Analytic tools for content and shape analysis in 3D brain images Pedro Alexander Díaz Quiroga Departamento de Ingeniería de Sistemas y Computación Universidad de los Andes A thesis submitted for the degree of Maestría en ingeniería de información Agosto, 2019 2 Gratitude I would like to thank my thesis director, Professor Jose Tiberio Hernandez for his guidance and advice during this thesis process. In the same way, I want to thank Dr. Nathalie Charpak for her constant support and answers to my concerns. I would also like to thank Dr. Jorge Marín, Dr. Diego Angulo and engineer Alejandra Castelblanco, who collaborated with me, framing the project within an even larger project of added value for industry and society. Finally, I thank my family. 3 Abstract This document is the product of the work done for the master´s degree in information engineering project of the author, which aims to add value to the information asset of the Canguro program, (http://fundacioncanguro.co/), concerning the study of the development of premature patients and specifically, the impact of different aspects of the environment in the brain of said patients. The project takes the brain images of subjects from different ages, environments and genders and provides tools that allow to visualize and group the subjects according to physical characteristics of the structures of their brain, such as volume and shape. 4 1 Contents CHAPTER 1. INTRODUCTION 7 CHAPTER 2. GENERAL PROJECT DESCRIPTION 8 2.1 Objectives 8 2.2 Background 8 2.3 Problem Definition and Significance 9 CHAPTER 3. PROJECT STATEMENT AND SPECIFICATIONS 11 3.1 Problem description 11 3.2 Design description 11 3.3 Data profiling 12 CHAPTER 4. PROJECT DEVELOPMENT 25 4.1 Referential Framework 25 4.2 Design proposal 45 CHAPTER 5 IMPLEMENTATION 55 5.1 Description 55 5.2 Dependencies 56 5.3 Studied Parameters 56 CHAPTER 6 USE CASES 64 6.1 Application possibilities 72 6.2 Dimensionality reduction 75 6.3 Some Cases observed 78 CHAPTER 7 CONCLUSIONS 89 5 7.1 Future Work 89 REFERENCES 91 6 Chapter 1. Introduction The purpose of this graduation project is to take advantage of the data that is available in the Canguro Foundation in Colombia, related to the brain images of patients taken during 20 years of follow-up since their premature birth. This data was exploited during the execution of the project, and the results were shown to medical experts for interpretation. Exploitation of the data in this context means to understand it, to transform it into an adequate format and to convert it into visual and statistical information for medical doctors to interact with. The characteristics of the data refer to the shape and content of the functional structures of the patients’ brain. It is based on the hypothesis that these characteristics are influenced by environmental elements in which the subject develops. This document is structured as follows: First, a summary the of state-of-the- art context is presented; then the design proposal defined to achieve the project’s objective is described; next, the elements that form part of the solution in the implementation are detailed; the study case, which has been designed in the simplest possible way is described next and finally the results and conclusions o are presented. 7 Chapter 2. General project description 2.1 Objectives Gather variables related to the volume, shape and content of brain structures and generate tools as input to the analysis of experts that allows them to create new hypotheses and / or generate new knowledge Present a summary of the review of the available tools to validate the value provided through the proposed tools in this project Contribute with the computation of new variables related to the volume, shape and content of the brain structures, such as relative mass center and determine its possible contribution in the characterization of the subjects of study Test with the expert users the developed tools through real data coming from the 20-year investigation of the kangaroo program in Bogotá 2.2 Background There are several references that are used as antecedents of this thesis. First, the following references suggest that the forms of brain structures and functions can characterize subjects ([17] Sherbondy et al., 2005; [21] Wang, Qi et al., 2016; [1] Cabral, Joana et al., 2017). However, it is not easy to find a study in which there are more than 100 subjects in periods of time greater than 3 years. There are several factors that make this kind of studies difficult: The process of taking brain images is not easy and requires time, money and patience from subjects and researchers. 8 Due to the so-called cerebral plasticity, the functions of the subject may not always be associated with certain structural forms. This makes the study complicated due to the large number of possibilities that may arise. There are many possible variables to consider which makes the problem not easy to handle. There are already many open tools that have been refined and in many cases they present much more information than what is actually used, because of its huge quantity and diversity and where a possible application is not perceived or because information engineers have not interacted with the doctors and researchers to generate valuable knowledge from these sources. There are references related to the comparison between the most important tools available, whose objective is to quantify the accuracy of the measurements. This is the case of ([16] Morey, Rajendra A et al., 2009), comparing structures such as the hippocampus and the amygdala. There are other references in which techniques are exposed to characterize a 3D shape in brain investigations such as the analysis of intracranial aneurysms ([15] Meuschke, Monique et al., 2018); tractography in the human brain ([17] Sherbondy et al., 2005); surface registration of cortical areas ([20] Tardif, Christine Lucas et al., 2015); cerebral microstructural subdivision ([7] Fischl, Bruceet al., 2018); Analysis of the shape of the cerebral ventricles ([11] Gerig, G et al., 2001); Brain split based on connectivity ([21] Wang, Qi al., 2016), etc. 2.3 Problem Definition and Significance The human brain is the most complex system known in the universe. From the brain much information can be extracted that can be used for a greater understanding of our nature. Understanding how our brain is affected by the factors that surround it will help to benefit it and therefore help human development. 9 This project studies the data from the CanguroFoundation, ([30] http://fundacioncanguro.co/), whose mission is to apply science to humanize neonatology. The Canguro Foundation has a wide set of data on brain images, medical, behavioral and social variables of patients with premature birth. The foundation was in charge of monitoring the patients who volunteered, gathering data during a 20-year period to enrich its scientific mission. This valuable resource, unique in the world, deserves to involve information engineers in an interdisciplinary group already composed of medical experts and scientific researchers. 10 Chapter 3. Project statement and Specifications 3.1 Problem description A friendly interactive web platform that allows analyzing parameters of shape and content of brain morphological structures either individually or for groups of individuals is currently not available. 3.2 Design description The comparison of parameters of shape and content in the morphology of the subjects´ brains requires a preprocessing module that allows making those parameters comparable by means of alignment, rotation, uniformization and displacement from the same common reference system. An adaptation layer for data processing that allows the information to be integrated into the analysis tool, which must be able to compare a large group of subjects, as well as to examine details of a single subject. The platform must be scalable and integrable with other modules that perform other types of analysis such as functional analysis and must also be web accessible, so that it can be reachable from any device, operating system and location. 11 3.3 Data profiling The medical images of the brain emerging from the measuring equipment, come in a format called DICOM (Digital imaging & communications in medicine), which contains the pixels of the image as well as a header with metadata and additional information. Each DICOM image contains a slice of the brain as if it were a single section of the 3D brain. On the other hand, there is another format, the NIFTI (Neuroimaging Informatics Technology Initiative) format, which represents all the slides of the brain, that is, the 3D brain image is obtained by stacking individual slices on top of each other. Then, with several DICOM files, a single NIFTI file can be generated. The NIFTI format is easier to use because it contains the 3D information necessary for the analysis of the volumetric images. The medical images of the brain can be of the MRI type (magnetic resonance imaging) or FMRI type (functional magnetic resonance imaging). The difference between the two is that for structural images there is no time variable, while for functional images there is a follow-up to the subject’s brain in time. The structural images represent the morphology of the brain of the subjects under study. Figure 3.1: the example of functional MRI left, which makes sense to be done in time. Right, an MRI image that does not take time into account and therefore constitutes a photograph that reveals structural details of the brain. 12 NIFTI images can be loaded with python through the nibabel library to be converted into numpy 3D arrays which allows for further processing. This project focuses on structural MRI images, that is, they represent the morphological structure in a given time.