MRI changes in visceral fat in Crohn’s Disease

Crohn’s Disease (CD) is a chronic inflammatory disease of the gastrointestinal tract affecting 115,000 people in the UK alone. As a chronic illness, CD management requires a stepwise escalation of treatment measures tethered with constant monitoring of the disease activity levels and progression. Hence, non-invasive disease activity assessment methods form an essential part of the treatment process. Endoscopy is considered to be the traditional method for CD diagnosis and disease activity assessment which is invasive and may be uncomfortable for patients. As traditional MRI-based disease assessment methods rely on intravenous gadolinium for contrast enhancement, CD patients typically undergo repeated exposure to gadolinium administration which adds cost and carries the risk of nephrogenic systemic fibrosis, allergic reaction, and long-term brain deposition following repeated use. Hence, the development of contrast-free MRI-based disease activity metrics eliminates the risks associated with gadolinium and allows for a more frequent assessment of the disease progression. However, all developed cross-sectional CD activity metrics so far rely on a visual assessment by radiologists which can be subjective and time-consuming. The aim of this thesis is to examine established radiological hallmarks of CD and employ MRI imaging sequences along with image processing techniques to generate objective and quantitative disease activity measurements. The first part of this thesis investigates visceral fat hypertrophy also known as fat wrapping which refers to an abnormal growth of the mesenteric fat to partially cover the small or large intestine. While fat wrapping has been established as a characteristic of CD, the complex nature of visceral fat hinders detailed analysis of the effect of fat wrapping. Hence, an automated abdominal fat segmentation algorithm was developed to generate an objective measure of abdominal fat volumes which was used to study the differences in visceral fat revealing significant differences between CD patients and healthy volunteers. The second part of the thesis examines mesenteric blood flow in CD patients. CD is known to be associated with hypervascularity of the mesentery, including vascular dilation and wide spacing of the vasa recta. The arteries supply the small bowel branch to a series of intestinal arteries within the mesentery. A second algorithm was developed to automatically trace abdominal vessels on a time-of-flight MRA scans and measure the number of vessels’ branching points which also revealed significant differences between CD patients and HVs. This research has demonstrated the potential for MRI and image processing techniques to provide objective and quantitative measurements of disease activity in CD. The development of automated algorithms for abdominal fat segmentation and vessel tracing allows for a more accurate and efficient assessment of key radiological hallmarks of CD which are often overlooked. These techniques have the potential to improve the management of CD by providing non-invasive and more frequent assessments of disease activity and progression, without the risks associated with traditional contrast-enhanced methods

IMAGE PROCESSING, SEGMENTATION AND MACHINE LEARNING MODELS TO CLASSIFY AND DELINEATE TUMOR VOLUMES TO SUPPORT MEDICAL DECISION

Techniques for processing and analysing images and medical data have become the main’s translational applications and researches in clinical and pre-clinical environments. The advantages of these techniques are the improvement of diagnosis accuracy and the assessment of treatment response by means of quantitative biomarkers in an efficient way. In the era of the personalized medicine, an early and efficacy prediction of therapy response in patients is still a critical issue. In radiation therapy planning, Magnetic Resonance Imaging (MRI) provides high quality detailed images and excellent soft-tissue contrast, while Computerized Tomography (CT) images provides attenuation maps and very good hard-tissue contrast. In this context, Positron Emission Tomography (PET) is a non-invasive imaging technique which has the advantage, over morphological imaging techniques, of providing functional information about the patient’s disease. In the last few years, several criteria to assess therapy response in oncological patients have been proposed, ranging from anatomical to functional assessments. Changes in tumour size are not necessarily correlated with changes in tumour viability and outcome. In addition, morphological changes resulting from therapy occur slower than functional changes. Inclusion of PET images in radiotherapy protocols is desirable because it is predictive of treatment response and provides crucial information to accurately target the oncological lesion and to escalate the radiation dose without increasing normal tissue injury. For this reason, PET may be used for improving the Planning Treatment Volume (PTV). Nevertheless, due to the nature of PET images (low spatial resolution, high noise and weak boundary), metabolic image processing is a critical task. The aim of this Ph.D thesis is to develope smart methodologies applied to the medical imaging field to analyse different kind of problematic related to medical images and data analysis, working closely to radiologist physicians. Various issues in clinical environment have been addressed and a certain amount of improvements has been produced in various fields, such as organs and tissues segmentation and classification to delineate tumors volume using meshing learning techniques to support medical decision. In particular, the following topics have been object of this study: • Technique for Crohn’s Disease Classification using Kernel Support Vector Machine Based; • Automatic Multi-Seed Detection For MR Breast Image Segmentation; • Tissue Classification in PET Oncological Studies; • KSVM-Based System for the Definition, Validation and Identification of the Incisinal Hernia Reccurence Risk Factors; • A smart and operator independent system to delineate tumours in Positron Emission Tomography scans; 3 • Active Contour Algorithm with Discriminant Analysis for Delineating Tumors in Positron Emission Tomography; • K-Nearest Neighbor driving Active Contours to Delineate Biological Tumor Volumes; • Tissue Classification to Support Local Active Delineation of Brain Tumors; • A fully automatic system of Positron Emission Tomography Study segmentation. This work has been developed in collaboration with the medical staff and colleagues at the: • Dipartimento di Biopatologia e Biotecnologie Mediche e Forensi (DIBIMED), University of Palermo • Cannizzaro Hospital of Catania • Istituto di Bioimmagini e Fisiologia Molecolare (IBFM) Centro Nazionale delle Ricerche (CNR) of Cefalù • School of Electrical and Computer Engineering at Georgia Institute of Technology The proposed contributions have produced scientific publications in indexed computer science and medical journals and conferences. They are very useful in terms of PET and MRI image segmentation and may be used daily as a Medical Decision Support Systems to enhance the current methodology performed by healthcare operators in radiotherapy treatments. The future developments of this research concern the integration of data acquired by image analysis with the managing and processing of big data coming from a wide kind of heterogeneous sources

MRI changes in visceral fat in Crohn’s Disease

Crohn’s Disease (CD) is a chronic inflammatory disease of the gastrointestinal tract affecting 115,000 people in the UK alone. As a chronic illness, CD management requires a stepwise escalation of treatment measures tethered with constant monitoring of the disease activity levels and progression. Hence, non-invasive disease activity assessment methods form an essential part of the treatment process. Endoscopy is considered to be the traditional method for CD diagnosis and disease activity assessment which is invasive and may be uncomfortable for patients. As traditional MRI-based disease assessment methods rely on intravenous gadolinium for contrast enhancement, CD patients typically undergo repeated exposure to gadolinium administration which adds cost and carries the risk of nephrogenic systemic fibrosis, allergic reaction, and long-term brain deposition following repeated use. Hence, the development of contrast-free MRI-based disease activity metrics eliminates the risks associated with gadolinium and allows for a more frequent assessment of the disease progression. However, all developed cross-sectional CD activity metrics so far rely on a visual assessment by radiologists which can be subjective and time-consuming. The aim of this thesis is to examine established radiological hallmarks of CD and employ MRI imaging sequences along with image processing techniques to generate objective and quantitative disease activity measurements. The first part of this thesis investigates visceral fat hypertrophy also known as fat wrapping which refers to an abnormal growth of the mesenteric fat to partially cover the small or large intestine. While fat wrapping has been established as a characteristic of CD, the complex nature of visceral fat hinders detailed analysis of the effect of fat wrapping. Hence, an automated abdominal fat segmentation algorithm was developed to generate an objective measure of abdominal fat volumes which was used to study the differences in visceral fat revealing significant differences between CD patients and healthy volunteers. The second part of the thesis examines mesenteric blood flow in CD patients. CD is known to be associated with hypervascularity of the mesentery, including vascular dilation and wide spacing of the vasa recta. The arteries supply the small bowel branch to a series of intestinal arteries within the mesentery. A second algorithm was developed to automatically trace abdominal vessels on a time-of-flight MRA scans and measure the number of vessels’ branching points which also revealed significant differences between CD patients and HVs. This research has demonstrated the potential for MRI and image processing techniques to provide objective and quantitative measurements of disease activity in CD. The development of automated algorithms for abdominal fat segmentation and vessel tracing allows for a more accurate and efficient assessment of key radiological hallmarks of CD which are often overlooked. These techniques have the potential to improve the management of CD by providing non-invasive and more frequent assessments of disease activity and progression, without the risks associated with traditional contrast-enhanced methods

New Techniques in Gastrointestinal Endoscopy

As result of progress, endoscopy has became more complex, using more sophisticated devices and has claimed a special form. In this moment, the gastroenterologist performing endoscopy has to be an expert in macroscopic view of the lesions in the gut, with good skills for using standard endoscopes, with good experience in ultrasound (for performing endoscopic ultrasound), with pathology experience for confocal examination. It is compulsory to get experience and to have patience and attention for the follow-up of thousands of images transmitted during capsule endoscopy or to have knowledge in physics necessary for autofluorescence imaging endoscopy. Therefore, the idea of an endoscopist has changed. Examinations mentioned need a special formation, a superior level of instruction, accessible to those who have already gained enough experience in basic diagnostic endoscopy. This is the reason for what these new issues of endoscopy are presented in this book of New techniques in Gastrointestinal Endoscopy

Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

Recent advances in clinical practice: advances in cross-sectional imaging in inflammatory bowel disease

Endoscopy remains the reference standard for the diagnosis and assessment of patients with inflammatory bowel disease (IBD), but it has several important limitations. Cross-sectional imaging techniques such as magnetic resonance enterography (MRE) and intestinal ultrasound (IUS) are better tolerated and safer. Moreover, they can examine the entire bowel, even in patients with stenoses and/or severe inflammation. A variety of cross-sectional imaging activity scores strongly correlate with endoscopic measures of mucosal inflammation in the colon and terminal ileum. Unlike endoscopy, cross-sectional techniques allow complete visualisation of the small-bowel and assess for extraintestinal disease, which occurs in nearly half of patients with IBD. Extramural findings may predict outcomes better than endoscopic mucosal assessment, so cross-sectional techniques might help identify more relevant therapeutic targets. Coupled with their high sensitivity, these advantages have made MRE and IUS the primary non-invasive options for diagnosing and monitoring Crohn’s disease; they are appropriate first-line investigations, and have become viable alternatives to colonoscopy. This review discusses cross-sectional imaging in IBD in current clinical practice as well as research lines that will define the future role of these techniques

A Supervised Learning Approach for Crohn's Disease Detection Using Higher-Order Image Statistics and a Novel Shape Asymmetry Measure

Increasing incidence of Crohn's disease (CD) in the Western world has made its accurate diagnosis an important medical challenge. The current reference standard for diagnosis, colonoscopy, is time-consuming and invasive while magnetic resonance imaging (MRI) has emerged as the preferred noninvasive procedure over colonoscopy. Current MRI approaches assess rate of contrast enhancement and bowel wall thickness, and rely on extensive manual segmentation for accurate analysis. We propose a supervised learning method for the identification and localization of regions in abdominal magnetic resonance images that have been affected by CD. Low-level features like intensity and texture are used with shape asymmetry information to distinguish between diseased and normal regions. Particular emphasis is laid on a novel entropy-based shape asymmetry method and higher-order statistics like skewness and kurtosis. Multi-scale feature extraction renders the method robust. Experiments on real patient data show that our features achieve a high level of accuracy and perform better than two competing method

Establishing volumetric biomarkers in MRI of the digestive tract

This extended abstract describes the background to the 14 research papers that the author, as staff candidate, is submitting for the award of PhD by published works. The core part of this work refers to the development of volumetric biomarkers within the human digestive tract using magnetic resonance imaging (MRI) and their application to answer novel biomedical research questions. In particular the author’s work has focussed on applying these techniques within the human colon and the first two papers (which detail this work) were led and written by the author. This work was pioneering in its field, the first time that physiologically undisturbed colon volumes were measured in healthy human subjects and in patients suffering from irritable bowel syndrome (IBS) and provided novel insights into the post-prandial symptoms experienced. Subsequently the effect of an experimental stress on this post prandial response was evaluated in healthy subjects, also the first time such an effect had been measured. The third paper, also written by the author, describes her work on the first clinical application of similar volumetric techniques to assess the human nasal airways and their response to pharmacological intervention, in this case the efficacy of a nasal decongestant. This document seeks to set the gastro-intestinal papers within their scientific and physiological background and to show their original contribution to the current understanding of the physiological processes within the human gastro-intestinal tract. Between mouth and anus, a complex myriad of mechanical, chemical and biological procedures interact to liquefy and transport food; to break it down into increasingly simpler chemical forms; absorb nutrients and then eject what is no longer required. MRI provides a unique window into the functions and form of this environment at the macroscopic level; a non-invasive tool for detecting and measuring the structure and physical movements of the abdominal organs and their contents, monitoring fluid transport and providing insights into the biological processing therein. This can provide quantitative biomarkers to rigorously assess the normal undisturbed physiology in health and disease and the effect of pharmacological interventions. It is a hitherto relatively unexplored area and it is the development and application of such measurements that form the bulk of the author’s research contained within the presented publications