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Novel Proof of Concept to Assess Multifocal Neuronal Disease in Individuals
Using MRI
Abby Hentel
White Matter Tracts
• Altered by neurodegenerative disorders, medications, or neuropsychological conditions(Croteau-Chonka, et al. 2015)
• $1.5 trillion of U.S. Economy annually (Thakur, et al. 2016)
• Traumatic Brain Injury (TBI) • 30% all injury deaths• 2013- 50,000 deaths• (Wintermark, et al. 2015)
Introduction Methods Results Discussion References
http://www.cannabisoils.ca/wp-content/uploads/2014/11/neurodegenerative-diseases.jpg
http://www.tbibraininjurysurvivor.com/what-is-tbi/
2
Traumatic Axonal Injury
https://www.lyslaw.com/Spine-Injury-Traumatic-Brain-Injury-Support/Two-Primary-Types-Brain-Injuries.aspx
Introduction Methods Results Discussion References
3
Problem with TBI• Mild Traumatic Brain Injury
(mTBI) – 80% all TBI• Does not typically show up
on conventional imaging
Introduction Methods Results Discussion References
http://blog.cincinnatichildrens.org/wp-content/uploads/2015/08/CTandMR_head_blog20150805C.jpg
4
Solution: DTI• Diffusion Tensor Imaging (DTI)
• Extremely sensitive to changes in white matter microstructure (Jones, et al. 2010) (Lerner, et al. 2013)
• How does this work?• Measures diffusion of water molecules
throughout white matter tracts • Quantitatively analyzed
• Fractional Anisotropy (FA)
Introduction Methods Results Discussion Bibliography
5
Limitations of Quantitative DTI
• Assessment of data • Control group• Same hardware, parameters, software• Demographics• Impossible/Costly• No clinical usage
• Clinically used for visualization
Introduction Methods Results Discussion References
6
Clinically used for visualization
Normal Brain Tumor
Tract Visualization with DTI
Normal Brain Tumor
Objective
3 scanners should show
same deviations
Quantify homogeneity of
each tract
Individual assessment
7
Introduction Methods Results Discussion References
Data Collection
Anonymized normative database
under medical college IRB
Subjects agreed to have MRI/DTI scan up to 3 different scanners•33 Direction GE DTI•55 Direction GE DTI•64 Direction Siemens DTI
All subjects had no history of brain abnormalities
Introduction Methods Results Discussion References
9
Data Breakdown
40 Total Participants
23 Male17 Female
Age range: 23-79 yearsMean: 40
yearsSD: 17 years
30 subjects 55 direction
GE75%
40 subjects64 direction
Siemens100%
11 subjects 33 direction
GE28%
Introduction Methods Results Discussion References
10
Analysis• Reproducible Objective
Quantification Scheme (ROQS) (Niogi, et al. 2007)
• 6 regions:1. Corpus Callosum (CC)2. Corticospinal Tract (CST) 3. Cingulum Bundle (CB)4. Superior Longitudinal Fasciculus
(SLF)5. Anterior Corona Radiata (ACR)6. Uncinate Faciculus (UF)
Introduction Methods Results Discussion References 11
Statistical Analysis
• Average fractional anisotropy scores • Wilcoxon-Mann-Whitney test
• Test statistical difference between groups
• Performed using SPSS Version 25.0• Local Variance
Introduction Methods Results Discussion References
12
Cingulum Bundle
Introduction Methods Results Discussion References
13
0.4
0.45
0.5
0.55
0.6
0.65
0.7
1 2 3 4 5 6 7 8
Frac
tiona
l Ani
sotr
topy
Cingulum Bundle
55 Direction 64 Direction 33 Direction
0
0.05
0.1
0.15
0.2
0.25
0.3
0 1 2 3 4 5 6 7 8
Loca
l Var
ianc
e
Cingulum Bundle - Local Variance
55 Direction 64 Direction 33 Direction
Corticospinal Tract
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Frac
tiona
l Ani
sotr
opy
Corticospinal Tract
55 Direction 64 Direction 33 Direction
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 2 4 6 8 10 12 14 16 18
Loca
l Var
ianc
e
Corticospinal Tract - Local Variance
55 Direction 64 Direction 33 Direction
Introduction Methods Results Discussion References
14
Superior Longitudinal Fasciculus
Introduction Methods Results Discussion References
15
Anterior Corona Radiata
0.03
0.035
0.04
0.045
0.05
0.055
0 1 2 3 4 5 6 7
Loca
l Var
ianc
e
Anterior Corona Radiata – Local Variance
55 Direction 64 Direction 33 Direction
Introduction Methods Results Discussion References
16
Uncinate Fasciculus
0.5
0.52
0.54
0.56
0.58
0.6
0.62
0.64
0.66
1 2 3 4 5 6 7 8
Frac
tiona
l Ani
sotr
opy
Uncinate Fasciculus
55 Direction 64 Direction 33 Direction
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
1 2 3 4 5 6 7 8
Loca
l Var
ianc
e
Uncinate Fasciculus - Local Variance
55 Direction 64 Direction 33 Direction
Introduction Methods Results Discussion References
17
Corpus Callosum
0
0.1
0.2
0.3
0.4
0.5
0.6
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Loca
l Var
ianc
e
Corpus Callosum – Local Variance
55 Direction 64 Direction 33 Direction
Introduction Methods Results Discussion References
18
Findings
Confirmed Findings• Systematic parameters impact
FA measurement• gradient directions, slice
thickness, voxel size, hardware
• Variations are not predictable and vary per tract
• Combining data = invalid• (Papadakis, et al. 1999) (Skare, et al. 2000) (Lebel,
et al. 2012)
Novel Findings• Homogeneity of the white
matter are scanner/system independent
• Alternate Approach• Combine data• Individual assessment
• Patent Submission in Progress
Introduction Methods Results Discussion References
19
TBI patient, example• 27 year old professional
football player• Grade II concussion
(symptoms for more than 15 minutes without loss of consciousness
• Trace hemorrhage in the lateral ventricles on acute conventional MRI. No direct or indirect evidence of axonal injury on conventional MRI
• DTI local variance measure strongly suggests axonal injury involving the genu of the corpus callous, a frequently injured tract 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Corpus Callosum VarianceAnterior to Posterior
Limitations
• Data Sets were Cross-sectional• Not every subject scanned on every scanner
• Local variance estimates were based on regions of interest• Future application of this technique will work as a continuous measure along
tractograms.
Introduction Methods Results Discussion References
20
Future Research/Work
• Validate findings with optimized algorithm and data on multi-institutional datasets
• Patient testing:• Retrospective study on Professional Boxers• Prospective study on both controls and TBI patients
• Complete patent application• Seek Licensing to industry partners
• We already have potential buyers (Athlemetrics, LLC)
Introduction Methods Results Discussion References
21
Acknowledgements
I would like to thank my my mentor, Science Research teachers, and parents for their continued support.
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Concussion is a subset of mild TBI. Generally, concussion is limited to the very mild end of mild TBI resulting specifically from an impact to the head. On the other hand, the severe end of mild TBI can manifest with loss of consciousness, severe symptoms, amnesia, dizziness, and headache. It also includes trauma from acceleration forces not associated with a direct impact.