Guest Editorial Special Issue on Medical Imaging and Image Computing in Computational Physiology

International audienceThe January 2013 Special Issue of IEEE transactions on medical imaging discusses papers on medical imaging and image computing in computational physiology. Aslanid and co-researchers present an experimental technique based on stained micro computed tomography (CT) images to construct very detailed atrial models of the canine heart. The paper by Sebastian proposes a model of the cardiac conduction system (CCS) based on structural information derived from stained calf tissue. Ho, Mithraratne and Hunter present a numerical simulation of detailed cerebral venous flow. The third category of papers deals with computational methods for simulating medical imagery and incorporate knowledge of imaging physics and physiology/biophysics. The work by Morales showed how the combination of device modeling and virtual deployment, in addition to patient-specific image-based anatomical modeling, can help to carry out patient-specific treatment plans and assess alternative therapeutic strategies

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

Methodologies to assess blood flow in cerebral aneurysms: Current state of research and perspectives

With intracranial aneurysms disease bringing a weakened arterial wall segment to initiate, grow and potentially rupture an aneurysm, current understanding of vessel wall biology perceives the disease to follow the path of a dynamic evolution and increasingly recognizes blood flow as being one of the main stakeholders driving the process. Although currently mostly morphological information is used to decide on whether or not to treat a yet unruptured aneurysm, among other factors, knowledge of blood flow parameters may provide an advanced understanding of the mechanisms leading to further aneurismal growth and potential rupture. Flow patterns, velocities, pressure and their derived quantifications, such as shear and vorticity, are today accessible by direct measurements or can be calculated through computation. This paper reviews and puts into perspective current experimental methodologies and numerical approaches available for such purposes. In our view, the combination of current medical imaging standards, numerical simulation methods and endovascular treatment methods allow for thinking that flow conditions govern more than any other factor fate and treatment in cerebral aneurysms. Approaching aneurysms from this perspective improves understanding, and while requiring a personalized aneurysm management by flow assessment and flow correction, if indicated

The detection of intracranial aneurysms by non-invasive imaging methods and the epidemiology of aneurysmal subarachnoid haemorrhage within the Scottish population

The aims of the research project, which led to the writing of this thesis were to: Examine whether non -invasive imaging methods could replace intra- arterial angiography (IADSA) in the detection of intracranial aneurysms by: a) systematically reviewing the literature; b) prospectively determining the accuracy of the non -invasive imaging methods currently available in Scotland, including the effect of observer experience on diagnostic performance and the patient acceptability of the alternative imaging modalities. To establish the incidence of aneurysmal subarachnoid haemorrhage (SAH) in families by a national retrospective study of occurrences of SAH in a one year period in Scotland, in parallel with a follow -up study of the families of patients who were admitted to the Institute of Neurosciences with aneurysmal SAH a decade earlier. The thesis is divided into three parts:PART ONE: a) summarises the current understanding of the epidemiology and pathophysiology of intracranial aneurysms; b) an overview of cerebrovascular anatomy with reference to aneurysm formation; c) the modalities available for imaging intracranial aneurysms and the current knowledge about their diagnostic performance are considered; d) an overview of the methods available for the treatment of intracranial aneurysms; e) the concept of screening for unruptured intracranial aneurysms is discussed and placed in context by comparison to other screening programmes.PART TWO: a) describes a systematic review of the non -invasive imaging of intracranial aneurysms. CT and MR angiography had similar accuracy compared to IADSA of ~90 %. Data on Transcranial Doppler Sonography (TCDS) were scanty but indicated poorer performance. Detection of very small aneurysms (<3mm diameter) was significantly poorer for the non -invasive tests; b) describes a prospective study of 200 patients examining CTA, MRA and TCDS vs IADSA in the detection of intracranial aneurysms. CTA and MRA had an accuracy (per subject) of 0.85. TCDS had similar accuracy per subject but poorer accuracy per aneurysm than CTA or MRA. Detection of aneurysms ≤5mm was significantly poorer than for those >5mm. Interobserver agreement was good for all modalities; c) combining TCDS with CTA or MRA improved the detection of aneurysms on a per subject basis. Non-invasive imaging tests, especially when used in combination, are reliable at detecting aneurysms >5mm; d) examines the effect of observer experience. Neuroradiologists were more consistent and had better agreement with IADSA than non - neuroradiologists. Small aneurysms and cavernous /terminal internal carotid aneurysms were poorly detected by all observers; e) assessment of patient preferences indicated that TCDS was preferred to the other non -invasive tests and CTA to MRA, with the differences being statistically significant.PART THREE describes: a) the rationale behind the epidemiological studies; b) the methodology used; c) describes the results: Comparative risk for 1st vs 2nd degree relatives suffering a SAH was 2.29 for the Scotland wide study (SWS) and 2.43 for the West of Scotland study (WOS). Absolute lifetime SAH risk was 4.7% for 1st degree and 1.9% for 2nd degree relatives in the SWS compared to 4.2% and 2.3% respectively in the WOS. Prospective 10 -year SAH risk was 1.2% for a 1st degree and 0.5% for a 2nd degree relative compared to background population risk of ~0.1%. The hierarchy of risk was greatest for a member of a family with ≥ 2 other 1st degree relatives affected by SAH, with a more than 20-fold increased risk over the background population risk; d) discusses the implications of the findings and examines the strengths and weaknesses of the study. Routine screening of families of patients who have had a SAH is not supported by these data; e) reviews the implications for i) clinical practice and ii) future research arising from the imaging and epidemiological studies

Inferring Geodesic Cerebrovascular Graphs: Image Processing, Topological Alignment and Biomarkers Extraction

A vectorial representation of the vascular network that embodies quantitative features - location, direction, scale, and bifurcations - has many potential neuro-vascular applications. Patient-specific models support computer-assisted surgical procedures in neurovascular interventions, while analyses on multiple subjects are essential for group-level studies on which clinical prediction and therapeutic inference ultimately depend. This first motivated the development of a variety of methods to segment the cerebrovascular system. Nonetheless, a number of limitations, ranging from data-driven inhomogeneities, the anatomical intra- and inter-subject variability, the lack of exhaustive ground-truth, the need for operator-dependent processing pipelines, and the highly non-linear vascular domain, still make the automatic inference of the cerebrovascular topology an open problem. In this thesis, brain vessels’ topology is inferred by focusing on their connectedness. With a novel framework, the brain vasculature is recovered from 3D angiographies by solving a connectivity-optimised anisotropic level-set over a voxel-wise tensor field representing the orientation of the underlying vasculature. Assuming vessels joining by minimal paths, a connectivity paradigm is formulated to automatically determine the vascular topology as an over-connected geodesic graph. Ultimately, deep-brain vascular structures are extracted with geodesic minimum spanning trees. The inferred topologies are then aligned with similar ones for labelling and propagating information over a non-linear vectorial domain, where the branching pattern of a set of vessels transcends a subject-specific quantized grid. Using a multi-source embedding of a vascular graph, the pairwise registration of topologies is performed with the state-of-the-art graph matching techniques employed in computer vision. Functional biomarkers are determined over the neurovascular graphs with two complementary approaches. Efficient approximations of blood flow and pressure drop account for autoregulation and compensation mechanisms in the whole network in presence of perturbations, using lumped-parameters analog-equivalents from clinical angiographies. Also, a localised NURBS-based parametrisation of bifurcations is introduced to model fluid-solid interactions by means of hemodynamic simulations using an isogeometric analysis framework, where both geometry and solution profile at the interface share the same homogeneous domain. Experimental results on synthetic and clinical angiographies validated the proposed formulations. Perspectives and future works are discussed for the group-wise alignment of cerebrovascular topologies over a population, towards defining cerebrovascular atlases, and for further topological optimisation strategies and risk prediction models for therapeutic inference. Most of the algorithms presented in this work are available as part of the open-source package VTrails