State of the art: iterative CT reconstruction techniques

Owing to recent advances in computing power, iterative reconstruction (IR) algorithms have become a clinically viable option in computed tomographic (CT) imaging. Substantial evidence is accumulating about the advantages of IR algorithms over established analytical methods, such as filtered back projection. IR improves image quality through cyclic image processing. Although all available solutions share the common mechanism of artifact reduction and/or potential for radiation dose savings, chiefly due to image noise suppression, the magnitude of these effects depends on the specific IR algorithm. In the first section of this contribution, the technical bases of IR are briefly reviewed and the currently available algorithms released by the major CT manufacturers are described. In the second part, the current status of their clinical implementation is surveyed. Regardless of the applied IR algorithm, the available evidence attests to the substantial potential of IR algorithms for overcoming traditional limitations in CT imaging

Reconstruction of coronary arteries from X-ray angiography: A review.

Despite continuous progress in X-ray angiography systems, X-ray coronary angiography is fundamentally limited by its 2D representation of moving coronary arterial trees, which can negatively impact assessment of coronary artery disease and guidance of percutaneous coronary intervention. To provide clinicians with 3D/3D+time information of coronary arteries, methods computing reconstructions of coronary arteries from X-ray angiography are required. Because of several aspects (e.g. cardiac and respiratory motion, type of X-ray system), reconstruction from X-ray coronary angiography has led to vast amount of research and it still remains as a challenging and dynamic research area. In this paper, we review the state-of-the-art approaches on reconstruction of high-contrast coronary arteries from X-ray angiography. We mainly focus on the theoretical features in model-based (modelling) and tomographic reconstruction of coronary arteries, and discuss the evaluation strategies. We also discuss the potential role of reconstructions in clinical decision making and interventional guidance, and highlight areas for future research

Three-dimensional reconstruction of myocardial contrast perfusion from biplane cineangiograms by means of linear programming techniques

The assessment of coronary flow reserve from the instantaneous distribution of the contrast agent within the coronary vessels and myocardial muscle at the control state and at maximal flow has been limited by the superimposition of myocardial regions of interest in the two-dimensional images. To overcome these limitations, we are in the process of developing a three-dimensional (3D) reconstruction technique to compute the contrast distribution in cross sections of the myocardial muscle from two orthogonal cineangiograms. To limit the number of feasible solutions in the 3D-reconstruction space, the 3D-geometry of the endo- and epicardial boundaries of the myocardium must be determined. For the geometric reconstruction of the epicardium, the centerlines of the left coronary arterial tree are manually or automatically traced in the biplane views. Next, the bifurcations are detected automatically and matched in these two views, allowing a 3D-representation of the coronary tree. Finally, the circumference of the left ventricular myocardium in a selected cross section can be computed from the intersection points of this cross section with the 3D coronary tree using B-splines. For the geometric reconstruction of the left ventricular cavity, we envision to apply the elliptical approximation technique using the LV boundaries defined in the two orthogonal views, or by applying more complex 3D-reconstruction techniques including densitometry. The actual 3D-reconstruction of the contrast distribution in the myocardium is based on a linear programming technique (Transportation model) using cost coefficient matrices. Such a cost coefficient matrix must contain a maximum amount of a priori information, provided by a computer generated model and updated with actual data from the angiographic views. We have only begun to solve this complex problem. However, based on our first experimental results we expect that the linear programming approach with advanced cost coefficient matrices and computed model will lead to a

Coarctation of the aorta: pre and postoperative evaluation with MRI and MR angiography; correlation with echocardiography and surgery

Aims: To compare MRI and MRA with Doppler-echocardiography (DE) in native and postoperative aortic coarctation, define the best MR protocol for its evaluation, compare MR with surgical findings in native coarctation. Materials and methods: 136 MR studies were performed in 121 patients divided in two groups: Group I, 55 preoperative; group II, 81 postoperative. In group I, all had DE and surgery was performed in 35 cases. In group II, DE was available for comparison in 71 cases. MR study comprised: spin-echo, cine, velocity-encoded cine (VEC) sequences and 3D contrast-enhanced MRA. Results: In group I, diagnosis of coarctation was made by DE in 33 cases and suspicion of coarctation and/or aortic arch hypoplasia in 18 cases. Aortic arch was not well demonstrated in 3 cases and DE missed one case. There was a close correlation between VEC MRI and Doppler gradient estimates across the coarctation, between MRI aortic arch diameters and surgery but a poor correlation in isthmic measurements. In group II, DE detected a normal isthmic region in 31 out of 35 cases. Postoperative anomalies (recoarctation, aortic arch hypoplasia, kinking, pseudoaneurysm) were not demonstrated with DE in 50% of cases. Conclusions: MRI is superior to DE for pre and post-treatment evaluation of aortic coarctation. An optimal MR protocol is proposed. Internal measurement of the narrowing does not correspond to the external aspect of the surgical narrowin

Acceleration of Subtractive Non-contrast-enhanced Magnetic Resonance Angiography

Although contrast-enhanced magnetic resonance angiography (CE-MRA) is widely established as a clinical examination for the diagnosis of human vascular diseases, non-contrast-enhanced MRA (NCE-MRA) techniques have drawn increasing attention in recent years. NCE-MRA is based on the intrinsic physical properties of blood and does not require the injection of any exogenous contrast agents. Subtractive NCE-MRA is a class of techniques that acquires two image sets with different vascular signal intensity, which are later subtracted to generate angiograms. The long acquisition time is an important drawback of NCE-MRA techniques, which not only limits the clinical acceptance of these techniques but also renders them sensitive to artefacts from patient motion. Another problem for subtractive NCE-MRA is the unwanted residual background signal caused by different static background signal levels on the two raw image sets. This thesis aims at improving subtractive NCE-MRA techniques by addressing both these limitations, with a particular focus on three-dimensional (3D) femoral artery fresh blood imaging (FBI). The structure of the thesis is as follows: Chapter 1 describes the anatomy and physiology of the vascular system, including the characteristics of arteries and veins, and the MR properties and flow characteristics of blood. These characteristics are the foundation of NCE-MRA technique development. Chapter 2 introduces commonly used diagnostic angiographic methods, particularly CE-MRA and NCE-MRA. Current NCE-MRA techniques are reviewed and categorised into different types. Their principles, implementations and limitations are summarised. Chapter 3 describes imaging acceleration theories including compressed sensing (CS), parallel imaging (PI) and partial Fourier (PF). The Split Bregman algorithm is described as an efficient CS reconstruction method. The SPIRiT reconstruction for PI and homodyne detection for PF are also introduced and combined with Split Bregman to form the basis of the reconstruction strategy for undersampled MR datasets. Four image quality metrics are presented for evaluating the quality of reconstructed images. In Chapter 4, an intensity correction method is proposed to improve background suppression for subtractive NCE-MRA techniques. Residual signals of background tissues are removed by performing a weighted subtraction, in which the weighting factor is obtained by a robust regression method. Image sparsity can also be increased and thereby potentially benefit CS reconstruction in the following chapters. Chapter 5 investigates the optimal k-space sampling patterns for the 3D accelerated femoral artery FBI sequence. A variable density Poisson-disk with a fully sampled centre region and missing partial Fourier fractions is employed for k-space undersampling in the ky-kz plane. Several key parameters in sampling pattern design, such as partial Fourier sampling ratios, fully sampled centre region size and density decay factor, are evaluated and optimised. Chapter 6 introduces several reconstruction strategies for accelerated subtractive NCE-MRA. A new reconstruction method, k-space subtraction with phase and intensity correction (KSPIC), is developed. By performing subtraction in k-space, KSPIC can exploit the sparsity of subtracted angiogram data and potentially improve the reconstruction performance. A phase correction procedure is used to restore the polarity of negative signals caused by subtraction. The intensity correction method proposed in Chapter 4 is also incorporated in KSPIC as it improves background suppression and thereby sparsity. The highly accelerated technique can be used not only to reduce the acquisition time, but also to enable imaging with increased resolution with no time penalty. A time-efficient high-resolution FBI technique is proposed in Chapter 7. By employing KSPIC and modifying the flow-compensation/spoiled gradients, the image matrix size can be increased from 256×256 to up to 512×512 without prolonging the acquisition time. Chapter 8 summarises the overall achievements and limitations of this thesis, as well as outlines potential future research directions.Cambridge Trust China Scholarship Council Addenbrooke’s Charitable Trust National Institute of Health Research, Cambridge Biomedical Research Cente

Four-dimensional imaging of thoracic target volumes in conformal radiotherapy

The goal of conformal radiotherapy (CRT) is to deliver the prescribed dose to a volume that closely conforms to the three-dimensional (3D) target volume while the dose to adjacent healthy tissues or organs at risk is minimized. Because the position of the target volume can change substantially both within and between radiation treatment fractions the fourth dimension, namely time, needs to be addressed as well. The consideration of time in the 3D treatment process is referred to as fourdimensional (4D) radiotherapy. Variations in the target volume position with time are mainly due to organ motion and patient and beam set-up deviations. Changes in the target volume position that occur within a treatment fraction are referred to as intra-fraction variation. Respiratory and cardiac motion are the main contributors to intra-fraction positional variations of thoracic and abdominal target volumes. In routine clinical practice thoracic and abdominal tumors are irradiated while the patient breathes freely. To account for target volume variations in size, shape and position and patient and beam set-up deviations, an empirical 3D margin is added to the clinical target volume to obtain the planning target volume (1, 2). The 3D margin is often derived from respiratory motion measurements in patients representative of the general population. Such a margin is not tailored to the individual patient and will therefore be suboptimal in most cases. Alternatively, the tumor motion in a specific patient can be determined as part of the treatment planning procedure. Fluoroscopy is most widely used for this purpose. However, tumors are often poorly visualized using this imaging modality. In addition, fluoroscopic data cannot directly be related to the treatment planning computed tomography (CT) data