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In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed for volumetric analysis (via segmentation) of the left ventricle in real-time free-breathing CMR at rest and under exercise stress. Data from healthy volunteers (n = 15) for cine and real-time free-breathing CMR at rest and under exercise stress were analyzed retrospectively. Exercise stress was performed using an ergometer in the supine position. Segmentations of two deep learning methods, a commercially available technique (comDL) and an openly available network (nnU-Net), were compared to a reference model created via the manual correction of segmentations obtained with comDL. Segmentations of left ventricular endocardium (LV), left ventricular myocardium (MYO), and right ventricle (RV) are compared for both end-systolic and end-diastolic phases and analyzed with Dice’s coefficient. The volumetric analysis includes the cardiac function parameters LV end-diastolic volume (EDV), LV end-systolic volume (ESV), and LV ejection fraction (EF), evaluated with respect to both absolute and relative differences. For cine CMR, nnU-Net and comDL achieve Dice’s coefficients above 0.95 for LV and 0.9 for MYO, and RV. For real-time CMR, the accuracy of nnU-Net exceeds that of comDL overall. For real-time CMR at rest, nnU-Net achieves Dice’s coefficients of 0.94 for LV, 0.89 for MYO, and 0.90 for RV and the mean absolute differences between nnU-Net and the reference are 2.9 mL for EDV, 3.5 mL for ESV, and 2.6% for EF. For real-time CMR under exercise stress, nnU-Net achieves Dice’s coefficients of 0.92 for LV, 0.85 for MYO, and 0.83 for RV and the mean absolute differences between nnU-Net and reference are 11.4 mL for EDV, 2.9 mL for ESV, and 3.6% for EF. Deep learning methods designed or trained for cine CMR segmentation can perform well on real-time CMR. For real-time free-breathing CMR at rest, the performance of deep learning methods is comparable to inter-observer variability in cine CMR and is usable for fully automatic segmentation. For real-time CMR under exercise stress, the performance of nnU-Net could promise a higher degree of automation in the future.

Cardiovascular magnetic resonance (CMR) imaging provides reliable assessments of biventricular morphology and function. Since manual post-processing is time-consuming and prone to observer variability, efforts have been directed towards novel artificial intelligence-based fully automated analyses. Hence, we sought to investigate the impact of artificial intelligence-based fully automated assessments on the inter-study variability of biventricular volumes and function. Eighteen participants (11 with normal, 3 with heart failure and preserved and 4 with reduced ejection fraction (EF)) underwent serial CMR imaging at in median 63 days (range 49–87) interval. Short axis cine stacks were acquired for the evaluation of left ventricular (LV) mass, LV and right ventricular (RV) end-diastolic, end-systolic and stroke volumes as well as EF. Assessments were performed manually (QMass, Medis Medical Imaging Systems, Leiden, Netherlands) by an experienced (3 years) and inexperienced reader (no active reporting, 45 min of training with five cases from the SCMR consensus data) as well as fully automated (suiteHEART, Neosoft, Pewaukee, WI, USA) without any manual corrections. Inter-study reproducibility was overall excellent with respect to LV volumetric indices, best for the experienced observer (intraclass correlation coefficient (ICC) > 0.98, coefficient of variation (CoV, < 9.6%) closely followed by automated analyses (ICC > 0.93, CoV < 12.4%) and lowest for the inexperienced observer (ICC > 0.86, CoV < 18.8%). Inter-study reproducibility of RV volumes was excellent for the experienced observer (ICC > 0.88, CoV < 10.7%) but considerably lower for automated and inexperienced manual analyses (ICC > 0.69 and > 0.46, CoV < 22.8% and < 28.7% respectively). In this cohort, fully automated analyses allowed reliable serial investigations of LV volumes with comparable inter-study reproducibility to manual analyses performed by an experienced CMR observer. In contrast, RV automated quantification with current algorithms still relied on manual post-processing for reliability.

Background Cardiovascular Magnetic Resonance myocardial feature tracking (CMR-FT) is a quantitative technique tracking tissue voxel motion on standard steady-state free precession (SSFP) cine images to assess ventricular myocardial deformation. The importance of left atrial (LA) deformation assessment is increasingly recognized and can be assessed with echocardiographic speckle tracking. However atrial deformation quantification has never previously been demonstrated with CMR. We sought to determine the feasibility and reproducibility of CMR-FT for quantitative derivation of LA strain and strain rate (SR) myocardial mechanics. Methods 10 healthy volunteers, 10 patients with hypertrophic cardiomyopathy (HCM) and 10 patients with heart failure and preserved ejection fraction (HFpEF) were studied at 1.5 Tesla. LA longitudinal strain and SR parameters were derived from SSFP cine images using dedicated CMR-FT software (2D CPA MR, TomTec, Germany). LA performance was analyzed using 4- and 2-chamber views including LA reservoir function (total strain [ε s ], peak positive SR [SRs]), LA conduit function (passive strain [ε e ], peak early negative SR [SRe]) and LA booster pump function (active strain [ε a ], late peak negative SR [SRa]). Results In all subjects LA strain and SR parameters could be derived from SSFP images. There was impaired LA reservoir function in HCM and HFpEF (ε s [%]: HCM 22.1 ± 5.5, HFpEF 16.3 ± 5.8, Controls 29.1 ± 5.3, p < 0.01; SRs [s -1 ]: HCM 0.9 ± 0.2, HFpEF 0.8 ± 0.3, Controls 1.1 ± 0.2, p < 0.05) and impaired LA conduit function as compared to healthy controls (ε e [%]: HCM 10.4 ± 3.9, HFpEF 11.9 ± 4.0, Controls 21.3 ± 5.1, p < 0.001; SRe [s -1 ]: HCM -0.5 ± 0.2, HFpEF -0.6 ± 0.1, Controls -1.0 ± 0.3, p < 0.01). LA booster pump function was increased in HCM while decreased in HFpEF (ε a [%]: HCM 11.7 ± 4.0, HFpEF 4.5 ± 2.9, Controls 7.8 ± 2.5, p < 0.01; SRa [s -1 ]: HCM -1.2 ± 0.4, HFpEF -0.5 ± 0.2, Controls -0.9 ± 0.3, p < 0.01). Observer variability was excellent for all strain and SR parameters on an intra- and inter-observer level as determined by Bland-Altman, coefficient of variation and intraclass correlation coefficient analyses. Conclusions CMR-FT based atrial performance analysis reliably quantifies LA longitudinal strain and SR from standard SSFP cine images and discriminates between patients with impaired left ventricular relaxation and healthy controls. CMR-FT derived atrial deformation quantification seems a promising novel approach for the study of atrial performance and physiology in health and disease states.

Background This study develops a model-based myocardial T1 mapping technique with sparsity constraints which employs a single-shot inversion-recovery (IR) radial fast low angle shot (FLASH) cardiovascular magnetic resonance (CMR) acquisition. The method should offer high resolution, accuracy, precision and reproducibility. Methods The proposed reconstruction estimates myocardial parameter maps directly from undersampled k-space which is continuously measured by IR radial FLASH with a 4 s breathhold and retrospectively sorted based on a cardiac trigger signal. Joint sparsity constraints are imposed on the parameter maps to further improve T1 precision. Validations involved studies of an experimental phantom and 8 healthy adult subjects. Results In comparison to an IR spin-echo reference method, phantom experiments with T1 values ranging from 300 to 1500 ms revealed good accuracy and precision at simulated heart rates between 40 and 100 bpm. In vivo T1 maps achieved better precision and qualitatively better preservation of image features for the proposed method than a real-time CMR approach followed by pixelwise fitting. Apart from good inter-observer reproducibility (0.6% of the mean), in vivo results confirmed good intra-subject reproducibility (1.05% of the mean for intra-scan and 1.17, 1.51% of the means for the two inter-scans, respectively) of the proposed method. Conclusion Model-based reconstructions with sparsity constraints allow for single-shot myocardial T1 maps with high spatial resolution, accuracy, precision and reproducibility within a 4 s breathhold. Clinical trials are warranted.

Since cardiovascular magnetic resonance feature-tracking (CMR-FT) has been demonstrated to be of incremental clinical merit we investigated the interchangeability of global left and right ventricular strain parameters between different CMR-FT software solutions. CMR-cine images of 10 patients without significant reduction in LVEF and RVEF and 10 patients with a significantly impaired systolic function were analyzed using two different types of FT-software (TomTec, Germany; QStrain, Netherlands). Global longitudinal strains (LV GLS, RV GLS), global left ventricular circumferential (GCS) and radial strains (GRS) were assessed. Differences in intra- and inter-observer variability within and between software types based on single and up to three repeated and subsequently averaged measurements were evaluated. Inter-vendor agreement was highest for GCS followed by LV GLS. GRS and RV GLS showed lower inter-vendor agreement. Variability was consistently higher in healthy volunteers as compared to the patient group. Intra-vendor reproducibility was excellent for GCS, LV GLS and RV GLS, but lower for GRS. The impact of repeated measurements was most pronounced for GRS and RV GLS on an intra-vendor level. Cardiac pathology has no influence on CMR-FT reproducibility. LV GLS and GCS qualify as the most robust parameters within and between individual software types. Since both parameters can be interchangeably assessed with different software solutions they may enter the clinical arena for optimized diagnostic and prognostic evaluation of cardiovascular morbidity and mortality in various pathologies.

BackgroundPrognosis in acute myocardial infarction (AMI) depends on the amount of infarct-related artery (IRA)-subtended myocardium and associated damage but has not been described in great detail. Consequently, we sought to describe IRA-associated pathophysiological consequences using cardiac magnetic resonance (CMR).Methods1235 AMI patients (n = 795 ST-elevation (STEMI) and 440 non-STEMI) underwent CMR following percutaneous coronary intervention. Blinded core-laboratory data were compared according to left anterior descending (LAD), left circumflex (LCx) and right coronary artery (RCA) regarding major adverse clinical events (MACE) within 12 months. Left ventricular (LV) global longitudinal/circumferential/radial (GLS/GCS/GRS) as well as left atrial (LA) total (εs), passive (εe) and active (εa) strains were determined using CMR-feature tracking. Tissue characterisation included infarct size (IS) and microvascular obstruction.ResultsLAD and LCx were associated with higher mortality compared to RCA lesions (4.6% and 4.4% vs 1.6%). LAD lesions showed largest IS (16.8%), largest ventricular [LV ejection fraction (EF) 47.4%, GLS − 13.2%, GCS − 20.8%] and atrial (εs 20.2%) impairment. There was less impairment in LCx (IS 11.8%, LVEF 50.8%, GLS − 17.4%, GCS − 25.0%, εs 20.7%) followed by RCA lesions (IS 11.3%, LVEF 50.8%, GLS − 19.1%, GCS − 26.6%, εs 21.7%). In AUC analyses, εs (LAD, RCA) and GLS (LCx) best predicted MACE (AUC > 0.69). Multivariate analyses identified εs (p = 0.017) in LAD and GLS (p = 0.034) in LCx infarcts as independent predictors of MACE.ConclusionsCMR allows IRA-specific phenotyping and characterisation of morphologic and functional changes. These alterations carry infarct-specific prognostic implications, and may represent novel diagnostic and therapeutic targets following AMI.Trial registrationClinicalTrials.gov: NCT00712101 and NCT01612312Graphic abstract

Absorption-based clinical computed tomography (CT) is the current imaging method of choice in the diagnosis of lung diseases. Many pulmonary diseases are affecting microscopic structures of the lung, such as terminal bronchi, alveolar spaces, sublobular blood vessels or the pulmonary interstitial tissue. As spatial resolution in CT is limited by the clinically acceptable applied X-ray dose, a comprehensive diagnosis of conditions such as interstitial lung disease, idiopathic pulmonary fibrosis or the characterization of small pulmonary nodules is limited and may require additional validation by invasive lung biopsies. Propagation-based imaging (PBI) is a phase sensitive X-ray imaging technique capable of reaching high spatial resolutions at relatively low applied radiation dose levels. In this publication, we present technical refinements of PBI for the characterization of different artificial lung pathologies, mimicking clinically relevant patterns in ventilated fresh porcine lungs in a human-scale chest phantom. The combination of a very large propagation distance of 10.7 m and a photon counting detector with 100 μ m pixel size enabled high resolution PBI CT with significantly improved dose efficiency, measured by thermoluminescence detectors. Image quality was directly compared with state-of-the-art clinical CT. PBI with increased propagation distance was found to provide improved image quality at the same or even lower X-ray dose levels than clinical CT. By combining PBI with iodine k-edge subtraction imaging we further demonstrate that, the high quality of the calculated iodine concentration maps might be a potential tool for the analysis of lung perfusion in great detail. Our results indicate PBI to be of great value for accurate diagnosis of lung disease in patients as it allows to depict pathological lesions non-invasively at high resolution in 3D. This will especially benefit patients at high risk of complications from invasive lung biopsies such as in the setting of suspected idiopathic pulmonary fibrosis (IPF).

PurposeTo assess the esophagogastric junction (EGJ) on real-time MRI and compare imaging parameters to EGJ morphology on high-resolution manometry (HRM).MethodsA total of 105 of 117 eligible patients who underwent real-time MRI and high-resolution manometry for GERD-like symptoms between 2015 and 2018 at a single center were retrospectively evaluated (male n = 57; female n = 48; mean age 52.5 ± 15.4 years). Real-time MRI was performed at a median investigation time of 15 min (1 frame/40 ms). On HRM, EGJ morphology was assessed according to the Chicago classification of esophageal motility disorders. Real-time MRI was performed at 3 T using highly undersampled radial fast low-angle shot acquisitions with NLINV image reconstruction. A 10 mL pineapple juice bolus served as oral contrast agent at supine position. Real-time MRI films of the EGJ were acquired during swallowing events and during Valsalva maneuver. Anatomic and functional MRI parameters were compared to EGJ morphology on HRM.ResultsOn HRM, n = 42 patients presented with EGJ type I (40.0%), n = 33 with EGJ type II (31.4%), and n = 30 with EGJ type III (28.6%). On real-time MRI, hiatal hernia was more common in patients with EGJ type III (66.7%) than in patients with EGJ type I (26.2%) and EGJ type II (30.3%; p < 0.001). Sliding hiatal hernia was more frequent in patients with EGJ type II (33.3%) than in patients with EGJ type III (16.7%) and EGJ type I (7.1%; p = 0.017). The mean esophagus–fundus angle of patients was 85 ± 31° at rest and increased to 101 ± 36° during Valsalva maneuver.ConclusionReal-time MRI is a non-invasive imaging method for assessment of the esophagogastric junction. Real-time MRI can visualize dynamic changes of the EGJ during swallowing events.

To assess epidemiology, clinical presentation, treatment and overall survival of adult patients with renal sarcomas, the 2004–2016 SEER and NCDB databases were queried for adult patients diagnosed with renal sarcoma, calculating average annual age-adjusted incidence rates (AAIR) and average annual percentage change (AAPC) as well as overall survival (OS). In n = 1279 included renal sarcoma patients, AAIR remained constant over the study period (average 0.53 cases/1million; AAPC = 0.7, p  = 0.6). Leiomyosarcoma (AAIR 0.14 cases/1 million) and malignant rhabdoid tumors (0.06 cases/1 million) were most common. Sarcoma histiotypes demonstrated considerable heterogeneity regarding demographic and cancer-related variables. Patients presented with advanced local extent (T3 33.3%; T4 14.2%) or distant metastases (29.1%) and commonly underwent surgical resection (81.6%). Longer OS was independently associated with younger age, female sex, lower comorbidity index, low T stage, negative surgical margins, absence of tumor necrosis or distant metastases and leiomyosarcoma histiotype (multivariable p  < 0.05 each). Treatment efficacy varied according to sarcoma histiotype (interaction p  < 0.001). Accounting for 0.25% of renal malignancies, renal sarcomas include 43 histiotypes with distinct epidemiology, clinical presentation, outcomes and sensitivity to systemic therapy, thereby reflecting soft-tissue sarcoma behavior. Renal sarcoma treatment patterns follow recommendations by renal cancer guidelines with surgical resection as the cornerstone of therapy.

Background Myocardial deformation analyses using cardiovascular magnetic resonance (CMR) feature tracking (CMR-FT) have incremental value in the assessment of cardiac function beyond volumetric analyses. Since guidelines do not recommend specific imaging parameters, we aimed to define optimal spatial and temporal resolutions for CMR cine images to enable reliable post-processing. Methods Intra- and inter-observer reproducibility was assessed in 12 healthy subjects and 9 heart failure (HF) patients. Cine images were acquired with different temporal (20, 30, 40 and 50 frames/cardiac cycle) and spatial resolutions (high in-plane 1.5 × 1.5 mm through-plane 5 mm, standard 1.8 × 1.8 x 8mm and low 3.0 × 3.0 x 10mm). CMR-FT comprised left ventricular (LV) global and segmental longitudinal/circumferential strain (GLS/GCS) and associated systolic strain rates (SR), and right ventricular (RV) GLS. Results Temporal but not spatial resolution did impact absolute strain and SR. Maximum absolute changes between lowest and highest temporal resolution were as follows: 1.8% and 0.3%/s for LV GLS and SR, 2.5% and 0.6%/s for GCS and SR as well as 1.4% for RV GLS. Changes of strain values occurred comparing 20 and 30 frames/cardiac cycle including LV and RV GLS and GCS (p < 0.001–0.046). In contrast, SR values (LV GLS/GCS SR) changed significantly comparing all successive temporal resolutions (p < 0.001–0.013). LV strain and SR reproducibility was not affected by either temporal or spatial resolution, whilst RV strain variability decreased with augmentation of temporal resolution. Conclusion Temporal but not spatial resolution significantly affects strain and SR in CMR-FT deformation analyses. Strain analyses require lower temporal resolution and 30 frames/cardiac cycle offer consistent strain assessments, whilst SR measurements gain from further increases in temporal resolution.