Patient-specific modelling of the cerebral circulation for aneurysm risk assessment

Cerebral aneurysms are localised pathological dilatations of cerebral arteries, most commonly found in the circle of Willis. Although not all aneurysms are unstable, the major clinical concern involved is the risk of rupture. High morbidity and mortality rates are associated with the haemorrhage resulting from rupture. New indicators of aneurysm stability are sought, since current indicators based on morphological factors have been shown to be unreliable. Haemodynamical factors are known to be relevant in vascular wall remodelling, and therefore believed to play an important role in aneurysmdevelopment and stability. Studies suggest that intra-aneurysmal wall shear stress and flow patterns, for example, are candidate parameters in aneurysm stability assessment. These factors can be estimated if the 3D patient-specific intra-aneurysmal velocity is known, which can be obtained via a combination of in vivo measurements and computational fluid dynamics models. The main determinants of the velocity field are the vascular geometry and flow through this geometry. Over the last decade the extraction of the vascular geometry has become well established. More recently, there has been a shift of attention towards extracting boundary conditions for the 3D vascular segment of interest. The aim of this research is to improve the reliability of the model-based representation of the velocity field in the aneurysmal sac. To this end, a protocol is proposed such that patient-specific boundary conditions for the 3D segment of interest can be estimated without the need for added invasive procedures. This is facilitated by a 1D wave propagation model based on patient-specific geometry and boundary conditions measured non-invasively in more accessible regions. Such a protocol offers improved statistical reliability owing to the increased number of patients that can participate in studies aiming to identify parameters of interest in aneurysm stability assessment. In chapter 2 the intra-aneurysmal velocity field in an idealised aneurysm model is validated with particle image velocimetry experiments, after which the flow patterns are evaluated using a vortex identification method. Chapter 3 describes a 1D model wave propagation model of the cerebral circulation with a patient-specific vascular geometry. The resulting flow pulses at the boundaries of the 3D segment of interest are compared to those obtained with a patient-generic geometry. The influence of these different boundary conditions on the 3D intra-aneurysmal velocity field is evaluated in chapter 4 by prescribing the end-diastolic flows extracted from the 1D models. In order to measure blood flow with videodensitometric methods, an injection of contrast agent is required. The effect of this injection on the flow of interest is assessed in chapter 5. In chapter 6, pressure measurements in the internal carotid are used to evaluate the variability of pressure waveform and its effect on the boundary conditions for the 1D model. Finally, a protocol for full patient-specific modelling is discussed in chapter 7

3D reconstruction of cerebral blood flow and vessel morphology from x-ray rotational angiography

Three-dimensional (3D) information on blood flow and vessel morphology is important when assessing cerebrovascular disease and when monitoring interventions. Rotational angiography is nowadays routinely used to determine the geometry of the cerebral vasculature. To this end, contrast agent is injected into one of the supplying arteries and the x-ray system rotates around the head of the patient while it acquires a sequence of x-ray images. Besides information on the 3D geometry, this sequence also contains information on blood flow, as it is possible to observe how the contrast agent is transported by the blood. The main goal of this thesis is to exploit this information for the quantitative analysis of blood flow. I propose a model-based method, called flow map fitting, which determines the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent transport to determine the flow parameters from the spatio-temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the c-arm using a reliability map. For the flow quantification, small changes to the clinical protocol of rotational angiography are desirable. These, however, hamper the standard 3D reconstruction. Therefore, a new method for the 3D reconstruction of the vessel morphology which is tailored to this application is also presented. To the best of my knowledge, I have presented the first quantitative results for blood flow quantification from rotational angiography. Additionally, the model-based approach overcomes several problems which are known from flow quantification methods for planar angiography. The method was mainly validated on images from different phantom experiments. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. Additionally, the applicability of the flow model was shown on clinical images from planar angiographic acquisitions. From this, I conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions

CT dose optimization with model based iterative reconstruction

The aim of this thesis is to assess the feasibility of using model-based iterative reconstruction (MBIR) to develop new low-dose CT (computed tomography) protocols in the areas of neck, chest, and abdominal imaging without compromising diagnostic performance. Medical imaging has become the largest source of radiation exposure for humans other than natural background radiation. The availability of and improvements in diagnostic imaging have led to a sevenfold increase in the use of imaging over the past 30 years. This is especially true for CT, with a 7.8% annual increase in the use of CT from 1996 to 2010. The major concern associated with the widespread uptake of CT is the parallel increase in radiation exposure incurred by patients, and while the relationship of diagnostic radiation exposure to a quantifiable risk of cancer induction remains a controversial topic, physicians are beholden to keep radiation doses from diagnostic imaging as low as reasonably possible to limit the risk of radiation-induced cancer. We conducted preliminary phantom and cadaveric studies to examine the performance of MBIR at different radiation dose levels in the thorax and abdomen. Cadavers and phantoms provide a means of safely assessing new technologies and optimizing scan protocols prior to clinical validation. An anthropomorphic torso phantom and 5 human cadavers were scanned at varying radiation dose levels and images reconstructed using three different reconstruction techniques: filtered back projection, hybrid IR and MBIR. MBIR reduced image noise and improved image quality even in CT images acquired with a mean radiation dose reduction of 62%, compared with conventional dose studies reconstructed with hybrid IR, with lower levels of objective image noise, superior diagnostic acceptability and contrast resolution, and comparable subjective image noise and streak artifact scores. We subsequently performed clinical studies with the objectives of assessing MBIR as a tool for image quality improvement and radiation dose reduction in CT, and for the development of new low-dose carotid angiography, chest, and abdominopelvic CT protocols. We developed a low-dose carotid CTA protocol reconstructed with MBIR comparable to a conventional dose CTA protocol in terms of image quality and diagnostic accuracy while enabling a dose reduction of 49.6%. 20 patients were scanned using a split-dose technique with radiation dose divided into a low-dose acquisition reconstructed with MBIR and a conventional dose acquisition reconstructed with hybrid IR. Mean effective dose was significantly lower for the low-dose studies (1.84mSv versus 3.71mSv) and subjective image noise, contrast resolution, and spatial resolution were significantly higher for the low-dose studies. There was excellent agreement for stenosis grading accuracy between low- and conventional dose studies (Cohen κ = 0.806). A modified low-dose CT thorax protocol reconstructed with MBIR was also developed to monitor pulmonary disease progression in patients with cystic fibrosis with our low-dose protocol enabling the acquisition of a full-volume diagnostic quality chest CT at a dose equivalent to that of a chest radiograph (0.09±0.01mSv). Finally, we assessed the feasibility of low-dose abdominopelvic CT performed with MBIR as a radiation dose reduction strategy for imaging patients presenting with acute abdominal pain. A 74.7% mean radiation dose reduction was achieved with scans performed in the peri- and submillisievert range in patients of normal and low BMI, respectively, without compromising diagnostic performance. Dose reduction to the submillisievert range for patients with an elevated BMI was a challenge. The current era is extremely exciting in terms of radiation dose optimization in CT. This thesis is a demonstration of the potential for substantial reductions in radiation exposure, when the benefits of iterative reconstruction are combined with automated tube current modulation and other CT scanner technologies. The combination of all these hardware and software developments is now seeing major benefits for the patient and moving beyond the narrow aim of radiation exposure reduction to a complete change in practice, towards replacement of conventional radiography with low-dose CT, without any penalty for the patient in terms of radiation exposure