Automated detection of left ventricle in arterial input function images for inline perfusion mapping using deep learning: A study of 15,000 patients

Purpose: Quantification of myocardial perfusion has the potential to improve the detection of regional and global flow reduction. Significant effort has been made to automate the workflow, where one essential step is the arterial input function (AIF) extraction. Failure to accurately identify the left ventricle (LV) prevents AIF estimation required for quantification, therefore high detection accuracy is required. This study presents a robust LV detection method using the convolutional neural network (CNN). Methods: CNN models were trained by assembling 25,027 scans (N = 12,984 patients) from three hospitals, seven scanners. Performance was evaluated using a hold‐out test set of 5721 scans (N = 2805 patients). Model inputs were a time series of AIF images (2D+T). Two variations were investigated: (1) two classes (2CS) for background and foreground (LV mask), and (2) three classes (3CS) for background, LV, and RV. The final model was deployed on MRI scanners using the Gadgetron reconstruction software framework. Results: Model loading on the MRI scanner took ~340 ms and applying the model took ~180 ms. The 3CS model successfully detected the LV in 99.98% of all test cases (1 failure out of 5721). The mean Dice ratio for 3CS was 0.87 ± 0.08 with 92.0% of all cases having Dice >0.75. The 2CS model gave a lower Dice ratio of 0.82 ± 0.22 (P .2) comparing automatically extracted AIF signals with signals from manually drawn contours. Conclusions: A CNN‐based solution to detect the LV blood pool from the arterial input function image series was developed, validated, and deployed. A high LV detection accuracy of 99.98% was achieved

Sex and Heart Failure with Preserved Ejection Fraction: From Pathophysiology to Clinical Studies

Heart failure with preserved ejection fraction (HFpEF) represents the most frequent form of heart failure in women, with almost two-fold higher prevalence than in men. Studies have revealed sex-specific HFpEF pathophysiology, and suggested the possibility of a sex-specific therapeutic approach in these patients. Some cardiovascular risk factors, such as arterial hypertension, obesity, diabetes mellitus, coronary artery disease, atrial fibrillation, and race, show specific features that might be responsible for the development of HFpEF in women. These risk factors are related to specific cardiovascular changes—left ventricular diastolic dysfunction and hypertrophy, ventricular–vascular coupling, and impaired functional capacity—that are related to specific cardiac phenotype and HFpEF development. However, there is no agreement regarding outcomes in women with HFpEF. For HFpEF, most studies have found higher hospitalization rates for women than for men. Mortality rates are usually not different. Pharmacological treatment in HFpEF is challenging, along with many unresolved issues and questions raised. Available data on medical therapy in patients with HFpEF show no difference in outcomes between the sexes. Further investigations are necessary to better understand the pathophysiology and mechanisms of HFpEF, as well as to improve and eventually develop sex-specific therapy for HFpEF

Imaging in population science: cardiovascular magnetic resonance in 100,000 participants of UK Biobank - rationale, challenges and approaches

PMCID: PMC3668194SEP was directly funded by the National Institute for Health Research Cardiovascular Biomedical Research Unit at Barts. SN acknowledges support from the Oxford NIHR Biomedical Research Centre and from the Oxford British Heart Foundation Centre of Research Excellence. SP and PL are funded by a BHF Senior Clinical Research fellowship. RC is supported by a BHF Research Chair and acknowledges the support of the Oxford BHF Centre for Research Excellence and the MRC and Wellcome Trust. PMM gratefully acknowledges training fellowships supporting his laboratory from the Wellcome Trust, GlaxoSmithKline and the Medical Research Council

Simultaneous 13N-Ammonia and gadolinium first-pass myocardial perfusion with quantitative hybrid PET-MR imaging: a phantom and clinical feasibility study

Background Positron emission tomography (PET) is the non-invasive reference standard for myocardial blood flow (MBF) quantification. Hybrid PET-MR allows simultaneous PET and cardiac magnetic resonance (CMR) acquisition under identical experimental and physiological conditions. This study aimed to determine feasibility of simultaneous 13N-Ammonia PET and dynamic contrast-enhanced CMR MBF quantification in phantoms and healthy volunteers. Methods Images were acquired using a 3T hybrid PET-MR scanner. Phantom study: MBF was simulated at different physiological perfusion rates and a protocol for simultaneous PET-MR perfusion imaging was developed. Volunteer study: five healthy volunteers underwent adenosine stress. 13N-Ammonia and gadolinium were administered simultaneously. PET list mode data was reconstructed using ordered subset expectation maximisation. CMR MBF was quantified using Fermi function-constrained deconvolution of arterial input function and myocardial signal. PET MBF was obtained using a one-tissue compartment model and image-derived input function. Results Phantom study: PET and CMR MBF measurements demonstrated high repeatability with intraclass coefficients 0.98 and 0.99, respectively. There was high correlation between PET and CMR MBF (r = 0.98, p < 0.001) and good agreement (bias − 0.85 mL/g/min; 95% limits of agreement 0.29 to − 1.98). Volunteer study: Mean global stress MBF for CMR and PET were 2.58 ± 0.11 and 2.60 ± 0.47 mL/g/min respectively. On a per territory basis, there was moderate correlation (r = 0.63, p = 0.03) and agreement (bias − 0.34 mL/g/min; 95% limits of agreement 0.49 to − 1.18). Conclusion Simultaneous MBF quantification using hybrid PET-MR imaging is feasible with high test repeatability and good to moderate agreement between PET and CMR. Future studies in coronary artery disease patients may allow cross-validation of techniques

Dobutamine stress cardiovascular magnetic resonance at 3 Tesla

<p>Abstract</p> <p>Purpose</p> <p>The assessment of inducible wall motion abnormalities during high-dose dobutamine-stress cardiovascular magnetic resonance (DCMR) is well established for the identification of myocardial ischemia at 1.5 Tesla. Its feasibility at higher field strengths has not been reported. The present study was performed to prospectively determine the feasibility and diagnostic accuracy of DCMR at 3 Tesla for depicting hemodynamically significant coronary artery stenosis (≥ 50% diameter stenosis) in patients with suspected or known coronary artery disease (CAD).</p> <p>Materials and methods</p> <p>Thirty consecutive patients (6 women) (66 ± 9.3 years) were scheduled for DCMR between January and May 2007 for detection of coronary artery disease. Patients were examined with a Philips Achieva 3 Tesla system (Philips Healthcare, Best, The Netherlands), using a spoiled gradient echo cine sequence. Technical parameters were: spatial resolution 2 × 2 × 8 mm³, 30 heart phases, spoiled gradient echo TR/TE: 4.5/2.6 msec, flip angle 15°. Images were acquired at rest and stress in accordance with a standardized high-dose dobutamine-atropine protocol during short breath-holds in three short and three long-axis views. Dobutamine was administered using a standard protocol (10 μg increments every 3 minutes up to 40 μg dobutamine/kg body weight/minute plus atropine if required to reach target heart rate). The study protocol included administration of 0.1 mmol/kg/body weight Gd-DTPA before the cine images at rest were acquired to improve the image quality. The examination was terminated if new or worsening wall-motion abnormalities or chest pain occurred or when > 85% of age-predicted maximum heart rate was reached. Myocardial ischemia was defined as new onset of wall-motion abnormality in at least one segment. In addition, late gadolinium enhancement (LGE) was performed. Images were evaluated by two blinded readers. Diagnostic accuracy was determined with coronary angiography as the reference standard. Image quality and wall-motion at rest and maximum stress level were evaluated using a four-point scale.</p> <p>Results</p> <p>In 27 patients DCMR was performed successfully, no patient had to be excluded due to insufficient image quality. Twenty-two patients were examined by coronary angiography, which depicted significant stenosis in 68.2% of the patients. Patient-based sensitivity and specificity were 80.0% and 85.7% respectively and accuracy was 81.8%. Interobserver variability for assessment of wall motion abnormalities was 88% (κ = 0.760; p < 0.0001). Negative and positive predictive values were 66.7% and 92.3%, respectively. No significant differences in average image quality at rest versus stress for short or long-axis cine images were found.</p> <p>Conclusion</p> <p>High-dose DCMR at 3T is feasible and an accurate method to depict significant coronary artery stenosis in patients with suspected or known CAD.</p

Performance of adenosine “stress-only” perfusion MRI in patients without a history of myocardial infarction: a clinical outcome study

To assess the diagnostic value of adenosine “stress-only” myocardial perfusion MR for ischemia detection as an indicator for coronary angiography in patients without a prior myocardial infarction and a necessity to exclude ischemia. Adenosine perfusion MRI was performed at 1.5 T in 139 patients with a suspicion of ischemia and no prior myocardial infarction. After 3 min of adenosine infusion a perfusion sequence was started. Patients with a perfusion defect were referred to coronary angiography (CAG). Patients with a normal perfusion were enrolled in follow-up. Fourteen out of 139 patients (10.1%) had a perfusion defect indicative of ischemia. These patients underwent a coronary angiogram, which showed complete agreement with the perfusion images. 125 patients with a normal myocardial perfusion entered follow-up (median 672 days, range 333–1287 days). In the first year of follow-up one Major Adverse Coronary Event (MACE) occurred and one patient had new onset chest pain with a confirmed coronary stenosis. Reaching a negative predictive value for MACE of 99.2% and for any coronary event of 98.4%. At 2 year follow-up no additional MACE occurred. Sensitivity of adenosine perfusion MR for MACE is 93.3% and specificity and positive predictive value are 100%. Adenosine myocardial perfusion MR for the detection of myocardial ischemia in a “stress-only” protocol in patients without prior myocardial infarctions, has a high diagnostic accuracy. This fast examination can play an important role in the evaluation of patients without prior myocardial infarctions and a necessity to exclude ischemia

A novel and practical screening tool for the detection of silent myocardial infarction in patients with type 2 diabetes

Silent myocardial infarction (MI) is a prevalent finding in patients with type 2 diabetes and is associated with significant mortality and morbidity. Late gadolinium enhancement (LGE) by cardiovascular magnetic resonance (CMR) is the most validated technique for detection of silent MI but is time consuming, costly and requires administration of intravenous contrast. We therefore planned to develop a simple and low cost population screening tool to identify those at highest risk of silent MI validated against the CMR reference standard.100 asymptomatic patients with type 2 diabetes underwent electrocardiogram (ECG), echocardiography, biomarker assessment and CMR at 3.0T including assessment of left ventricular ejection fraction and LGE. Global longitudinal strain (GLS) from 2 and 4 chamber cines was measured using feature tracking.17/100 patients with no history of cardiovascular disease had silent MI defined by LGE in an infarct pattern on CMR. Only 4 silent MI patients had Q waves on ECG. Patients with silent MI were older (65 vs 60, p=0.05), had lower E/A ratio (0.75 vs 0.89, p=0.004), lower GLS (-15.2% vs -17.7%, p=0.004) and higher NT-proBNP (106ng/L vs 52ng/L, p=0.003). A combined risk score derived from these 4 factors had an area under the receiver operating characteristic (ROC) curve of 0.823 (0.734-0.892), P<0.0001. A score of ?3/5 had 82% sensitivity and 72% specificity for silent MI.Using measures that can be derived in an outpatient clinic setting, we have developed a novel screening tool for the detection of silent MI in type 2 diabetes. The screening tool had significantly superior diagnostic accuracy than current ECG criteria for the detection of silent MI in asymptomatic patients

Mitral regurgitation quantification by cardiac magnetic resonance imaging (MRI) remains reproducible between software solutions [version 2; peer review: 1 approved]

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 (MRMVAV and MRJet) and two non-4D-flow techniques (MRStandard and MRLVRV). 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

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 (MRMVAV and MRJet) and two non-4D-flow techniques (MRStandard and MRLVRV). We conducted within-software and inter-software correlation and agreement analyses. Results: All methods demonstrated significant correlation between the two software solutions: MRStandard (r=0.92, p<0.001), MRLVRV (r=0.95, p<0.001), MRJet (r=0.86, p<0.001), and MRMVAV (r=0.91, p<0.001). Between CAAS and MASS, MRJet and MRMVAV, 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

Society for Cardiovascular Magnetic Resonance (SCMR) guidance for re-activation of cardiovascular magnetic resonance practice after peak phase of the COVID-19 pandemic

During the peak phase of the COVID-19 pandemic, alterations of standard operating procedures were necessary for health systems to protect patients and healthcare workers and ensure access to vital hospital resources. As the peak phase passes, re-activation plans are required to safely manage increasing clinical volumes. In the context of cardiovascular magnetic resonance (CMR), re-activation objectives include continued performance of urgent CMR studies and resumption of CMR in patients with semi-urgent and elective indications in an environment that is safe for both patients and health care workers