Scott Beeman

Scott Beeman

Assistant Professor,
School of Biological and Health Systems Engineering
Other ASU affiliations
Neuroscience (PhD) program
Assistant Professor, Program Director Masters in Medical Engineering and Course Director Applications in Medical Engineering 1, John Shufeldt School of Medicine and Medical Engineering
Biodesign Center for Single Molecule Biophysics
  • [email protected]
  • Phone: 480-727-9061
  • ‌
  • ISTB1 Building, Room 281D 550 E Orange St. PO Box 879709 Tempe, AZ 85287
  • Mail code: 9709
    Campus: Tempe
  • ‌
Biography Research Teaching
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Long Bio

My laboratory develops quantitative magnetic‑resonance (MRI and NMR) methods to measure tissue microstructure and metabolism in vivo. Specifically, our team integrates advanced diffusion MRI signal modelling, deuterium (2H) metabolic MRI, and oxygen‑sensitive MRI techniques to study neurodegenerative, metabolic, and oncologic disease. These tools form the technical foundation of a current NCI R37 MERIT award on invasive glioma subtypes and foundation‑ and state‑supported studies in Alzheimer’s disease and tumor metabolism. To date, my research has produced 47 peer‑reviewed publications, >1500 citations, and more than $4 M in research funding, demonstrating my capacity to lead multidisciplinary projects and manage complex budgets. Central to my research program is trainee mentorship; current and past primary trainees include three post‑doctoral fellows, eight PhD students, and numerous master’s and undergraduate researchers, several of whom have earned competitive fellowships and awards. 

Education
  • Postdoctoral Research Associate. Washington University School of Medicine, St. Louis, MO. 2013-2016    
  • Ph.D. Biomedical Engineering, Arizona State University 2012 
  • B.S.E. Bioengineering, Arizona State University 2007
Google Scholar URL
Google Scholar Profile
Research Interests

The mission of Dr. Beeman’s laboratory is to design quantitative magnetic resonance (MR)-based methods, informed by the fundamental biophysics that underpin the complex in vivo MR signal, to advance the scientific understanding of health and disease. Current funded research efforts are aimed at developing quantitative MR-based methods to: (i) identify and characterize invasive glioma brain tumor subtypes and (ii) interrogate the unknown pathogenesis of type 2 diabetes and its downstream complications.

Publications
  1. Hakhu S, VanGilder JL, Baxter LC, Schilling K, Zhou Y, Hu L, Beeman SC*. White matter characterization in regions of edema surrounding meningioma brain tumor using DTI and NODDI: A comparative study of DTI and NODDI. MEdRxiv. MEDRXIV/2025/325393
  2. Lingo VanGilder J, Hakhu S, Hooyman A, Schilling KG, Hu LS, Zhou Y, Caselli RJ, Baxter LC, Beeman SC*. Relating hippocampal subfield microstructure to delayed verbal memory in cognitively intact individuals at genetic risk for developing Alzheimer's disease. American Journal of Neuroradiology. MedRxiv. MEDRXIV/2025/325398
  3. Hakhu S, Hooyman A, VanGilder JL, Schaefer SY, Beeman SC*. Diffusion MRI-based measures of neurite microstructure associate with future risk of Alzheimer’s Disease. MEdRxiv. MEDRXIV/2025/325401
  4. Hakhu S, Hu LS, Beeman S, Sadleir RJ. Comparison of modelled diffusion-derived electrical conductivities found using magnetic resonance imaging. Front Radiol. 2025 Jan 22;5:1492479. doi: 10.3389/fradi.2025.1492479. PMID: 39917284; PMCID: PMC11794185.
  5. Hu, L.S., D’Angelo, F., Weiskittel, T.M. et al. Integrated molecular and multiparametric MRI mapping of high-grade glioma identifies regional biologic signatures. Nat Commun 14, 6066 (2023). https://doi.org/10.1038/s41467-023-41559-1
  6. Lingo VanGilder J, Bergamino, M., Hooyman, A., Fitzhugh, M. C., Rogalsky, C., Stewart, J. C., Beeman, S. C., & Schaefer, S. Y. (2022). Using whole-brain diffusion tensor analysis to evaluate white matter structural correlates of delayed visuospatial memory and one-week motor skill retention in nondemented older adults: A preliminary study. PloS One, 17(9), e0274955. 
  7. Morozov, D., Parvin, N., Conaway, M., Oxley, G., Baldelomar, E. J., Cwiek, A., deRonde, K., Beeman, S. C., Charlton, J. R., & Bennett, K. M. (2022). Estimating Nephron Number from Biopsies: Impact on Clinical Studies. Journal of the American Society of Nephrology : JASN, 33(1), 39–48. 
  8. Charlton, J. R., Xu, Y., Parvin, N., Wu, T., Gao, F., Baldelomar, E. J., Morozov, D., Beeman, S. C., Derakhshan, J., & Bennett, K. M. (2021). Image analysis techniques to map pyramids, pyramid structure, glomerular distribution, and pathology in the intact human kidney from 3-D MRI. American Journal of Physiology. Renal Physiology, 321(3), F293–F304. 
  9. Morozov, D., Quirk, J. D., Beeman, SC* (2020). Toward noninvasive quantification of adipose tissue oxygenation with MRI. International Journal of Obesity, 44(8), 1776–1783. 
  10. Baldelomar, E. J., Reichert, D., Shoghi, K. I., Beeman, S. C., Charlton, J. R., Strong, L., Fettig, N., Klaas, A., & Bennett, K. M. (2020). Mapping nephron mass in vivo using positron emission tomography. American Journal of Physiology. Renal Physiology. 
  11. Cifarelli, V+, Beeman, SC+, Smith, G. I., Yoshino, J., Morozov, D., Beals, J. W., Kayser, B. D., Watrous, J. D., Jain, M., Patterson, B. W., & Klein, S. (2020). Decreased adipose tissue oxygenation associates with insulin resistance in individuals with obesity. The Journal of Clinical Investigation. 
  12. Som, A., Raliya, R., Paranandi, K., High, R. A., Reed, N., Beeman, S. C., Brandenburg, M., Sudlow, G., Prior, J. L., Akers, W., Mah-Som, A. Y., Habimana-Griffin, L., Garbow, J., Ippolito, J. E., Pagel, M. D., Biswas, P., & Achilefu, S. (2019). Calcium carbonate nanoparticles stimulate tumor metabolic reprogramming and modulate tumor metastasis. Nanomedicine (London, England), 14(2), 169–182.
  13. Seo, J. B., Riopel, M., Cabrales, P., Huh, J. Y., Bandyopadhyay, G. K., Andreyev, A. Y., Murphy, A. N., Beeman, S. C., Smith, G. I., Klein, S., Lee, Y. S., & Olefsky, J. M. (2019). Knockdown of Ant2 Reduces Adipocyte Hypoxia And Improves Insulin Resistance in Obesity. Nature Metabolism, 1(1), 86–97.
  14. Garbow, J. R., Tsien, C. I., & Beeman, S. C. (2018). Preclinical MRI: Studies of the irradiated brain. Journal of Magnetic Resonance (San Diego, Calif. : 1997), 292, 73–81. 
  15. Knutsen, RH+, Beeman, SC+, Broekelmann, T. J., Liu, D., Tsang, K. M., Kovacs, A., Ye, L., Danback, J. R., Watson, A., Wardlaw, A., Wagenseil, J. E., Garbow, J. R., Shoykhet, M., & Kozel, B. A. (2018). Minoxidil improves vascular compliance, restores cerebral blood flow, and alters extracellular matrix gene expression in a model of chronic vascular stiffness. American Journal of Physiology. Heart and Circulatory Physiology, 315(1), H18–H32. 
  16. Yang, R., Duan, C., Yuan, L., Engelbach, J. A., Tsien, C. I., Beeman, S. C., Perez-Torres, C. J., Ge, X., Rich, K. M., Ackerman, J. J. H., & Garbow, J. R. (2018). Inhibitors of HIF-1α and CXCR4 Mitigate the Development of Radiation Necrosis in Mouse Brain. International Journal of Radiation Oncology, Biology, Physics, 100(4), 1016–1025. 
  17. Chondronikola, M., Beeman, S. C., & Wahl, R. L. (2018). Non-invasive methods for the assessment of brown adipose tissue in humans. The Journal of Physiology, 596(3), 363–378. 
  18. Duan, C., Kallehauge, J. F., Pérez-Torres, C. J., Bretthorst, G. L., Beeman, S. C., Tanderup, K., Ackerman, J. J. H., & Garbow, J. R. (2018). Modeling Dynamic Contrast-Enhanced MRI Data with a Constrained Local AIF. Molecular Imaging and Biology, 20(1), 150–159. 
  19. Baldelomar, E. J., Charlton, J. R., Beeman, S. C., & Bennett, K. M. (2018). Measuring rat kidney glomerular number and size in vivo with MRI. American Journal of Physiology. Renal Physiology, 314(3), F399–F406. 
  20. Beeman, S. C., Knutsen, R. H., Broekelmann, T., Kovacs, A., Ye, L., Danback, J., Watson, A., Garbow, J. R., & Kozel, B. A. (2018). Minoxidil rescues elastin mediated vasculopathy and improves cerebral blood flow. Am J Physiol Heart Circ Physiol, 315(1), H18–H32. 
  21. Church, J. T., Werner, N. L., Coughlin, M. A., Menzel-Smith, J., Najjar, M., Carr, B. D., Parmar, H., Neil, J., Alexopoulos, D., Perez-Torres, C., Ge, X., Beeman, S. C., Garbow, J. R., & Mychaliska, G. B. (2018). Effects of an artificial placenta on brain development and injury in premature lambs. Journal of Pediatric Surgery, 53(6), 1234–1239. 
  22. Meinerz, K., Beeman, S. C., Duan, C., Bretthorst, G. L., Garbow, J. R., & Ackerman, J. J. H. (2018). Bayesian Modeling of NMR Data: Quantifying Longitudinal Relaxation , and  with a Tissue-Water-Relaxation Mimic (Crosslinked Bovine Serum Albumin). Applied Magnetic Resonance, 49(1), 3–24. 
  23. Duan, C., Perez-Torres, C. J., Yuan, L., Engelbach, J. A., Beeman, S. C., Tsien, C. I., Rich, K. M., Schmidt, R. E., Ackerman, J. J. H., & Garbow, J. R. (2017). Can anti-vascular endothelial growth factor antibody reverse radiation necrosis? A preclinical investigation. Journal of Neuro-Oncology, 133(1), 9–16. 
  24. Duan, C., Perez-Torres, C. J., Yuan, L., Engelbach, J. A., Beeman, S. C., Tsien, C. I., Rich, K. M., Schmidt, R. E., Ackerman, J. J. H., & Garbow, J. R. (2017). Can anti-vascular endothelial growth factor antibody reverse radiation necrosis? A preclinical investigation. J. Neurooncol, 133, 9–16. 
  25. Charlton, J. R., Pearl, V. M., Denotti, A. R., Lee, J. B., Swaminathan, S., Scindia, Y. M., Charlton, N. P., Baldelomar, E. J., Beeman, S. C., & Bennett, K. M. (2016). Biocompatibility of ferritin-based nanoparticles as targeted MRI contrast agents. Nanomedicine : Nanotechnology, Biology, and Medicine, 12(6), 1735–1745. 
  26. Beeman, S. C., Shui, Y.-B., Perez-Torres, C. J., Engelbach, J. A., Ackerman, J. J. H. J., & Garbow, J. R. (2016). O2 -sensitive MRI distinguishes brain tumor versus radiation necrosis in murine models. Magnetic Resonance in Medicine, 75(6), 2442–2447. 
  27. Charlton, J. R., Pearl, V. M., Denotti, A. R., Lee, J. B., Swaminathan, S., Scindia, Y. M., Charlton, N. P., Baldelomar, E. J., Beeman, S. C., & Bennett, K. M. (2016). Biocompatibility of ferritin-based nanoparticles as targeted MRI contrast agents. Nanomedicine: Nanotechnology, Biology and Medicine, 12(6), 1735–1745. 
  28. Bennett, K. M., Beeman, S. C., Baldelomar, E. J., Zhang, M., Wu, T., Hann, B. D., Bertram, J. F., & Charlton, J. R. (2016). Use of Cationized Ferritin Nanoparticles to Measure Renal Glomerular Microstructure with MRI. Methods in Molecular Biology (Clifton, N.J.), 1397, 67–79. 
  29. Baldelomar, E. J., Charlton, J. R., Beeman, S. C., Hann, B. D., Cullen-McEwen, L., Pearl, V. M., Bertram, J. F., Wu, T., Zhang, M., & Bennett, K. M. (2016). Phenotyping by magnetic resonance imaging nondestructively measures glomerular number and volume distribution in mice with and without nephron reduction. Kidney International, 89(2), 498–505. 
  30. Zhang, M., Wu, T., Beeman, S. C., Cullen-McEwen, L., Bertram, J. F., Charlton, J. R., Baldelomar, E., & Bennett, K. M. (2016). Efficient Small Blob Detection Based on Local Convexity, Intensity and Shape Information. IEEE Transactions on Medical Imaging, 35(4), 1127–1137. 
  31. Beeman, S. C., Osei-Owusu, P., Duan, C., Engelbach, J., Bretthorst, G. L., Ackerman, J. J. H., Blumer, K. J., & Garbow, J. R. (2015). Renal DCE-MRI Model Selection Using Bayesian Probability Theory. Tomography (Ann Arbor, Mich.), 1(1), 61–68. 
  32. Baldelomar, E., Charlton, J., Beeman, S. C., Hann, B., Cullen-McEwen, L., Pearl, V., Bertram, J. F., Wu, T., Zhang, M., & Bennett, K. M. (2015). MRI phenotyping to nondestructively measure glomerular number and volume distribution in mice with and without nephron reduction. Kidney Int., 89(2), 498–505. 
  33. Beeman, S. C., Cullen-McEwen, L. A., Puelles, V. G., Zhang, M., Wu, T., Baldelomar, E. J., Dowling, J., Charlton, J. R., Forbes, M. S., Ng, A., Wu, Q.-Z., Armitage, J. A., Egan, G. F., Bertram, J. F., & Bennett, K. M. (2014). MRI-based glomerular morphology and pathology in whole human kidneys. American Journal of Physiology. Renal Physiology, 306(11), F1381–F1390. 
  34. Bertram,  Cullen-McEwen LA, Egan G, Gretz N, Beeman SC, J. F., Bennett., K. M., & Beeman, S. C. (2014). How and why we determine nephron number. Ped Neprol, 29(4), 575–580. 
  35. Clavijo Jordan, M. V., Beeman, S. C., Baldelomar, E. J., & Bennett, K. M. (2014). Disruptive chemical doping in a ferritin-based iron oxide nanoparticle to decrease r2 and enhance detection with T1-weighted MRI. Contrast Media & Molecular Imaging, 9(5), 323–332. 
  36. Bertram, J. F., Cullen-McEwen, L. A., Egan, G. F., Gretz, N., Baldelomar, E., Beeman, S. C., & Bennett, K. M. (2014). Why and how we determine nephron number. Pediatric Nephrology (Berlin, Germany), 29(4), 575–580. 
  37. Charlton, J. R., Beeman, S. C., & Bennett, K. M. (2013). MRI-detectable nanoparticles: the potential role in the diagnosis of and therapy for chronic kidney disease. Advances in Chronic Kidney Disease, 20(6), 479–487. 
  38. Beeman, S. C., Mandarino, L. J., Georges, J. F., & Bennett, K. M. (2013). Cationized ferritin as a magnetic resonance imaging probe to detect microstructural changes in a rat model of non-alcoholic steatohepatitis. Magnetic Resonance in Medicine, 70(6), 1728–1738. 
  39. Qian, C., Yu, X., Chen, D.-Y., Dodd, S., Bouraoud, N., Pothayee, N., Chen, Y., Beeman, S., Bennett, K., Murphy-Boesch, J., & Koretsky, A. (2013). Wireless amplified nuclear MR detector (WAND) for high-spatial-resolution MR imaging of internal organs: preclinical demonstration in a rodent model. Radiology, 268(1), 228–236..
  40. Beeman, S. C., Georges, J. F., & Bennett, K. M. (2013). Toxicity, biodistribution, and ex vivo MRI detection of intravenously injected cationized ferritin. Magnetic Resonance in Medicine, 69(3), 853–861. 
  41. Bennett, K. M., Bertram, J. F., Beeman, S. C., & Gretz, N. (2013). The emerging role of MRI in quantitative renal glomerular morphology. American Journal of Physiology. Renal Physiology, 304(10), F1252–F1257. 
  42. Clavijo-Jordan, V., Kodibagkar, V. D., Beeman, S. C., Hann, B. D., & Bennett, K. M. (2012). Principles and emerging applications of nanomagnetic materials in medicine. Wiley Interdisciplinary Reviews. Nanomedicine and Nanobiotechnology, 4(4), 345–365. 
  43. Beeman, S. C., Zhang, M., Gubhaju, L., Wu, T., Bertram, J. F., Frakes, D. H., Cherry, B. R., & Bennett, K. M. (2011). Measuring glomerular number and size in perfused kidneys using MRI. American Journal of Physiology. Renal Physiology, 300(6), F1454–F1457. 
  44. Losey, T., Beeman, S. C., Ng, Y. T., Kerrigan, J. F., & Baxter, L. C. (2011). White matter density is increased in patients with hypothalamic hamartoma and multiple seizure types. Epilepsy Res, 93(2-3), 212–215. 
  45. Little, A. S., Liu, S., Beeman, S. C., Sankar, T., Preul, M. C., Hu, L. S., Smith, K. A., & Baxter, L. C. (2010). Brain retraction and thickness of cerebral neocortex: an automated technique for detecting retraction-induced anatomic changes using magnetic resonance imaging. Neurosurgery, 67(3 Suppl Operative), 277–282. 
  46. Zöllner, F. G., Dastrù, W., Irrera, P., Longo, D. L., Bennett, K. M., Beeman, S. C., Bretthorst, G. L., & Garbow, J. R. (2021). Analysis Protocol for Dynamic Contrast Enhanced (DCE) MRI of Renal Perfusion and Filtration. In Methods in molecular biology (Clifton, N.J.) (Vol. 2216, pp. 637–653). 
  47. Pedersen, M., Irrera, P., Dastrù, W., Zöllner, F. G., Bennett, K. M., Beeman, S. C., Bretthorst, G. L., Garbow, J. R., & Longo, D. L. (2021). Dynamic Contrast Enhancement (DCE) MRI-Derived Renal Perfusion and Filtration: Basic Concepts. In Methods in molecular biology (Clifton, N.J.) (Vol. 2216, pp. 205–227). 
  48. Beeman SC, & Garbow JR (2018). Fatty Liver Disease. In J. S. Lewis & K. R. Keshari (Eds.), Imaging and Metabolism (1st Edition; pp. 223–241). Springer Nature. 
  49. Bennett, K. M., Beeman, S. C., Baldelomar, E. J., Zhang, M., Wu, T., Hann, B. D., Bertram, J. F., & Charlton, J. R. (2016). Use of cationized ferritin nanoparticles to measure renal glomerular microstructure with MRI. In T. D. Hewitson, E. R. Smith, & S. G. Holt (Eds.), Kidney Research: Experimental Protocols (2nd Edition; pp. 67–69). Humana Press Springer. 
Courses
2027 Spring
Course Number Course Title
BIO 495 Undergraduate Research
2026 Spring
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BIO 495 Undergraduate Research
BME 394 Special Topics
2025 Fall
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BME 566 Medical Imaging Instrumentatn
BME 494 Special Topics
2025 Spring
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BIO 495 Undergraduate Research
2024 Fall
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SHS 592 Research
BME 350 Signals & Systems for Bioengrs
BME 566 Medical Imaging Instrumentatn
BME 494 Special Topics
2024 Spring
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BME 493 Honors Thesis
BIO 495 Undergraduate Research
2023 Fall
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BME 492 Honors Directed Study
SHS 592 Research
BME 566 Medical Imaging Instrumentatn
BME 494 Special Topics
2023 Spring
Course Number Course Title
BIO 495 Undergraduate Research
BME 382 Biomedical Prod Dsgn & Dev III
2022 Fall
Course Number Course Title
ASU 101-BME The ASU Experience
ASU 101-BME The ASU Experience
BME 566 Medical Imaging Instrumentatn
BME 494 Special Topics
2022 Spring
Course Number Course Title
BME 493 Honors Thesis
BIO 495 Undergraduate Research
BME 382 Biomedical Prod Dsgn & Dev III
2021 Fall
Course Number Course Title
ASU 101-BME The ASU Experience
ASU 101-BME The ASU Experience
ASU 101-BME The ASU Experience
BME 566 Medical Imaging Instrumentatn
BME 494 Special Topics
Expertise Areas
Bioimaging
Cellular, Molecular and Metabolic Imaging
Biophysics
Bioengineering
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