Multicenter Standardization of Phase-Resolved Functional Lung MRI in Patients With Suspected Chronic Thromboembolic Pulmonary Hypertension

BACKGROUND

Detection of pulmonary perfusion defects is the recommended approach for diagnosing chronic thromboembolic pulmonary hypertension (CTEPH). This is currently achieved in a clinical setting using scintigraphy. Phase-resolved functional lung (PREFUL) magnetic resonance imaging (MRI) is an alternative technique for evaluating regional ventilation and perfusion without the use of ionizing radiation or contrast media.

PURPOSE

To assess the feasibility and image quality of PREFUL-MRI in a multicenter setting in suspected CTEPH.

STUDY TYPE

This is a prospective cohort sub-study.

POPULATION

Forty-five patients (64 ± 16 years old) with suspected CTEPH from nine study centers.

FIELD STRENGTH/SEQUENCE

1.5 T and 3 T/2D spoiled gradient echo/bSSFP/T2 HASTE/3D MR angiography (TWIST).

ASSESSMENT

Lung signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were compared between study centers with different MRI machines. The contrast between normally and poorly perfused lung areas was examined on PREFUL images. The perfusion defect percentage calculated using PREFUL-MRI (QDPPREFUL) was compared to QDP from the established dynamic contrast-enhanced MRI technique (QDPDCE). Furthermore, QDPPREFUL was compared between a patient subgroup with confirmed CTEPH or chronic thromboembolic disease (CTED) to other clinical subgroups.

STATISTICAL TESTS

t-Test, one-way analysis of variance (ANOVA), Pearson's correlation. Significance level was 5%.

RESULTS

Significant differences in lung SNR and CNR were present between study centers. However, PREFUL perfusion images showed a significant contrast between normally and poorly perfused lung areas (mean delta of normalized perfusion -4.2% SD 3.3) with no differences between study sites (ANOVA: P = 0.065). QDPPREFUL was significantly correlated with QDPDCE (r = 0.66), and was significantly higher in 18 patients with confirmed CTEPH or CTED (57.9 ± 12.2%) compared to subgroups with other causes of PH or with excluded PH (in total 27 patients with mean ± SD QDPPREFUL = 33.9 ± 17.2%).

DATA CONCLUSION

PREFUL-MRI could be considered as a non-invasive method for imaging regional lung perfusion in multicenter studies.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 1.

Sex-specific cardiac magnetic resonance pulmonary capillary wedge pressure

Aims

Heart failure (HF) with preserved ejection fraction disproportionately affects women. There are no validated sex-specific tools for HF diagnosis despite widely reported differences in cardiac structure. This study investigates whether sex, as assigned at birth, influences cardiac magnetic resonance (CMR) assessment of left ventricular filling pressure (LVFP), a hallmark of HF agnostic to ejection fraction.

Methods and results

A derivation cohort of patients with suspected pulmonary hypertension and HF from the Sheffield centre underwent invasive right heart catheterization and CMR within 24 h of each other. A sex-specific CMR model to estimate LVFP, measured as pulmonary capillary wedge pressure (PCWP), was developed using multivariable regression. A validation cohort of patients with confirmed HF from the Leeds centre was used to evaluate for the primary endpoints of HF hospitalization and major adverse cardiovascular events (MACEs). Comparison between generic and sex-specific CMR-derived PCWP was undertaken. A total of 835 (60% female) and 454 (36% female) patients were recruited into the derivation and validation cohorts respectively. A sex-specific model incorporating left atrial volume and left ventricular mass was created. The generic CMR PCWP showed significant differences between males and females (14.7 ± 4 vs. 13 ± 3.0 mmHg, P > 0.001), not present with the sex-specific CMR PCWP (14.1 ± 3 vs. 13.8 mmHg, P = 0.3). The sex-specific, but not the generic, CMR PCWP was associated with HF hospitalization (hazard ratio 3.9, P = 0.0002) and MACE (hazard ratio 2.5, P = 0.001) over a mean follow-up period of 2.4 ± 1.2 years.

Conclusion

Accounting for sex improves precision and prognostic performance of CMR biomarkers for HF.

Characterisation of the octogenarians presenting to the diagnostic heart failure clinic: SHEAF registry

INTRODUCTION

Heart failure (HF) incidence is increasing in older adults with high hospitalisation and mortality rates. Treatment is complicated by side effects and comorbidities. We investigated the clinical characteristics of octogenarians presenting to the HF clinic.

METHODS

Data were collected on octogenarians (80-89 years) referred to the HF clinic in two periods. The data included demographics, HF phenotype, comorbidities, symptoms and treatment. We investigate the temporal changes in clinical characteristics using χ2 test. We aimed to determine the clinical characteristics which were associated with optimisation of HF pharmacological intervention in the clinic, conducting multivariate regression analysis. Statistical significance is determined at p<0.05.

RESULTS

Data were collected in April 2012 to January 2014 and in June 2021 to December 2022. In this cross-sectional study of temporal data, 571 octogenarians were referred to the clinic in the latter period, in whom the prevalence of HF was 68.48% (391 patients). HF with preserved ejection fraction (HFpEF) was the most common phenotype and increased significantly compared with the first period (46.3% and 29.2%, p<0.001). Frailty, chronic kidney disease and ischaemic heart disease increased significantly versus the first period (p<0.001). During the second period, and following the consultation, of the patients with HF with reduced ejection fraction (HFrEF), 86.4% and 82.7% were on a beta blocker and on an ACE inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitor, respectively. Clinical characteristics associated with further optimisations of HF pharmacological therapy in the HF clinic were: New York Heart Association (NYHA) functional class III and the presence of HFrEF phenotype CONCLUSIONS: With a prevalence of HF at 68% among the octogenarians referred to the HF clinic, HFpEF incidence is rising. The decision to optimise HF pharmacological treatment in octogenarians is driven by NYHA functional class III and the presence of HFrEF phenotype.

Validation of Left Atrial Volume Correction for Single Plane Method on Four-Chamber Cine Cardiac MRI

BACKGROUND

Left atrial (LA) assessment is an important marker of adverse cardiovascular outcomes. Cardiovascular magnetic resonance (CMR) accurately quantifies LA volume and function based on biplane long-axis imaging. We aimed to validate single-plane-derived LA indices against the biplane method to simplify the post-processing of cine CMR.

METHODS

In this study, 100 patients from Leeds Teaching Hospitals were used as the derivation cohort. Bias correction for the single plane method was applied and subsequently validated in 79 subjects.

RESULTS

There were significant differences between the biplane and single plane mean LA maximum and minimum volumes and LA ejection fraction (EF) (all p < 0.01). After correcting for biases in the validation cohort, significant correlations in all LA indices were observed (0.89 to 0.98). The area under the curve (AUC) for the single plane to predict biplane cutoffs of LA maximum volume ≥ 112 mL was 0.97, LA minimum volume ≥ 44 mL was 0.99, LA stroke volume (SV) ≤ 21 mL was 1, and LA EF ≤ 46% was 1, (all p < 0.001).

CONCLUSIONS

LA volumetric and functional assessment by the single plane method has a systematic bias compared to the biplane method. After bias correction, single plane LA volume and function are comparable to the biplane method.

Validation of 2D flow MRI for helical and vortical flows

PURPOSE

The main objective of this study was to develop two-dimensional (2D) phase contrast (PC) methods to quantify the helicity and vorticity of blood flow in the aortic root.

METHODS

This proof-of-concept study used four-dimensional (4D) flow cardiovascular MR (4D flow CMR) data of five healthy controls, five patients with heart failure with preserved ejection fraction and five patients with aortic stenosis (AS). A PC through-plane generated by 4D flow data was treated as a 2D PC plane and compared with the original 4D flow. Visual assessment of flow vectors was used to assess helicity and vorticity. We quantified flow displacement (FD), systolic flow reversal ratio (sFRR) and rotational angle (RA) using 2D PC.

RESULTS

For visual vortex flow presence near the inner curvature of the ascending aortic root on 4D flow CMR, sFRR demonstrated an area under the curve (AUC) of 0.955, p<0.001. A threshold of >8% for sFRR had a sensitivity of 82% and specificity of 100% for visual vortex presence. In addition, the average late systolic FD, a marker of flow eccentricity, also demonstrated an AUC of 0.909, p<0.001 for visual vortex flow. Manual systolic rotational flow angle change (ΔsRA) demonstrated excellent association with semiautomated ΔsRA (r=0.99, 95% CI 0.9907 to 0.999, p<0.001). In reproducibility testing, average systolic FD (FDsavg) showed a minimal bias at 1.28% with a high intraclass correlation coefficient (ICC=0.92). Similarly, sFRR had a minimal bias of 1.14% with an ICC of 0.96. ΔsRA demonstrated an acceptable bias of 5.72°-and an ICC of 0.99.

CONCLUSION

2D PC flow imaging can possibly quantify blood flow helicity (ΔRA) and vorticity (FRR). These imaging biomarkers of flow helicity and vorticity demonstrate high reproducibility for clinical adoption.

TRIALS REGISTRATION NUMBER

NCT05114785.

Aortic flow is abnormal in HFpEF

Aims

Turbulent aortic flow makes the cardiovascular system less effective. It remains unknown if patients with heart failure with preserved ejection fraction (HFpEF) have disturbed aortic flow. This study sought to investigate advanced markers of aortic flow disturbances in HFpEF.

Methods

This case-controlled observational study used four-dimensional flow cardiovascular magnetic resonance derived, two-dimensional phase-contrast reformatted plane data at an orthogonal plane just above the sino-tubular junction. We recruited 10 young healthy controls (HCs), 10 old HCs and 23 patients with HFpEF. We analysed average systolic aortic flow displacement (FDsavg), systolic flow reversal ratio (sFRR) and pulse wave velocity (PWV). In a sub-group analysis, we compared old HCs versus age-gender-matched HFpEF (N=10).

Results

Differences were significant in mean age (P<0.001) among young HCs (22.9±3.5 years), old HCs (60.5±10.2 years) and HFpEF patients (73.7±9.7 years). FDsavg, sFRR and PWV varied significantly (P<0.001) in young HCs (8±4%, 2±2%, 4±2m/s), old HCs (16±5%, 7±6%, 11±8m/s), and HFpEF patients (23±10%, 11±10%, 8±3). No significant PWV differences existed between old HCs and HFpEF.HFpEF had significantly higher FDsavg versus old HCs (23±10% vs 16±5%, P<0.001). A FDsavg > 17.7% achieved 74% sensitivity, 70% specificity for differentiating them. sFRR was notably higher in HFpEF (11±10% vs 7±6%, P<0.001). A sFRR > 7.3% yielded 78% sensitivity, 70% specificity in differentiating these groups. In sub-group analysis, FDsavg remained distinctly elevated in HFpEF (22.4±9.7% vs 16±4.9%, P=0.029). FDsavg of >16% showed 100% sensitivity and 70% specificity (P=0.01). Similarly, sFRR remained significantly higher in HFpEF (11.3±9.5% vs 6.6±6.4%, P=0.007). A sFRR of >7.2% showed 100% sensitivity and 60% specificity (P<0.001).

Conclusion

Aortic flow haemodynamics namely FDsavg and sFRR are significantly affected in ageing and HFpEF patients.

Effect of Macitentan in Pulmonary Arterial Hypertension and the Relationship Between Echocardiography and cMRI Variables: REPAIR Echocardiography Sub-study Results

INTRODUCTION

The aim of this sub-study was to evaluate the relationship between echocardiography (echo) and cardiac magnetic resonance imaging (cMRI) variables and to utilize echo to assess the effect of macitentan on right ventricle (RV) structure and function.

METHODS

REPAIR (NCT02310672) was a prospective, multicenter, single-arm, open-label, 52-week, phase 4 study in pulmonary arterial hypertension (PAH) patients, which investigated the effect of macitentan 10 mg as monotherapy, or in combination with a phosphodiesterase 5 inhibitor, on RV structure, function, and hemodynamics using cMRI and right heart catheterization. In this sub-study, patients were also assessed by echo at screening and at weeks 26 and/or 52. Post hoc correlation analyses between echo and cMRI variables were performed using Pearson's correlation coefficient, Spearman's correlation coefficient, and Bland-Altman analyses.

RESULTS

The Echo sub-study included 45 patients. Improvements in echo-assessed RV stroke volume (RVSV), left ventricular SV (LVSV), LV end-diastolic volume (LVEDV), RV fractional area change (RVFAC), tricuspid annular plane systolic excursion (TAPSE), and in 2D global longitudinal RV strain (2D GLRVS) were observed at weeks 26 and 52 compared to baseline. There was a strong correlation between echo (LVSV, 2D GLRVS, and LVEDV) and cMRI variables, with a moderate correlation for RVSV. Bland-Altman analyses showed a good agreement for LVSV measured by echo versus cMRI, whereas an overestimation in echo-assessed RVSV was observed compared to cMRI (bias of - 15 mL). Hemodynamic and functional variables, as well as safety, were comparable between the Echo sub-study and REPAIR.

CONCLUSIONS

A good relationship between relevant echo and cMRI parameters was shown. Improvements in RV structure and function with macitentan treatment was observed by echo, consistent with results observed by cMRI in the primary analysis of the REPAIR study. Echo is a valuable complementary method to cMRI, with the potential to non-invasively monitor treatment response at follow-up.

TRIAL REGISTRATION NUMBER

REPAIR NCT02310672.

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.

Clinical assessment of an AI tool for measuring biventricular parameters on cardiac MR

Introduction

Cardiac magnetic resonance (CMR) is of diagnostic and prognostic value in a range of cardiopulmonary conditions. Current methods for evaluating CMR studies are laborious and time-consuming, contributing to delays for patients. As the demand for CMR increases, there is a growing need to automate this process. The application of artificial intelligence (AI) to CMR is promising, but the evaluation of these tools in clinical practice has been limited. This study assessed the clinical viability of an automatic tool for measuring cardiac volumes on CMR.

Methods

Consecutive patients who underwent CMR for any indication between January 2022 and October 2022 at a single tertiary centre were included prospectively. For each case, short-axis CMR images were segmented by the AI tool and manually to yield volume, mass and ejection fraction measurements for both ventricles. Automated and manual measurements were compared for agreement and the quality of the automated contours was assessed visually by cardiac radiologists.

Results

462 CMR studies were included. No statistically significant difference was demonstrated between any automated and manual measurements (p > 0.05; independent T-test). Intraclass correlation coefficient and Bland-Altman analysis showed excellent agreement across all metrics (ICC > 0.85). The automated contours were evaluated visually in 251 cases, with agreement or minor disagreement in 229 cases (91.2%) and failed segmentation in only a single case (0.4%). The AI tool was able to provide automated contours in under 90 s.

Conclusions

Automated segmentation of both ventricles on CMR by an automatic tool shows excellent agreement with manual segmentation performed by CMR experts in a retrospective real-world clinical cohort. Implementation of the tool could improve the efficiency of CMR reporting and reduce delays between imaging and diagnosis.

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.

Comparison of cardiac magnetic resonance imaging, functional and haemodynamic variables in pulmonary arterial hypertension: insights from REPAIR

Background

Measures that can detect large treatment effects are important for monitoring therapeutic effectiveness. The 2022 European Society of Cardiology/European Respiratory Society guidelines highlight the importance of imaging in monitoring disease status and treatment response in pulmonary arterial hypertension (PAH). Are the standardised treatment effect sizes (STES) of cardiac magnetic resonance imaging (cMRI) comparable with functional and haemodynamic variables?

Methods

REPAIR (ClinicalTrials.gov: NCT02310672) was a prospective, multicentre, single-arm, open-label, 52-week phase 4 study evaluating the effect of macitentan 10 mg, with or without a phosphodiesterase 5 inhibitor (PDE5i), on right ventricular (RV) remodelling, cardiac function and cardiopulmonary haemodynamics. Both cMRI and functional assessments were performed at screening and at weeks 26 and 52; haemodynamic measurements were conducted at screening and week 26. In this post hoc analysis, STES were estimated using the parametric Cohen's d and non-parametric Cliff's delta tests.

Results

At week 26, large STES (Cohen's d) were observed for 10 of the 20 cMRI variables assessed, including the prognostic measures of RV and left ventricular stroke volume and RV ejection fraction and the haemodynamic trial end-point, pulmonary vascular resistance; medium STES were observed for 6-min walk distance (6MWD). The STES were consistent in treatment-naïve patients and those escalating therapy and maintained at week 52. Similar results were obtained using the non-parametric Cliff's delta method.

Conclusions

The treatment effect of macitentan, alone or in combination with a PDE5i, was comparable for several cMRI and haemodynamic variables with prognostic value in PAH, and greater than that of 6MWD in patients with PAH, highlighting the emerging relevance of cMRI in PAH.

Cardiac MR modelling of systolic and diastolic blood pressure

AIMS

Blood pressure (BP) is a crucial factor in cardiovascular health and can affect cardiac imaging assessments. However, standard outpatient cardiovascular MR (CMR) imaging procedures do not typically include BP measurements prior to image acquisition. This study proposes that brachial systolic BP (SBP) and diastolic BP (DBP) can be modelled using patient characteristics and CMR data.

METHODS

In this multicentre study, 57 patients from the PREFER-CMR registry and 163 patients from other registries were used as the derivation cohort. All subjects had their brachial SBP and DBP measured using a sphygmomanometer. Multivariate linear regression analysis was applied to predict brachial BP. The model was subsequently validated in a cohort of 169 healthy individuals.

RESULTS

Age and left ventricular ejection fraction were associated with SBP. Aortic forward flow, body surface area and left ventricular mass index were associated with DBP. When applied to the validation cohort, the correlation coefficient between CMR-derived SBP and brachial SBP was (r=0.16, 95% CI 0.011 to 0.305, p=0.03), and CMR-derived DBP and brachial DBP was (r=0.27, 95% CI 0.122 to 0.403, p=0.0004). The area under the curve (AUC) for CMR-derived SBP to predict SBP>120 mmHg was 0.59, p=0.038. Moreover, CMR-derived DBP to predict DBP>80 mmHg had an AUC of 0.64, p=0.002.

CONCLUSION

CMR-derived SBP and DBP models can estimate brachial SBP and DBP. Such models may allow efficient prospective collection, as well as retrospective estimation of BP, which should be incorporated into assessments due to its critical effect on load-dependent parameters.

Anatomical characterization of pulmonary artery and implications to pulmonary artery pressure monitor implantation

In patients with heart failure, guideline directed medical therapy improves outcomes and requires close patient monitoring. Pulmonary artery pressure monitors permit remote assessment of cardiopulmonary haemodynamics and facilitate early intervention that has been shown to decrease heart failure hospitalization. Pressure sensors implanted in the pulmonary vasculature are stabilized through passive or active interaction with the anatomy and communicate with an external reader to relay invasively measured pressure by radiofrequency. A body mass index  > 35 kg/m2 and chest circumference > 165 cm prevent use due to poor communication. Pulmonary vasculature anatomy is variable between patients and the pulmonary artery size, angulation of vessels and depth of sensor location from the chest wall in heart failure patients who may be candidates for pressure sensors remains largely unexamined. The present study analyses the size, angulation, and depth of the pulmonary artery at the position of implantation of two pulmonary artery pressure sensors: the CardioMEMS sensor typically implanted in the left pulmonary artery and the Cordella sensor implanted in the right pulmonary artery. Thirty-four computed tomography pulmonary angiograms from patients with heart failure were analysed using the MIMICS software. Distance from the bifurcation of the pulmonary artery to the implant site was shorter for the right pulmonary artery (4.55 ± 0.64 cm vs. 7.4 ± 1.3 cm) and vessel diameter at the implant site was larger (17.15 ± 2.87 mm vs. 11.83 ± 2.30 mm). Link distance (length of the communication path between sensor and reader) was shorter for the left pulmonary artery (9.40 ± 1.43 mm vs. 12.54 ± 1.37 mm). Therefore, the detailed analysis of pulmonary arterial anatomy using computed tomography pulmonary angiograms may alter the choice of implant location to reduce the risk of sensor migration and improve readability by minimizing sensor-to-reader link distance.

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.

Pulmonary emphysema subtypes defined by unsupervised machine learning on CT scans

BACKGROUND

Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.

METHODS

New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction. Subtypes were compared with symptoms and physiology among 2949 participants in the population-based Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study and with prognosis among 6658 MESA participants. Associations with genome-wide single-nucleotide-polymorphisms were examined.

RESULTS

The algorithm discovered six reproducible (interlearner intraclass correlation coefficient, 0.91-1.00) CT emphysema subtypes. The most common subtype in SPIROMICS, the combined bronchitis-apical subtype, was associated with chronic bronchitis, accelerated lung function decline, hospitalisations, deaths, incident airflow limitation and a gene variant near DRD1, which is implicated in mucin hypersecretion (p=1.1 ×10-8). The second, the diffuse subtype was associated with lower weight, respiratory hospitalisations and deaths, and incident airflow limitation. The third was associated with age only. The fourth and fifth visually resembled combined pulmonary fibrosis emphysema and had distinct symptoms, physiology, prognosis and genetic associations. The sixth visually resembled vanishing lung syndrome.

CONCLUSION

Large-scale unsupervised machine learning on CT scans defined six reproducible, familiar CT emphysema subtypes that suggest paths to specific diagnosis and personalised therapies in COPD and pre-COPD.

Cardiac magnetic resonance left ventricular filling pressure is linked to symptoms, signs and prognosis in heart failure

AIMS

Left ventricular filling pressure (LVFP) can be estimated from cardiovascular magnetic resonance (CMR). We aimed to investigate whether CMR-derived LVFP is associated with signs, symptoms, and prognosis in patients with recently diagnosed heart failure (HF).

METHODS AND RESULTS

This study recruited 454 patients diagnosed with HF who underwent same-day CMR and clinical assessment between February 2018 and January 2020. CMR-derived LVFP was calculated, as previously, from long- and short-axis cines. CMR-derived LVFP association with symptoms and signs of HF was investigated. Patients were followed for median 2.9 years (interquartile range 1.5-3.6 years) for major adverse cardiovascular events (MACE), defined as the composite of cardiovascular death, HF hospitalization, non-fatal stroke, and non-fatal myocardial infarction. The mean age was 62 ± 13 years, 36% were female (n = 163), and 30% (n = 135) had raised LVFP. Forty-seven per cent of patients had an ejection fraction < 40% during CMR assessment. Patients with raised LVFP were more likely to have pleural effusions [hazard ratio (HR) 3.2, P = 0.003], orthopnoea (HR 2.0, P = 0.008), lower limb oedema (HR 1.7, P = 0.04), and breathlessness (HR 1.7, P = 0.01). Raised CMR-derived LVFP was associated with a four-fold risk of HF hospitalization (HR 4.0, P < 0.0001) and a three-fold risk of MACE (HR 3.1, P < 0.0001). In the multivariable model, raised CMR-derived LVFP was independently associated with HF hospitalization (adjusted HR 3.8, P = 0.0001) and MACE (adjusted HR 3.0, P = 0.0001).

CONCLUSIONS

Raised CMR-derived LVFP is strongly associated with symptoms and signs of HF. In addition, raised CMR-derived LVFP is independently associated with subsequent HF hospitalization and MACE.

Longitudinal Lung Function Assessment of Patients Hospitalized With COVID-19 Using 1H and 129Xe Lung MRI

BACKGROUND

Microvascular abnormalities and impaired gas transfer have been observed in patients with COVID-19. The progression of pulmonary changes in these patients remains unclear.

RESEARCH QUESTION

Do patients hospitalized with COVID-19 without evidence of architectural distortion on structural imaging exhibit longitudinal improvements in lung function measured by using 1H and 129Xe MRI between 6 and 52 weeks following hospitalization?

STUDY DESIGN AND METHODS

Patients who were hospitalized with COVID-19 pneumonia underwent a pulmonary 1H and 129Xe MRI protocol at 6, 12, 25, and 51 weeks following hospital admission in a prospective cohort study between November 2020 and February 2022. The imaging protocol was as follows: 1H ultra-short echo time, contrast-enhanced lung perfusion, 129Xe ventilation, 129Xe diffusion-weighted, and 129Xe spectroscopic imaging of gas exchange.

RESULTS

Nine patients were recruited (age 57 ± 14 [median ± interquartile range] years; six of nine patients were male). Patients underwent MRI at 6 (n = 9), 12 (n = 9), 25 (n = 6), and 51 (n = 8) weeks following hospital admission. Patients with signs of interstitial lung damage were excluded. At 6 weeks, patients exhibited impaired 129Xe gas transfer (RBC to membrane fraction), but lung microstructure was not increased (apparent diffusion coefficient and mean acinar airway dimensions). Minor ventilation abnormalities present in four patients were largely resolved in the 6- to 25-week period. At 12 weeks, all patients with lung perfusion data (n = 6) showed an increase in both pulmonary blood volume and flow compared with 6 weeks, although this was not statistically significant. At 12 weeks, significant improvements in 129Xe gas transfer were observed compared with 6-week examinations; however, 129Xe gas transfer remained abnormally low at weeks 12, 25, and 51.

INTERPRETATION

129Xe gas transfer was impaired up to 1 year following hospitalization in patients who were hospitalized with COVID-19 pneumonia, without evidence of architectural distortion on structural imaging, whereas lung ventilation was normal at 52 weeks.

Artificial Intelligence framework with traditional computer vision and deep learning approaches for optimal automatic segmentation of left ventricle with scar

Automatic segmentation of the cardiac left ventricle with scars remains a challenging and clinically significant task, as it is essential for patient diagnosis and treatment pathways. This study aimed to develop a novel framework and cost function to achieve optimal automatic segmentation of the left ventricle with scars using LGE-MRI images. To ensure the generalization of the framework, an unbiased validation protocol was established using out-of-distribution (OOD) internal and external validation cohorts, and intra-observation and inter-observer variability ground truths. The framework employs a combination of traditional computer vision techniques and deep learning, to achieve optimal segmentation results. The traditional approach uses multi-atlas techniques, active contours, and k-means methods, while the deep learning approach utilizes various deep learning techniques and networks. The study found that the traditional computer vision technique delivered more accurate results than deep learning, except in cases where there was breath misalignment error. The optimal solution of the framework achieved robust and generalized results with Dice scores of 82.8 ± 6.4% and 72.1 ± 4.6% in the internal and external OOD cohorts, respectively. The developed framework offers a high-performance solution for automatic segmentation of the left ventricle with scars using LGE-MRI. Unlike existing state-of-the-art approaches, it achieves unbiased results across different hospitals and vendors without the need for training or tuning in hospital cohorts. This framework offers a valuable tool for experts to accomplish the task of fully automatic segmentation of the left ventricle with scars based on a single-modality cardiac scan.

Pulmonary Artery Strain Predicts Prognosis in Pulmonary Arterial Hypertension

BACKGROUND

Current cardiac magnetic resonance (CMR) imaging in pulmonary arterial hypertension (PAH) focuses on measures of ventricular function and coupling.

OBJECTIVES

The purpose of this study was to evaluate pulmonary artery (PA) global longitudinal strain (GLS) as a prognostic marker in patients with PAH.

METHODS

The authors included 169 patients with PAH from the ASPIRE (Assessing the Spectrum of Pulmonary hypertension Identified at a REferral centre) and INITIATE (Integrated computatioNal modelIng of righT heart mechanIcs and blood flow dynAmics in congeniTal hEart disease) registries, and 82 normal controls with similar age and gender distributions. PA GLS was derived from CMR feature tracking. Right ventricular measurements including volumes, ejection fraction, and right ventricular GLS were also derived from CMR. Patients were followed up a median of 34 months with all-cause mortality as the primary endpoint. Other known risk scores were collected, including the REVEAL (Registry to Evaluate Early and Long-term Pulmonary Arterial Hypertension Disease Management) 2.0 and COMPERA (Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension) 2.0 scores.

RESULTS

Of 169 patients (mean age: 57 ± 15 years; 80% female), 45 (26.6%) died (median follow-up: 34 months). Mean PA GLS was 23% ± 6% in normal controls and 10% ± 5% in patients with PAH (P < 0.0001). Patients with PA GLS <9% had a higher risk of mortality than those with PA GLS ≥9% (P < 0.001), and this was an independent predictor of mortality in PAH on multivariable analysis after adjustment for known risk factors (HR: 2.93; P = 0.010). Finally, in patients with PAH, PA GLS provided incremental prognostic value over the REVEAL 2.0 (global chi-square; P = 0.001; C statistic comparison; P = 0.030) and COMPERA 2.0 (global chi-square; P = 0.001; C statistic comparison; P = 0.048).

CONCLUSIONS

PA GLS confers incremental prognostic utility over the established risk scores for identifying patients with PAH at higher risk of death, who may be targeted for closer monitoring and/or intensified therapy.

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.

Hyperpolarised xenon-129 diffusion-weighted magnetic resonance imaging for assessing lung microstructure in idiopathic pulmonary fibrosis

Background

Hyperpolarised 129-xenon (129Xe) magnetic resonance imaging (MRI) shows promise in monitoring the progression of idiopathic pulmonary fibrosis (IPF) due to the lack of ionising radiation and the ability to quantify functional impairment. Diffusion-weighted (DW)-MRI with hyperpolarised gases can provide information about lung microstructure. The aims were to compare 129Xe DW-MRI measurements with pulmonary function tests (PFTs), and to assess whether they can detect early signs of disease progression in patients with newly diagnosed IPF.

Methods

This is a prospective, single-centre, observational imaging study of patients presenting with IPF to Northern General Hospital (Sheffield, UK). Hyperpolarised 129Xe DW-MRI was performed at 1.5 T on a whole-body General Electric HDx scanner and PFTs were performed on the same day as the MRI scan.

Results

There was an increase in global 129Xe apparent diffusion coefficient (ADC) between the baseline and 12-month visits (mean 0.043 cm2·s-1, 95% CI 0.040-0.047 cm2·s-1 versus mean 0.045 cm2·s-1, 95% CI 0.040-0.049 cm2·s-1; p=0.044; n=20), with no significant change in PFTs over the same time period. There was also an increase in 129Xe ADC in the lower zone (p=0.027), and an increase in 129Xe mean acinar dimension in the lower zone (p=0.033) between the baseline and 12-month visits. 129Xe DW-MRI measurements correlated strongly with diffusing capacity of the lung for carbon monoxide (% predicted), transfer coefficient of the lung for carbon monoxide (KCO) and KCO (% predicted).

Conclusions

129Xe DW-MRI measurements appear to be sensitive to early changes of microstructural disease that are consistent with progression in IPF at 12 months. As new drug treatments are developed, the ability to quantify subtle changes using 129Xe DW-MRI could be particularly valuable.

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.

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.

Mitral regurgitation quantification by cardiac magnetic resonance imaging (MRI) remains reproducible between software solutions

Background: The reproducibility of mitral regurgitation (MR) quantification by cardiovascular magnetic resonance (CMR) imaging using different software solutions remains unclear. This research aimed to investigate the reproducibility of MR quantification between two software solutions: MASS (version 2019 EXP, LUMC, Netherlands) and CAAS (version 5.2, Pie Medical Imaging). Methods: CMR data of 35 patients with MR (12 primary MR, 13 mitral valve repair/replacement, and ten secondary MR) was used. Four methods of MR volume quantification were studied, including two 4D-flow CMR methods (MR MVAV and MR Jet) and two non-4D-flow techniques (MR Standard and MR LVRV). We conducted within-software and inter-software correlation and agreement analyses. Results: All methods demonstrated significant correlation between the two software solutions: MR Standard (r=0.92, p<0.001), MR LVRV (r=0.95, p<0.001), MR Jet (r=0.86, p<0.001), and MR MVAV (r=0.91, p<0.001). Between CAAS and MASS, MR Jet and MR MVAV, compared to each of the four methods, were the only methods not to be associated with significant bias. Conclusions: We conclude that 4D-flow CMR methods demonstrate equivalent reproducibility to non-4D-flow methods but greater levels of agreement between software solutions.

Non-invasive detection of severe PH in lung disease using magnetic resonance imaging

Introduction

Severe pulmonary hypertension (mean pulmonary artery pressure ≥35 mmHg) in chronic lung disease (PH-CLD) is associated with high mortality and morbidity. Data suggesting potential response to vasodilator therapy in patients with PH-CLD is emerging. The current diagnostic strategy utilises transthoracic Echocardiography (TTE), which can be technically challenging in some patients with advanced CLD. The aim of this study was to evaluate the diagnostic role of MRI models to diagnose severe PH in CLD.

Methods

167 patients with CLD referred for suspected PH who underwent baseline cardiac MRI, pulmonary function tests and right heart catheterisation were identified. In a derivation cohort (n = 67) a bi-logistic regression model was developed to identify severe PH and compared to a previously published multiparameter model (Whitfield model), which is based on interventricular septal angle, ventricular mass index and diastolic pulmonary artery area. The model was evaluated in a test cohort.

Results

The CLD-PH MRI model [= (-13.104) + (13.059 * VMI)-(0.237 * PA RAC) + (0.083 * Systolic Septal Angle)], had high accuracy in the test cohort (area under the ROC curve (0.91) (p < 0.0001), sensitivity 92.3%, specificity 70.2%, PPV 77.4%, and NPV 89.2%. The Whitfield model also had high accuracy in the test cohort (area under the ROC curve (0.92) (p < 0.0001), sensitivity 80.8%, specificity 87.2%, PPV 87.5%, and NPV 80.4%.

Conclusion

The CLD-PH MRI model and Whitfield model have high accuracy to detect severe PH in CLD, and have strong prognostic value.

Uncertainty Estimation for Heatmap-Based Landmark Localization

Automatic anatomical landmark localization has made great strides by leveraging deep learning methods in recent years. The ability to quantify the uncertainty of these predictions is a vital component needed for these methods to be adopted in clinical settings, where it is imperative that erroneous predictions are caught and corrected. We propose Quantile Binning, a data-driven method to categorize predictions by uncertainty with estimated error bounds. Our framework can be applied to any continuous uncertainty measure, allowing straightforward identification of the best subset of predictions with accompanying estimated error bounds. We facilitate easy comparison between uncertainty measures by constructing two evaluation metrics derived from Quantile Binning. We compare and contrast three epistemic uncertainty measures (two baselines, and a proposed method combining aspects of the two), derived from two heatmap-based landmark localization model paradigms (U-Net and patch-based). We show results across three datasets, including a publicly available Cephalometric dataset. We illustrate how filtering out gross mispredictions caught in our Quantile Bins significantly improves the proportion of predictions under an acceptable error threshold. Finally, we demonstrate that Quantile Binning remains effective on landmarks with high aleatoric uncertainty caused by inherent landmark ambiguity, and offer recommendations on which uncertainty measure to use and how to use it. The code and data are available at https://github.com/schobs/qbin.

A transparent artificial intelligence framework to assess lung disease in pulmonary hypertension

Recent studies have recognized the importance of characterizing the extent of lung disease in pulmonary hypertension patients by using Computed Tomography. The trustworthiness of an artificial intelligence system is linked with the depth of the evaluation in functional, operational, usability, safety and validation dimensions. The safety and validation of an artificial tool is linked to the uncertainty estimation of the model's prediction. On the other hand, the functionality, operation and usability can be achieved by explainable deep learning approaches which can verify the learning patterns and use of the network from a generalized point of view. We developed an artificial intelligence framework to map the 3D anatomical models of patients with lung disease in pulmonary hypertension. To verify the trustworthiness of the framework we studied the uncertainty estimation of the network's prediction, and we explained the learning patterns of the network. Therefore, a new generalized technique combining local explainable and interpretable dimensionality reduction approaches (PCA-GradCam, PCA-Shape) was developed. Our open-source software framework was evaluated in unbiased validation datasets achieving accurate, robust and generalized results.

How should studies using AI be reported? lessons from a systematic review in cardiac MRI

Recent years have seen a dramatic increase in studies presenting artificial intelligence (AI) tools for cardiac imaging. Amongst these are AI tools that undertake segmentation of structures on cardiac MRI (CMR), an essential step in obtaining clinically relevant functional information. The quality of reporting of these studies carries significant implications for advancement of the field and the translation of AI tools to clinical practice. We recently undertook a systematic review to evaluate the quality of reporting of studies presenting automated approaches to segmentation in cardiac MRI (Alabed et al. 2022 Quality of reporting in AI cardiac MRI segmentation studies-a systematic review and recommendations for future studies. Frontiers in Cardiovascular Medicine 9:956811). 209 studies were assessed for compliance with the Checklist for AI in Medical Imaging (CLAIM), a framework for reporting. We found variable-and sometimes poor-quality of reporting and identified significant and frequently missing information in publications. Compliance with CLAIM was high for descriptions of models (100%, IQR 80%-100%), but lower than expected for descriptions of study design (71%, IQR 63-86%), datasets used in training and testing (63%, IQR 50%-67%) and model performance (60%, IQR 50%-70%). Here, we present a summary of our key findings, aimed at general readers who may not be experts in AI, and use them as a framework to discuss the factors determining quality of reporting, making recommendations for improving the reporting of research in this field. We aim to assist researchers in presenting their work and readers in their appraisal of evidence. Finally, we emphasise the need for close scrutiny of studies presenting AI tools, even in the face of the excitement surrounding AI in cardiac imaging.

The Importance of Mitral Valve Prolapse Doming Volume in the Assessment of Left Ventricular Stroke Volume with Cardiac MRI

There remains a debate whether the ventricular volume within prolapsing mitral valve (MV) leaflets should be included in the left ventricular (LV) end-systolic volume, and therefore factored in LV stroke volume (SV), in cardiac magnetic resonance (CMR) assessments. This study aims to compare LV volumes during end-systolic phases, with and without the inclusion of the volume of blood on the left atrial aspect of the atrioventricular groove but still within the MV prolapsing leaflets, against the reference LV SV by four-dimensional flow (4DF). A total of 15 patients with MV prolapse (MVP) were retrospectively enrolled in this study. We compared LV SV with (LV SV_MVP) and without (LV SV_standard) MVP left ventricular doming volume, using 4D flow (LV SV_4DF) as the reference value. Significant differences were observed when comparing LV SV_standard and LV SV_MVP (p < 0.001), and between LV SV_standard and LV SV_4DF (p = 0.02). The Intraclass Correlation Coefficient (ICC) test demonstrated good repeatability between LV SV_MVP and LV SV_4DF (ICC = 0.86, p < 0.001) but only moderate repeatability between LV SV_standard and LV SV_4DF (ICC = 0.75, p < 0.01). Calculating LV SV by including the MVP left ventricular doming volume has a higher consistency with LV SV derived from the 4DF assessment. In conclusion, LV SV short-axis cine assessment incorporating MVP dooming volume can significantly improve the precision of LV SV assessment compared to the reference 4DF method. Hence, in cases with bi-leaflet MVP, we recommend factoring in MVP dooming into the left ventricular end-systolic volume to improve the accuracy and precision of quantifying mitral regurgitation.

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.

Semi-automatic thresholding of RV trabeculation improves repeatability and diagnostic value in suspected pulmonary hypertension

Objectives

Right ventricle (RV) mass is an imaging biomarker of mean pulmonary artery pressure (MPAP) and pulmonary vascular resistance (PVR). Some methods of RV mass measurement on cardiac MRI (CMR) exclude RV trabeculation. This study assessed the reproducibility of measurement methods and evaluated whether the inclusion of trabeculation in RV mass affects diagnostic accuracy in suspected pulmonary hypertension (PH).

Materials and methods

Two populations were enrolled prospectively. (i) A total of 144 patients with suspected PH who underwent CMR followed by right heart catheterization (RHC). Total RV mass (including trabeculation) and compacted RV mass (excluding trabeculation) were measured on the end-diastolic CMR images using both semi-automated pixel-intensity-based thresholding and manual contouring techniques. (ii) A total of 15 healthy volunteers and 15 patients with known PH. Interobserver agreement and scan-scan reproducibility were evaluated for RV mass measurements using the semi-automated thresholding and manual contouring techniques.

Results

Total RV mass correlated more strongly with MPAP and PVR (r = 0.59 and 0.63) than compacted RV mass (r = 0.25 and 0.38). Using a diagnostic threshold of MPAP ≥ 25 mmHg, ROC analysis showed better performance for total RV mass (AUC 0.77 and 0.81) compared to compacted RV mass (AUC 0.61 and 0.66) when both parameters were indexed for LV mass. Semi-automated thresholding was twice as fast as manual contouring (p < 0.001).

Conclusion

Using a semi-automated thresholding technique, inclusion of trabecular mass and indexing RV mass for LV mass (ventricular mass index), improves the diagnostic accuracy of CMR measurements in suspected PH.

Image Phenotyping of Preterm-Born Children Using Hyperpolarized 129Xe Lung Magnetic Resonance Imaging and Multiple-Breath Washout

Rationale: Preterm birth is associated with low lung function in childhood, but little is known about the lung microstructure in childhood. Objectives: We assessed the differential associations between the historical diagnosis of bronchopulmonary dysplasia (BPD) and current lung function phenotypes on lung ventilation and microstructure in preterm-born children using hyperpolarized 129Xe ventilation and diffusion-weighted magnetic resonance imaging (MRI) and multiple-breath washout (MBW). Methods: Data were available from 63 children (aged 9-13 yr), including 44 born preterm (⩽34 weeks' gestation) and 19 term-born control subjects (⩾37 weeks' gestation). Preterm-born children were classified, using spirometry, as prematurity-associated obstructive lung disease (POLD; FEV1 < lower limit of normal [LLN] and FEV1/FVC < LLN), prematurity-associated preserved ratio of impaired spirometry (FEV1 < LLN and FEV1/FVC ⩾ LLN), preterm-(FEV1 ⩾ LLN) and term-born control subjects, and those with and without BPD. Ventilation heterogeneity metrics were derived from 129Xe ventilation MRI and SF6 MBW. Alveolar microstructural dimensions were derived from 129Xe diffusion-weighted MRI. Measurements and Main Results: 129Xe ventilation defect percentage and ventilation heterogeneity index were significantly increased in preterm-born children with POLD. In contrast, mean 129Xe apparent diffusion coefficient, 129Xe apparent diffusion coefficient interquartile range, and 129Xe mean alveolar dimension interquartile range were significantly increased in preterm-born children with BPD, suggesting changes of alveolar dimensions. MBW metrics were all significantly increased in the POLD group compared with preterm- and term-born control subjects. Linear regression confirmed the differential effects of obstructive disease on ventilation defects and BPD on lung microstructure. Conclusion: We show that ventilation abnormalities are associated with POLD, and BPD in infancy is associated with abnormal lung microstructure.

First Genotype-Phenotype Study in TBX4 Syndrome: Gain-of-Function Mutations Causative for Lung Disease

Rationale: Despite the increased recognition of TBX4 (T-BOX transcription factor 4)-associated pulmonary arterial hypertension (PAH), genotype-phenotype associations are lacking and may provide important insights. Objectives: To compile and functionally characterize all TBX4 variants reported to date and undertake a comprehensive genotype-phenotype analysis. Methods: We assembled a multicenter cohort of 137 patients harboring monoallelic TBX4 variants and assessed the pathogenicity of missense variation (n = 42) using a novel luciferase reporter assay containing T-BOX binding motifs. We sought genotype-phenotype correlations and undertook a comparative analysis with patients with PAH with BMPR2 (Bone Morphogenetic Protein Receptor type 2) causal variants (n = 162) or no identified variants in PAH-associated genes (n = 741) genotyped via the National Institute for Health Research BioResource-Rare Diseases. Measurements and Main Results: Functional assessment of TBX4 missense variants led to the novel finding of gain-of-function effects associated with older age at diagnosis of lung disease compared with loss-of-function effects (P = 0.038). Variants located in the T-BOX and nuclear localization domains were associated with earlier presentation (P = 0.005) and increased incidence of interstitial lung disease (P = 0.003). Event-free survival (death or transplantation) was shorter in the T-BOX group (P = 0.022), although age had a significant effect in the hazard model (P = 0.0461). Carriers of TBX4 variants were diagnosed at a younger age (P < 0.001) and had worse baseline lung function (FEV1, FVC) (P = 0.009) than the BMPR2 and no identified causal variant groups. Conclusions: We demonstrated that TBX4 syndrome is not strictly the result of haploinsufficiency but can also be caused by gain of function. The pleiotropic effects of TBX4 in lung disease may be in part explained by the differential effect of pathogenic mutations located in critical protein domains.

The reproducibility of manual RV/LV ratio measurement on CT pulmonary angiography

Objectives

Right ventricular (RV) dysfunction carries elevated risk in acute pulmonary embolism (PE). An increased ratio between the size of the right and left ventricles (RV/LV ratio) is a biomarker of RV dysfunction. This study evaluated the reproducibility of RV/LV ratio measurement on CT pulmonary angiography (CTPA).

Methods

20 inpatient CTPA scans performed to assess for acute PE were retrospectively identified from a tertiary UK centre. Each scan was evaluated by 14 radiologists who provided a qualitative overall opinion on the presence of RV dysfunction and measured the RV/LV ratio. Using a threshold of 1.0, the RV/LV ratio measurements were classified as positive (≥1.0) or negative (<1.0) for RV dysfunction. Interobserver agreement was quantified using the Fleiss κ and intraclass correlation coefficient (ICC).

Results

Qualitative opinion of RV dysfunction showed weak agreement (κ = 0.42, 95% CI 0.37-0.46). The mean RV/LV ratio measurement for all cases was 1.28 ± 0.68 with significant variation between reporters (p < 0.001). Although agreement for RV/LV measurement was good (ICC = 0.83, 95% CI 0.73-0.91), categorisation of RV dysfunction according to RV/LV ratio measurements showed weak agreement (κ = 0.46, 95% CI 0.41-0.50).

Conclusion

Both qualitative opinion and quantitative manual RV/LV ratio measurement show poor agreement for identifying RV dysfunction on CTPA.

Advances in knowledge

Caution should be exerted if using manual RV/LV ratio measurements to inform clinical risk stratification and management decisions.

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.

Unconventional Pathways to Carbide Phase Synthesis via Thermal Decomposition of UI4(1,4-dioxane)2

UI₄(1,4-dioxane)₂ was subjected to laser-based heating─a method that enables localized, fast heating (T > 2000 °C) and rapid cooling under controlled conditions (scan rate, power, atmosphere, etc.)─to understand its thermal decomposition. A predictive computational thermodynamic technique estimated the decomposition temperature of UI₄(1,4-dioxane)₂ to uranium (U) metal to be 2236 °C, a temperature achievable under laser irradiation. Dictated by the presence of reactive, gaseous byproducts, the thermal decomposition of UI₄(1,4-dioxane)₂ under furnace conditions up to 600 °C revealed the formation of UO₂, UI_x, and U(C_1-xO_x)_y, while under laser irradiation, UI₄(1,4-dioxane)₂ decomposed to UO₂, U(C_1-xO_x)_y, UC_2-zO_z, and UC. Despite the fast dynamics associated with laser irradiation, the central uranium atom reacted with the thermal decomposition products of the ligand (1,4-dioxane = C₄H₈O₂) instead of producing pure U metal. The results highlight the potential to co-develop uranium precursors with specific irradiation procedures to advance nuclear materials research by finding new pathways to produce uranium carbide.

Phenotyping of idiopathic pulmonary arterial hypertension: a registry analysis

BACKGROUND

Among patients meeting diagnostic criteria for idiopathic pulmonary arterial hypertension (IPAH), there is an emerging lung phenotype characterised by a low diffusion capacity for carbon monoxide (DLCO) and a smoking history. The present study aimed at a detailed characterisation of these patients.

METHODS

We analysed data from two European pulmonary hypertension registries, COMPERA (launched in 2007) and ASPIRE (from 2001 onwards), to identify patients diagnosed with IPAH and a lung phenotype defined by a DLCO of less than 45% predicted and a smoking history. We compared patient characteristics, response to therapy, and survival of these patients to patients with classical IPAH (defined by the absence of cardiopulmonary comorbidities and a DLCO of 45% or more predicted) and patients with pulmonary hypertension due to lung disease (group 3 pulmonary hypertension).

FINDINGS

The analysis included 128 (COMPERA) and 185 (ASPIRE) patients with classical IPAH, 268 (COMPERA) and 139 (ASPIRE) patients with IPAH and a lung phenotype, and 910 (COMPERA) and 375 (ASPIRE) patients with pulmonary hypertension due to lung disease. Most patients with IPAH and a lung phenotype had normal or near normal spirometry, a severe reduction in DLCO, with the majority having no or a mild degree of parenchymal lung involvement on chest computed tomography. Patients with IPAH and a lung phenotype (median age, 72 years [IQR 65-78] in COMPERA and 71 years [65-76] in ASPIRE) and patients with group 3 pulmonary hypertension (median age 71 years [65-77] in COMPERA and 69 years [63-74] in ASPIRE) were older than those with classical IPAH (median age, 45 years [32-60] in COMPERA and 52 years [38-64] in ASPIRE; p<0·0001 for IPAH with a lung phenotype vs classical IPAH in both registries). While 99 (77%) patients in COMPERA and 133 (72%) patients in ASPIRE with classical IPAH were female, there was a lower proportion of female patients in the IPAH and a lung phenotype cohort (95 [35%] COMPERA; 75 [54%] ASPIRE), which was similar to group 3 pulmonary hypertension (336 [37%] COMPERA; 148 [39%] ASPIRE]). Response to pulmonary arterial hypertension therapies at first follow-up was available from COMPERA. Improvements in WHO functional class were observed in 54% of patients with classical IPAH, 26% of patients with IPAH with a lung phenotype, and 22% of patients with group 3 pulmonary hypertension (p<0·0001 for classical IPAH vs IPAH and a lung phenotype, and p=0·194 for IPAH and a lung phenotype vs group 3 pulmonary hypertension); median improvements in 6 min walking distance were 63 m, 25 m, and 23 m for these cohorts respectively (p=0·0015 for classical IPAH vs IPAH and a lung phenotype, and p=0·64 for IPAH and a lung phenotype vs group 3 pulmonary hypertension), and median reductions in N-terminal-pro-brain-natriuretic-peptide were 58%, 27%, and 16% respectively (p=0·0043 for classical IPAH vs IPAH and a lung phenotype, and p=0·14 for IPAH and a lung phenotype vs group 3 pulmonary hypertension). In both registries, survival of patients with IPAH and a lung phenotype (1 year, 89% in COMPERA and 79% in ASPIRE; 5 years, 31% in COMPERA and 21% in ASPIRE) and group 3 pulmonary hypertension (1 year, 78% in COMPERA and 64% in ASPIRE; 5 years, 26% in COMPERA and 18% in ASPIRE) was worse than survival of patients with classical IPAH (1 year, 95% in COMPERA and 98% in ASPIRE; 5 years, 84% in COMPERA and 80% in ASPIRE; p<0·0001 for IPAH with a lung phenotype vs classical IPAH in both registries).

INTERPRETATION

A cohort of patients meeting diagnostic criteria for IPAH with a distinct, presumably smoking-related form of pulmonary hypertension accompanied by a low DLCO, resemble patients with pulmonary hypertension due to lung disease rather than classical IPAH. These observations have pathogenetic, diagnostic, and therapeutic implications, which require further exploration.

FUNDING

COMPERA is funded by unrestricted grants from Acceleron, Bayer, GlaxoSmithKline, Janssen, and OMT. The ASPIRE Registry is supported by Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK.

Validation of time-resolved, automated peak trans-mitral velocity tracking: Two center four-dimensional flow cardiovascular magnetic resonance study

OBJECTIVE

We aim to validate four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) peak velocity tracking methods for measuring the peak velocity of mitral inflow against Doppler echocardiography.

METHOD

Fifty patients were recruited who had 4D flow CMR and Doppler Echocardiography. After transvalvular flow segmentation using established valve tracking methods, peak velocity was automatically derived using three-dimensional streamlines of transvalvular flow. In addition, a static-planar method was used at the tip of mitral valve to mimic Doppler technique.

RESULTS

Peak E-wave mitral inflow velocity was comparable between TTE and the novel 4D flow automated dynamic method (0.9 ± 0.5 vs 0.94 ± 0.6 m/s; p = 0.29) however there was a statistically significant difference when compared with the static planar method (0.85 ± 0.5 m/s; p = 0.01). Median A-wave peak velocity was also comparable across TTE and the automated dynamic streamline (0.77 ± 0.4 vs 0.76 ± 0.4 m/s; p = 0.77). A significant difference was seen with the static planar method (0.68 ± 0.5 m/s; p = 0.04). E/A ratio was comparable between TTE and both the automated dynamic and static planar method (1.1 ± 0.7 vs 1.15 ± 0.5 m/s; p = 0.74 and 1.15 ± 0.5 m/s; p = 0.5 respectively). Both novel 4D flow methods showed good correlation with TTE for E-wave (dynamic method; r = 0.70; P < 0.001 and static-planar method; r = 0.67; P < 0.001) and A-wave velocity measurements (dynamic method; r = 0.83; P < 0.001 and static method; r = 0.71; P < 0.001). The automated dynamic method demonstrated excellent intra/inter-observer reproducibility for all parameters.

CONCLUSION

Automated dynamic peak velocity tracing method using 4D flow CMR is comparable to Doppler echocardiography for mitral inflow assessment and has excellent reproducibility for clinical use.

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.

Kat-ARC accelerated 4D flow CMR: clinical validation for transvalvular flow and peak velocity assessment

BACKGROUND

To validate the k-adaptive-t autocalibrating reconstruction for Cartesian sampling (kat-ARC), an exclusive sparse reconstruction technique for four-dimensional (4D) flow cardiac magnetic resonance (CMR) using conservation of mass principle applied to transvalvular flow.

METHODS

This observational retrospective study (2020/21-075) was approved by the local ethics committee at the University of East Anglia. Consent was waived. Thirty-five patients who had a clinical CMR scan were included. CMR protocol included cine and 4D flow using Kat-ARC acceleration factor 6. No respiratory navigation was applied. For validation, the agreement between mitral net flow (MNF) and the aortic net flow (ANF) was investigated. Additionally, we checked the agreement between peak aortic valve velocity derived by 4D flow and that derived by continuous-wave Doppler echocardiography in 20 patients.

RESULTS

The median age of our patient population was 63 years (interquartile range [IQR] 54-73), and 18/35 (51%) were male. Seventeen (49%) patients had mitral regurgitation, and seven (20%) patients had aortic regurgitation. Mean acquisition time was 8 ± 4 min. MNF and ANF were comparable: 60 mL (51-78) versus 63 mL (57-77), p = 0.310). There was an association between MNF and ANF (rho = 0.58, p < 0.001). Peak aortic valve velocity by Doppler and 4D flow were comparable (1.40 m/s, [1.30-1.75] versus 1.46 m/s [1.25-2.11], p = 0.602) and also correlated with each other (rho = 0.77, p < 0.001).

CONCLUSIONS

Kat-ARC accelerated 4D flow CMR quantified transvalvular flow in accordance with the conservation of mass principle and is primed for clinical translation.

The quality of reporting in cardiac MRI artificial intelligence segmentation studies - a systematic review

Funding Acknowledgements

Type of funding sources: Public Institution(s). Main funding source(s): This work was supported by an NIHR AI Award, AI_AWARD01706. This research was also funded in part, by the Wellcome Trust [Grant number 205188/Z/16/Z ].

Background

There has been a rapid increase in the number of Artificial Intelligence (AI) studies of cardiac MRI (CMR) segmentation. AI has huge potential to improve image analysis assessments. However, advancement and clinical translation in this field depend on researchers presenting their work in a transparent and reproducible manner.

Purpose

This systematic review aimed to evaluate the quality of reporting in AI studies involving CMR segmentation.

Methods

MEDLINE and EMBASE databases were searched for AI CMR segmentation studies on 18/11/2021. The flow of study inclusion is shown in Figure 1. Any AI method to segment any cardiac structure on CMR was eligible for inclusion. Each study was assessed for compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM).

Results

70 studies were included in the qualitative analysis. Studies were published between 2015 to 2021, with the majority (71%) published in 2020 and 2021. Most studies were performed in Europe (33%), China (27%) and the USA (26%). Short-axis sections were segmented in 70% of studies and most commonly included both ventricles (51%) or the left ventricle alone (30%). 20 different architecture implementations were represented. Figure 2 summarises the most relevant CLAIM domains to AI segmentation. The training sample eligibility criteria, demographics and clinical characteristics were not reported in 47% and 81% of studies, respectively. Ground truth annotations, source of the annotations and annotation tool were absent in 31%, 36% and 51% of studies respectively. Preprocessing steps and software libraries and packages used in training were not included in 27% and 24%. Details on the training approach including the number of models trained and method of selecting the final model were missing in 20% and 17% of the studies. Methods of validation or testing on external data, inter- and intra- rater variability and failure analysis were unreported in 57%, 63% and 74%, respectively.

Conclusion

This systematic review highlights important gaps in the AI literature of CMR studies. We identified key items missing in the dataset description, model development, validation and testing that limit the transparency, reproducibility and hence validity of published AI studies. This review may support closer adherence to established frameworks for reporting standards.

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.

Right ventricular remodelling in pulmonary arterial hypertension predicts treatment response

OBJECTIVES

To determine the prognostic value of patterns of right ventricular adaptation in patients with pulmonary arterial hypertension (PAH), assessed using cardiac magnetic resonance (CMR) imaging at baseline and follow-up.

METHODS

Patients attending the Sheffield Pulmonary Vascular Disease Unit with suspected pulmonary hypertension were recruited into the ASPIRE (Assessing the Spectrum of Pulmonary hypertension Identified at a REferral Centre) Registry. With exclusion of congenital heart disease, consecutive patients with PAH were followed up until the date of census or death. Right ventricular end-systolic volume index adjusted for age and sex and ventricular mass index were used to categorise patients into four different volume/mass groups: low-volume-low-mass, low-volume-high-mass, high-volume-low-mass and high-volume-high-mass. The prognostic value of the groups was assessed with one-way analysis of variance and Kaplan-Meier plots. Transition of the groups was studied.

RESULTS

A total of 505 patients with PAH were identified, 239 (47.3%) of whom have died at follow-up (median 4.85 years, IQR 4.05). The mean age of the patients was 59±16 and 161 (32.7%) were male. Low-volume-low-mass was associated with CMR and right heart catheterisation metrics predictive of improved prognosis. There were 124 patients who underwent follow-up CMR (median 1.11 years, IQR 0.78). At both baseline and follow-up, the high-volume-low-mass group had worse prognosis than the low-volume-low-mass group (p<0.001). With PAH therapy, 73.5% of low-volume-low-mass patients remained in this group, whereas only 17.4% of high-volume-low-mass patients transitioned into low-volume-low-mass.

CONCLUSIONS

Right ventricular adaptation assessed using CMR has prognostic value in patients with PAH. Patients with maladaptive remodelling (high-volume-low-mass) are at high risk of treatment failure.

Quality of reporting in AI cardiac MRI segmentation studies - A systematic review and recommendations for future studies

Background

There has been a rapid increase in the number of Artificial Intelligence (AI) studies of cardiac MRI (CMR) segmentation aiming to automate image analysis. However, advancement and clinical translation in this field depend on researchers presenting their work in a transparent and reproducible manner. This systematic review aimed to evaluate the quality of reporting in AI studies involving CMR segmentation.

Methods

MEDLINE and EMBASE were searched for AI CMR segmentation studies in April 2022. Any fully automated AI method for segmentation of cardiac chambers, myocardium or scar on CMR was considered for inclusion. For each study, compliance with the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) was assessed. The CLAIM criteria were grouped into study, dataset, model and performance description domains.

Results

209 studies published between 2012 and 2022 were included in the analysis. Studies were mainly published in technical journals (58%), with the majority (57%) published since 2019. Studies were from 37 different countries, with most from China (26%), the United States (18%) and the United Kingdom (11%). Short axis CMR images were most frequently used (70%), with the left ventricle the most commonly segmented cardiac structure (49%). Median compliance of studies with CLAIM was 67% (IQR 59-73%). Median compliance was highest for the model description domain (100%, IQR 80-100%) and lower for the study (71%, IQR 63-86%), dataset (63%, IQR 50-67%) and performance (60%, IQR 50-70%) description domains.

Conclusion

This systematic review highlights important gaps in the literature of CMR studies using AI. We identified key items missing-most strikingly poor description of patients included in the training and validation of AI models and inadequate model failure analysis-that limit the transparency, reproducibility and hence validity of published AI studies. This review may support closer adherence to established frameworks for reporting standards and presents recommendations for improving the quality of reporting in this field.

Systematic Review Registration

[www.crd.york.ac.uk/prospero/], identifier [CRD42022279214].

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.

Cardiovascular medication in patients with raised NT-proBNP, but no heart failure in the SHEAF registry

OBJECTIVES

We aim to assess the association of cardiovascular medications with outcomes of patients referred to the diagnostic heart failure (HF) clinic with symptoms or signs of possible HF, raised N-terminal pro-brain-type natriuretic peptide (NT-proBNP) but no evidence of HF on transthoracic echocardiography (TTE).

METHODS

Data were collected prospectively into the Sheffield HEArt Failure (SHEAF) registry between April 2012 and January 2020. The inclusion criteria were symptoms or signs suggestive of HF, NT-proBNP >400 pg/mL, but no evidence of HF on TTE. Cox proportional-hazards regression model was used to investigate the association between the survival time of patients and different cardiovascular medications. The outcome was defined as all-cause mortality.

RESULTS

From the SHEAF registry, we identified 1766 patients with raised NT-proBNP with no evidence of HF on TTE. Survival was higher among the younger patients, and among those with hypertension or atrial fibrillation (AF). Mortality was increased with male gender, valvular heart disease and chronic kidney disease. Using univariate Cox proportional-hazards regression, the only cardiac therapeutic agent independently associated with all-cause mortality was beta-blocker (HR 0.86; 95% CI: 0.77 to 0.97; p=0.02). The use of beta-blockers was significantly higher in patients with AF (63% vs 39%, p<0.01) and hypertension (51% vs 42%, p<0.01). However, using multivariate Cox proportional-hazards regression to adjust for all variables associated with mortality, the influence of beta-blockers became non-significant (HR 0.96; 95% CI: 0.85 to 1.1, p=0.49).

CONCLUSION

When all variables associated with mortality are considered, none of the cardiovascular agents are associated with the improved survival of patients with suspected HF, raised NT-proBNP but no HF on echocardiography.