Heart failure is a leading cause of mortality in the Western world. The mouse is a widely used model for a number of diseases, induced by genetic modification or surgical intervention. When performing experiments in mice, in vivo magnetic resonance imaging (MRI) can be used to evaluate heart anatomy and function at multiple levels. Volumetric measurements of ventricle size at each phase of the heart cycle (obtained with cine MRI) can be used as a sensitive measure for heart failure. Cine MRI is applied here to genetic models of heart disease, including stress tests with pharmacological manipulation. As the long duration of the acquisition for functional assessment is a critical limitation, a new method to make cine MRI twelve times faster is presented and validated, maintaining standard accuracy. The method utilises a combination of compressed sensing and parallel imaging with a radial acquisition of k-space. Eddy-current induced artifacts, present when acquiring radially, are corrected retrospectively with a novel scheme. Tissue viability can be measured with late gadolinium enhancement (LGE) imaging, where a contrast agent is utilised. After injection, the agent rapidly washes out of healthy tissue, though has a slower kinetic in infarcted regions. A novel method to perform LGE efficiently is presented and validated against histology. This method is applied to the evaluation of a new treatment for infarction. Finally, a novel method to perform a multi-modal assessment of the mouse heart within a single exam is presented. The method includes cine and LGE MRI as well as a measure of mechanical strain in the myocardium with displacement encoding with stimulated echoes (DENSE) MRI and assessment of cellular metabolism with positron emission tomography (PET). This method is demonstrated in the evaluation of a new protective agent for infarction.
Purpose: Bowel motion is a significant source of artifacts in mouse abdominal MRI. Fasting and administration of hyoscine butylbromide (BUSC) have been proposed for bowel motion reduction, but with inconsistent results and limited efficacy assessments. Here, we evaluate these regimes for mouse abdominal MRI at high field. Methods: Thirty-two adult C57BL/6J mice were imaged on a 9.4T scanner with a FLASH sequence, acquired over 90 minutes with ~19s temporal resolution. During MRI acquisition, eight mice were injected with a low-dose and eight mice with a high-dose bolus of BUSC (0.5 and 5 mg/kg…
Cardiac Magnetic Resonance Imaging (MRI) is time-consuming and error-prone. To ease the patient's burden and to increase the efficiency and robustness of cardiac exams, interest in methods based on continuous steady-state acquisition and self-gating has been growing in recent years. Self-gating methods extract the cardiac and respiratory signals from the measurement data and then retrospectively sort the data into cardiac and respiratory phases. Repeated breathholds and synchronization with the heart beat using some external device as required in conventional MRI are then not necessary. In thi…
Cardiac cine magnetic resonance imaging (MRI) can be considered the optimal criterion for measuring cardiac function. This imaging technique can provide us with detailed information about cardiac structure, tissue composition and even blood flow. This work considers the application of the higher order dynamic mode decomposition (HODMD) method to a set of MR images of a heart, with the ultimate goal of identifying the main patterns and frequencies driving the heart dynamics. A novel algorithm based on singular value decomposition combined with HODMD is introduced, providing a three-dimensional …
Rensselaer Polytechnic Institute（伦斯勒理工学院）；Cedars-Sinai Medical Center（西达赛奈医疗中心）；University of California, Los Angeles（加州大学洛杉矶分校）
Cine cardiac magnetic resonance imaging (MRI) is widely used for diagnosis of cardiac diseases thanks to its ability to present cardiovascular features in excellent contrast. As compared to computed tomography (CT), MRI, however, requires a long scan time, which inevitably induces motion artifacts and causes patients' discomfort. Thus, there has been a strong clinical motivation to develop techniques to reduce both the scan time and motion artifacts. Given its successful applications in other medical imaging tasks such as MRI super-resolution and CT metal artifact reduction, deep learning is a…
MRI-guided cardiac radiotherapy using a 1.5 T MR-linac: surveying emerging patterns of care
University Medical Center Utrecht（乌得勒支大学医学中心）；University of Texas MD Anderson Cancer Center（德克萨斯大学安德森癌症中心）；Allegheny Health Network（阿勒格尼健康网络）；GenesisCare（创生医疗）
GE Global Research Center（GE全球研究中心）；Technische Universität München（慕尼黑工业大学）；INSERM（法国国家健康与医学研究院）；Université de Lorraine（洛林大学）；GE Healthcare（GE医疗）
To develop an efficient motion-compensated reconstruction technique for free-breathing cardiac magnetic resonance imaging (MRI) that allows high-quality images to be reconstructed from multiple undersampled single-shot acquisitions. The proposed method is a joint image reconstruction and motion correction method consisting of several steps, including a non-rigid motion extraction and a motion-compensated reconstruction. The reconstruction includes a denoising with the Beltrami regularization, which offers an ideal compromise between feature preservation and staircasing reduction. Results were …
Imperial College London（帝国理工学院）；Royal Brompton Hospital（皇家布朗普顿医院）
Segmentation of cardiac fibrosis and scar are essential for clinical diagnosis and can provide invaluable guidance for the treatment of cardiac diseases. Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been successful for its efficacy in guiding the clinical diagnosis and treatment reliably. For LGE CMR, many methods have demonstrated success in accurately segmenting scarring regions. Co-registration with other non-contrast-agent (non-CA) modalities, balanced steady-state free precession (bSSFP) and cine magnetic resonance imaging (MRI) for example, can further en…
Personalized Topology-Informed Localization of Standard 12-Lead ECG Electrode Placement from Incomplete Cardiac MRIs for Efficient Cardiac Digital Twins
School of Electronics & Computer Science, University of Southampton（南安普顿大学电子与计算机科学学院）；University of Oxford（牛津大学）；National University of Singapore（新加坡国立大学）；School of Biomedical Engineering and Imaging Sciences, Kings College London（伦敦国王学院生物医学工程与影像科学学院）
University of Auckland（奥克兰大学）；Johns Hopkins Medical Center（约翰斯·霍普金斯医疗中心）；University of Wisconsin School of Medicine and Public Health（威斯康星大学医学与公共卫生学院）；Aalborg University（奥尔堡大学）；Auckland Bioengineering Institute（奥克兰生物工程研究所）；Eindhoven University of Technology（埃因霍温理工大学）
The shape and motion of the heart provide essential clues to understanding the mechanisms of cardiovascular disease. With the advent of large-scale cardiac imaging data, statistical atlases become a powerful tool to provide automated and precise quantification of the status of patient-specific heart geometry with respect to reference populations. The Multi-Ethnic Study of Atherosclerosis (MESA), begun in 2000, was the first large cohort study to incorporate cardiovascular MRI in over 5000 participants, and there is now a wealth of follow-up data over 20 years. Building a machine learning based…
Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg（生物医学工程人工智能系，埃尔朗根-纽伦堡弗里德里希-亚历山大大学）；Department of Biomedical Engineering, The Ohio State University（生物医学工程系，俄亥俄州立大学）；Research & Clinical Translation, Magnetic Resonance, Siemens Healthineers AG（研究与临床转化，磁共振，西门子医疗有限公司）；Division of Cardiovascular Medicine, The Ohio State University（心血管医学系，俄亥俄州立大学）
Fudan University（复旦大学）；Imperial College London（帝国理工学院）；University of Oxford（牛津大学）；Zhongshan Hospital Affiliated to Fudan University（复旦大学附属中山医院）
The quality of cardiac magnetic resonance (CMR) imaging is susceptible to respiratory motion artifacts. The model robustness of automated segmentation techniques in face of real-world respiratory motion artifacts is unclear. This manuscript describes the design of extreme cardiac MRI analysis challenge under respiratory motion (CMRxMotion Challenge). The challenge aims to establish a public benchmark dataset to assess the effects of respiratory motion on image quality and examine the robustness of segmentation models. The challenge recruited 40 healthy volunteers to perform different breath-ho…
Universidad de Valladolid（巴利亚多利德大学）；King’s College London（伦敦国王学院）；Instituto Superior Técnico, Universidade de Lisboa（里斯本大学高等技术学院）；Centre for Marine Sciences - CCMAR（海洋科学中心（CCMAR））
First-pass perfusion cardiac magnetic resonance (FPP-CMR) is becoming an essential non-invasive imaging method for detecting deficits of myocardial blood flow, allowing the assessment of coronary heart disease. Nevertheless, acquisitions suffer from relatively low spatial resolution and limited heart coverage. Compressed sensing (CS) methods have been proposed to accelerate FPP-CMR and achieve higher spatial resolution. However, the long reconstruction times have limited the widespread clinical use of CS in FPP-CMR. Deep learning techniques based on supervised learning have emerged as alternat…
