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The adoption of machine learning (ML) and, more specifically, deep learning (DL) applications into all major areas of our lives is underway. The development of trustworthy AI is especially important in medicine due to the large implications for patients' lives. While trustworthiness concerns various aspects including ethical, transparency and safety requirements, we focus on the importance of data quality (training/test) in DL. Since data quality dictates the behaviour of ML products, evaluating data quality will play a key part in the regulatory approval of medical ML products. We perform a systematic review following PRISMA guidelines using the databases Web of Science, PubMed and ACM Digital Library. We identify 5408 studies, out of which 120 records fulfil our eligibility criteria. From this literature, we synthesise the existing knowledge on data quality frameworks and combine it with the perspective of ML applications in medicine. As a result, we propose the METRIC-framework, a specialised data quality framework for medical training data comprising 15 awareness dimensions, along which developers of medical ML applications should investigate the content of a dataset. This knowledge helps to reduce biases as a major source of unfairness, increase robustness, facilitate interpretability and thus lays the foundation for trustworthy AI in medicine. The METRIC-framework may serve as a base for systematically assessing training datasets, establishing reference datasets, and designing test datasets which has the potential to accelerate the approval of medical ML products. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to investigate an approach for motion-corrected T1 mapping of the abdomen that allows for free breathing data acquisition with 100% scan efficiency. Materials and methods: Data were acquired using a continuous golden radial trajectory and multiple inversion pulses. For the correction of respiratory motion, motion estimation based on a surrogate was performed from the same data used for T1 mapping. Image-based self-navigation allowed for binning and reconstruction of respiratory-resolved images, which were used for the estimation of respiratory motion fields. Finally, motion-corrected T1 maps were calculated from the data applying the estimated motion fields. The method was evaluated in five healthy volunteers. For the assessment of the image-based navigator, we compared it to a simultaneously acquired ultrawide band radar signal. Motion-corrected T1 maps were evaluated qualitatively and quantitatively for different scan times. Results: For all volunteers, the motion-corrected T1 maps showed fewer motion artifacts in the liver as well as sharper kidney structures and blood vessels compared to uncorrected T1 maps. Moreover, the relative error to the reference breathhold T1 maps could be reduced from up to 25% for the uncorrected T1 maps to below 10% for the motion-corrected maps for the average value of a region of interest, while the scan time could be reduced to 6-8 s. Discussion: The proposed approach allows for respiratory motion-corrected T1 mapping in the abdomen and ensures accurate T1 maps without the need for any breathholds. [ABSTRACT FROM AUTHOR]

Machine learning (ML) methods for the analysis of electrocardiography (ECG) data are gaining importance, substantially supported by the release of large public datasets. However, these current datasets miss important derived descriptors such as ECG features that have been devised in the past hundred years and still form the basis of most automatic ECG analysis algorithms and are critical for cardiologists' decision processes. ECG features are available from sophisticated commercial software but are not accessible to the general public. To alleviate this issue, we add ECG features from two leading commercial algorithms and an open-source implementation supplemented by a set of automatic diagnostic statements from a commercial ECG analysis software in preprocessed format. This allows the comparison of ML models trained on clinically versus automatically generated label sets. We provide an extensive technical validation of features and diagnostic statements for ML applications. We believe this release crucially enhances the usability of the PTB-XL dataset as a reference dataset for ML methods in the context of ECG data. [ABSTRACT FROM AUTHOR]

Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths. [ABSTRACT FROM AUTHOR]

Objective: To provide respiratory motion correction for free-breathing myocardial T1 mapping using a pilot tone (PT) and a continuous golden-angle radial acquisition. Materials and methods: During a 45 s prescan the PT is acquired together with a dynamic sagittal image covering multiple respiratory cycles. From these images, the respiratory heart motion in head-feet and anterior–posterior direction is estimated and two linear models are derived between the PT and heart motion. In the following scan through-plane motion is corrected prospectively with slice tracking based on the PT. In-plane motion is corrected for retrospectively. Our method was evaluated on a motion phantom and 11 healthy subjects. Results: Non-motion corrected measurements using a moving phantom showed T1 errors of 14 ± 4% (p < 0.05) compared to a reference measurement. The proposed motion correction approach reduced this error to 3 ± 4% (p < 0.05). In vivo the respiratory motion led to an overestimation of T1 values by 26 ± 31% compared to breathhold T1 maps, which was successfully corrected to an average difference of 3 ± 2% (p < 0.05) between our free-breathing approach and breathhold data. Discussion: Our proposed PT-based motion correction approach allows for T1 mapping during free-breathing with the same accuracy as a corresponding breathhold T1 mapping scan. [ABSTRACT FROM AUTHOR]

Background: Cardiac PET has recently found novel applications in coronary atherosclerosis imaging using [18F]NaF as a radiotracer, highlighting vulnerable plaques. However, the resulting uptakes are relatively small, and cardiac motion and respiration-induced movement of the heart can impair the reconstructed images due to motion blurring and attenuation correction mismatches. This study aimed to apply an MR-based motion compensation framework to [18F]NaF data yielding high-resolution motion-compensated PET and MR images. Methods: Free-breathing 3-dimensional Dixon MR data were acquired, retrospectively binned into multiple respiratory and cardiac motion states, and split into fat and water fraction using a model-based reconstruction framework. From the dynamic MR reconstructions, both a non-rigid cardiorespiratory motion model and a motion-resolved attenuation map were generated and applied to the PET data to improve image quality. The approach was tested in 10 patients and focal tracer hotspots were evaluated concerning their target-to-background ratio, contrast-to-background ratio, and their diameter. Results: MR-based motion models were successfully applied to compensate for physiological motion in both PET and MR. Target-to-background ratios of identified plaques improved by 7 ± 7%, contrast-to-background ratios by 26 ± 38%, and the plaque diameter decreased by −22 ± 18%. MR-based dynamic attenuation correction strongly reduced attenuation correction artefacts and was not affected by stent-related signal voids in the underlying MR reconstructions. Conclusions: The MR-based motion correction framework presented here can improve the target-to-background, contrast-to-background, and width of focal tracer hotspots in the coronary system. The dynamic attenuation correction could effectively mitigate the risk of attenuation correction artefacts in the coronaries at the lung-soft tissue boundary. In combination, this could enable a more reproducible and reliable plaque localisation. [ABSTRACT FROM AUTHOR]

Electrocardiography (ECG) is a key non-invasive diagnostic tool for cardiovascular diseases which is increasingly supported by algorithms based on machine learning. Major obstacles for the development of automatic ECG interpretation algorithms are both the lack of public datasets and well-defined benchmarking procedures to allow comparison s of different algorithms. To address these issues, we put forward PTB-XL, the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10 seconds length. The ECG-waveform data was annotated by up to two cardiologists as a multi-label dataset, where diagnostic labels were further aggregated into super and subclasses. The dataset covers a broad range of diagnostic classes including, in particular, a large fraction of healthy records. The combination with additional metadata on demographics, additional diagnostic statements, diagnosis likelihoods, manually annotated signal properties as well as suggested folds for splitting training and test sets turns the dataset into a rich resource for the development and the evaluation of automatic ECG interpretation algorithms. Measurement(s) electrocardiography • cardiovascular system Technology Type(s) 12 lead electrocardiography Factor Type(s) presence of co-occurring diseases Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12098055 [ABSTRACT FROM AUTHOR]

Magnetic particle imaging (MPI) is a non-invasive, non-ionizing imaging technique for the visualization and quantification of magnetic nanoparticles (MNPs). The technique is especially suitable for cell imaging as it offers zero background contribution from the surrounding tissue, high sensitivity, and good spatial and temporal resolutions. Previous studies have demonstrated that the dynamic magnetic behaviour of MNPs changes during cellular binding and internalization. In this study, we demonstrate how this information is encoded in the MPI imaging signal. Through MPI imaging we are able to discriminate between free and cell-bound MNPs in reconstructed images. This technique was used to image and quantify the changes that occur in-vitro when free MNPs come into contact with cells and undergo cellular-uptake over time. The quantitative MPI results were verified by colorimetric measurements of the iron content. The results showed a mean relative difference between the MPI results and the reference method of 23.8% for the quantification of cell-bound MNPs. With this technique, the uptake of MNPs in cells can be imaged and quantified directly from the first MNP cell contact, providing information on the dynamics of cellular uptake. [ABSTRACT FROM AUTHOR]

Objectives: The aim of this study was to investigate the impact of BMI on late gadolinium enhancement (LGE) of the coronary artery wall in identical monozygous twins discordant for BMI. Coronary LGE represents a useful parameter for the detection and quantification of atherosclerotic coronary vessel wall disease.Methods: Thirteen monozygote female twin pairs (n = 26) with significantly different BMIs (>1.6 kg/m2) were recruited out of >10,000 twin pairs (TwinsUK Registry). A coronary 3D-T2prep-TFE MR angiogram and 3D-IR-TFE vessel wall scan were performed prior to and following the administration of 0.2 mmol/kg of Gd-DTPA on a 1.5 T MR scanner. The number of enhancing coronary segments and contrast to noise ratios (CNRs) of the coronary wall were quantified.Results: An increase in BMI was associated with an increased number of enhancing coronary segments (5.3 ± 1.5 vs. 3.5 ± 1.6, p < 0.0001) and increased coronary wall enhancement (6.1 ± 1.1 vs. 4.8 ± 0.9, p = 0.0027) compared to matched twins with lower BMI.Conclusions: This study in monozygous twins indicates that acquired factors predisposing to obesity, including lifestyle and environmental factors, result in increased LGE of the coronary arteries, potentially reflecting an increase in coronary atherosclerosis in this female study population.Key Points: • BMI-discordant twins allow the investigation of the influence of lifestyle factors independent from genetic confounders. • Only thirteen obesity-discordant twins were identified underlining the strong genetic component of BMI. • In female twins, a BMI increase is associated with increased coronary late gadolinium enhancement. • Increased late gadolinium enhancement in the coronary vessel wall potentially reflects increased atherosclerosis. [ABSTRACT FROM AUTHOR]

The aim of this prospective study is to compare the performance of 2D time-resolved phase-contrast (PC) MRI prior to and after the administration of an intravascular (gadofosveset-trisodium) and extravascular (gadopentetate-dimeglumine) contrast agent in the same patient in the cardiovascular system. This study was approved by the ethics committee (Study-Number-07/Q0704/2) and registered with the MedicinesAndHealthcareProductsRegulatoryAgency (MHRA-Study-Number-28482/0002/001-0001, EudraCT-Number-2006-007042). All patients signed an informed consent. 20 patients were examined using a 1.5T MR-scanner and 32-channel-coil-technology. Gadopentetate-dimeglumine (GdD) and gadofosveset-trisodium (GdT) were administered in the same patient on consecutive days. Image quality, velocity-to-noise-ratios (VNRs) and standard-deviation of blood-flow-velocities (phase-noise) were compared between GdT, GdD and non-contrast-enhanced imaging. On both days pre- and post-contrast-scans were performed. The administration of GdT significantly improved the delineation of the perfused lumen and the VNR compared to GdD and non-contrast-enhanced imaging. Standard deviations of through-plane and in-plane velocity-measurements (phase-noise) were significantly reduced after GdT administration ( p < 0.05). No significant differences ( p > 0.05) were measured regarding absolute flow values prior to and after the administration of GdD and GdT. PC flow imaging benefits from the administration of an intravascular contrast agent by improving the delineation of the perfused lumen and reducing phase noise in flow measurements. [ABSTRACT FROM AUTHOR]

A common approach to compensate for respiratory motion in free-breathing 3D magnetic resonance imaging (MRI) is navigator gating where MRI data is only acquired when the respiratory signal coincides within a small predefined acceptance window. However, this leads to poor scan efficiency and prolonged scan times. Here, we propose a method to reconstruct motion-compensated 3D MRI of the abdomen acquired during free-breathing with nearly 100 % scan efficiency without increasing scan time. Materials and methods: The approach is based on a self-gated golden-radial phase encoding sampling scheme that allows for the reconstruction of multiple undersampled 3D images at different respiratory positions. Non-rigid image registrations and time-wise motion field interpolations are employed to form 3D motion models that combine all low-quality images into one high-quality motion-compensated image. Results: Our highly efficient technique allows reconstruction of 3D liver MRI with a high isotropic resolution of 1.75 mm from a short acquisition of 1.1 min. The approach is validated in 10 healthy volunteers by comparing image quality to data sets acquired with a self-gating approach. Conclusion: Our method reduces scan time by 56 % compared to the gating technique while similar image quality is preserved. [ABSTRACT FROM AUTHOR]

Myocardial fibrosis is a common denominator in a wide spectrum of cardiomyopathies; it plays a major role in the pathophysiology of structural remodelling and as a predictor of adverse outcome. Quantification of myocardial fibrosis by invasive biopsy is limited in clinical practice due to the commonly scattered tissue distribution and procedural risks. Late gadolinium enhancement by cardiac magnetic resonance has revolutionized the assessment of ischemic cardiomyopathy by visualization of regional scarring after myocardial infarction. The binary (white-black) principle of contrast development and a requirement for well separated layers of healthy and diseased myocardium is straightforward for clinical decision making in ischemic heart disease, but renders this technique less powerful in conditions where the myocardium is affected diffusely. Recently emerged T1 mapping techniques allow for an individualized quantification of global and regional myocardial signal and are promising tools to separate between healthy and diseased. In this article we review the emerging evidence for T1 mapping techniques and outline the necessary future directions for a successful translational pathway. [ABSTRACT FROM AUTHOR]

Atherosclerosis and its consequences remain the main cause of mortality in industrialized and developing nations. Plaque burden and progression have been shown to be independent predictors for future cardiac events by intravascular ultrasound. Routine prospective imaging is hampered by the invasive nature of intravascular ultrasound. A noninvasive technique would therefore be more suitable for screening of atherosclerosis in large populations. Here we introduce an elastin-specific magnetic resonance contrast agent (ESMA) for noninvasive quantification of plaque burden in a mouse model of atherosclerosis. The strong signal provided by ESMA allows for imaging with high spatial resolution, resulting in accurate assessment of plaque burden. Additionally, plaque characterization by quantifying intraplaque elastin content using signal intensity measurements is possible. Changes in elastin content and the high abundance of elastin during plaque development, in combination with the imaging properties of ESMA, provide potential for noninvasive assessment of plaque burden by molecular magnetic resonance imaging (MRI). [ABSTRACT FROM AUTHOR]

Objective: Positron emission tomography (PET) provides an accurate measurement of radiotracer concentration in vivo, but performance can be limited by subject motion which degrades spatial resolution and quantitative accuracy. This effect may become a limiting factor for PET studies in the body as PET scanner technology improves. In this work, we propose a new approach to address this problem by employing motion information from images measured simultaneously using a magnetic resonance (MR) scanner. Methods: The approach is demonstrated using an MR-compatible PET scanner and PET-MR acquisition with a purpose-designed phantom capable of non-rigid deformations. Measured, simultaneously acquired MR data were used to correct for motion in PET, and results were compared with those obtained using motion information from PET images alone. Results: Motion artefacts were significantly reduced and the PET image quality and quantification was significantly improved by the use of MR motion fields, whilst the use of PET-only motion information was less successful. Conclusions: Combined PET-MR acquisitions potentially allow PET motion compensation in whole-body acquisitions without prolonging PET acquisition time or increasing radiation dose. This, to the best of our knowledge, is the first study to demonstrate that simultaneously acquired MR data can be used to estimate and correct for the effects of non-rigid motion in PET. [ABSTRACT FROM AUTHOR]

The case of an 8-year-old girl with atrial septal defect and associated anomalous pulmonary venous return is presented to illustrate the advantages of four dimensional flow (4D flow) over the current two dimensional flow (2D flow) in terms of time efficiency, easy planning, accurate and individual quantification of the blood sources contributing to the left-to-right shunting from one single acquisition, internal validation of flow measurement accuracy, possibility of reanalysis without rescanning in case of unexpected findings during the postprocessing, and comprehensive understanding of flow insight by use of particle tracing visualization. [ABSTRACT FROM AUTHOR]

Patient-specific preoperative planning in complex congenital heart disease may be greatly facilitated by virtual cardiotomy. Surgeons can perform an unlimited number of surgical incisions on a virtual 3-D reconstruction to evaluate the feasibility of different surgical strategies. To quantitatively evaluate the quality of the underlying imaging data and the accuracy of the corresponding segmentation, and to qualitatively evaluate the feasibility of virtual cardiotomy. A whole-heart MRI sequence was applied in 42 children with congenital heart disease (age 3 ± 3 years, weight 13 ± 9 kg, heart rate 96 ± 21 bpm). Image quality was graded 1–4 (diagnostic image quality ≥2) by two independent blinded observers. In patients with diagnostic image quality the segmentation quality was also graded 1–4 (4 no discrepancies, 1 misleading error). The average image quality score was 2.7 – sufficient for virtual reconstruction in 35 of 38 patients (92%) older than 1 month. Segmentation time was 59 ± 10 min (average quality score 3.5). Virtual cardiotomy was performed in 19 patients. Accurate virtual reconstructions of patient-specific cardiac anatomy can be produced in less than 1 h from 3-D MRI. The presented work thus introduces a new, clinically feasible noninvasive technique for improved preoperative planning in complex cases of congenital heart disease. [ABSTRACT FROM AUTHOR]

A major challenge in constructing three dimensional patient specific hemodynamic models is the calibration of model parameters to match patient data on flow, pressure, wall motion, etc. acquired in the clinic. Current workflows are manual and time-consuming. This work presents a flexible computational framework for model parameter estimation in cardiovascular flows that relies on the following fundamental contributions. (i) A Reduced-Order Unscented Kalman Filter (ROUKF) model for data assimilation for wall material and simple lumped parameter network (LPN) boundary condition model parameters. (ii) A constrained least squares augmentation (ROUKF-CLS) for more complex LPNs. (iii) A "Netlist" implementation, supporting easy filtering of parameters in such complex LPNs. The ROUKF algorithm is demonstrated using non-invasive patient-specific data on anatomy, flow and pressure from a healthy volunteer. The ROUKF-CLS algorithm is demonstrated using synthetic data on a coronary LPN. The methods described in this paper have been implemented as part of the CRIMSON hemodynamics software package. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Influence of acquired obesity on coronary vessel wall late gadolinium enhancement in discordant monozygote twin" published in the perodical.