Identifying the best PCR enzyme for library amplification in NGS.

Background. PCR amplification is a necessary step in many next-generation sequencing (NGS) library preparation methods [1, 2]. Whilst many PCR enzymes are developed to amplify single targets efficiently, accurately and with specificity, few are developed to meet the challenges imposed by NGS PCR, namely unbiased amplification of a wide range of different sizes and GC content. As a result PCR amplification during NGS library prep often results in bias toward GC neutral and smaller fragments. As NGS has matured, optimized NGS library prep kits and polymerase formulations have emerged and in this study we have tested a wide selection of available enzymes for both short-read Illumina library preparation and long fragment amplification ahead of long-read sequencing.We tested over 20 different hi-fidelity PCR enzymes/NGS amplification mixes on a range of Illumina library templates of varying GC content and composition, and find that both yield and genome coverage uniformity characteristics of the commercially available enzymes varied dramatically. Three enzymes Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) 'Equinox' and Takara Ex Premier were found to give a consistent performance, over all genomes, that mirrored closely that observed for PCR-free datasets. We also test a range of enzymes for long-read sequencing by amplifying size fractionated S. cerevisiae DNA of average size 21.6 and 13.4 kb, respectively.The enzymes of choice for short-read (Illumina) library fragment amplification are Quantabio RepliQa Hifi Toughmix, Watchmaker Library Amplification Hot Start Master Mix (2X) 'Equinox' and Takara Ex Premier, with RepliQa also being the best performing enzyme from the enzymes tested for long fragment amplification prior to long-read sequencing.

A Deep Learning Pipeline for Assessing Ventricular Volumes from a Cardiac MRI Registry of Patients with Single Ventricle Physiology.

Purpose To develop an end-to-end deep learning (DL) pipeline for automated ventricular segmentation of cardiac MRI data from a multicenter registry of patients with Fontan circulation (Fontan Outcomes Registry Using CMR Examinations [FORCE]). Materials and Methods This retrospective study used 250 cardiac MRI examinations (November 2007-December 2022) from 13 institutions for training, validation, and testing. The pipeline contained three DL models: a classifier to identify short-axis cine stacks and two U-Net 3+ models for image cropping and segmentation. The automated segmentations were evaluated on the test set (n = 50) by using the Dice score. Volumetric and functional metrics derived from DL and ground truth manual segmentations were compared using Bland-Altman and intraclass correlation analysis. The pipeline was further qualitatively evaluated on 475 unseen examinations. Results There were acceptable limits of agreement (LOA) and minimal biases between the ground truth and DL end-diastolic volume (EDV) (bias: -0.6 mL/m2, LOA: -20.6 to 19.5 mL/m2) and end-systolic volume (ESV) (bias: -1.1 mL/m2, LOA: -18.1 to 15.9 mL/m2), with high intraclass correlation coefficients (ICCs > 0.97) and Dice scores (EDV, 0.91 and ESV, 0.86). There was moderate agreement for ventricular mass (bias: -1.9 g/m2, LOA: -17.3 to 13.5 g/m2) and an ICC of 0.94. There was also acceptable agreement for stroke volume (bias: 0.6 mL/m2, LOA: -17.2 to 18.3 mL/m2) and ejection fraction (bias: 0.6%, LOA: -12.2% to 13.4%), with high ICCs (>0.81). The pipeline achieved satisfactory segmentation in 68% of the 475 unseen examinations, while 26% needed minor adjustments, 5% needed major adjustments, and in 0.4%, the cropping model failed. Conclusion The DL pipeline can provide fast standardized segmentation for patients with single ventricle physiology across multiple centers. This pipeline can be applied to all cardiac MRI examinations in the FORCE registry. Keywords: Cardiac, Adults and Pediatrics, MR Imaging, Congenital, Volume Analysis, Segmentation, Quantification Supplemental material is available for this article. © RSNA, 2023.

Haplotype-specific assembly of shattered chromosomes in esophageal adenocarcinomas.

The epigenetic landscape of cancer is regulated by many factors, but primarily it derives from the underlying genome sequence. Chromothripsis is a catastrophic localized genome shattering event that drives, and often initiates, cancer evolution. We characterized five esophageal adenocarcinoma organoids with chromothripsis using long-read sequencing and transcriptome and epigenome profiling. Complex structural variation and subclonal variants meant that haplotype-aware de novo methods were required to generate contiguous cancer genome assemblies. Chromosomes were assembled separately and scaffolded using haplotype-resolved Hi-C reads, producing accurate assemblies even with up to 900 structural rearrangements. There were widespread differences between the chromothriptic and wild-type copies of chromosomes in topologically associated domains, chromatin accessibility, histone modifications, and gene expression. Differential epigenome peaks were most enriched within 10 kb of chromothriptic structural variants. Alterations in transcriptome and higher-order chromosome organization frequently occurred near differential epigenetic marks. Overall, chromothripsis reshapes gene regulation, causing coordinated changes in epigenetic landscape, transcription, and chromosome conformation.

Somatic evolution of marine transmissible leukemias in the common cockle, Cerastoderma edule.

Transmissible cancers are malignant cell lineages that spread clonally between individuals. Several such cancers, termed bivalve transmissible neoplasia (BTN), induce leukemia-like disease in marine bivalves. This is the case of BTN lineages affecting the common cockle, Cerastoderma edule, which inhabits the Atlantic coasts of Europe and northwest Africa. To investigate the evolution of cockle BTN, we collected 6,854 cockles, diagnosed 390 BTN tumors, generated a reference genome and assessed genomic variation across 61 tumors. Our analyses confirmed the existence of two BTN lineages with hemocytic origins. Mitochondrial variation revealed mitochondrial capture and host co-infection events. Mutational analyses identified lineage-specific signatures, one of which likely reflects DNA alkylation. Cytogenetic and copy number analyses uncovered pervasive genomic instability, with whole-genome duplication, oncogene amplification and alkylation-repair suppression as likely drivers. Satellite DNA distributions suggested ancient clonal origins. Our study illuminates long-term cancer evolution under the sea and reveals tolerance of extreme instability in neoplastic genomes.

NCTC3000: a century of bacterial strain collecting leads to a rich genomic data resource.

The National Collection of Type Cultures (NCTC) was founded on 1 January 1920 in order to fulfil a recognized need for a centralized repository for bacterial and fungal strains within the UK. It is among the longest-established collections of its kind anywhere in the world and today holds approximately 6000 type and reference bacterial strains - many of medical, scientific and veterinary importance - available to academic, health, food and veterinary institutions worldwide. Recently, a collaboration between NCTC, Pacific Biosciences and the Wellcome Sanger Institute established the NCTC3000 project to long-read sequence and assemble the genomes of up to 3000 NCTC strains. Here, at the beginning of the collection's second century, we introduce the resulting NCTC3000 sequence read datasets, genome assemblies and annotations as a unique, historically and scientifically relevant resource for the benefit of the international bacterial research community.

The evolution of two transmissible cancers in Tasmanian devils.

Tasmanian devils have spawned two transmissible cancer lineages, named devil facial tumor 1 (DFT1) and devil facial tumor 2 (DFT2). We investigated the genetic diversity and evolution of these clones by analyzing 78 DFT1 and 41 DFT2 genomes relative to a newly assembled, chromosome-level reference. Time-resolved phylogenetic trees reveal that DFT1 first emerged in 1986 (1982 to 1989) and DFT2 in 2011 (2009 to 2012). Subclone analysis documents transmission of heterogeneous cell populations. DFT2 has faster mutation rates than DFT1 across all variant classes, including substitutions, indels, rearrangements, transposable element insertions, and copy number alterations, and we identify a hypermutated DFT1 lineage with defective DNA mismatch repair. Several loci show plausible evidence of positive selection in DFT1 or DFT2, including loss of chromosome Y and inactivation of MGA, but none are common to both cancers. This study reveals the parallel long-term evolution of two transmissible cancers inhabiting a common niche in Tasmanian devils.

Shape-driven deep neural networks for fast acquisition of aortic 3D pressure and velocity flow fields.

Computational fluid dynamics (CFD) can be used to simulate vascular haemodynamics and analyse potential treatment options. CFD has shown to be beneficial in improving patient outcomes. However, the implementation of CFD for routine clinical use is yet to be realised. Barriers for CFD include high computational resources, specialist experience needed for designing simulation set-ups, and long processing times. The aim of this study was to explore the use of machine learning (ML) to replicate conventional aortic CFD with automatic and fast regression models. Data used to train/test the model consisted of 3,000 CFD simulations performed on synthetically generated 3D aortic shapes. These subjects were generated from a statistical shape model (SSM) built on real patient-specific aortas (N = 67). Inference performed on 200 test shapes resulted in average errors of 6.01% ±3.12 SD and 3.99% ±0.93 SD for pressure and velocity, respectively. Our ML-based models performed CFD in ∼0.075 seconds (4,000x faster than the solver). This proof-of-concept study shows that results from conventional vascular CFD can be reproduced using ML at a much faster rate, in an automatic process, and with reasonable accuracy.

The genome sequence of the Norway rat, Rattus norvegicus Berkenhout 1769.

We present a genome assembly from an individual male Rattus norvegicus (the Norway rat; Chordata; Mammalia; Rodentia; Muridae). The genome sequence is 2.44 gigabases in span. The majority of the assembly is scaffolded into 20 chromosomal pseudomolecules, with both X and Y sex chromosomes assembled. This genome assembly, mRatBN7.2, represents the new reference genome for R. norvegicus and has been adopted by the Genome Reference Consortium.

The genome sequence of the European golden eagle, Aquila chrysaetos chrysaetos Linnaeus 1758.

We present a genome assembly from an individual female Aquila chrysaetos chrysaetos (the European golden eagle; Chordata; Aves; Accipitridae). The genome sequence is 1.23 gigabases in span. The majority of the assembly is scaffolded into 28 chromosomal pseudomolecules, including the W and Z sex chromosomes.

The complete genome sequence of Eimeria tenella (Tyzzer 1929), a common gut parasite of chickens.

We present a genome assembly from a clonal population of Eimeria tenella Houghton parasites (Apicomplexa; Conoidasida; Eucoccidiorida; Eimeriidae). The genome sequence is 53.25 megabases in span. The entire assembly is scaffolded into 15 chromosomal pseudomolecules, with complete mitochondrion and apicoplast organellar genomes also present.

Patterns of within-host genetic diversity in SARS-CoV-2.

Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95.1% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within- and between-host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.

The COVID-19 pandemic has had major health impacts across the globe. The scientific community has focused much attention on finding ways to monitor how the virus responsible for the pandemic, SARS-CoV-2, spreads. One option is to perform genetic tests, known as sequencing, on SARS-CoV-2 samples to determine the genetic code of the virus and to find any differences or mutations in the genes between the viral samples. Viruses mutate within their hosts and can develop into variants that are able to more easily transmit between hosts. Genetic sequencing can reveal how genetically similar two SARS-CoV-2 samples are. But tracking how SARS-CoV-2 moves from one person to the next through sequencing can be tricky. Even a sample of SARS-CoV-2 viruses from the same individual can display differences in their genetic material or within-host variants. Could genetic testing of within-host variants shed light on factors driving SARS-CoV-2 to evolve in humans? To get to the bottom of this, Tonkin-Hill, Martincorena et al. probed the genetics of SARS-CoV-2 within-host variants using 1,181 samples. The analyses revealed that 95.1% of samples contained within-host variants. A number of variants occurred frequently in many samples, which were consistent with mutational hotspots in the SARS-CoV-2 genome. In addition, within-host variants displayed mutation patterns that were similar to patterns found between infected individuals. The shared within-host variants between samples can help to reconstruct transmission chains. However, the observed mutational hotspots and the detection of multiple strains within an individual can make this challenging. These findings could be used to help predict how SARS-CoV-2 evolves in response to interventions such as vaccines. They also suggest that caution is needed when using information on within-host variants to determine transmission between individuals.

Nanopore Sequencing Indicates That Tandem Amplification of Chromosome 20q11.21 in Human Pluripotent Stem Cells Is Driven by Break-Induced Replication.

Copy number variants (CNVs) are genomic rearrangements implicated in numerous congenital and acquired diseases, including cancer. The appearance of culture-acquired CNVs in human pluripotent stem cells (PSCs) has prompted concerns for their use in regenerative medicine. A particular problem in PSC is the frequent occurrence of CNVs in the q11.21 region of chromosome 20. However, the exact mechanism of origin of this amplicon remains elusive due to the difficulty in delineating its sequence and breakpoints. Here, we have addressed this problem using long-read Nanopore sequencing of two examples of this CNV, present as duplication and as triplication. In both cases, the CNVs were arranged in a head-to-tail orientation, with microhomology sequences flanking or overlapping the proximal and distal breakpoints. These breakpoint signatures point to a mechanism of microhomology-mediated break-induced replication in CNV formation, with surrounding Alu sequences likely contributing to the instability of this genomic region.

A high-quality, chromosome-level genome assembly of the Black Soldier Fly (Hermetia illucens L.).

Hermetia illucens L. (Diptera: Stratiomyidae), the Black Soldier Fly (BSF) is an increasingly important species for bioconversion of organic material into animal feed. We generated a high-quality chromosome-scale genome assembly of the BSF using Pacific Bioscience, 10X Genomics linked read and high-throughput chromosome conformation capture sequencing technology. Scaffolding the final assembly with Hi-C data produced a highly contiguous 1.01 Gb genome with 99.75% of scaffolds assembled into pseudochromosomes representing seven chromosomes with 16.01 Mb contig and 180.46 Mb scaffold N50 values. The highly complete genome obtained a Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness of 98.6%. We masked 67.32% of the genome as repetitive sequences and annotated a total of 16,478 protein-coding genes using the BRAKER2 pipeline. We analyzed an established lab population to investigate the genomic variation and architecture of the BSF revealing six autosomes and an X chromosome. Additionally, we estimated the inbreeding coefficient (1.9%) of the lab population by assessing runs of homozygosity. This provided evidence for inbreeding events including long runs of homozygosity on chromosome 5. The release of this novel chromosome-scale BSF genome assembly will provide an improved resource for further genomic studies, functional characterization of genes of interest and genetic modification of this economically important species.

Reducing Contrast Agent Dose in Cardiovascular MR Angiography with Deep Learning.

BACKGROUND: Contrast-enhanced magnetic resonance angiography (MRA) is used to assess various cardiovascular conditions. However, gadolinium-based contrast agents (GBCAs) carry a risk of dose-related adverse effects. PURPOSE: To develop a deep learning method to reduce GBCA dose by 80%. STUDY TYPE: Retrospective and prospective. POPULATION: A total of 1157 retrospective and 40 prospective congenital heart disease patients for training/validation and testing, respectively. FIELD STRENGTH/SEQUENCE: A 1.5 T, T1-weighted three-dimensional (3D) gradient echo. ASSESSMENT: A neural network was trained to enhance low-dose (LD) 3D MRA using retrospective synthetic data and tested with prospective LD data. Image quality for LD (LD-MRA), enhanced LD (ELD-MRA), and high-dose (HD-MRA) was assessed in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and a quantitative measure of edge sharpness and scored for perceptual sharpness and contrast on a 1-5 scale. Diagnostic confidence was assessed on a 1-3 scale. LD- and ELD-MRA were assessed against HD-MRA for sensitivity/specificity and agreement of vessel diameter measurements (aorta and pulmonary arteries). STATISTICAL TESTS: SNR, CNR, edge sharpness, and vessel diameters were compared between LD-, ELD-, and HD-MRA using one-way repeated measures analysis of variance with post-hoc t-tests. Perceptual quality and diagnostic confidence were compared using Friedman's test with post-hoc Wilcoxon signed-rank tests. Sensitivity/specificity was compared using McNemar's test. Agreement of vessel diameters was assessed using Bland-Altman analysis. RESULTS: SNR, CNR, edge sharpness, perceptual sharpness, and perceptual contrast were lower (P < 0.05) for LD-MRA compared to ELD-MRA and HD-MRA. SNR, CNR, edge sharpness, and perceptual contrast were comparable between ELD and HD-MRA, but perceptual sharpness was significantly lower. Sensitivity/specificity was 0.824/0.921 for LD-MRA and 0.882/0.960 for ELD-MRA. Diagnostic confidence was 2.72, 2.85, and 2.92 for LD, ELD, and HD-MRA, respectively (PLD-ELD , PLD-HD  < 0.05). Vessel diameter measurements were comparable, with biases of 0.238 (LD-MRA) and 0.278 mm (ELD-MRA). DATA CONCLUSION: Deep learning can improve contrast in LD cardiovascular MRA. LEVEL OF EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

The genome sequence of the European water vole, Arvicola amphibius Linnaeus 1758.

We present a genome assembly from an individual male Arvicola amphibius (the European water vole; Chordata; Mammalia; Rodentia; Cricetidae). The genome sequence is 2.30 gigabases in span. The majority of the assembly is scaffolded into 18 chromosomal pseudomolecules, including the X sex chromosome. Gene annotation of this assembly on Ensembl has identified 21,394 protein coding genes.

A preoperative estimate of central venous pressure is associated with early Fontan failure.

OBJECTIVE: Early Fontan failure is a serious complication after total cavopulmonary connection, characterized by high central venous pressure, low cardiac output, and resistance to medical therapy. This study aimed to estimate postoperative central venous pressure in patients with total cavopulmonary connection using data routinely collected during preoperative assessment. We sought to determine if this metric correlated with measured postoperative central venous pressure and if it was associated with early Fontan failure. METHODS: In this retrospective study, central venous pressure in total cavopulmonary connection was estimated in 131 patients undergoing pre-total cavopulmonary connection assessment by cardiac magnetic resonance imaging and central venous pressure measurement under general anesthesia. Postoperative central venous pressure during the first 24 hours in the intensive care unit was collected from electronic patient records in a subset of patients. Early Fontan failure was defined as death, transplantation, total cavopulmonary connection takedown, or emergency fenestration within the first 30 days. RESULTS: Estimated central venous pressure in total cavopulmonary connection correlated significantly with central venous pressure during the first 24 hours in the intensive care unit (r = 0.26, P = .03), particularly in patients without a fenestration (r = 0.45, P = .01). Central venous pressure in total cavopulmonary connection was significantly associated with early Fontan failure (odds ratio, 1.1; 95% confidence interval, 1.01-1.21; P = .03). A threshold of central venous pressure in total cavopulmonary connection 33 mm Hg or greater was found to have the highest specificity (90%) and sensitivity (58%) for identifying early Fontan failure (area under receiver operating curve = 0.73; odds ratio, 12.4; 95% confidence interval, 2.5-62.3; P = .002). This association was stronger in patients with single superior vena cava. CONCLUSIONS: Estimated central venous pressure in total cavopulmonary connection is an easily calculated metric combining preoperative pressure and flow data. Higher central venous pressure in total cavopulmonary connection is associated with an increased risk of early Fontan failure and is correlated with directly measured post-total cavopulmonary connection pressure. Identification of patients at risk of early Fontan failure has the potential to guide risk-mitigation strategies.

The genome sequence of the eastern grey squirrel, Sciurus carolinensis Gmelin, 1788.

We present a genome assembly from an individual male Sciurus carolinensis (the eastern grey squirrel; Vertebrata; Mammalia; Eutheria; Rodentia; Sciuridae). The genome sequence is 2.82 gigabases in span. The majority of the assembly (92.3%) is scaffolded into 21 chromosomal-level scaffolds, with both X and Y sex chromosomes assembled.

Genomic and transcriptomic variation defines the chromosome-scale assembly of Haemonchus contortus, a model gastrointestinal worm.

Haemonchus contortus is a globally distributed and economically important gastrointestinal pathogen of small ruminants and has become a key nematode model for studying anthelmintic resistance and other parasite-specific traits among a wider group of parasites including major human pathogens. Here, we report using PacBio long-read and OpGen and 10X Genomics long-molecule methods to generate a highly contiguous 283.4 Mbp chromosome-scale genome assembly including a resolved sex chromosome for the MHco3(ISE).N1 isolate. We show a remarkable pattern of conservation of chromosome content with Caenorhabditis elegans, but almost no conservation of gene order. Short and long-read transcriptome sequencing allowed us to define coordinated transcriptional regulation throughout the parasite's life cycle and refine our understanding of cis- and trans-splicing. Finally, we provide a comprehensive picture of chromosome-wide genetic diversity both within a single isolate and globally. These data provide a high-quality comparison for understanding the evolution and genomics of Caenorhabditis and other nematodes and extend the experimental tractability of this model parasitic nematode in understanding helminth biology, drug discovery and vaccine development, as well as important adaptive traits such as drug resistance.

The mutational signature profile of known and suspected human carcinogens in mice.

Epidemiological studies have identified many environmental agents that appear to significantly increase cancer risk in human populations. By analyzing tumor genomes from mice chronically exposed to 1 of 20 known or suspected human carcinogens, we reveal that most agents do not generate distinct mutational signatures or increase mutation burden, with most mutations, including driver mutations, resulting from tissue-specific endogenous processes. We identify signatures resulting from exposure to cobalt and vinylidene chloride and link distinct human signatures (SBS19 and SBS42) with 1,2,3-trichloropropane, a haloalkane and pollutant of drinking water, and find these and other signatures in human tumor genomes. We define the cross-species genomic landscape of tumors induced by an important compendium of agents with relevance to human health.

Rapid whole-heart CMR with single volume super-resolution.

BACKGROUND: Three-dimensional, whole heart, balanced steady state free precession (WH-bSSFP) sequences provide delineation of intra-cardiac and vascular anatomy. However, they have long acquisition times. Here, we propose significant speed-ups using a deep-learning single volume super-resolution reconstruction, to recover high-resolution features from rapidly acquired low-resolution WH-bSSFP images. METHODS: A 3D residual U-Net was trained using synthetic data, created from a library of 500 high-resolution WH-bSSFP images by simulating 50% slice resolution and 50% phase resolution. The trained network was validated with 25 synthetic test data sets. Additionally, prospective low-resolution data and high-resolution data were acquired in 40 patients. In the prospective data, vessel diameters, quantitative and qualitative image quality, and diagnostic scoring was compared between the low-resolution, super-resolution and reference high-resolution WH-bSSFP data. RESULTS: The synthetic test data showed a significant increase in image quality of the low-resolution images after super-resolution reconstruction. Prospectively acquired low-resolution data was acquired ~× 3 faster than the prospective high-resolution data (173 s vs 488 s). Super-resolution reconstruction of the low-resolution data took < 1 s per volume. Qualitative image scores showed super-resolved images had better edge sharpness, fewer residual artefacts and less image distortion than low-resolution images, with similar scores to high-resolution data. Quantitative image scores showed super-resolved images had significantly better edge sharpness than low-resolution or high-resolution images, with significantly better signal-to-noise ratio than high-resolution data. Vessel diameters measurements showed over-estimation in the low-resolution measurements, compared to the high-resolution data. No significant differences and no bias was found in the super-resolution measurements in any of the great vessels. However, a small but significant for the underestimation was found in the proximal left coronary artery diameter measurement from super-resolution data. Diagnostic scoring showed that although super-resolution did not improve accuracy of diagnosis, it did improve diagnostic confidence compared to low-resolution imaging. CONCLUSION: This paper demonstrates the potential of using a residual U-Net for super-resolution reconstruction of rapidly acquired low-resolution whole heart bSSFP data within a clinical setting. We were able to train the network using synthetic training data from retrospective high-resolution whole heart data. The resulting network can be applied very quickly, making these techniques particularly appealing within busy clinical workflow. Thus, we believe that this technique may help speed up whole heart CMR in clinical practice.