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Objective: In preclinical research, in vivo imaging of mice and rats is more
common than any other animal species, since their physiopathology is very well-
known and many genetically altered disease models exist. Animal studies based on
small rodents are usually performed using dedicated preclinical imaging systems
with high spatial resolution. For studies that require animal models such as mini-
pigs or New-Zealand White (NZW) rabbits, imaging systems with larger bore
sizes are required. In case of hybrid imaging using Positron Emission Tomography
(PET) and Magnetic Resonance Imaging (MRI), clinical systems have to be used,
as these animal models do not typically fi t in preclinical simultaneous PET-MRI
scanners.
Approach. In this paper, we present initial imaging results obtained with the
Hyperion IID PET insert which can accommodate NZW rabbits when combined
with a large volume MRI RF coil. First, we developed a rabbit-sized image
quality phantom of comparable size to a NZW rabbit in order to evaluate the
PET imaging performance of the insert under high count rates. For this phantom,
radioactive spheres with inner diameters between 3.95 and 7.86 mm were visible
in a warm background with a tracer activity ratio of 4.1 to 1 and with a total
18-F activity in the phantom of 58MBq at measurement start. Second, we performed
simultaneous PET-MR imaging of atherosclerotic plaques in a rabbit in vivo using
a single injection containing 18-F-FDG for detection of infl ammatory activity,
and Gd-ESMA for visualization of the aortic vessel wall and plaques with MRI.
Main results. The fused PET-MR images reveal 18-F-FDG uptake within an
active plaques with plaque thicknesses in the sub-millimeter range. Histology
showed colocalization of 18-F-FDG uptake with macrophages in the aortic vessel wall lesions. 
Significance. Our initial results demonstrate that this PET insert
is a promising system for simultaneous high-resolution PET-MR atherosclerotic
plaque imaging studies in NZW rabbits., (Creative Commons Attribution license.)

Purpose: To develop a 3D free-breathing cardiac multi-parametric mapping framework that is robust to confounders of respiratory motion, fat, and B1+ inhomogeneities and validate it for joint myocardial T1 and T1ρ mapping at 3T., Methods: An electrocardiogram-triggered sequence with dual-echo Dixon readout was developed, where nine cardiac cycles were repeatedly acquired with inversion recovery and T1ρ preparation pulses for T1 and T1ρ sensitization. A subject-specific respiratory motion model relating the 1D diaphragmatic navigator to the respiration-induced 3D translational motion of the heart was constructed followed by respiratory motion binning and intra-bin 3D translational and inter-bin non-rigid motion correction. Spin history B1+ inhomogeneities were corrected with optimized dual flip angle strategy. After water-fat separation, the water images were matched to the simulated dictionary for T1 and T1ρ quantification. Phantoms and 10 heathy subjects were imaged to validate the proposed technique., Results: The proposed technique achieved strong correlation (T1: R 2  = 0.99; T1ρ: R 2  = 0.98) with the reference measurements in phantoms. 3D cardiac T1 and T1ρ maps with spatial resolution of 2 × 2 × 4 mm were obtained with scan time of 5.4 ± 0.5 min, demonstrating comparable T1 (1236 ± 59 ms) and T1ρ (50.2 ± 2.4 ms) measurements to 2D separate breath-hold mapping techniques. The estimated B1+ maps showed spatial variations across the left ventricle with the septal and inferior regions being 10%-25% lower than the anterior and septal regions., Conclusion: The proposed technique achieved efficient 3D joint myocardial T1 and T1ρ mapping at 3T with respiratory motion correction, spin history B1+ correction and water-fat separation., (© 2024 International Society for Magnetic Resonance in Medicine.)

Background: The diagnosis of myocarditis by CMR requires the use of T2 and T1 weighted imaging, ideally incorporating parametric mapping. Current 2D mapping sequences are acquired sequentially and involve multiple breath-holds resulting in prolonged scan times and anisotropic image resolution. We developed an isotropic free-breathing 3D whole-heart sequence which allows simultaneous T1 and T2 mapping and validated it in patients with suspected acute myocarditis., Methods: Eighteen healthy volunteers and 28 patients with suspected myocarditis underwent conventional 2D T1 and T2 mapping with whole heart coverage and 3D joint T1/T2 mapping on a 1.5T scanner. Acquisition time, image quality, and diagnostic performance were compared. Qualitative analysis was performed using a 4-point Likert scale. Bland-Altman plots were used to assess the quantitative agreement between 2D and 3D sequences., Results: The 3D T1/T2 sequence was acquired in 8mins 26s under free breathing, whereas 2D T1 and T2 sequences were acquired with breath holds in 11mins 44s (p=0.0001). All 2D images were diagnostic. For 3D images, 89% of T1 and 96% of T2 images were diagnostic with no significant difference in the proportion of diagnostic images for the 3D and 2D T1 (p=0.2482) and T2 maps (p=1.0000). Systematic bias in T1 was noted with biases of 102ms, 115ms, and 152ms for basal-apical segments, with a larger bias for higher T1 values. Good agreement between T2 values for 3D and 2D techniques was found (bias of 1.8ms, 3.9ms, and 3.6ms for basal-apical segments). The sensitivity and specificity of the 3D sequence for diagnosing acute myocarditis was 74% (95% confidence interval [CI] 49-91%) and 83% (36-100%) respectively, with an estimated c-statistic (95% CI) of 0.85 (0.79-0.91) and no statistically significant difference between the 2D and 3D sequences for the detection of acute myocarditis for T1 (p=0.2207) or T2 (p=1.0000)., Conclusion: Free-breathing whole heart 3D joint T1/T2 mapping was comparable to 2D mapping sequences with respect to diagnostic performance, but with the added advantages of free-breathing, and shorter scan times. Further work is required to address the bias noted at high T1 values, but this did not significantly impact on diagnostic accuracy., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests. Alina Hua reports financial support was provided by British Heart Foundation. Instutition support reports financial support was provided by National Institute for Health Research. Dr Karl P Kunze is an employee of Siemens Healthcare Limited. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Competing interests Dr Karl P Kunze is an employee of Siemens Healthcare Limited., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Atherosclerosis is a chronic inflammatory condition of the arteries and represents the primary cause of various cardiovascular diseases. Despite ongoing progress, finding effective anti-inflammatory therapeutic strategies for atherosclerosis remains a challenge. Here, we assessed the potential of molecular magnetic resonance imaging (MRI) to visualize the effects of 01BSUR, an anti-interleukin-1β monoclonal antibody, for treating atherosclerosis in a murine model. Male apolipoprotein E-deficient mice were divided into a therapy group (01BSUR, 2 × 0.3 mg/kg subcutaneously, n = 10) and control group (no treatment, n = 10) and received a high-fat diet for eight weeks. The plaque burden was assessed using an elastin-targeted gadolinium-based contrast probe (0.2 mmol/kg intravenously) on a 3 T MRI scanner. T1-weighted imaging showed a significantly lower contrast-to-noise (CNR) ratio in the 01BSUR group (pre: 3.93042664; post: 8.4007067) compared to the control group (pre: 3.70679168; post: 13.2982156) following administration of the elastin-specific MRI probe (p < 0.05). Histological examinations demonstrated a significant reduction in plaque size (p < 0.05) and a significant decrease in plaque elastin content (p < 0.05) in the treatment group compared to control animals. This study demonstrated that 01BSUR hinders the progression of atherosclerosis in a mouse model. Using an elastin-targeted MRI probe, we could quantify these therapeutic effects in MRI., (© 2024. The Author(s).)

Background: Active inflammatory bowel disease (A-IBD) but not remission (R-IBD) has been associated with an increased risk of cardiovascular death and hospitalization for heart failure., Objectives: Using cardiovascular magnetic resonance (CMR), this study aims to assess adverse myocardial remodeling in patients with IBD in correlation with disease activity., Methods: Forty-four IBD patients without cardiovascular disease (24 female, median-age: 39.5 years, 26 A-IBD, 18 R-IBD) and 44 matched healthy volunteers (HV) were prospectively enrolled. The disease stage was determined by endoscopic and patient-reported criteria. Participants underwent CMR for cardiac phenotyping: cine imaging and strain analysis were performed to assess ventricular function. T1 mapping, extracellular volume and late-gadolinium enhanced images were obtained to assess focal and diffuse myocardial fibrosis. Simultaneous T1 and T2 elevation (T1 > 1049.3 ms, T2 > 54 ms) was considered to indicate a myocardial segment was inflamed., Results: 16/44 (16.4%) IBD patients described dyspnea on exertion and 10/44 (22.7%) reported chest pain. A-IBD patients showed impaired ventricular function, indicated by reduced global circumferential and radial strain despite preserved left-ventricular ejection fraction. 16% of all IBD patients had focal fibrosis in a non-ischemic pattern. A-IDB patients had increased markers of diffuse left ventricular fibrosis (T1-values: A-IBD: 1022.0 ± 34.83 ms, R-IBD: 1010.10 ± 32.88 ms, HV: 990.61 ± 29.35 ms, p < .01). Significantly more participants with A-IDB (8/26, 30.8%) had at least one inflamed myocardial segment than patients in remission (0/18) and HV (1/44, 2.3%, p < .01). Markers of diffuse fibrosis correlated with disease activity., Conclusion: This study, using CMR, provides evidence of myocardial involvement and patterns of adverse left ventricular remodeling in patients with IBD., Clinical Trial Registration: ISRCTN30941346., (© 2024. The Author(s).)

Objectives: Visualizing left atrial anatomy including the pulmonary veins (PVs) is important for planning the procedure of pulmonary vein isolation with ablation in patients with atrial fibrillation (AF). The aims of our study are to investigate the feasibility of the 3D whole-heart bright-blood and black-blood phase-sensitive (BOOST) inversion recovery sequence in patients with AF scheduled for ablation or electro-cardioversion, and to analyze the correlation between image quality and heart rate and rhythm of patients., Methods: BOOST was performed for assessing PVs both with T2 preparation pre-pulse (T2prep) and magnetization transfer preparation (MTC) in 45 patients with paroxysmal or permanent AF scheduled for ablation or electro-cardioversion. Image quality analyses were performed by two independent observers. Qualitative assessment was made using the Likert scale; for quantitative analysis, signal to noise ratios (SNR) and contrast to noise ratios (CNR) were calculated for each PV. Heart rate and rhythm were analyzed based on standard 12-lead ECGs., Results: All MTC-BOOST acquisitions achieved diagnostic quality in the PVs, while a significant proportion of T2prep-BOOST images were not suitable for assessing PVs. SNR and CNR values of the MTC-BOOST bright-blood images were higher if patients had sinus rhythm. We found a significant or nearly significant negative correlation between heart rate and the SNR and CNR values of MTC-BOOST bright-blood images., Conclusion: 3D whole-heart MTC-BOOST bright-blood imaging is suitable for visualizing the PVs in patients with AF, producing diagnostic image quality in 100% of cases. However, image quality was influenced by heart rate and rhythm., Clinical Relevance Statement: The novel 3D whole-heart BOOST CMR sequence needs no contrast administration and is performed during free-breathing; therefore, it is easy to use for a wide range of patients and is suitable for visualizing the PVs in patients with AF., Key Points: • The applicability of the novel 3D whole-heart bright-blood and black-blood phase-sensitive sequence to pulmonary vein imaging in clinical practice is unknown. • Magnetization transfer-bright-blood and black-blood phase-sensitive imaging is suitable for visualizing the pulmonary veins in patients with atrial fibrillation with excellent or good image quality. • Bright-blood and black-blood phase-sensitive cardiac magnetic resonance sequence is easy to use for a wide range of patients as it needs no contrast administration and is performed during free-breathing., (© 2023. The Author(s).)

Background: Quantification of three-dimensional (3D) cardiac anatomy is important for the evaluation of cardiovascular diseases. Changes in anatomy are indicative of remodeling processes as the heart tissue adapts to disease. Although robust segmentation methods exist for computed tomography angiography (CTA), few methods exist for whole-heart cardiovascular magnetic resonance angiograms (CMRA) which are more challenging due to variable contrast, lower signal to noise ratio and a limited amount of labeled data., Methods: Two state-of-the-art unsupervised generative deep learning domain adaptation architectures, generative adversarial networks and variational auto-encoders, were applied to 3D whole heart segmentation of both conventional (n = 20) and high-resolution (n = 45) CMRA (target) images, given segmented CTA (source) images for training. An additional supervised loss function was implemented to improve performance given 10%, 20% and 30% segmented CMRA cases. A fully supervised nn-UNet trained on the given CMRA segmentations was used as the benchmark., Results: The addition of a small number of segmented CMRA training cases substantially improved performance in both generative architectures in both standard and high-resolution datasets. Compared with the nn-UNet benchmark, the generative methods showed substantially better performance in the case of limited labelled cases. On the standard CMRA dataset, an average 12% (adversarial method) and 10% (variational method) improvement in Dice score was obtained., Conclusions: Unsupervised domain-adaptation methods for CMRA segmentation can be boosted by the addition of a small number of supervised target training cases. When only few labelled cases are available, semi-supervised generative modelling is superior to supervised methods., (© 2023. The Author(s).)

Purpose To evaluate the feasibility of liver MR fingerprinting (MRF) for quantitative characterization and diagnosis of focal liver lesions. Materials and Methods This single-site, prospective study included 89 participants (mean age, 62 years ± 15 [SD]; 45 women, 44 men) with various focal liver lesions who underwent MRI between October 2021 and August 2022. The participants underwent routine clinical MRI, non-contrast-enhanced liver MRF, and reference quantitative MRI with a 1.5-T MRI scanner. The bias and repeatability of the MRF measurements were assessed using linear regression, Bland-Altman plots, and coefficients of variation. The diagnostic capability of MRF-derived T1, T2, T2*, proton density fat fraction (PDFF), and a combination of these metrics to distinguish benign from malignant lesions was analyzed according to the area under the receiver operating characteristic curve (AUC). Results Liver MRF measurements showed moderate to high agreement with reference measurements (intraclass correlation = 0.94, 0.77, 0.45, and 0.61 for T1, T2, T2*, and PDFF, respectively), with underestimation of T2 values (mean bias in lesion = -0.5%, -29%, 5.8%, and -8.2% for T1, T2, T2*, and PDFF, respectively). The median coefficients of variation for repeatability of T1, T2, and T2* values were 2.5% (IQR, 3.6%), 3.1% (IQR, 5.6%), and 6.6% (IQR, 13.9%), respectively. After considering multicollinearity, a combination of MRF measurements showed a high diagnostic performance in differentiating benign from malignant lesions (AUC = 0.92 [95% CI: 0.86, 0.98]). Conclusion Liver MRF enabled the quantitative characterization of various focal liver lesions in a single breath-hold acquisition. Keywords: MR Imaging, Abdomen/GI, Liver, Imaging Sequences, Technical Aspects, Tissue Characterization, Technology Assessment, Diagnosis, Liver Lesions, MR Fingerprinting, Quantitative Characterization Supplemental material is available for this article. © RSNA, 2023.

Purpose: To develop an open-source, high-performance, easy-to-use, extensible, cross-platform, and general MRI simulation framework (Koma)., Methods: Koma was developed using the Julia programming language. Like other MRI simulators, it solves the Bloch equations with CPU and GPU parallelization. The inputs are the scanner parameters, the phantom, and the pulse sequence that is Pulseq-compatible. The raw data is stored in the ISMRMRD format. For the reconstruction, MRIReco.jl is used. A graphical user interface utilizing web technologies was also designed. Two types of experiments were performed: one to compare the quality of the results and the execution speed, and the second to compare its usability. Finally, the use of Koma in quantitative imaging was demonstrated by simulating Magnetic Resonance Fingerprinting (MRF) acquisitions., Results: Koma was compared to two well-known open-source MRI simulators, JEMRIS and MRiLab. Highly accurate results (with mean absolute differences below 0.1% compared to JEMRIS) and better GPU performance than MRiLab were demonstrated. In an experiment with students, Koma was proved to be easy to use, eight times faster on personal computers than JEMRIS, and 65% of test subjects recommended it. The potential for designing acquisition and reconstruction techniques was also shown through the simulation of MRF acquisitions, with conclusions that agree with the literature., Conclusions: Koma's speed and flexibility have the potential to make simulations more accessible for education and research. Koma is expected to be used for designing and testing novel pulse sequences before implementing them in the scanner with Pulseq files, and for creating synthetic data to train machine learning models., (© 2023 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Introduction: Left atrial appendage (LAA) thrombus is the most common source of embolization in atrial fibrillation (AF). Transesophageal echocardiography (TEE) is the gold standard method for LAA thrombus exclusion. Our pilot study aimed to compare the efficacy of a new non-contrast-enhanced cardiac magnetic resonance (CMR) sequence (BOOST) with TEE for the detection of LAA thrombus and to evaluate the usefulness of BOOST images for planning radiofrequency catheter ablation (RFCA) compared with left atrial (LA) contrast-enhanced computed tomography (CT). We also attempted to assess the patients' subjective experiences with TEE and CMR., Methods: Patients with AF undergoing either electrical cardioversion or RFCA were enrolled. Participants underwent pre-procedural TEE and CMR scans to evaluate LAA thrombus status and pulmonary vein anatomy. Patient experiences with TEE and CMR were assessed using a questionnaire developed by our team. Some patients scheduled for RFCA also had pre-procedural LA contrast-enhanced CT. In such cases, the operating physician was asked to subjectively define the quality of the CT and CMR scan on a scale of 1-10 (1 = worst, 10 = best) and comment on CMR's usefulness in RFCA planning., Results: Seventy-one patients were enrolled. In 94.4%, both TEE and CMR excluded, and in 1 patient, both modalities reported the presence of LAA thrombus. In 1 patient, TEE was inconclusive, but CMR excluded LAA thrombus. In 2 patients, CMR could not exclude the presence of thrombus, but in 1 of those cases, TEE was also indecisive. During TEE, 67%, during CMR, only 1.9% of patients reported pain ( p  < 0.0001), and 89% would prefer CMR in case of a repeat examination. The quality of the left atrial contrast-enhanced CT scans was better compared with the image quality of the CMR BOOST sequence [8 (7-9) vs. 6 (5-7), p  < 0.0001]. Still, the CMR images were useful for procedural planning in 91% of cases., Conclusion: The new CMR BOOST sequence provides appropriate image quality for ablation planning. The sequence might be useful for excluding larger LAA thrombi; however, its accuracy in detecting smaller thrombi is limited. Most patients preferred CMR over TEE in this indication., Competing Interests: KK, RN, and MK are employees of Siemens Healthineers. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Orbán, Dohy, Suhai, Nagy, Salló, Boga, Kiss, Kunze, Neji, Botnar, Prieto, Gellér, Merkely, Vágó and Szegedi.)

The aim of this study was to investigate the diagnostic accuracy and reader confidence for late-gadolinium enhancement (LGE) detection of a novel free-breathing, image-based navigated 3D whole-heart LGE sequence with fat-water separation, compared to a free-breathing motion-corrected 2D LGE sequence in patients with ischemic and non-ischemic cardiomyopathy. Cardiac MRI patients including the respective sequences were retrospectively included. Two independent, blinded readers rated image quality, depiction of segmental LGE and documented acquisition time, SNR, CNR and amount of LGE. Results were compared using the Friedman or the Kruskal-Wallis test. For LGE rating, a jackknife free-response receiver operating characteristic analysis was performed with a figure of merit (FOM) calculation. Forty-two patients were included, thirty-two were examined with a 1.5 T-scanner and ten patients with a 3 T-scanner. The mean acquisition time of the 2D sequence was significantly shorter compared to the 3D sequence (07:12 min vs. 09:24 min; p < 0.001). The 3D scan time was significantly shorter when performed at 3 T compared to 1.5 T (07:47 min vs. 09:50 min; p < 0.001). There were no differences regarding SNR, CNR or amount of LGE. 3D imaging had a significantly higher FOM (0.89 vs. 0.78; p < 0.001). Overall image quality ratings were similar, but 3D sequence ratings were higher for fine anatomical structures. Free-breathing motion-corrected 3D LGE with high isotropic resolution results in enhanced LGE-detection with higher confidence and better delineation of fine structures. The acquisition time for 3D imaging was longer, but may be reduced by performing on a 3 T-scanner., (© 2022. The Author(s).)

Purpose: To develop a fast free-breathing whole-heart high-resolution myocardial T 1ρ mapping technique with robust spin-lock preparation that can be performed at 3 Tesla., Methods: An adiabatically excited continuous-wave spin-lock module, insensitive to field inhomogeneities, was implemented with an electrocardiogram-triggered low-flip angle spoiled gradient echo sequence with variable-density 3D Cartesian undersampling at a 3 Tesla whole-body scanner. A saturation pulse was performed at the beginning of each cardiac cycle to null the magnetization before T 1ρ preparation. Multiple T 1ρ -weighted images were acquired with T 1ρ preparations with different spin-lock times in an interleaved fashion. Respiratory self-gating approach was adopted along with localized autofocus to enable 3D translational motion correction of the data acquired in each heartbeat. After motion correction, multi-contrast locally low-rank reconstruction was performed to reduce undersampling artifacts. The accuracy and feasibility of the 3D T 1ρ mapping technique was investigated in phantoms and in vivo in 10 healthy subjects compared with the 2D T 1ρ mapping., Results: The 3D T 1ρ mapping technique provided similar phantom T 1ρ measurements in the range of 25-120 ms to the 2D T 1ρ mapping reference over a wide range of simulated heart rates. With the robust adiabatically excited continuous-wave spin-lock preparation, good quality 2D and 3D in vivo T 1ρ -weighted images and T 1ρ maps were obtained. Myocardial T 1ρ values with the 3D T 1ρ mapping were slightly longer than 2D breath-hold measurements (septal T 1ρ : 52.7 ± 1.4 ms vs. 50.2 ± 1.8 ms, P < 0.01)., Conclusion: A fast 3D free-breathing whole-heart T 1ρ mapping technique was proposed for T 1ρ quantification at 3 T with isotropic spatial resolution (2 mm 3 ) and short scan time of ∼4.5 min., (© 2022 International Society for Magnetic Resonance in Medicine.)

Background: Coronary artery disease (CAD) is the single most common cause of death worldwide. Recent technological developments with coronary cardiovascular magnetic resonance angiography (CCMRA) allow high-resolution free-breathing imaging of the coronary arteries at submillimeter resolution without contrast in a predictable scan time of ~ 10 min. The objective of this study was to determine the diagnostic accuracy of high-resolution CCMRA for CAD detection against the gold standard of invasive coronary angiography (ICA)., Methods: Forty-five patients (15 female, 62 ± 10 years) with suspected CAD underwent sub-millimeter-resolution (0.6 mm 3 ) non-contrast CCMRA at 1.5T in this prospective clinical study from 2019-2020. Prior to CCMR, patients were given an intravenous beta blockers to optimize heart rate control and sublingual glyceryl trinitrate to promote coronary vasodilation. Obstructive CAD was defined by lesions with ≥ 50% stenosis by quantitative coronary angiography on ICA., Results: The mean duration of image acquisition was 10.4 ± 2.1 min. On a per patient analysis, the sensitivity, specificity, positive predictive value and negative predictive value (95% confidence intervals) were 95% (75-100), 54% (36-71), 60% (42-75) and 93% (70-100), respectively. On a per vessel analysis the sensitivity, specificity, positive predictive value and negative predictive value (95% confidence intervals) were 80% (63-91), 83% (77-88), 49% (36-63) and 95% (90-98), respectively., Conclusion: As an important step towards clinical translation, we demonstrated a good diagnostic accuracy for CAD detection using high-resolution CCMRA, with high sensitivity and negative predictive value. The positive predictive value is moderate, and combination with CMR stress perfusion may improve the diagnostic accuracy. Future multicenter evaluation is now required., (© 2022. The Author(s).)

Artificial intelligence (AI) refers to the area of knowledge that develops computerised models to perform tasks that typically require human intelligence. These algorithms are programmed to learn and identify patterns from "training data," that can be subsequently applied to new datasets, without being explicitly programmed to do so. AI is revolutionising the field of medical imaging and in particular of Cardiovascular Magnetic Resonance (CMR) by providing deep learning solutions for image acquisition, reconstruction and analysis, ultimately supporting the clinical decision making. Numerous methods have been developed over recent years to enhance and expedite CMR data acquisition, image reconstruction, post-processing and analysis; along with the development of promising AI-based biomarkers for a wide spectrum of cardiac conditions. The exponential rise in the availability and complexity of CMR data has fostered the development of different AI models. Integration in clinical routine in a meaningful way remains a challenge. Currently, innovations in this field are still mostly presented in proof-of-concept studies with emphasis on the engineering solutions; often recruiting small patient cohorts or relying on standardised databases such as Multi-ethnic Study on atherosclerosis (MESA), UK Biobank and others. The wider incorporation of clinically valid endpoints such as symptoms, survival, need and response to treatment remains to be seen. This review briefly summarises the current principles of AI employed in CMR and explores the relevant prospective observational studies in cardiology patient cohorts. It provides an overview of clinical studies employing undersampled reconstruction techniques to speed up the scan encompassing cine imaging, whole-heart imaging, multi-parametric mapping and magnetic resonance fingerprinting along with the clinical utility of AI applications in image post-processing, and analysis. Specific focus is given to studies that have incorporated CMR-derived prediction models for prognostication in cardiac disease. It also discusses current limitations and proposes potential developments to enable multi-disciplinary collaboration for improved evidence-based medicine. AI is an extremely promising field and the timely integration of clinician's input in the ingenious technical investigator's paradigm holds promise for a bright future in the medical field., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Fotaki, Puyol-Antón, Chiribiri, Botnar, Pushparajah and Prieto.)

MRI is a versatile technique that offers many different options for tissue contrast, including suppressing the blood signal, so-called black-blood contrast. This contrast mechanism is extremely useful to visualize the vessel wall with high conspicuity or for characterization of tissue adjacent to the blood pool. In this review we cover the physics of black-blood contrast and different techniques to achieve blood suppression, from methods intrinsic to the imaging readout to magnetization preparation pulses that can be combined with arbitrary readouts, including flow-dependent and flow-independent techniques. We emphasize the technical challenges of black-blood contrast that can depend on flow and motion conditions, additional contrast weighting mechanisms (T 1 , T 2 , etc.), magnetic properties of the tissue, and spatial coverage. Finally, we describe specific implementations of black-blood contrast for different vascular beds. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 5., (© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.)

Physiological motion, such as cardiac and respiratory motion, during Magnetic Resonance (MR) image acquisition can cause image artifacts. Motion correction techniques have been proposed to compensate for these types of motion during thoracic scans, relying on accurate motion estimation from undersampled motion-resolved reconstruction. A particular interest and challenge lie in the derivation of reliable non-rigid motion fields from the undersampled motion-resolved data. Motion estimation is usually formulated in image space via diffusion, parametric-spline, or optical flow methods. However, image-based registration can be impaired by remaining aliasing artifacts due to the undersampled motion-resolved reconstruction. In this work, we describe a formalism to perform non-rigid registration directly in the sampled Fourier space, i.e. k-space. We propose a deep-learning based approach to perform fast and accurate non-rigid registration from the undersampled k-space data. The basic working principle originates from the Local All-Pass (LAP) technique, a recently introduced optical flow-based registration. The proposed LAPNet is compared against traditional and deep learning image-based registrations and tested on fully-sampled and highly-accelerated (with two undersampling strategies) 3D respiratory motion-resolved MR images in a cohort of 40 patients with suspected liver or lung metastases and 25 healthy subjects. The proposed LAPNet provided consistent and superior performance to image-based approaches throughout different sampling trajectories and acceleration factors.