Stephanie Barnes has a PhD in Biomedical Engineering from Vanderbilt University. She has extensive experience in preclinical research including computational modeling, data analysis, and quantitative imaging modalities like MRI, ultrasound, and PET. Her research has focused on developing techniques to predict treatment response in cancer using quantitative imaging data from preclinical models and patients.

1. Stephanie Lynne (Barnes) Eldridge
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1005 Meandering Way, Franklin, TN 37067
(615) 479-6390
steph.barnes@vanderbilt.edu vba8264552@comcast.net
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Education
Vanderbilt University Nashville, TN
Doctor of Philosophy, Biomedical Engineering May 2011
Vanderbilt University Nashville, TN
Master of Science, Biomedical Engineering May 2007
University of Tennessee Knoxville, TN
Bachelor of Science, Biomedical Engineering, summa cum laude May 2004
Experience
Clinical data analysis
Optimization techniques
Computational modeling
Data analysis
Preclinical research
Preclinical imaging
Magnetic resonance imaging
Ultrasound imaging
Positron emission tomography imaging
Computed tomography imaging
Cell culture
Dissertation
Interrogation of the Limitations and Capabilities of the Model-Gel-Tissue Assay and Application to
Soft Tissue Modulus Evaluation
Publications
D.A. Hormuth II, J.A. Weis, S.L. Barnes, M.I. Miga, E.C. Rericha, V. Quaranta, and T. E. Yankeelov.
Predicting In Vivo Glioma Growth with the Reaction Diffusion Equation Constrained by Quantitative
Magnetic Resonance Imaging Data. Phys Biol, 2015. 12(4): 46006.

2. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
S.L. Barnes, C.C. Quarles, T.E. Yankeelov. Modeling the Effect of Intra-voxel Diffusion of Contrast
Agent on the Quantitative Analysis of Dynamic Contrast Enhanced Magnetic Resonance Imaging.
PLOS One, 2014. DOI: 10.1371/journal.pone.0013636
S.L. Barnes, J.G. Whisenant, X. Li, T.E. Yankeelov. Techniques and Applications of Dynamic
Contrast Enhanced Magnetic Resonance Imaging in Cancer. Conf Proc IEEE Eng Med Biol Soc.
2014. 4264-7.
D.D. Felix, J.C. Gore, T.E. Yankeelov, T.E. Peterson, S.L. Barnes, J. Whisenant, J. Weis, S.
Shoukouhi, J. Virotsko, M. Nickels, J.O. McIntyre, M. Sanders, V. Abramson, M.N. Tantawy.
Detection of Breast Cancer Microcalcification Using (99m)Tc-MDP SPECT or Osteosense 750EX
FMT Imaging. Nucl Med Biol, 2014.
G.H Wilson III, J.C. Gore, T.E. Peterson, S.L. Barnes, J.G. Whisenant, J. True, D. Colvin, M. Nickels,
T.E. Yankeelov, M.N. Tantawy. A novel approach to breast cancer diagnosis via PET imaging of
microcalcifications using 18
F-NaF. JNM, 2014. 55(7): 1138-1143.
J.G. Whisenant, G.D. Ayers, M.E. Loveless, S.L. Barnes, D.C. Colvin, and T.E. Yankeelov.
Assessing the reproducibility of diffusion-weighted magnetic resonance imaging studies in a murine
model of HER2+ breast cancer. MRI, 2014. 32(3): 245-249.
N.D. Bryant, K. Li, M.D. Does, S.L. Barnes, D. F. Gochberg, T.E. Yankeelov, J.H. Park, and B.M.
Damon. Multi-parametric MRI characterization of inflammation in murine skeletal muscle. NMR in
Biomedicine, 2013. 27: 716-725.
J. Cardenas, J. Whisenant, S.L. Barnes, X. Li, R. Stolberger, T.E. Yankeelov. Basic Principles of
DCE-MRI. MR and CT Perfusion Imaging: Clinical Applications and Theoretical Principles, R.
Bammer ed. Lippincott Williams & Wilkins, 2013.
T.E. Yankeelov, N. Atuegwu, D. Hormuth, J.A. Weis, S.L. Barnes, M.I. Miga, E.C. Rericha, V.
Quaranta. Clinically Relevant Modeling of Tumor Growth and Treatment Response. Science
Translational Medicine, 2013. 5(87).
J.U. Fluckiger, M.E. Loveless, S.L. Barnes, M. Lepage, T.E. Yankeelov. A diffusion-compensated
model for the analysis of DCE-MRI data: theory, simulations, and experimental results. Physics in
Medicine and Biology, 2013. 58(6), 1983-1998.
S.L. Barnes, J.G. Whisenant, M.E. Loveless, G.D. Ayers, and T.E. Yankeelov. Assessing the
Reproducibility of Dynamic Contrast Enhanced Magnetic Resonance Imaging in a Murine Model of
Breast Cancer. Journal of Magnetic Resonance in Medicine, 2013. 69(6): 1721-1734.
S.L. Barnes, J.G. Whisenant, M.E. Loveless, and T.E. Yankeelov. Practical Dynamic Contrast
Enhanced MRI in Small Animal Models of Cancer. Pharmaceutics, 2012. 4(3): 442-478.
S.L. Barnes, P.P. Young, M.I. Miga. A novel model-gel-tissue assay analysis for comparing tumor
elastic properties to collagen content. Biomechanics and Modeling in Mechanobiology, 2009.
8(4): 337-343.
September 16, 2014

3. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
S.L. Barnes, A. Lyshchik, M.K. Washington, J.C. Gore, and M.I. Miga. Development of a mechanical
testing assay for fibrotic murine liver. Medical Physics, 2007. 34 (11): 4439-4450.
A. Lyshchik, R. Moses, S.L. Barnes, T. Higashi, R. Asato, M.I. Miga, J.C. Gore, A.C. Fleischer.
Quantitative analysis of tumor vascularity in benign and malignant solid thyroid nodules. Journal of
Ultrasound in Medicine, 2007. 26(6): 837-846.
A. Lyshchik, R. Moses, S.L. Barnes, T. Higashi, M.I. Miga, A.C. Fleischer. Sonographic appearance
of thyroid tumors with different aggressiveness and metastatic potential. American Journal of
Roentgenology, 2007. 188(5).
Abstracts and Presentations
S.L. Barnes*, A.G. Sorace*, J.G. Whisenant, M.E. Loveless, T.E. Yankeelov. ‘Correlation of
Quantitative MRI-derived Tumor Characteristics with Histology in Breast Cancer Murine Models.’
International Society for Magnetic Resonance in Medicine. Toronto, 2015.
X. Jiang, H. Li, P. Zhao, J. Xie, S.L. Barnes, T.E. Yankeelov, J. Xu, and J. Gore. ‘Quantitative
Characterization of tumor Microstructural Variations in Response to Chemotherapy Using Temporal
Diffusion Spectroscopy.’ International Society for Magnetic Resonance in Medicine, Toronto, 2015.
S.L. Barnes, M.T. McKenna, D.A. Hormuth II, J.A. Weis, L.R. Arlinghaus, X. Li, E.C. Rericha, D.
Tyson, M.I. Miga, V. Quaranta, and T.E. Yankeelov. ‘Incorporating Patient-Specific Imaging Data
and Treatment Regimes to Predict Treatment Response in a Multi-Scale Model of Breast Cancer.’
International Society for Magnetic Resonance in Medicine Workshop on Breast Disease, San
Francisco, 2015.
S.L. Barnes, J.G. Whisenant, J.O. McIntyre, and T.E. Yankeelov. ‘Investigating MRI Biomarkers as
Indicators of Early Treatment Response in a Triple Negative Model of Breast Cancer’, International
Society for Magnetic Resonance in Medicine, Milan, 2014.
S.L. Barnes, N.B. Semmineh, C. Chad Quarles, and T.E. Yankeelov. ‘Evaluation of the Effect of
Intra-voxel Contrast Agent Diffusion on Quantitative DCE-MRI’, International Society for Magnetic
Resonance in Medicine, Milan, 2014.
S.L. Barnes. ‘Investigating Imaging Biomarkers of Treatment Response in a Pre-Clinical Model of
Triple Negative Breast Cancer’, Cancer Imaging Group presentation, Vanderbilt University,
1/16/2013.
J.A. Weis, T.E. Yankeelov, S.A. Munoz, R.A. Sastry, S.L. Barnes, L.R. Arlinghaus, X. Li, and M.I.
Miga, ‘A Consistent Pre-clinical/Clinical Elastography Approach for Assessing Tumor Mechanical
Properties in Therapeutic Systems’, SPIE 2013 Medical Imaging: Biomedical Applications in
Molecular, Structural, and Functional Imaging, (in press), 2013.
M.N. Tantawy, G.H. Wilson, T.E. Peterson, S.L. Barnes, J.G. Whisenant, J.M. True, D.C. Colvin,
M.L. Nickels, T.E. Yankeelov, J.C. Gore. ‘A Novel Approach to Breast Cancer Diagnosis via PET
Imaging of Microcalcifications Using 18F-NaF’, SNMMI Annual Meeting, 2013:449.
September 16, 2014

4. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
S.L. Barnes, C. Chad Quarles, and T.E. Yankeelov. ‘Investigating the Effect of Intra-voxel Contrast
Agent Diffusion on Quantitative DCE-MRI’, International Society for Magnetic Resonance in
Medicine, Salt Lake City, 2013.
S.L. Barnes, J.G. Whisenant, and T.E. Yankeelov. ‘Investigating Molecular Imaging Biomarkers as
Preliminary Indicators of Treatment Response in a Triple-Negative Model of Breast Cancer’, Journal
of Nuclear Medicine, 54: S1, p3. AACR-SNMMI Joint Conference on State-of-the-Art Molecular
Imaging in Cancer Biology and Therapy, San Diego, 2013.
D. Smith, S.L. Barnes, and T.E. Yankeelov. ‘Separation of Signal and Noise in Dynamic MRI Data
using the Kolmogorov-Smirnov Test’, International Society for Magnetic Resonance in Medicine, Salt
Lake City, 2013.
S.L. Barnes, J.G. Whisenant, G.D. Ayers, and T.E. Yankeelov. ‘Investigating the Repeatability of
Quantitative DCE-MRI in Mice’, International Society for Magnetic Resonance in Medicine,
Melbourne, 2012.
S.L. Barnes. ‘Quantitative MRI (and PET) in Pre-Clinical Models of Breast Cancer’, R25 EAB
Presentation, Vanderbilt University, 11/16/2012.
J.A. Weis, S.L. Barnes, T.E. Yankeelov, M. Miga. ‘Material Property Assessment of a Murine Model
of Triple Negative Breast Cancer Using Modality Independent Elastography: Preliminary Results’,
BMES Annual Meeting, 2012.
S.L. Barnes. ‘Imaging Biomarkers of Treatment Response in Murine Models of Breast Cancer’,
Vanderbilt University Institute of Imaging Sciences Friday Seminar, Vanderbilt University,
11/18/2011.
S.L. Barnes. ‘Assessing Repeatability in Small Animal Imaging’, Cancer Imaging Group
presentation, Vanderbilt University, 10/13/2011.
S.L. Barnes, J.C. Gore, and T.E. Yankeelov. ‘Modeling the Effect of Diffusion on the Assessment of
Ktrans
, ve, and vp in DCE-MRI', International Society for Magnetic Resonance in Medicine, Montréal,
2011.
S.L. Barnes. ‘Aspects of Diffusion in MRI: Compressed Sensing in DW-MRI and Contrast Agent
Diffusion in DCE-MRI’, Vanderbilt University Institute of Imaging Sciences Annual Retreat,
Louisville, KY, 7/15/2011.
S.L. Barnes. ‘Modeling the Effect of Diffusion on DCE-MRI Parameterization and Investigating
Imaging Biomarkers of Treatment Response in a Preclinical Model of Human Breast Cancer’, Cancer
Imaging Group presentation, Vanderbilt University, 4/7/2011.
S.L. Barnes and M.I. Miga. ‘Application of a soft tissue modulus evaluation assay to breast tumor
tissue’, Proc. Biomedical Engineering Society Conference 2010, 10/6-9/10, Austin, TX, 2010.
S.L. Barnes, A. Lyschik, J.C. Gore, M.I. Miga. Development of a mechanical assay for modulus
analysis of fibrotic murine livers. 6th
International Conference on the Ultrasonic Measurement and
Imaging of Tissue Elasticity, Sante Fe, New Mexico, pg. 48, 11/2-5/2007.
September 16, 2014

5. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
D.R. Schuler III, J.J. Ou, S.L. Barnes, and M.I. Miga. ‘Automatic surface correspondence methods for
a deformed breast’, Medical Imaging 2006: Visualization, Image-guided Procedures, and Display:
Proc. of the SPIE, 2006.
J.J. Ou, S.L. Barnes, and M.I. Miga. 'Application of Multi-resolution Modality Independent
Elastography for Detection of Multiple Anomalous Objects', Medical Imaging 2006: Physiology,
Function and Structure from Medical Images: Proc. of the SPIE, 2006.
J.J. Ou, S.L. Barnes, and M.I. Miga. 'Preliminary testing of sensitivity to input data quality in an
elastographic reconstruction method', International Symposium on Biomedical Imaging 2006.
Invited Reviewer
British Journal of Medicine and Medical Research
Cancer Medicine
NMR in Biomedicine
PLOS One
Research
Utilizing Quantitative Imaging Data to Predict Treatment Response In Patients Undergoing
Neoadjuvant Treatment for Breast Cancer
Post-doctoral research at Vanderbilt University Institute of Imaging Sciences (3/14) –
(11/14)
This work utilizes imaging data sets obtained from patients undergoing neoadjuvant
treatment for breast cancer. The work focused on modeling breast cancer growth and
response to treatment using patient specific data from quantitative imaging sets.
Investigating Potential Imaging Biomarkers of Treatment Response in a Preclinical Model of
Triple Negative Breast Cancer
Post-doctoral research at Vanderbilt University Institute of Imaging Sciences (9/11) –
(5/14)
This research focused on investigating and identifying potential imaging biomarkers of
treatment response that can be used to evaluate an individual patient’s response to
treatment prior to the standard criteria, which is a change in tumor volume.
Modeling the Effect of Diffusion on DCE-Parameterization Error
Post-doctoral research at Vanderbilt University Institute of Imaging Sciences (9/10) –
(2/14)
I developed a finite element model simulating diffusion in a physiologically relevant
preclinically-sized voxel containing vessels, cells, and extravascular extracellular space
in order to evaluate the error of the extended model in evaluating Ktrans
, ve, and vp in
dynamic contrast enhanced MRI. The work required programming and finite element
analysis.
September 16, 2014

6. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
Evaluating the Repeatability of DCE-MRI
Post-doctoral research at Vanderbilt University Institute of Imaging Sciences (9/10) –
(8/11)
This research focused on quantifying the repeatability of the dynamic acquisition of
DCE-MRI. The intent was to evaluate the measurement error associated with the
acquisition so that changes in the derived parameters due to treatment response may be
identified. The research required mouse work, MRI acquisition, and statistical analysis.
Development and Evaluation of the Model-Gel-Tissue Assay
Master of Science and Doctor of Philosophy research at Vanderbilt University (8/05) –
(8/10)
This work focused on the development of the MGT assay which is a soft tissue modulus
evaluation technique that combines mechanical testing and computational modeling. I
was responsible for development of the assay including dictating the specifics of the
system, evaluating the system’s limitations and capabilities, and testing the assay with
various soft tissues. The work required programming, finite element analysis, and
mechanical testing.
Sensitivity Testing of Modality Independent Elastography Reconstruction Method
Research at Vanderbilt University (8/04) – (8/05)
I performed work in evaluating the sensitivity of the MIE modulus reconstruction
method to initiating parameters and image noise. This work utilized MATLAB
evaluation and image processing.
Computational Modeling of the Abdominal Aortic Aneurysm
Internship at Oak Ridge National Laboratory (6/03) – (8/03)
For this work I focused on abdominal aortic aneurysms and determining the point of
rupture through computational modeling. The work required utilizing computer
programs for 3D modeling, NURBS geometry, geometry meshing, and finite element
analysis.
The University of Tennessee (10/03) – (5/04)
Continuation of research from ORNL internship. The work included revision of the
computational models of the aneurysm in considering various properties of the vessel
wall.
Grants, Fellowships, and Honors
National Science Foundation Graduate Research Fellowship 2005-08
Harold Stirling Vanderbilt Graduate Scholarships 2004-08
L. Raymon Shobe Scholarship from the Department of Mechanical, Aerospace,
and Biomedical Engineering 2003-04
Outstanding Sophomore in Engineering 2002-03
Society of Women Engineers, President 2003-04
Tau Beta Pi, Engineering Honors Society
Mortar Board National Honor Society
September 16, 2014

7. Stephanie Lynne Barnes
steph.barnes@vanderbilt.edu
vba8264552@comcast.net
September 16, 2014