automated quality control procedures for brain magnetic resonance images acquired in multi

198 Pages·2011·8.4 MB·English

AUTOMATED QUALITY CONTROL PROCEDURES FOR
BRAIN MAGNETIC RESONANCE IMAGES ACQUIRED IN
MULTI-CENTRE CLINICAL TRIALS FOR MULTIPLE
SCLEROSIS

Elias Gedamu

Department of Biomedical Engineering, Faculty of Medicine
McGill University
Montreal, QC, Canada

16 November 2010

A thesis submitted to McGill University in partial fulfillment of the requirements of
the degree of Masters of Engineering

© Elias Gedamu 2011
Acknowledgements
I would like to acknowledge my family for their support during my research as
a graduate student. I have the utmost reverence for my parents who have shown
me that anything can and shall be accomplished through perseverance,
determination, and positive thinking. They are moral people who are guided by
ethics and these attributes have been instilled in me. I acknowledge my brother
for always being there throughout my research. He has been dependable,
reliable, and supportive and has taught me the value of patience and focus, both
of which were beneficial during my research.
I would like to acknowledge Dr. Jacqueline Chen for her support and being
my mentor and close friend. She has guided me since the beginning of my
research and exemplifies all the qualities of an extraordinary supervisor. She has
a wealth of knowledge, both in depth and breadth, and a remarkable capability of
explaining complex concepts in simple terms while conveying details with
i
exactitude. Dr. Jacqueline Chen has had a clear impact on my success in
academia and future aspirations.
Finally, the natural sciences and engineering research council (NSERC) of
Canada and the mathematics of information technology and complex systems
(MITACS) funding agency are gratefully acknowledged for their provision of
financial assistance for this research.
ii
Abstract
Automated quality control procedures are critical for efficiently obtaining
precise quantitative brain imaging-based metrics of in vivo brain pathology. This
is especially important for multi-centre clinical trials of therapeutics for multiple
sclerosis, in which MRI-derived brain pathology metrics may be used to quantify
therapeutic efficacy.
Currently, a large number of QC procedures have been developed for
scanner maintenance with the idea that optimal scanner performance should
produce MRIs with acceptable image quality and, thus, limit the effect of brain
pathology measurement errors on quantitative analyses like therapeutic efficacy.
Unfortunately these procedures may not be applicable to real subject MRI scans
where non-ideal conditions like subject motion during an acquisition exist. The
goal of this thesis is to provide an automated QC procedure for brain MRIs
iii
acquired in multi-centre clinical trials for multiple sclerosis where image quality is
evaluated directly from the acquired MRI itself.
iv
Abrégé
Les procédures automatisées de contrôle de qualité (CQ) sont essentielles
afin d’obtenir de manière efficace des mesures précises d'imagerie cérébrale
fondées sur la pathologie du cerveau in vivo. Ceci est particulièrement important
pour les essais cliniques multicentriques de produits thérapeutiques destinés aux
maladies neurologiques, dont les mesures de pathologie cérébrale dérivées des
IRMs peuvent être utilisées pour quantifier l'efficacité thérapeutique.
Présentement, la littérature met l'accent sur les procédures de CQ pour
l'entretien des scanners, en supposant que ce bon entretien du scanner d’IRM
produirait une qualité d'image acceptable et, par conséquent, limiterait les
erreurs de mesures sur les analyses quantitatives, comme l'efficacité
thérapeutique. Malheureusement, ces procédures peuvent ne pas être
applicables sur des scans de sujets réels où des conditions non-idéals seraient
présents, comme le mouvement du sujet lors d'une prise. L'objectif de cette
thèse est de fournir une procédure automatisée de CQ pour les IRM cérébrales
v
acquises lors de plusieurs essais cliniques sur la sclérose en plaques, où la
qualité de l'image est évaluée directement à partir de l'IRM elle-même. Cette
procédure a été testée, validée et appliquée dans l'industrie.
vi
Table of Contents
1  Introduction .............................................................................................................................. 1 
1.1  Multiple Sclerosis ............................................................................................................ 1 
1.2  Magnetic Resonance Imaging (MRI) and MS ................................................................. 6 
1.2.1 MRI and Clinical Trials for MS ......................................................................................... 9 
1.2.2 MRIs and Derived Brain Pathology Metrics in MS ........................................................ 10 
2  MRI Quality and Quality Control (QC) Procedures ................................................................ 13 
2.1  Image Quality ................................................................................................................ 13 
2.1.1 Definition of Quality ....................................................................................................... 13 
2.1.2 Aspects of MRI Quality and Examples of Poor Quality Images .................................... 14 
2.1.3 Disadvantages of Unacceptable MRIs .......................................................................... 20 
2.2  Imaging Markers to Evaluate Image Quality ................................................................. 22 
2.2.1 Phantoms ...................................................................................................................... 22 
2.2.2 External Markers ........................................................................................................... 25 
2.2.3 Acquired Brain MRIs ..................................................................................................... 26 
2.3  Overview of Clinical Trial Pipeline ................................................................................. 30 
2.4  Quality Control Procedures for Brain MRIs ................................................................... 32 
2.5  Literature Review of QC Procedures for Brain MRIs .................................................... 33 
2.5.1 MRI Quality and MRI-Based Brain Metrics ................................................................... 33 
2.5.2 Suggested MRI Quality Control Protocols and Procedures .......................................... 37 
2.6  Complexities of Developing QC procedures for Clinical Trials ..................................... 47 
3  Automated Quality Control of Brain MR Images .................................................................... 53 
3.1  Abstract ......................................................................................................................... 53 
3.2  Introduction .................................................................................................................... 54 
3.3  Materials and Methods .................................................................................................. 63 
3.3.1 Subjects ......................................................................................................................... 63 
3.3.2 Quality Control Tool ...................................................................................................... 66 
3.3.3 Modality Specific Transformation Matrices ................................................................... 66 
3.3.4 Brain Identity Verification .............................................................................................. 70 
3.3.5 MRI Parameter Verification ........................................................................................... 74 
3.3.6 MRI Signal-to-Noise Ratio ............................................................................................. 77 
3.3.7 Standard Deviation of Noise Manual ROI Selection Variability Test ............................ 82 
vii
3.3.8 Ghosting ........................................................................................................................ 83 
3.3.9 Gadolinium Enhancement Verification .......................................................................... 87 
3.4  Results .......................................................................................................................... 89 
3.4.1 Brain Identity Verification .............................................................................................. 89 
3.4.2 MRI Parameter Verification ........................................................................................... 91 
3.4.3 MRI Signal-to-Noise Ratio ............................................................................................. 92 
3.4.4 Ghosting ........................................................................................................................ 96 
3.4.5 Gadolinium Enhancement Verification .......................................................................... 97 
3.5  Discussion ..................................................................................................................... 98 
4  Inter-Packet Movement Correction Procedure for Brain MRIs ............................................ 106 
4.1  Abstract ....................................................................................................................... 108 
4.2  Introduction .................................................................................................................. 109 
4.3  Methods ....................................................................................................................... 113 
4.4  Experiments ................................................................................................................ 117 
4.4.1 Simulations to Test the Transformation Recovery ...................................................... 118 
4.4.2 Simulations to test structure volume recovery ............................................................ 124 
4.4.3 Real Data Evaluation .................................................................................................. 128 
4.4.4 Quantitative Evaluation of Data................................................................................... 129 
4.5  Results ........................................................................................................................ 133 
4.5.1 Simulations to Test the Transformation Recovery ...................................................... 133 
4.5.2 Real Data Cases ......................................................................................................... 136 
4.5.3 Statistical Analysis ...................................................................................................... 136 
4.6  Discussion ................................................................................................................... 144 
5  Overall Discussion, Future Work, and Conclusions ............................................................. 149 
5.1  Overall Discussion ...................................................................................................... 149 
5.2  Future Work ................................................................................................................. 155 
5.3  Conclusions ................................................................................................................. 160 
6  References ........................................................................................................................... 161 
7  Appendices .......................................................................................................................... 183 
7.1  List of Abbreviations .................................................................................................... 183 

viii
List of Figures
Figure 1-1: MRI Modalities Highlighting Different Aspects of Brain Anatomy and Pathology ..........5 
Figure 2-1: Poor Quality Magnetic Resonance Images ..................................................................15 
Figure 2-2: Effect of Improper Subject Positioning on MRIs ..........................................................17 
Figure 2-3: Effect of Labelling MRIs with Incorrect Patient Identifiers ............................................19 
Figure 2-4: MRI Process Pipeline Example for Multi-Centre Clinical Trials ...................................29 
Figure 3-1: Visual Depiction of the Automated QC Pipeline...........................................................65 
Figure 3-2: Modality Specific Transformation Matrices ..................................................................67 
Figure 3-3: Masks and Regions of Interest used by the Automated QC Procedure ......................79 
Figure 3-4: Masks used for Ghosting and Gadolinium Enhancement Tests ..................................84 
Figure 3-5: ROC Graphs for 4 QC Tests in the Automated QC Pipeline .......................................90 
Figure 3-6: Scatter Plots Comparing Automated to Manual QC Results for Signal and Noise ......94 
Figure 3-7: Manual Noise Selection Process Variability .................................................................95 
Figure 4-1: Set of MRIs Illustrating Inter-Packet Motion .............................................................. 120 
Figure 4-2: Shifts in SSG ............................................................................................................. 122 
Figure 4-3: Effect of Rotational Movements ................................................................................ 122 
Figure 4-4: Effect of Moderate and Severe Inter-packet Movement ........................................... 134 
Figure 4-5: Effect of Inter-Packet Motion Correction Algorithm ................................................... 135 
Figure 4-6: Individual Correlation vs. Iteration ............................................................................. 137 
Figure 4-7: Average Correlation vs. Iteration .............................................................................. 137 
Figure 4-8: Average RMS Error Before and After Inter-Packet Correction ................................. 138 
Figure 4-9: Comparison of Expected and Post-Corrected Lesion Volumes................................ 140 
Figure 4-10: Effects of Motion on Lesion Volumes After Inter-Packet Correction ....................... 141 
Figure 4-11: Accuracy of Lesion Quantification After Inter-Packet Correction ............................ 143 
ix