Optimization and Data Analysis in Biomedical Informatics

Abstract Intravascular ultrasound (IVUS) is a catheter-based medical imaging modality that is capable of providing cross-sectional images of the interior of blood vessels. A comprehensive analysis of the IVUS data allows collecting information about the morphology and structure of the vessel and the atherosclerotic plaque, if present. Atherosclerotic plaque formation is considered to be a part of an inflammatory process. Recent evidence has suggested that the presence and proliferation of vasa vasorum (VV) in the plaque is correlated with the increase of plaque inflammation and the processes which lead to its destabilization. Hence, the detection and measurement of VV in plaque has the potential to enable the development of an index of plaque vulnerability. In this paper, we review the research at the Computational Biomedicine Lab towards the development of a complete pipeline for the detection and quantification of extra-luminal blood detection from IVUS data which may be an indication of the existence of VV

Probabilistic segmentation of the lumen from intravascular ultrasound radio frequency data

Abstract. Intravascular ultrasound (IVUS) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels. In this paper, we present a method for the segmentation of the luminal border using IVUS radio frequency (RF) data. Specifically, we parameterize the lumen contour using Fourier series. This contour is deformed by minimizing a cost function that is formulated using a probabilistic approach in which the a priori term is obtained using the prediction confidence of a Support Vector Machine classifier using features extracted from the RF signal. We evaluated the performance of our method by comparing our results with manual segmentations from two expert observers on 280 frames from eight 40 MHz IVUS sequences from rabbits and pigs. The performance was evaluated using the Dice similarity coefficient, coefficient of determination, and linear regressions of the lumen area for each frame. Our results indicate the feasibility of our method for the segmentation of the lumen from IVUS RF data

Combination of the Level-Set Methods with the Contourlet Transform for the Segmentation of the IVUS Images

Intravascular ultrasound (IVUS) imaging is a catheter-based medical methodology establishing itself as a useful modality for studying atherosclerosis. The detection of lumen and media-adventitia boundaries in IVUS images constitutes an essential step towards the reliable quantitative diagnosis of atherosclerosis. In this paper, a novel scheme is proposed to automatically detect lumen and media-adventitia borders. This segmentation method is based on the level-set model and the contourlet multiresolution analysis. The contourlet transform decomposes the original image into low-pass components and band-pass directional bands. The circular hough transform (CHT) is adopted in low-pass bands to yield the initial lumen and media-adventitia contours. The anisotropic diffusion filtering is then used in band-pass subbands to suppress noise and preserve arterial edges. Finally, the curve evolution in the level-set functions is used to obtain final contours. The proposed method is experimentally evaluated via 20 simulated images and 30 real images from human coronary arteries. It is demonstrated that the mean distance error and the relative mean distance error have increased by 5.30 pixels and 7.45%, respectively, as compared with those of a recently traditional level-set model. These results reveal that the proposed method can automatically and accurately extract two vascular boundaries

Image and Signal Processing in Intravascular Ultrasound

Intravascular ultrasound (rvUS) is a new imaging mOdality providing real-time, crosssectional, high-resolution images of the arterial lumen and vessel wall. In contrast to conventional x-ray angiography that only displays silhouette views of the vessel lumen, IVUS imaging permits visualization of lesion morphology and accurate measurements of arterial cross-sectional dimensions in patients. These unique capabilities have led to many important clinical applications including quantitative assessment of the severity, restenosis, progression of atherosclerosis, selection and guidance of catheterbased therapeutic procedures and short- and long-term evaluation of the outcome of an intravascular intervention. Like the progress of other medial imaging modalities, the advent of IVUS techniques has brought in new challenges in the field of signal and image processing. Quantitative analysis of IVUS images requires the identification of arterial structures such as the lumen and plaque within an image. Manual contour tracing is well known to be time consuming and subjective. Development of an automated contour detection method may improve the reproducibility of quantitative IVUS and avoid a tedious manual procedure. Computerized three-dimensional (3D) reconstruction of an IVUS image series may extend the tomographic data to a more powerful volumetric assessment of the vessel segment. Obviously, this could not be achieved without the advance of 3D image processing techniques. Furthermore, it is demonstrated that processing of the original radio frequency (RF) echo signals provides an efficient means to improve the IVUS image quality as well as a new approach to extract volumetric flow information. The goals of the studies reported in this thesis are therefore directed toward development of video image and RF signal processing techniques for image enhancement, automated contour detection, 3D reconstruction and flow imaging. In this chapter several IVUS scanning mechanisms and some background information about ultrasonic imaging are briefly introduced. The principles of different video-based contour detection approaches and examples of contour detection in echocardiograms are discussed. Subsequently, applications of RF analysis in IVUS images are reviewed, followed by the scope of this thesis in the final part

Optical coherence tomography for the assessment of coronary atherosclerosis and vessel response after stent implantation

Optical Coherence Tomography (OCT) is a light-based imaging modality that can provide in vivo high-resolution images of the coronary artery with a level of resolution (axial 10-20 µm) ten times higher than intravascular ultrasound. The technique, uses low-coherent near infrarred light to create high-resolution cross sectional images of the vessel. The technology refinement achieved in the last years has made this imaging modality less procedurally demanding opening its possibilities for clinical use. The present thesis provides im

High-resolution intravascular magnetic resonance quantification of atherosclerotic plaque at 3T

<p>Abstract</p> <p>Background</p> <p>The thickness of fibrous caps (FCT) of atherosclerotic lesions is a critical factor affecting plaque vulnerability to rupture. This study tests whether 3 Tesla high-resolution intravascular cardiovascular magnetic resonance (CMR) employing tiny loopless detectors can identify lesions and accurately measure FCT in human arterial specimens, and whether such an approach is feasible <it>in vivo </it>using animal models.</p> <p>Methods</p> <p>Receive-only 2.2 mm and 0.8 mm diameter intravascular loopless CMR detectors were fabricated for a clinical 3 Tesla MR scanner, and the absolute signal-to-noise ratio determined. The detectors were applied in a two-step protocol comprised of CMR angiography to identify atherosclerotic lesions, followed by high-resolution CMR to characterize FCT, lesion size, and/or vessel wall thickness. The protocol was applied in fresh human iliac and carotid artery specimens in a human-equivalent saline bath. Mean FCT measured by 80 μm intravascular CMR was compared with histology of the same sections. <it>In vivo </it>studies compared aortic wall thickness and plaque size in healthy and hyperlipidemic rabbit models, with post-mortem histology.</p> <p>Results</p> <p>Histology confirmed plaques in human specimens, with calcifications appearing as signal voids. Mean FCT agreed with histological measurements within 13% on average (correlation coefficient, <it>R </it>= 0.98; Bland-Altman analysis, -1.3 ± 68.9 μm). <it>In vivo </it>aortic wall and plaque size measured by 80 μm intravascular CMR agreed with histology.</p> <p>Conclusion</p> <p>Intravascular 3T CMR with loopless detectors can both locate atherosclerotic lesions, and accurately measure FCT at high-resolution in a strategy that appears feasible <it>in vivo</it>. The approach shows promise for quantifying vulnerable plaque for evaluating experimental therapies.</p

Computer Vision Techniques for Transcatheter Intervention

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and treatment of cardiovascular diseases. For example, TAVI is an alternative to AVR for the treatment of severe aortic stenosis and TAFA is widely used for the treatment and cure of atrial fibrillation. In addition, catheter-based IVUS and OCT imaging of coronary arteries provides important information about the coronary lumen, wall and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial for the evaluation and treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation, motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods.We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence it is important to understand the application domain, clinical background, and imaging modality so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on background information of transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area

Intravascular ultrasound: a technique in evolution: methodological considerations

As the title of the thesis suggests, intravascular ultrasound has been, and continues to be, an imaging technique that is in active evolution. Image quality has improved dramatically from the crude, low resolution 'black and white' images of the first generation of intravascular ultrasound scanners and transducers are now small enough to image most arteries before intervention. Although intravascular ultrasound is increasingly seen as the most informative method of assessing the coronary arteries, there are outstanding problems that must be addressed and overcome before its full potential can be achieved.The aim of this thesis is to examine a number of these methodological shortcomings of intravascular ultrasound so that appropriate solutions can be found.After a general overview, provided in Chapter 1, the reproducibility of intravascular ultrasound quantitation is assessed in Chapter 2. For reasons elaborated above, ultrasound is seen as the best technique to study the acute and long term outcome of coronary interventions and the effect of plaque modifying agents. Without detailed data concerning its reproducibility, such studies are uninterpretable.Chapter 3 deals with the impact of catheter malfunction on the geometric integrity of intravascular ultrasound images. At present, the mechanical ultrasound devices are the most widely used systems. All mechanical systems are potentially subject to the problem of non -uniform rotation of the transducer, and to date its impact has been poorly characterised.The difficulty encountered in discriminating unstable coronary lesions is examined in Chapter 4. There is a widely held view that acute coronary lesions cannot be discriminated using intravascular ultrasound. Specific echographic markers are described that are found in the majority of unstable lesions. Close scrutiny of grey scale images allows identification of acute lesions and may allow discrimination of thrombus from underlying atheromatous plaque.In the last two chapters, methodological issues relating to the clinical application of intravascular ultrasound in guiding coronary stenting are explored. In chapter 5, the findings of an observational study confirm the potential of intravascular ultrasound to provide additional information in cases in which favourable angiographic appearances have been achieved. However, the choice of one particular 'expansion index' over another is seen to impact significantly on the proportion of lesions that are judged to be successful. Before ultrasound guidance based on the attainment of specific quantitative expansion criteria be advocated as a widely applied technique, the reproducibility of reference segment measurements must be known. This issue is studied in chapter 6.Separate studies are described in each of the data chapters. A similar layout is employed in each, consisting of the study aims, methods, findings, discussion and conclusion. At the risk of introducing a degree of repetition in the methods sections of each chapter, the ultrasound examination and image interpretation protocol are elaborated in each case, as important differences exist between the studies