Review
Cardiac & Cardiovascular Systems
Ahmet Demirkiran, Pim van Ooij, Jos J. M. Westenberg, Mark B. M. Hofman, Hans C. van Assen, Linda J. Schoonmade, Usman Asim, Carmen P. S. Blanken, Aart J. Nederveen, Albert C. van Rossum, Marco J. W. Gotte
Summary: The identification of flow patterns within the heart is important for understanding cardiovascular diseases. Four-dimensional flow cardiovascular magnetic resonance imaging (4D flow CMR) is a novel tool that provides comprehensive assessment of flow through encoding velocity in all 3 directions. However, the analysis of 4D flow data is still complex and requires accurate analysis tools.
EUROPEAN HEART JOURNAL-CARDIOVASCULAR IMAGING
(2022)
Article
Cardiac & Cardiovascular Systems
Xiaodan Zhao, Ru-San Tan, Pankaj Garg, Ping Chai, Shuang Leng, Jennifer Bryant, Lynette L. S. Teo, Ching Ching Ong, Rob J. van der Geest, John C. Allen, James W. Yip, Ju Le Tan, Sven Plein, Jos J. W. Westenberg, Liang Zhong
Summary: A study established reference ranges for 4D flow CMR parameters among healthy Asian subjects, showing sex differences in retained inflow, residual volume, and some kinetic energy parameters, and age effects on certain parameters. Compared with Caucasian subjects, there were no significant differences in all studied parameters.
INTERNATIONAL JOURNAL OF CARDIOLOGY
(2021)
Article
Multidisciplinary Sciences
Theresa Reiter, Ingo Weiss, Oliver M. Weber, Wolfgang R. Bauer
Summary: Recent technical advancements have made it possible to perform cardiac MRI examinations at 3.0 T in the presence of MRI conditional active cardiac implants. However, susceptibility effects still cause artifact burden. This study presents a reproducible and highly defined approach to characterize signal void artifacts at 3.0 T and their influencing factors.
SCIENTIFIC REPORTS
(2022)
Review
Cardiac & Cardiovascular Systems
Sophie Paddock, Vasiliki Tsampasian, Hosamadin Assadi, Bruno Calife Mota, Andrew J. Swift, Amrit Chowdhary, Peter Swoboda, Eylem Levelt, Eva Sammut, Amardeep Dastidar, Jordi Broncano Cabrero, Javier Royuela Del Val, Paul Malcolm, Julia Sun, Alisdair Ryding, Chris Sawh, Richard Greenwood, David Hewson, Vassilios Vassiliou, Pankaj Garg
Summary: CMR imaging is a versatile tool for functional assessment and tissue characterisation. Emerging methods such as DTI and 4D flow CMR have the potential to offer personalized medicine approaches. Quantitative CMR is advancing with motion corrections in tissue characterisation and first-pass perfusion.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2021)
Review
Radiology, Nuclear Medicine & Medical Imaging
Paul R. Roos, Friso M. Rijnberg, Jos J. M. Westenberg, Hildo J. Lamb
Summary: This article systematically reviews the methods, clinical value, clinical applications, and current developments of particle tracing based on 4D Flow MRI. The results show that particle tracing methods often use an adaptive timestep, fourth order Runge-Kutta integration method, and linear interpolation in the time dimension. Particle tracing is applied in various cardiovascular areas. Further studies are needed to evaluate the clinical value of this technique in different cardiovascular diseases.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Review
Cardiac & Cardiovascular Systems
Jiaxing Jason Qin, Ben Indja, Alireza Gholipour, Mustafa Gok, Stuart M. Grieve
Summary: There is increasing recognition of the value of four-dimensional flow cardiovascular magnetic resonance (4D-flow MRI) in detecting and measuring abnormal flow behavior in early left ventricular dysfunction. This systematic review examines the current literature on the role of 4D-flow MRI-derived flow parameters in quantifying left ventricular function, with a focus on potential clinical applicability. However, there is considerable variability in methodologies and analyses, limiting the collective power of the studies in evaluating clinical applicability. Larger scale investigations and standardization of methodologies are needed for broader clinical application of 4D-flow MRI.
JOURNAL OF CARDIOVASCULAR DEVELOPMENT AND DISEASE
(2022)
Article
Biophysics
Marie Schafstedde, Lina Jarmatz, Jan Bruening, Markus Huellebrand, Sarah Nordmeyer, Andreas Harloff, Anja Hennemuth
Summary: This study assesses age-related differences of thoracic aorta blood flow profiles and provides age- and sex-specific reference values using 4D flow cardiovascular magnetic resonance (CMR) data. The results show age-related differences in blood flow parameters in the ascending aorta, with higher values for NFD and angle and lower values for WPD and A80 in older subjects. These age- and sex-specific reference values for quantitative parameters describing blood flow within the aorta might help to study the clinical relevance of flow profiles in the future.
PHYSIOLOGICAL MEASUREMENT
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Barbara Elisabeth Ursula Burkhardt, Christian Johannes Kellenberger, Fraser Maurice Callaghan, Emanuela Regina Valsangiacomo Buechel, Julia Geiger
Summary: In this study, the net flow volumes in the ascending aorta and pulmonary arteries were measured using four different postprocessing software packages for 4D flow MRI and compared with 2D cine phase-contrast measurements. The results showed that the 4D flow MRI-derived data matched the 2D PC values, indicating its readiness for clinical use in patients with CHD.
Article
Radiology, Nuclear Medicine & Medical Imaging
Mariana Bustamante, Federica Viola, Jan Engvall, Carl-Johan Carlhall, Tino Ebbers
Summary: This study aimed to develop and evaluate a deep learning-based segmentation method for automatically segmenting the cardiac chambers and great thoracic vessels from 4D flow MRI. The results demonstrated that the deep learning-based method achieved good segmentation accuracy.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Review
Cardiac & Cardiovascular Systems
Ayah Elsayed, Kathleen Gilbert, Miriam Scadeng, Brett R. Cowan, Kuberan Pushparajah, Alistair A. Young
Summary: 4D flow CMR shows potential in assessing rTOF, particularly in retrospective valve tracking for flow evaluation, velocity profiling, intra-cardiac kinetic energy quantification, and vortex visualization. Protocols should be targeted to pathology. Prospective, randomized, multi-centered studies are required to validate these new characteristics and establish their clinical use.
JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
(2021)
Article
Multidisciplinary Sciences
Dennis Korthals, Grigorios Chatzantonis, Michael Bietenbeck, Claudia Meier, Philipp Stalling, Ali Yilmaz
Summary: The study found that CMR-based T1-mapping and ECV measurement are more accurate in diagnosing cardiac amyloidosis (CA) compared to longitudinal strain analysis. ECV was identified as the most significant predictor for distinguishing CA from hypertrophic cardiomyopathy (HCM).
SCIENTIFIC REPORTS
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Lei Zhang, Fang-Fang Yin, Tian Li, Xinzhi Teng, Haonan Xiao, Wendy Harris, Lei Ren, Feng-Ming Spring Kong, Hong Ge, Ronghu Mao, Jing Cai
Summary: The MC-4D-MRI technique developed in this study expands single image contrast 4D-MRI to a spectrum of native and synthetic image contrasts, showing enhancements in image contrast variety, tumor contrast, and ITV contouring consistencies in liver tumor patients. This technique offers new perspectives on the image contrast of MRI and 4D-MRI in MR-guided radiotherapy.
Review
Radiology, Nuclear Medicine & Medical Imaging
Baiyan Zhuang, Arlene Sirajuddin, Shihua Zhao, Minjie Lu
Summary: 4D flow MRI utilizes blood flow encoding in three directions to comprehensively and accurately quantify and visualize hemodynamic parameters. It is widely used in various parts of the body and plays a crucial role in modern clinical practice.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
(2021)
Review
Cardiac & Cardiovascular Systems
Malenka M. Bissell, Francesca Raimondi, Lamia Ait Ali, Bradley D. Allen, Alex J. Barker, Ann Bolger, Nicholas Burris, Carl-Johan Carhaell, Jeremy D. Collins, Tino Ebbers, Christopher J. Francois, Alex Frydrychowicz, Pankaj Garg, Julia Geiger, Hojin Ha, Anja Hennemuth, Michael D. Hope, Albert Hsiao, Kevin Johnson, Sebastian Kozerke, Liliana E. Ma, Michael Markl, Duarte Martins, Marci Messina, Thekla H. Oechtering, Pim van Ooij, Cynthia Rigsby, Jose Rodriguez-Palomares, Arno A. W. Roest, Alejandro Roldan-Alzate, Susanne Schnell, Julio Sotelo, Matthias Stuber, Ali B. Syed, Johannes Toeger, Rob van der Geest, Jos Westenberg, Liang Zhong, Yumin Zhong, Oliver Wieben, Petter Dyverfeldt
Summary: This consensus paper provides an updated overview of the importance of four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) in the diagnosis and management of cardiovascular disease. It discusses sequence options, imaging considerations, acquisition parameters, post-processing workflows, and integration into clinical practice. The paper also defines quality assurance and validation standards for clinical centers, addresses challenges in the research setting, and includes a checklist for publication standards.
JOURNAL OF CARDIOVASCULAR MAGNETIC RESONANCE
(2023)
Article
Multidisciplinary Sciences
Shanmukha Srinivas, Evan Masutani, Alexander Norbash, Albert Hsiao
Summary: This study evaluated the impact of background phase errors on cerebrovascular flow volume measurements and assessed the effectiveness of manual image-based correction. It also explored the potential of a convolutional neural network (CNN) to directly infer the phase-error correction field. The results showed that manual correction improved the correlation and reduced the variance of flow measurements. The CNN correction was found to be non-inferior to manual correction, indicating its potential for fully automating phase error correction.
SCIENTIFIC REPORTS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Kelly Jarvis, Michael B. Scott, Gilles Soulat, Mohammed S. M. Elbaz, Alex J. Barker, James C. Carr, Michael Markl, Ann Ragin
Summary: This study characterized the pulse wave velocity (PWV) in the thoracic aorta using 4D flow MRI in a cohort of healthy adults. The results showed that PWV increased significantly with age, and there were significant differences between different age groups. PWV was also found to be correlated with decline in cardiac function and reduced aortic blood flow velocity.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2022)
Review
Cardiac & Cardiovascular Systems
Vasiliki Tsampasian, Sandeep S. Hothi, Thuwarahan Ravindrarajah, Andrew J. Swift, Pankaj Garg, Vassilios S. Vassiliou
Summary: Cardiovascular magnetic resonance (CMR) imaging has had a significant impact on understanding disease processes and mechanisms. It has played a crucial role in the diagnosis and risk stratification of valvular heart disease patients. CMR allows for detailed evaluation of left ventricular volumes and mass, providing insights into the hemodynamic impact of valvular lesions on the myocardium. Additionally, CMR techniques such as feature tracking, T1 mapping, and late gadolinium enhancement (LGE) imaging offer valuable information on myocardial deformation, strain parameters, and tissue characterization, aiding in risk assessment and management of patients.
CARDIOLOGY RESEARCH AND PRACTICE
(2022)
Article
Cardiac & Cardiovascular Systems
Pankaj Garg, Rebecca Gosling, Peter Swoboda, Rachel Jones, Alexander Rothman, Jim M. Wild, David G. Kiely, Robin Condliffe, Samer Alabed, Andrew J. Swift
Summary: CMR can estimate LVFP in patients with suspected HF and has prognostic power.
EUROPEAN HEART JOURNAL
(2022)
Article
Cardiac & Cardiovascular Systems
Li-Hsin Cheng, Pablo B. J. Bosch, Rutger F. H. Hofman, Timo B. Brakenhoff, Eline F. Bruggemans, Rob J. van der Geest, Eduard R. Holman
Summary: In this study, a deep learning method was developed for automated detection of impaired left ventricular function and aortic valve regurgitation from apical 4-chamber ultrasound cineloops. The study showed that deep learning methods can detect diseases in a different way than conventionally agreed on methods, and potentially reveal unforeseen diagnostic image features.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2022)
Article
Cardiac & Cardiovascular Systems
Jeroen Venlet, Sebastiaan R. Piers, Jarieke Hoogendoorn, Alexander F. A. Androulakis, Marta de Riva, Rob J. van der Geest, Katja Zeppenfeld
Summary: Transmural activation delay in right ventricular cardiomyopathy can be used to identify ventricular tachycardia substrates, which is important for treatment.
Editorial Material
Cardiac & Cardiovascular Systems
Rebecca Gosling, Andrew J. Swift, Pankaj Garg
EUROPEAN HEART JOURNAL
(2023)
Article
Physics, Fluids & Plasmas
Abdulaziz Al Baraikan, Krzysztof Czechowicz, Paul D. Morris, Ian Halliday, Rebecca C. Gosling, Julian P. Gunn, Andrew J. Narracott, Gareth Williams, Pankaj Garg, Maciej Malawski, Frans van de Vosse, Angela Lungu, Dan Rafiroiu, David Rodney Hose
Summary: Based on clinical patient data, we have developed a framework using hierarchical, multi-stage data handling protocols and mathematical models to quantify the burden of ischaemia. Our core tool is a compartmental, zero-dimensional model of the circulation system, which includes heart chambers, circulations, and coronary arteries. By validating with patient data, we have demonstrated the capability of our model to represent physiological states and assess the impact of coronary artery disease on individuals.
Article
Computer Science, Artificial Intelligence
Michail Mamalakis, Pankaj Garg, Tom Nelson, Justin Lee, Andrew J. Swift, James M. Wild, Richard H. Clayton
Summary: This study aimed to develop a novel framework and cost function for optimal automatic segmentation of the left ventricle with scars using LGE-MRI images. The study found that the traditional computer vision technique delivered more accurate results than deep learning, except in cases of breath misalignment error. The developed framework achieved robust and generalized results, offering a valuable tool for experts to accomplish fully automatic segmentation of the left ventricle with scars based on a single-modality cardiac scan.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Cardiac & Cardiovascular Systems
Pankaj Garg, Michael Markl, Janarthanan Sathananthan, Stephanie L. Sellers, Chris Meduri, Joao Cavalcante
Summary: Aortic blood flow patterns are closely related to cardiovascular diseases, and abnormal aortic flow patterns are associated with adverse cardiovascular outcomes. Novel aortic valve interventions can be used to regulate aortic flow patterns, improving patient outcomes.
NATURE REVIEWS CARDIOLOGY
(2023)
Article
Cardiac & Cardiovascular Systems
Ciaran Grafton-Clarke, Pankaj Garg, Andrew J. Swift, Samer Alabed, Ross Thomson, Nay Aung, Bradley Chambers, Joel Klassen, Eylem Levelt, Jonathan Farley, John P. Greenwood, Sven Plein, Peter P. Swoboda
Summary: In this study, CMR-derived LVFP was found to be associated with signs, symptoms, and prognosis in patients with recently diagnosed heart failure. Raised CMR-derived LVFP was independently associated with HF hospitalization and major adverse cardiovascular events.
Editorial Material
Cardiac & Cardiovascular Systems
Hosamadin Assadi, Rimma Hall, Pankaj Garg
EUROPEAN HEART JOURNAL-CASE REPORTS
(2023)
Editorial Material
Cardiac & Cardiovascular Systems
Hosamadin Assadi, Jordi Broncano, Daniel Carrasco Fernandez, Pankaj Garg
EUROPEAN HEART JOURNAL-CASE REPORTS
(2023)
Article
Medicine, General & Internal
Ciaran Grafton-Clarke, Gareth Matthews, Rebecca Gosling, Peter Swoboda, Alexander Rothman, Jim M. Wild, David G. Kiely, Robin Condliffe, Samer Alabed, Andrew J. Swift, Pankaj Garg, Marco Fogante
Summary: This study aimed to evaluate a simple CMR-derived model for estimating pulmonary capillary wedge pressure (PCWP) in patients with heart failure. The results showed that the model had good diagnostic accuracy and predictive value for mortality.
MEDICINA-LITHUANIA
(2023)
Review
Medicine, General & Internal
Hosamadin Assadi, Samer Alabed, Ahmed Maiter, Mahan Salehi, Rui Li, David P. Ripley, Rob J. Van der Geest, Yumin Zhong, Liang Zhong, Andrew J. Swift, Pankaj Garg
Summary: This systematic review assessed the use of artificial intelligence (AI) in cardiac magnetic resonance imaging (CMR) to predict outcomes in patients with cardiovascular disease. Three methods demonstrated high prognostic accuracy: three-dimensional motion assessment in pulmonary hypertension, automated perfusion quantification in coronary artery disease, and automated volumetric, functional, and area assessment in myocardial infarction.
MEDICINA-LITHUANIA
(2022)
