Accelerated CMR using zonal, parallel and prior knowledge driven imaging methods

Accelerated imaging is highly relevant for many CMR applications as competing constraints with respect to spatiotemporal resolution and tolerable scan times are frequently posed. Three approaches, all involving data undersampling to increase scan efficiencies, are discussed in this review. Zonal imaging can be considered a niche but nevertheless has found application in coronary imaging and CMR flow measurements. Current work on parallel-transmit systems is expected to revive the interest in zonal imaging techniques. The second and main approach to speeding up CMR sequences has been parallel imaging. A wide range of CMR applications has benefited from parallel imaging with reduction factors of two to three routinely applied for functional assessment, perfusion, viability and coronary imaging. Large coil arrays, as are becoming increasingly available, are expected to support reduction factors greater than three to four in particular in combination with 3D imaging protocols. Despite these prospects, theoretical work has indicated fundamental limits of coil encoding at clinically available magnetic field strengths. In that respect, alternative approaches exploiting prior knowledge about the object being imaged as such or jointly with parallel imaging have attracted considerable attention. Five to eight-fold scan accelerations in cine and dynamic CMR applications have been reported and image quality has been found to be favorable relative to using parallel imaging alone

Improved 3D MR Image Acquisition and Processing in Congenital Heart Disease

Congenital heart disease (CHD) is the most common type of birth defect, affecting about 1% of the population. MRI is an essential tool in the assessment of CHD, including diagnosis, intervention planning and follow-up. Three-dimensional MRI can provide particularly rich visualization and information. However, it is often complicated by long scan times, cardiorespiratory motion, injection of contrast agents, and complex and time-consuming postprocessing. This thesis comprises four pieces of work that attempt to respond to some of these challenges. The first piece of work aims to enable fast acquisition of 3D time-resolved cardiac imaging during free breathing. Rapid imaging was achieved using an efficient spiral sequence and a sparse parallel imaging reconstruction. The feasibility of this approach was demonstrated on a population of 10 patients with CHD, and areas of improvement were identified. The second piece of work is an integrated software tool designed to simplify and accelerate the development of machine learning (ML) applications in MRI research. It also exploits the strengths of recently developed ML libraries for efficient MR image reconstruction and processing. The third piece of work aims to reduce contrast dose in contrast-enhanced MR angiography (MRA). This would reduce risks and costs associated with contrast agents. A deep learning-based contrast enhancement technique was developed and shown to improve image quality in real low-dose MRA in a population of 40 children and adults with CHD. The fourth and final piece of work aims to simplify the creation of computational models for hemodynamic assessment of the great arteries. A deep learning technique for 3D segmentation of the aorta and the pulmonary arteries was developed and shown to enable accurate calculation of clinically relevant biomarkers in a population of 10 patients with CHD

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Respiratory organ motion in interventional MRI : tracking, guiding and modeling

Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy. In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities. Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well. Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence

Magnetic resonance imaging and its applicability in veterinary cardiology

Magnetic Resonance Imaging (MRI) is a technique whereby images are created by the manipulation of hydrogen atoms in magnetic fields; it is based on the principle of nuclear magnetic resonance (MR), which is non-invasive and non-ionising (Constantine, Shan, Flamm, & Sivananthan, 2004). Cardiac Magnetic Resonance Imaging (CMRI) uses the same principle: application of magnetic-field gradients that are adjusted to highlight desired tissue characteristics, producing a variety of sequences that allow detection of cardiac tissue and blood, and consequently anatomical and/or physiological abnormalities (Jeudy & White, 2008; Constantine et al., 2004). Basic pulse sequences used in CMRI are spin-echo and gradient-echo sequences, or their faster hybrids dark- or black-blood and bright-blood respectively (Constantine et al., 2004). CMRI is rapidly developing and is now an important diagnostic tool in human clinical cardiology (Gilbert, McConnell, Holden, Sivananthan, & Dukes-McEwan, 2010). In veterinary medicine the use of CMRI is still sporadic; its limitations in this field include the need for general anaesthesia, the cost and availability of the equipment, the steep learning curve to obtain and analyse the images, and the time needed to manually trace endocardial borders if semi-automated analysis is not available (MacDonald, Kittleson, Garcia-Nolen, Larson, & Wisner, 2006). CMRI was considered to be the reference method in many veterinary studies (Eskofier, Wefstaedt, Beyerbach, Nolte, & Hungerbuhler, 2015; Fattal et al., 2015; Sargent et al., 2015). Still, not many studies have been published or made available in this field. It is therefore essential to fully ascertain the clinical applications, advantages and limitations of CMRI in veterinary medicine. The aim of this review is to identify the potential applications of CMRI from a clinical point of view and compare it with echocardiography, which is still the gold standard in veterinary cardiology. We describe the principles and technique of MRI in small animal cardiology, and the diseases in which CMRI could be an important tool for diagnosis and prognosis

A comparison between magnetic resonance angiography at 3 teslas (time-of-flight and contrast-enhanced) and flat-panel digital subtraction angiography in the assessment of embolized brain aneurysms

PURPOSE: To compare the time-of-flight and contrast-enhanced- magnetic resonance angiography techniques in a 3 Tesla magnetic resonance unit with digital subtraction angiography with the latest flat-panel technology and 3D reconstruction in the evaluation of embolized cerebral aneurysms. INTRODUCTION: Many embolized aneurysms are subject to a recurrence of intra-aneurismal filling. Traditionally, imaging surveillance of coiled aneurysms has consisted of repeated digital subtraction angiography. However, this method has a small but significant risk of neurological complications, and many authors have advocated the use of noninvasive imaging methods for the surveillance of embolized aneurysms. METHODS: Forty-three aneurysms in 30 patients were studied consecutively between November 2009 and May 2010. Two interventional neuroradiologists rated the time-of-flight-magnetic resonance angiography, the contrast-enhanced-magnetic resonance angiography, and finally the digital subtraction angiography, first independently and then in consensus. The status of aneurysm occlusion was assessed according to the Raymond scale, which indicates the level of recanalization according to degrees: Class 1: excluded aneurysm; Class 2: persistence of a residual neck; Class 3: persistence of a residual aneurysm. The agreement among the analyses was assessed by applying the Kappa statistic. RESULTS: Inter-observer agreement was excellent for both methods (K = 0.93; 95 % CI: 0.84-1). Inter-technical agreement was almost perfect between time-of-flight-magnetic resonance angiography and digital subtraction angiography (K = 0.98; 95 % CI: 0.93-1) and between time-of-flight-magnetic resonance angiography and contrast-enhanced-magnetic resonance angiography (K = 0.98; 95% CI: 0.93-1). Disagreement occurred in only one case (2.3%), which was classified as Class I by time-of-flight-magnetic resonance angiography and Class II by digital subtraction angiography. The agreement between contrast-enhanced-magnetic resonance angiography and digital subtraction angiography was perfect (K = 1; 95% CI: 1-1). In three patients, in-stent stenosis was identified by magnetic resonance angiography but not confirmed by digital subtraction angiography. CONCLUSION: Digital subtraction angiography and both 3T magnetic resonance angiography techniques have excellent reproducibility for the assessment of aneurysms embolized exclusively with coils. In those cases also treated with stent remodeling, digital subtraction angiography may still be necessary to confirm eventual parent artery stenosis, as identified by magnetic resonance angiography