Jose Guerrero, MS

The emphasis of my research is on characterizing the microstructural organization of the human brain using Magnetic Resonance Imaging. More specifically, I am focused on using diffusion-weighted MRI (dMRI) to study microstructural connectivity patterns in brain regions.

I am currently working on the optimization and implementation of dMRI methods that go beyond diffusion tensor imaging (DTI) such us neurite orientation dispersion and density imaging. I am also working on the development of novel approaches for the analysis of dMRI quantitative measures as well as on the development of novel tools for quality assurance of dMRI data acquisition.

Such techniques are to be used for investigating the brain of typically developing individuals as well as the brain of individuals suffering from neurological conditions such as traumatic brain injury and developmental disorders like autism.

Home Departments: Medical Physics

Major Professor: Andy Alexander, PhD

Disciplines that I pull from in my research include: Physics, Mathematics, Computer Science, Neuroscience, Engineering.

Articles That Influenced My Research: 

Alexander AL, Lee JE, Lazar M, Field AS. (2007). Diffusion tensor imaging of the brain. Neurotherapeutics: The Journal of the American Society for Experimental NeuroTherapeutics, 4(3), 316–329. https://doi.org/10.1016/j.nurt.2007.05.011. PMCID: PMC2041910

Alexander DC. (2008). A general framework for experiment design in diffusion MRI and its application in measuring direct tissue-microstructure features. Magnetic Resonance in Medicine, 60(2), 439–448. https://doi.org/10.1002/mrm.21646

Dean DC, Lange N, Travers BG, Prigge MB, Matsunami N, Kellett KA, … Alexander AL. (2017). Multivariate characterization of white matter heterogeneity in autism spectrum disorder. NeuroImage. Clinical, 14, 54–66. https://doi.org/10.1016/j.nicl.2017.01.002. PMCID: PMC5257193

Jelescu IO, Veraart J, Fieremans E, Novikov DS. (2016). Degeneracy in model parameter estimation for multi-compartmental diffusion in neuronal tissue: Degeneracy in Model Parameter Estimation of Diffusion in Neural Tissue. NMR in Biomedicine, 29(1), 33–47. https://doi.org/10.1002/nbm.3450. PMCID: PMC4920129

Jones DK, Cercignani M. (2010). Twenty-five pitfalls in the analysis of diffusion MRI data. NMR in Biomedicine, 23(7), 803–820. https://doi.org/10.1002/nbm.1543

Jones DK, Knösche TR, Turner R. (2013). White matter integrity, fiber count, and other fallacies: The do’s and don’ts of diffusion MRI. NeuroImage, 73, 239–254. https://doi.org/10.1016/j.neuroimage.2012.06.081

Kiselev VG. (2010). The Cumulant Expansion: An Overarching Mathematical Framework For Understanding Diffusion NMR. In D. K. Jones, PhD (Ed.), Diffusion MRI (pp. 152–168). Oxford University Press. https://doi.org/10.1093/med/9780195369779.003.0010

Lipton ML, Kim N, Park YK, Hulkower MB, Gardin TM, Shifteh K, … Branch CA. (2012). Robust detection of traumatic axonal injury in individual mild traumatic brain injury patients: Intersubject variation, change over time and bidirectional changes in anisotropy. Brain Imaging and Behavior, 6(2), 329–342. https://doi.org/10.1007/s11682-012-9175-2

Malyarenko D, Galbán CJ, Londy FJ, Meyer CR, Johnson TD, Rehemtulla A, … Chenevert TL. (2013). Multi-system repeatability and reproducibility of apparent diffusion coefficient measurement using an ice-water phantom. Journal of Magnetic Resonance Imaging: JMRI, 37(5), 1238–1246. https://doi.org/10.1002/jmri.23825. PMCID: PMC3548033

Tofts PS, Lloyd D, Clark CA, Barker GJ, Parker GJ, McConville P, … Pope JM. (2000). Test liquids for quantitative MRI measurements of self-diffusion coefficient in vivo. Magnetic Resonance in Medicine, 43(3), 368–374.

Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. (2012). NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage, 61(4), 1000–1016. https://doi.org/10.1016/j.neuroimage.2012.03.072