Alexandra Badea

Research Themes

Biomedical Imaging & Biophotonics

Research Interests

Alzheimer's Disease, Brain Imaging, MRI, Connectivity, Multivariate Biomarkers, Image Analysis, Neurological Conditions. 

Bio

I have a joint appointment in Radiology and Neurology and my research focuses on neurological conditions like Alzheimer’s disease. I work on imaging and analysis to provide a comprehensive characterization of the brain. MRI is particularly suitable for brain imaging, and diffusion tensor imaging is an important tool for studying brain microstructure, and the connectivity amongst gray matter regions.  

I am interested in image segmentation, morphometry and shape analysis, as well as in integrating information from MRI with genetics, and behavior. Our approaches  target: 1) phenotyping the neuroanatomy using imaging; 2) uncovering the link between structural and functional changes, the genetic bases, and environmental factors. I am interested in generating methods and tools for comprehensive phenotyping.

We use high-performance cluster computing to accelerate our image analysis. We use compressed sensing image reconstruction, and process large image arrays using deformable registration, perform segmentation based on multiple image contrasts including diffusion tensor imaging, as well as voxel, and graph analysis for connectomics.

At BIAC  my efforts focus on developing multivariate biomarkers and identifying vulnerable networks based on genetic risk for Alzheimer's disease.

My enthusiasm comes from the possibility to extend from single to integrative multivariate and network based analyses to obtain a comprehensive picture of normal development and aging, stages of disease, and the effects of treatments.  I am working on multivariate image analysis and predictive modeling approaches to help better understand early biomarkers for human disease indirectly through mouse models, as well as directly in human studies. 

I am dedicated to supporting an increase in female presence in STEM fields, and love working with students. The Bass Connections teams involve undergraduate students in research, providing them the opportunity to do independent research studies and get involved with the community. These students have for example takes classes such as:

BME 394: Projects in Biomedical Engineering (GE)
BME 493: Projects in Biomedical Engineering (GE)
ECE 899: Special Readings in Electrical Engineering
NEUROSCI 493: Research Independent Study 1

Education

• Ph.D. University of Patras (Greece), 2003

Positions

• Associate Professor in Radiology
• Associate Professor in Neurology
• Assistant Professor of Biomedical Engineering
• Member of the Center for Brain Imaging and Analysis

Courses Taught

• NEUROSCI 494: Research Independent Study 2
• MEDPHY 791: Independent Study in Medical Physics
• EGR 393: Research Projects in Engineering
• BRAINSOC 796T: Bass Connections in Brain & Society Research Team
• BRAINSOC 795T: Bass Connections in Brain & Society Research Team
• BRAINSOC 398T: Bass Connections in Brain & Society Research Team
• BRAINSOC 398: Bass Connections in Brain and Society 4: Interdisciplinary Team Projects
• BRAINSOC 398-1: Bass Connections in Brain and Society 4: Interdisciplinary Team Projects
• BRAINSOC 397T: Bass Connections in Brain & Society Research Team
• BRAINSOC 397-1: Bass Connections in Brain and Society 3: Interdisciplinary Team Projects
• BRAINSOC 396T: Bass Connections in Brain & Society Research Team
• BRAINSOC 396-1: Bass Connections in Brain and Society 2: Interdisciplinary Team Projects
• BRAINSOC 395T: Bass Connections in Brain & Society Research Team
• BRAINSOC 395: Bass Connections in Brain and Society: Interdisciplinary Team Projects
• BRAINSOC 395-1: Bass Connections in Brain and Society: Interdisciplinary Team Projects
• BME 791: Graduate Independent Study
• BME 494: Projects in Biomedical Engineering (GE)
• BME 493: Projects in Biomedical Engineering (GE)

Publications

• Winter S, Mahzarnia A, Anderson RJ, Han ZY, Tremblay J, Stout JA, et al. Brain network fingerprints of Alzheimer's disease risk factors in mouse models with humanized APOE alleles. Magn Reson Imaging. 2024 Dec;114:110251.
• Shen C, Wang S, Badea A, Priebe CE, Vogelstein JT. Discovering the signal subgraph: An iterative screening approach on graphs. Pattern Recognition Letters. 2024 Aug 1;184:97–102.
• Stout J, Anderson RJ, Mahzarnia A, Han Z, Beck K, Browndyke J, et al. Mapping the impact of age and APOE risk factors for late onset Alzheimer's disease on long range brain connections through multiscale bundle analysis. 2024.
• Stout JA, Mahzarnia A, Dai R, Anderson RJ, Cousins S, Zhuang J, et al. Accelerated Brain Atrophy, Microstructural Decline and Connectopathy in Age-Related Macular Degeneration. Biomedicines. 2024 Jan 10;12(1).
• Nadkarni R, Han ZY, Anderson RJ, Allphin AJ, Clark DP, Badea A, et al. High-resolution hybrid micro-CT imaging pipeline for mouse brain region segmentation and volumetric morphometry. PLoS One. 2024;19(5):e0303288.
• Moon HS, Mahzarnia A, Stout J, Anderson RJ, Strain M, Tremblay JT, et al. Multivariate investigation of aging in mouse models expressing the Alzheimer's protective APOE2 allele: integrating cognitive metrics, brain imaging, and blood transcriptomics. Brain Struct Funct. 2024 Jan;229(1):231–49.
• Moon HS, Mahzarnia A, Stout J, Anderson RJ, Han ZY, Badea CT, et al. Predicting brain age and associated structural networks in mouse models with humanized APOE alleles using integrative and interpretable graph neural networks. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2024.
• Mahzarnia A, Lutz MW, Badea A. A Continuous Extension of Gene Set Enrichment Analysis Using the Likelihood Ratio Test Statistics Identifies Vascular Endothelial Growth Factor as a Candidate Pathway for Alzheimer's Disease via ITGA5. J Alzheimers Dis. 2024;97(2):635–48.
• Mahzarnia A, Lutz MW, Badea A. A Continuous Extension of Gene Set Enrichment Analysis using the Likelihood Ratio Test Statistics Identifies VEGF as a Candidate Pathway for Alzheimer's disease. bioRxiv. 2023 Aug 26;
• Mahzarnia A, Stout JA, Anderson RJ, Moon HS, Yar Han Z, Beck K, et al. Identifying vulnerable brain networks associated with Alzheimer's disease risk. Cereb Cortex. 2023 Apr 25;33(9):5307–22.
• Gammon ST, Cohen AS, Lehnert AL, Sullivan DC, Malyarenko D, Manning HC, et al. An Online Repository for Pre-Clinical Imaging Protocols (PIPs). Tomography. 2023 Mar 27;9(2):750–8.
• Allphin AJ, Mahzarnia A, Clark DP, Qi Y, Han ZY, Bhandari P, et al. Advanced photon counting CT imaging pipeline for cardiac phenotyping of apolipoprotein E mouse models. PLoS One. 2023;18(10):e0291733.
• Moon HS, Heffron L, Mahzarnia A, Obeng-Gyasi B, Holbrook M, Badea CT, et al. Automated multimodal segmentation of acute ischemic stroke lesions on clinical MR images. Magn Reson Imaging. 2022 Oct;92:45–57.
• Stout JA, Dai R, Anderson RJ, Cousins S, Zhuang J, Lad EM, et al. Age-related Macular Degeneration is associated with faster rates of structural brain changes and widespread differences in connectivity. Cold Spring Harbor Laboratory. 2022.
• Badea A, Li D, Niculescu AR, Anderson RJ, Stout JA, Williams CL, et al. Absolute Winding Number Differentiates Spatial Navigation Strategies with Genetic Risk for Alzheimer's Disease. Cold Spring Harbor Laboratory. 2022.
• Badea A, Li D, Niculescu AR, Anderson RJ, Stout JA, Williams CL, et al. Corrigendum: Absolute winding number differentiates mouse spatial navigation strategies with genetic risk for Alzheimer's disease. Front Neurosci. 2022;16:1070425.
• Badea A, Li D, Niculescu AR, Anderson RJ, Stout JA, Williams CL, et al. Absolute Winding Number Differentiates Mouse Spatial Navigation Strategies With Genetic Risk for Alzheimer's Disease. Front Neurosci. 2022;16:848654.
• Allphin AJ, Clark DP, Badea A, Badea CT. Anatomical and functional cardiac PCCT imaging pipeline for characterization of Apolipoprotein E mouse models. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2022.
• Badea A, Stout JA, Anderson RJ, Cofer GP, Duan LL, Vogelstein JT. Imaging Biomarkers for Alzheimer’s Disease Using Magnetic Resonance Microscopy. In: Magnetic Resonance Microscopy: Instrumentation and Applications in Engineering, Life Science, and Energy Research. 2022. p. 283–314.
• Nair KS, Srivastava C, Brown RV, Koli S, Choquet H, Kang HS, et al. GLIS1 regulates trabecular meshwork function and intraocular pressure and is associated with glaucoma in humans. Nat Commun. 2021 Aug 12;12(1):4877.
• Bryan J, Mandan A, Kamat G, Gottschalk WK, Badea A, Adams KJ, et al. Likelihood ratio statistics for gene set enrichment in Alzheimer's disease pathways. Alzheimers Dement. 2021 Apr;17(4):561–73.
• Badea A, Schmalzigaug R, Kim W, Bonner P, Ahmed U, Johnson GA, et al. Microcephaly with altered cortical layering in GIT1 deficiency revealed by quantitative neuroimaging. Magn Reson Imaging. 2021 Feb;76:26–38.
• Whitson H, Badea A, Stout J, Davis S, Zhuang J, Madden D. AGE-RELATED MACULAR DEGENERATION AND THE AGING BRAIN. In: INNOVATION IN AGING. 2021. p. 156–156.
• Zhuang J, Madden DJ, Cunha P, Badea A, Davis SW, Potter GG, et al. Cerebral white matter connectivity, cognition, and age-related macular degeneration. Neuroimage Clin. 2021;30:102594.
• Slosky LM, Bai Y, Toth K, Ray C, Rochelle LK, Badea A, et al. β-Arrestin-Biased Allosteric Modulator of NTSR1 Selectively Attenuates Addictive Behaviors. Cell. 2020 Jun 11;181(6):1364-1379.e14.
• Anderson RJ, Long CM, Calabrese ED, Robertson SH, Johnson GA, Cofer GP, et al. Optimizing Diffusion Imaging Protocols for Structural Connectomics in Mouse Models of Neurological Conditions. Front Phys. 2020 Apr;8.
• Holbrook MD, Blocker SJ, Mowery YM, Badea A, Qi Y, Xu ES, et al. MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice. Tomography. 2020 Mar;6(1):23–33.
• Nair S, Srivastava C, Koli S, Kang HS, Kuo Y-M, Choquet H, et al. Kruppel-like zinc finger transcription factor GLIS1 regulates intraocular pressure by maintaining trabecular meshwork function. In: INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE. 2020.
• Holbrook MD, Blocker SJ, Mowery Y, Badea A, Qi Y, Kirsch DG, et al. MRI-based radiomics of sarcomas in the preclinical arm of a Co-clinical trial. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2020.
• Lorenzo DN, Badea A, Zhou R, Mohler PJ, Zhuang X, Bennett V. βII-spectrin promotes mouse brain connectivity through stabilizing axonal plasma membranes and enabling axonal organelle transport. Proc Natl Acad Sci U S A. 2019 Jul 30;116(31):15686–95.
• Yang R, Walder-Christensen KK, Kim N, Wu D, Lorenzo DN, Badea A, et al. ANK2 autism mutation targeting giant ankyrin-B promotes axon branching and ectopic connectivity. Proc Natl Acad Sci U S A. 2019 Jul 23;116(30):15262–71.
• Anderson RJ, Cook JJ, Delpratt N, Nouls JC, Gu B, McNamara JO, et al. Small Animal Multivariate Brain Analysis (SAMBA) - a High Throughput Pipeline with a Validation Framework. Neuroinformatics. 2019 Jul;17(3):451–72.
• Badea A, Delpratt NA, Anderson RJ, Dibb R, Qi Y, Wei H, et al. Multivariate MR biomarkers better predict cognitive dysfunction in mouse models of Alzheimer's disease. Magn Reson Imaging. 2019 Jul;60:52–67.
• Tange R, Ketcha M, Badea A, Calabrese ED, Margulies DS, Vogelstein JT, et al. Connectome Smoothing via Low-Rank Approximations. IEEE Trans Med Imaging. 2019 Jun;38(6):1446–56.
• Nouls JC, Virgincar RS, Culbert AG, Morand N, Bobbert DW, Yoder AD, et al. Applications of 3D printing in small animal magnetic resonance imaging. J Med Imaging (Bellingham). 2019 Apr;6(2):021605.
• Badea A, Wu W, Shuff J, Wang M, Anderson RJ, Qi Y, et al. Identifying Vulnerable Brain Networks in Mouse Models of Genetic Risk Factors for Late Onset Alzheimer's Disease. Front Neuroinform. 2019;13:72.
• Badea A, Ng KL, Anderson RJ, Zhang J, Miller MI, O’Brien RJ. Magnetic resonance imaging of mouse brain networks plasticity following motor learning. PLoS One. 2019;14(5):e0216596.
• Wang N, Anderson RJ, Badea A, Cofer G, Dibb R, Qi Y, et al. Whole mouse brain structural connectomics using magnetic resonance histology. Brain Struct Funct. 2018 Dec;223(9):4323–35.
• Nouls JC, Badea A, Anderson RBJ, Cofer GP, Allan Johnson G. Diffusion tensor imaging using multiple coils for mouse brain connectomics. NMR Biomed. 2018 Jun;31(6):e3921.
• Badea A, Kamnaksh A, Anderson RJ, Calabrese E, Long JB, Agoston DV. Repeated mild blast exposure in young adult rats results in dynamic and persistent microstructural changes in the brain. Neuroimage Clin. 2018;18:60–73.
• Graña GD, Hutson KA, Badea A, Pappa A, Scott W, Fitzpatrick DC. The organization of frequency and binaural cues in the gerbil inferior colliculus. J Comp Neurol. 2017 Jun 15;525(9):2050–74.
• Anderson RJ, Cook JJ, Delpratt NA, Nouls JC, Gu B, McNamara JO, et al. An HPC Pipeline with Validation Framework for Small Animal Multivariate Brain Analysis (SAMBA). CoRR. 2017;abs/1709.10483.
• Badea A, Kane L, Anderson RJ, Qi Y, Foster M, Cofer GP, et al. The fornix provides multiple biomarkers to characterize circuit disruption in a mouse model of Alzheimer's disease. Neuroimage. 2016 Nov 15;142:498–511.
• Bhagat SL, Qiu S, Caffall ZF, Wan Y, Pan Y, Rodriguiz RM, et al. Mouse model of rare TOR1A variant found in sporadic focal dystonia impairs domains affected in DYT1 dystonia patients and animal models. Neurobiol Dis. 2016 Sep;93:137–45.
• Wang X, Bey AL, Katz BM, Badea A, Kim N, David LK, et al. Altered mGluR5-Homer scaffolds and corticostriatal connectivity in a Shank3 complete knockout model of autism. Nat Commun. 2016 May 10;7:11459.
• Lorenzo DN, Badea A, Johnson G, Bennett V. An ankyrin-B/beta-2 spectrin-based mechanism regulates axonal organelle transport and axonal growth. In: MOLECULAR BIOLOGY OF THE CELL. AMER SOC CELL BIOLOGY; 2016.
• Johnson GA, Anderson RJ, Cook JJ, Long C, Badea A. Image-processing pipelines: Applications in magnetic resonance histology. In: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2016.
• Calabrese E, Badea A, Cofer G, Qi Y, Johnson GA. A Diffusion MRI Tractography Connectome of the Mouse Brain and Comparison with Neuronal Tracer Data. Cereb Cortex. 2015 Nov;25(11):4628–37.
• Calabrese E, Badea A, Coe CL, Lubach GR, Shi Y, Styner MA, et al. A diffusion tensor MRI atlas of the postmortem rhesus macaque brain. Neuroimage. 2015 Aug 15;117:408–16.
• Borg JS, Vu M-A, Badea C, Badea A, Johnson GA, Dzirasa K. Localization of Metal Electrodes in the Intact Rat Brain Using Registration of 3D Microcomputed Tomography Images to a Magnetic Resonance Histology Atlas. eNeuro. 2015;2(4).
• Lorenzo DN, Badea A, Davis J, Hostettler J, He J, Zhong G, et al. A PIK3C3-ankyrin-B-dynactin pathway promotes axonal growth and multiorganelle transport. J Cell Biol. 2014 Dec 22;207(6):735–52.
• Lorenzo DN, Badea A, Davis J, Hostettler JD, He J, Zhong G, et al. A PIK3C3/Ankyrin-B/Dynactin pathway promotes axonal growth and multi-organelle transport. In: MOLECULAR BIOLOGY OF THE CELL. AMER SOC CELL BIOLOGY; 2014.
• Calabrese E, Badea A, Coe CL, Lubach GR, Styner MA, Johnson GA. Investigating the tradeoffs between spatial resolution and diffusion sampling for brain mapping with diffusion tractography: time well spent? Hum Brain Mapp. 2014 Nov;35(11):5667–85.
• Johnson GA, Badea A, Calabrese E, Liu C, Xie L. Magnetic resonance histology—Applications in toxicology. In: Toxicology Letters. Elsevier BV; 2014. p. S31–2.
• Johnson GA, Calabrese E, Little PB, Hedlund L, Qi Y, Badea A. Quantitative mapping of trimethyltin injury in the rat brain using magnetic resonance histology. Neurotoxicology. 2014 May;42:12–23.
• Ashbrook DG, Delprato A, Grellmann C, Klein M, Wetzel R, Overall RW, et al. Transcript co-variance with Nestin in two mouse genetic reference populations identifies Lef1 as a novel candidate regulator of neural precursor cell proliferation in the adult hippocampus. Front Neurosci. 2014;8:418.
• Clark D, Badea A, Johnson GA, Badea CT. Constructing a 4D murine cardiac micro-CT atlas for automated segmentation and phenotyping applications. Progress in Biomedical Optics and Imaging - Proceedings of SPIE. 2013 Jun 3;8669.
• Calabrese E, Badea A, Watson C, Johnson GA. A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability. Neuroimage. 2013 May 1;71:196–206.
• Badea A, Johnson GA. Magnetic resonance microscopy. Stud Health Technol Inform. 2013;185:153–84.
• Johnson GA, Badea A, Calabrese E, Liu C, Xie L. Magnetic resonance histology: cool images- but who cares? TOXICOLOGY LETTERS. 2013;221:S50–S50.
• Badea A, Gewalt S, Avants BB, Cook JJ, Johnson GA. Quantitative mouse brain phenotyping based on single and multispectral MR protocols. Neuroimage. 2012 Nov 15;63(3):1633–45.
• Clark D, Badea A, Liu Y, Johnson GA, Badea CT. Registration-based segmentation of murine 4D cardiac micro-CT data using symmetric normalization. Phys Med Biol. 2012 Oct 7;57(19):6125–45.
• Driehuys B, Nouls J, Badea A, Bucholz E, Ghaghada K, Petiet A, et al. Small animal imaging with magnetic resonance microscopy. ILAR Journal. 2012 Sep 11;53(1):35–53.
• Johnson GA, Calabrese E, Badea A, Paxinos G, Watson C. A multidimensional magnetic resonance histology atlas of the Wistar rat brain. Neuroimage. 2012 Sep;62(3):1848–56.
• Wu T, Bae MH, Zhang M, Pan R, Badea A. A prior feature SVM-MRF based method for mouse brain segmentation. Neuroimage. 2012 Feb 1;59(3):2298–306.
• Badea A, Johnson GA. Magnetic resonance microscopy. Anal Cell Pathol (Amst). 2012;35(4):205–27.
• Poot M, Badea A, Williams RW, Kas MJ. Identifying human disease genes through cross-species gene mapping of evolutionary conserved processes. PLoS One. 2011 May 4;6(5):e18612.
• Bowden DM, Johnson GA, Zaborsky L, Green WDK, Moore E, Badea A, et al. A symmetrical Waxholm canonical mouse brain for NeuroMaps. J Neurosci Methods. 2011 Feb 15;195(2):170–5.
• Johnson GA, Badea A, Jiang Y. Quantitative neuromorphometry using magnetic resonance histology. Toxicol Pathol. 2011 Jan;39(1):85–91.
• Johnson GA, Badea A, Brandenburg J, Cofer G, Fubara B, Liu S, et al. Waxholm space: an image-based reference for coordinating mouse brain research. Neuroimage. 2010 Nov 1;53(2):365–72.
• Badea A, Johnson GA, Jankowsky JL. Remote sites of structural atrophy predict later amyloid formation in a mouse model of Alzheimer's disease. Neuroimage. 2010 Apr 1;50(2):416–27.
• Badea A, Johnson GA, Williams RW. Genetic dissection of the mouse CNS using magnetic resonance microscopy. Curr Opin Neurol. 2009 Aug;22(4):379–86.
• Bae MH, Pan R, Wu T, Badea A. Automated segmentation of mouse brain images using extended MRF. Neuroimage. 2009 Jul 1;46(3):717–25.
• Badea A, Johnson GA, Williams RW. Genetic dissection of the mouse brain using high-field magnetic resonance microscopy. Neuroimage. 2009 May 1;45(4):1067–79.
• Johnson AG, Badea A, Brandenberg J, Burstein P, Gustafson C, Liu S, et al. Waxholm Space: Target Volumes for a Standard Coordinate System for the Mouse Brain. Frontiers in Neuroinformatics. 2009;3.
• Sharief AA, Badea A, Dale AM, Johnson GA. Automated segmentation of the actively stained mouse brain using multi-spectral MR microscopy. Neuroimage. 2008 Jan 1;39(1):136–45.
• Driehuys B, Nouls J, Badea A, Bucholz E, Ghaghada K, Petiet A, et al. Small animal imaging with magnetic resonance microscopy. ILAR J. 2008;49(1):35–53.
• Badea A, Ali-Sharief AA, Johnson GA. Morphometric analysis of the C57BL/6J mouse brain. Neuroimage. 2007 Sep 1;37(3):683–93.
• Johnson GA, Ali-Sharief A, Badea A, Brandenburg J, Cofer G, Fubara B, et al. High-throughput morphologic phenotyping of the mouse brain with magnetic resonance histology. Neuroimage. 2007 Aug 1;37(1):82–9.
• Badea A, Nicholls PJ, Johnson GA, Wetsel WC. Neuroanatomical phenotypes in the reeler mouse. Neuroimage. 2007 Feb 15;34(4):1363–74.
• Ali AA, Dale AM, Badea A, Johnson GA. Automated segmentation of neuroanatomical structures in multispectral MR microscopy of the mouse brain. Neuroimage. 2005 Aug 15;27(2):425–35.
• Bowsher JE, Yuan H, Hedlund LW, Turkington TG, Akabani G, Badea A, et al. Utilizing MRI information to estimate F18-FDG distributions in rat flank tumors. In: IEEE Nuclear Science Symposium Conference Record. 2004. p. 2488–92.
• Badea A, Kostopoulos GK, Ioannides AA. Surface visualization of electromagnetic brain activity. J Neurosci Methods. 2003 Aug 15;127(2):137–47.

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