Medical Imaging Informatics docx

Medical Imaging Informatics

Medical Imaging

Informatics

Alex A.T. Bui, Ricky K. Taira (eds.)

Editors

Alex A.T. Bui Ricky K. Taira

Medical Imaging Informatics Group Medical Imaging Informatics Group

Department of Radiological Sciences Department of Radiological Sciences

David Geffen School of Medicine David Geffen School of Medicine

University of California, Los Angeles University of California, Los Angeles

924 Westwood Blvd. 924 Westwood Blvd.

Los Angeles, CA 90024 Los Angeles, CA 90024

Suite 420 Suite 420

USA USA

[email protected] [email protected]

ISBN 978-1-4419-0384-6 e-ISBN 978-1-4419-0385-3

DOI 10.1007/978-1-4419-0385-3

Springer New York Dordrecht Heidelberg London

© Springer Science+Business Media, LLC 2010

All rights reserved. This work may not be translated or copied in whole or in part without the written per￾mission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013,

USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any

form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar

methodology now known or hereafter developed is forbidden.

The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not

identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to

proprietary rights.

While the advice and information in this book are believed to be true and accurate at the date of going to

press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors

or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the

material contained herein.

Printed on acid-free paper

Springer is part of Springer Science+Business Media (www.springer.com)

Library of Congress Control Number: 2009939431

For our mentor and friend, Hoosh, who has the wisdom and leadership to realize a

vision; and to our students past, present, and future, for helping to pave a path

forward.

vii

Foreword

Imaging is considered as one of the most effective – if not the most effective – in vivo

sampling techniques applicable to chronic serious illnesses like cancer. This simple yet

comprehensive textbook in medical imaging informatics (MII) promotes and facili￾tates two different areas of innovation: the innovations in technology that improve the

field of biomedical informatics itself; and the application of these novel technologies

to medicine, thus, improving health. Aside from students in imaging disciplines such

as radiological sciences (vs. radiology as a service), this book is also very pertinent to

other disciplines such as cardiology and surgery. Faculty and students familiar with

this book will come to have their own ideas how to innovate, whether it be in core

technologies or in applications to biomedicine.

Organizationally, the book follows a very sensible structure related to the process of

care, which can in principle be summarized in three questions: what is wrong; how

serious is it; and what to do? The first question (what is wrong) focuses mostly on

diagnosis (i.e., what studies should be obtained). In this way, issues such as individu￾ally-tailored image protocol selection are addressed so that the most appropriate and

correct study is obtained – as opposed to the traditional sequential studies. For example,

a patient with knee pain and difficulty going up stairs or with minor trauma to the knee

and evidence of effusion is directly sent for an MRI (magnetic resonance imaging)

study rather than first going to x-ray; or in a child suspected of having abnormal (or

even normal) brain development, MRI studies are recommended rather than traditional

insurance-required computed tomography (CT). The role of imaging, not only in

improving diagnosis but reducing health costs is highlighted. The second question

(how serious is it) relates to how we can standardize and document image findings, on

the way to providing truly objective, quantitative assessment from an imaging study as

opposed to today’s norm of largely qualitative descriptors. Finally, the third question

is in regard to how we can act upon the information we obtain clinically, from imaging

and other sources: how can decisions be made rationally and how can we assess the

impact of either research or an intervention?

The textbook has been edited by two scientists, an Associate Professor and a Professor

in MII who are both founders of this discipline at our institution. Contributions come

from various specialists in medical imaging, informatics, computer science, and bio￾statistics. The book is not focused on image acquisition techniques or image process￾ing, which are both well-known and described elsewhere in other texts; rather, it

focuses on how to extract knowledge and information from imaging studies and

related data. The material in this textbook has been simplified eloquently, one of the

most difficult tasks by any teacher to simplify difficult material so that it is under￾standable at all levels.

viii Foreword

In short, this textbook is highly recommended for students in any discipline dealing

with imaging as well as faculty interested in disciplines of medical imaging and

informatics.

Hooshang Kangarloo, MD

Professor Emeritus of Radiological Sciences, Pediatrics, and Bioengineering

University of California at Los Angeles

With the advancement of picture archiving and communications systems (PACS) into

“mainstream” use in healthcare facilities, there is a natural transition from the dis￾ciplines of engineering research and technology assessment to clinical operations.

While much research in PACS-related areas continues, commercial systems are

widely available. The burgeoning use of PACS in a range of healthcare facility sizes

has created entirely new employment opportunities for “PACS managers,” “modality

managers,” “interface analysts,” and others who are needed to get these systems

implemented, keep them operating, and expand them as necessary. The field of medical

imaging informatics is often described as the discipline encompassing the subject

areas that these new specialists need to understand. As the Society of Imaging Infor￾matics in Medicine (SIIM) defines it:

Imaging informatics is a relatively new multidisciplinary field that intersects

with the biological sciences, health services, information sciences and com￾puting, medical physics, and engineering. Imaging informatics touches every

aspect of the imaging chain and forms a bridge with imaging and other

medical disciplines.1

Because the technology of PACS continues to evolve, imaging informatics is also

important for the researcher. Each of the areas comprising the field of imaging infor￾matics has aspects that make for challenging research topics. Absent the research these

challenges foster and PACS would stagnate.

For the student of medical imaging informatics, there is a wealth of literature available

for study. However, much of this is written for trainees in a particular discipline.

Anatomy, for example, is typically aimed at medical, dental, veterinary, and physical

therapy students, not at engineers. Texts on networks or storage systems are not

designed for physicians. Even primers on such topics tend not to provide a cross￾disciplinary perspective of the subject.

1

Society of Imaging Informatics in Medicine website: http://www.siimweb.org.

Foreword ix

The authors of Medical Imaging Informatics have accepted the challenge of creating a

textbook that provides the student of medical imaging informatics with the broad

range of topical areas necessary for the field and doing so without being superficial.

Unusual for a text on informatics, the book contains a chapter, A Primer on Imaging

Anatomy and Physiology, subject material this writer knows is important, but is often

lacking in the knowledge-base of the information technology (IT) people he works

with. Similarly, many informatics-oriented physicians this writer knows do not have

the in-depth understanding of information systems and components that IT experts

have. Such is the subject matter of the “middle” chapters of the book – Chapter 3:

Information Systems & Architectures, Chapter 4: Medical Data Visualization: Toward

Integrated Clinical Workstations, and Chapter 5: Characterizing Imaging Data. The

succeeding chapters are directed towards integrating IT theory and infrastructure with

medical practice topics – Chapter 6: Natural Language Processing of Medical Reports,

Chapter 7: Organizing Observations: Data Models, Chapter 8: Disease Models, Part I:

Graphical Models, and Chapter 9: Disease Models, Part II: Querying & Applications.

Finally, because a practitioner of medical imaging informatics is expected to keep up

with the current literature and to know the bases of decision making, the authors have

included a chapter on Evaluation. With the statistical methods and technology assess￾ment areas covered, the reader will gain the understanding needed to be a critical

reader of scientific publications and to understand how systems are evaluated during

development and after deployment.

Structured in this way, this book forms a unique and valuable resource both for the

trainee who intends to become an expert in medical imaging informatics and a refer￾ence for the established practitioner.

Steven C. Horii, MD, FACR, FSIIM

Professor of Radiology,

Clinical Director, Medical Informatics Group, and

Modality Chief for Ultrasound

Department of Radiology

University of Pennsylvania Medical Center

xi

Preface

This book roughly follows the process of care, illustrating the techniques involved in

medical imaging informatics. Our intention in this text is to provide a roadmap for the

different topics that are involved in this field: in many cases, the topics covered in the

ensuing chapters are themselves worthy of lengthy descriptions, if not an entire book.

As a result, when possible the authors have attempted to provide both seminal and

current references for the reader to pursue additional details.

For the imaging novice and less experienced informaticians, in Part I of this book,

Performing the Imaging Exam, we cover the current state of medical imaging and set

the foundation for understanding the role of imaging and informatics in routine clinical

practice:

ƒ Chapter 1 (Introduction) provides an introduction to the field of medical imaging

informatics and its role in transforming healthcare research and delivery. The

interwoven nature of imaging with preventative, diagnostic, and therapeutic elements

of patient care are touched upon relative to the process of care. A brief historic

perspective is provided to illustrate both past and current challenges of the discipline.

ƒ Chapter 2 (An Introduction to Imaging Anatomy & Physiology) starts with a

review of clinical imaging modalities (i.e., projectional x-ray, computed tomography

(CT), magnetic resonance (MR), ultrasound) and a primer on imaging anatomy

and physiology. The modality review encompasses core physics principles and

image formation techniques, along with brief descriptions of present and future

directions for each imaging modality. To familiarize non-radiologists with medical

imaging and the human body, the second part of this chapter presents an overview

of anatomy and physiology from the perspective of projectional and cross￾sectional imaging. A few systems (neurological, respiratory, breast) are covered in

detail, with additional examples from other major systems (gastrointestinal,

urinary, cardiac, musculoskeletal).

More experienced readers will likely benefit from starting with Part II of this book,

Integrating Imaging into the Patient Record, which examines topics related to

communicating and presenting imaging data alongside the growing wealth of clinical

information:

ƒ Once imaging and other clinical data are acquired, Chapter 3 (Information Systems

& Architectures) tackles the question of how we store and access imaging and

other patient information as part of an increasingly distributed and heterogeneous

EMR. A description of major information systems (e.g., PACS; hospital informa￾tion systems, HIS; etc.) as well as the different data standards employed today to

represent and communicate data (e.g., HL7, DICOM) are provided. A discussion

xii Preface

of newer distributed architectures as they apply to clinical databases (peer-to-peer,

grid computing) and information processing is given, examining issues of scal￾ability and searching. Different informatics-driven applications are used to high￾light ongoing efforts with respect to the development of information architectures,

including telemedicine, IHE, and collaborative clinical research involving imaging.

ƒ After the data is accessed, the challenge is to integrate and to present patient

information in such a way to support the physician’s cognitive tasks. The longitud￾inal EMR, in conjunction with the new types of information available to clinicians,

has created an almost overwhelming flow of data that must be fully understood to

properly inform decision making. Chapter 4 (Medical Data Visualization:

Toward Integrated Clinical Workstations) presents works related to the visualiz￾ation of medical data. A survey of graphical metaphors (lists and tables; plots and

charts; graphs and trees; and pictograms) is given, relating their use to convey

clinical concepts. A discussion of portraying temporal, spatial, multidimensional,

and causal relationships is provided, using the navigation of images as an example

application. Methods to combine these visual components are illustrated, based on

a definition of (task) context and user modeling, resulting in a means of creating

an adaptive graphical user interface to accommodate the range of different user

goals involving patient data.

Part III, Documenting Imaging Findings, discusses techniques for automatically

extracting content from images and related data in order to objectify findings:

ƒ In Chapter 5 (Characterizing Imaging Data), an introduction to medical image

understanding is presented. Unlike standard image processing, techniques within

medical imaging informatics focus on how imaging studies, alongside other clinical

data, can be standardized and their content (automatically) extracted to guide

medical decision making processes. Notably, unless medical images are standard￾ized, quantitative comparisons across studies is subject to various sources of bias/

artifacts that negatively influence assessment. From the perspective of creating

scientific-quality imaging databases, this chapter starts with the groundwork for

understanding what exactly an image captures, and commences to outline the dif￾ferent aspects encompassing the standardization process: intensity normalization;

denoising; and both linear and nonlinear image registration methods are covered.

Subsequently, a discussion of commonly extracted imaging features is given,

divided amongst appearance- and shape-based descriptors. With the wide array of

image features that can be computed, an overview of image feature selection and

dimensionality reduction methods is provided. Lastly, this chapter concludes with

a description of increasingly popular imaging-based anatomical atlases, detailing

their construction and usage as a means for understanding population-based

norms and differences arising due to a disease process.

Preface xiii

ƒ Absent rigorous methods to automatically analyze and quantify image findings,

radiology reports are the sole source of expert image interpretation. In point of

fact, a large amount of information about a patient remains locked within clinical

documents; and as with images, the concepts therein are not readily computer un￾derstandable. Chapter 6 (Natural Language Processing of Medical Reports)

deals with the structuring and standardization of free-text medical reports via

natural language processing (NLP). Issues related to medical NLP representation,

computation, and evaluation are presented. An overview of the NLP task is first

described to frame the problem, providing an analysis of past efforts and applica￾tions of NLP. A sequence of subtasks is then related: structural analysis (e.g., section

and sentence boundary detection), lexical analysis (e.g., logical word sequences,

disambiguation, concept coding), phrasal chunking, and parsing are covered. For

each subtask, a description of the challenges and the range of approaches are

given to familiarize the reader with the field.

ƒ Core to informatics endeavors is a systematic method to organize both data and

knowledge, representing original (clinical) observations, derived data, and conclu￾sions in a logical manner. Chapter 7 (Organizing Observations: Data Models)

describes the different types of relationships between healthcare entities, particularly

focusing on those relations commonly encountered in medical imaging. Often in

clinical practice, a disease is studied from a specific perspective (e.g., genetic,

pathologic, radiologic, clinical). But disease is a phenomenon of nature, and is thus

typically multifaceted in its presentation. The goal is to aggregate the observations

for a single patient to characterize the state and behavior of the patient’s disease,

both in terms of its natural course and as the result of (therapeutic) interventions.

The chapter divides the organization of such information along spatial (e.g.,

physical and anatomical relations, such as between objects in space), temporal

(e.g., sequences of clinical events, episodes of care), and clinically-oriented

models (i.e., those models specific to representing a healthcare abstraction).

A discussion of the motivation behind what drives the design of a medical data

model is given, leading to the description of a phenomenon-centric data model to

support healthcare research.

Finally, in Part IV, Toward Medical Decision Making, we reflect on issues pertain￾ing to reasoning with clinical observations derived from imaging and other data

sources in order to reach a conclusion about patient care and the value of our decision:

ƒ A variety of formalisms are used to represent disease models; of these, probabilistic

graphical models have become increasingly popular given their ability to reason

in light of missing data, and their relatively intuitive representation. Chapter 8

(Disease Models, Part I: Graphical Models) commences with a review of key

concepts in probability theory as the basis for understanding these graphical models

xiv Preface

and their different formulations. In particular, the first half of the chapter handles

Bayesian belief networks (BBNs), appraising past and current efforts to apply

these models to the medical environment. The latter half of this chapter addresses

the burgeoning exploration of causal models, and the implications for analysis and

positing questions to such networks. Throughout, a discussion of the practical

considerations in the building of these models and the assumptions that must be

made, are given.

ƒ Following the discussion of the creation of the models, in Chapter 9 (Disease

Models, Part II: Querying & Applications), we address the algorithms and tools

that enable us to query BBNs. Two broad classes of queries are considered: belief

updating, and abductive reasoning. The former entails the re-computation of pos￾terior probabilities in a network given some specific evidence; the latter involves

calculating the optimal configuration of the BBN in order to maximize some

specified criteria. Brief descriptions of exact and approximate inference methods

are provided. Special types of belief networks (naïve Bayes classifiers, influence

diagrams, probabilistic relational models) are covered, illustrating their potential

usage in medicine. Importantly, issues related to the evaluation of belief networks

are discussed in this chapter, looking to standard technical accuracy metrics, but

also ideas in parametric sensitivity analysis. Lastly, the chapter concludes with

some example applications of BBNs in medicine, including to support case-based

retrieval and image processing tasks.

ƒ Chapter 10 (Evaluation) concludes by considering how to assess informatics

endeavors. A primer on biostatistics and study design starts this chapter, including

a review of basic concepts (e.g., confidence intervals, significance and hypothesis

testing) and the statistical tests that are used to evaluate hypotheses under differ￾ent circumstances and assumptions. A discussion of error and performance

assessment is then introduced, including sensitivity/specificity and receiver opera￾tive characteristic analysis. Study design encompasses a description of the differ￾ent types of experiments that can be formed to test a hypothesis, and goes over the

process of variable selection and sample size/power calculations. Sources of study

bias/error are briefly described, as are statistical tools for decision making. The

second part of this chapter uses the foundation set out by the primer to focus

specifically on informatics-related evaluations. Two areas serve as focal points:

evaluating information retrieval (IR) systems, including content-based image

retrieval; and assessing (system) usability.

xv

Contributors

Pablo Abbona, MD Neda Jahanshad, BS

Department of Radiological Sciences Medical Imaging Informatics

UCLA David Geffen School of Medicine UCLA Biomedical Engineering IDP

Denise Aberle, MD Hooshang Kangarloo, MD

Medical Imaging Informatics & Medical Imaging Informatics

Department of Radiological Sciences UCLA David Geffen School of Medicine

UCLA David Geffen School of Medicine

Corey Arnold, PhD Kambiz Motamedi, MD

Medical Imaging Informatics & Department of Radiological Sciences

Department of Information Studies UCLA David Geffen School of Medicine

University of California, Los Angeles

Lawrence Bassett, MD Craig Morioka, PhD

Department of Radiological Sciences Department of Radiology

UCLA David Geffen School of Medicine Veteran’s Administration Wadsworth

Los Angeles, California

Kathleen Brown, MD Nagesh Ragavendra, MD

Department of Radiological Sciences Department of Radiological Sciences

UCLA David Geffen School of Medicine UCLA David Geffen School of Medicine

Matthew Brown, PhD James Sayre, PhD

Thoracic Imaging Laboratory & Departments of Biostatistics &

Department of Radiological Sciences Radiological Sciences

UCLA David Geffen School of Medicine UCLA David Geffen School of Medicine

Suzie El-Saden, MD Leanne Seeger, MD

Department of Radiology Department of Radiological Sciences

Veteran’s Administration Wadsworth UCLA David Geffen School of Medicine

Los Angeles, California

Ana Gomez, MD Ilya Shpitser, PhD

Department of Radiological Sciences School of Public Health

UCLA David Geffen School of Medicine Harvard University

William Hsu, PhD Emily Watt, MLIS

Medical Imaging Informatics Medical Imaging Informatics

UCLA David Geffen School of Medicine UCLA Biomedical Engineering IDP

Juan Eugenio Iglesias, MSc

Medical Imaging Informatics

UCLA Biomedical Engineering IDP

xvii

Table of Contents

FOREWORD...................................................................................................VII

PREFACE........................................................................................................XI

CONTRIBUTORS..............................................................................................XV

TABLE OF CONTENTS ..................................................................................... XVII

PART I PERFORMING THE IMAGING EXAM ........................................................... 1

CHAPTER 1: INTRODUCTION .............................................................................. 3

What is Medical Imaging Informatics? .................................................................3

The Process of Care and the Role of Imaging ........................................................ 4

Medical Imaging Informatics: From Theory to Application ................................... 5

Improving the Use of Imaging......................................................................................... 5

Choosing a Protocol: The Role of Medical Imaging Informatics...................................... 7

Cost Considerations ...................................................................................................... 10

A Historic Perspective and Moving Forward ....................................................... 11

PACS: Capturing Images Electronically.......................................................................... 11

Teleradiology: Standardizing Data and Communications ............................................. 12

Integrating Patient Data................................................................................................ 12

Understanding Images: Today’s Challenge ................................................................... 13

References.........................................................................................................14

CHAPTER 2: A PRIMER ON IMAGING ANATOMY AND PHYSIOLOGY ........................... 17

A Review of Basic Imaging Modalities ................................................................17

Projectional Imaging............................................................................................ 18

Core Physical Concepts ................................................................................................. 18

Imaging ......................................................................................................................... 20

Computed Tomography....................................................................................... 27

Imaging ......................................................................................................................... 28

Additional CT Applications ............................................................................................ 39

Magnetic Resonance ........................................................................................... 41

Core Physical Concepts ................................................................................................. 41

Imaging ......................................................................................................................... 44

Additional MR Imaging Sequences................................................................................ 49

Ultrasound Imaging ............................................................................................. 53

xviii Table of Contents

An Introduction to Imaging-based Anatomy & Physiology .................................55

Respiratory System.............................................................................................. 56

The Larynx and Trachea ................................................................................................ 56

The Lungs and Airways.................................................................................................. 57

The Pleura, Chest Wall, and Respiratory Muscles......................................................... 61

Pulmonary Ventilation: Inspiration and Expiration....................................................... 62

Pressure Relationships during Inspiration and Expiration ............................................ 63

Factors Influencing Airflow ........................................................................................... 63

Measures of Lung Function........................................................................................... 65

Basic Respiratory Imaging ............................................................................................. 66

Imaging Analysis of Pulmonary Pathophysiology.......................................................... 68

The Brain ............................................................................................................. 71

Cerebral Hemispheres................................................................................................... 72

Cerebral White Matter.................................................................................................. 76

Basal Nuclei................................................................................................................... 76

Brainstem...................................................................................................................... 77

Meninges ...................................................................................................................... 78

Cerebral Vascular Anatomy........................................................................................... 78

Breast Anatomy and Imaging .............................................................................. 80

Breast Imaging .............................................................................................................. 80

Breast Cancer and other Findings ................................................................................. 85

Musculoskeletal System ...................................................................................... 87

Imaging of the Musculoskeletal System........................................................................ 88

Cardiac System .................................................................................................... 94

Cardiac Medical Problems............................................................................................. 95

Basic Cardiac and Vascular Imaging .............................................................................. 96

Urinary System .................................................................................................... 98

Basic Imaging of the Urinary System............................................................................. 99

Urinary Medical Problems........................................................................................... 100

Upper Gastrointestinal (GI) System................................................................... 103

References....................................................................................................... 105

PART II INTEGRATING IMAGING INTO THE PATIENT RECORD .................................113

CHAPTER 3: INFORMATION SYSTEMS & ARCHITECTURES.......................................115

The Electronic Medical Record ......................................................................... 115

EMR Information Systems ................................................................................. 117

Hospital Information Systems..................................................................................... 117

Picture Archive and Communication Systems............................................................. 119