitamin K antagonists following percutaneous coronary interventions (PCI) in people with non-valvular atrial fibrillation. NOACs probably reduce the risk of recurrent hospitalisation for adverse events compared with vitamin K antagonists. Low- to moderate-certainty evidence suggests that dabigatran may reduce the rates of major and non-major bleeding, and apixaban and rivaroxaban probably reduce the rates of non-major bleeding compared with vitamin K antagonists. Our network meta-analysis did not show superiority of one NOAC over another for any of the outcomes. Head to head trials, directly comparing NOACs against each other, are required to provide more certain evidence.