Dr. Francesca Zanderigo, PhD, is a Bioengineer, Associate Professor in the Department of Psychiatry at Columbia University, and Co-Director of the Brain Imaging Lab in the Molecular Imaging and Neuropathology Area at the New York State Psychiatric Institute. She has worked for over 17 years now in the field of medical imaging research, performing extensive quantification, mathematical modeling and analysis of brain images and data from both Magnetic Resonance Imaging and Positron Emission Tomography (PET) for the investigation of cerebral hemodynamics and neuroreceptor systems. In particular, Dr. Zanderigo is a pioneer in the development and application of computational algorithms for the analysis of data from PET that do not require invasive blood sampling during imaging. Dr. Zanderigo is currently Principal Investigator of an R01 funded by the National Institute of Biomedical Imaging and Bioengineering that aims at developing noninvasive quantification methods for data acquired with next-generation portable PET cameras. Dr. Zanderigo is Co-Investigator in the Conte Center for Suicide Prevention Project 3, “PET Neuroimaging in Vivo in Mood Disorders and Suicidal Behavior”.
Research Focus
Dr. Zanderigo’s research focuses on the extraction of accurate quantitative information from medical data and images, for the purpose of improving disease diagnosis and treatment. This includes the development of sophisticated methods for data quantification that simplify the acquisition of Positron Emission Tomography (PET) images, while maintaining accuracy and precision of the information extracted from such images, with the aim of promoting the translation of PET technique into clinical practice. These advanced methods allow investigators to reduce, and in some cases, eliminate the need for arterial blood sampling during imaging with PET, and have been applied to PET radiotracers used to image, for example, the translocator protein, monoamine oxidase A, the incorporation of arachidonic acid, the serotonin 1A receptor and transporter, and glucose metabolism. Further contributions from Dr. Zanderigo include creating approaches that overcome the problem posed by many targets of PET imaging, the absence of a valid reference region, to provide measurements of PET binding that are specific only to the target of interest. As well, her work includes developing other advanced methodologies in the field of in vivo brain imaging, ranging in scope from the generation of quantitative parametric images at the voxel level, to data-adaptive robust fitting approaches to improve statistical power and sensitivity of imaging studies, to model-free quantification for PET images.
Select Publications
1. Roccia E, Mikhno A, Ogden RT, Mann JJ, Laine AF, Angelini ED, Zanderigo F. Quantifying Brain [18F]FDG Uptake Noninvasively by Combining Medical Health Records and Dynamic PET Imaging Data. IEEE J Biomed Health Inform. 2019 Jan 1. doi: 10.1109/JBHI.2018.2890459. (Epub ahead of print).
2. Schain M, Zanderigo F, Ogden RT. Likelihood Estimation of Drug Occupancy for Brain PET Studies. Neuroimage, 2018; 178: 255-265.
3. Zanderigo F, Pantazatos S, Rubin-Falcone H, Ogden RT, Thapa-Chhetry B, Sullivan G, Oquendo MA, Miller JM, Mann JJ. In vivo relationship between serotonin 1A receptor binding and gray matter volume in the healthy brain and in major depressive disorder. Brain Structure and Function, 2018; 223(6): 2609-2625.
4. Zanderigo F, D’Agostino AE, Joshi N, Schain M, Kumar D, Parsey RV, Delorenzo C, Mann JJ. [11C]harmine binding to brain monoamine oxidase A: test-retest properties and noninvasive quantification. Molecular Imaging and Biology, 2018, 20(4), 667-681.
5. Zanderigo F, Kang Y, Kumar D, Nikolopoulou A, Mozley PD, Kothari PJ, He B, Schlyer D, Rapoport SI, Oquendo MA, Vallabhajosula S, Mann JJ, Sublette ME. [11C]arachidonic acid incorporation measurement in human brain: optimization for clinical use. Synapse, 2018; 72(2), e22018.
6. Zanderigo F, Mann J, Ogden T. A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region. PLoS One, 2017; 12(5): e0176636.
7. Schain M, Zanderigo F, Mann JJ, Ogden RT. Estimation of the binding potential BPND without a reference region or blood samples for brain PET studies. Neuroimage, 2017; 146: 121-131.
8. Zanderigo F, Parsey RV, Ogden RT. Model-free quantification of dynamic PET data using nonparametric deconvolution. J Cereb Blood Flow Metab, 2015; 35(8): 1368-1379.
9. Ogden RT, Zanderigo F, Parsey RV. Estimation of in vivo nonspecific binding in positron emission tomography studies without requiring a reference region. Neuroimage, 2015; 108: 234-242.
10. Zanderigo F, Ogden RT, Parsey RV. Noninvasive blood-free full quantification of positron emission tomography radioligand binding. J Cereb Blood Flow Metab, 2015; 35(1): 148-156.
11. Zanderigo F, Ogden RT, Parsey RV. Reference region approaches in PET: a comparative study on multiple radioligands. J Cereb Blood Flow Metab, 2013; 33(6): 888-897.
12. Zanderigo F, Ogden RT, Chang C, Choy S, Wong A, Parsey RV. Robust fitting of [11C]-WAY-100635 PET data. J Cereb Blood Flow Metab, 2010; 30(7): 1366-1372.
13. Zanderigo F, Ogden RT, Bertoldo A, Cobelli C, Mann JJ, Parsey RV. Empirical Bayesian estimation in graphical analysis: a voxel-based approach for the determination of the volume of distribution in PET studies. Nuclear Medicine and Biology, 2010; 37: 443-451.
14. Zanderigo F, Bertoldo A, Pillonetto G, Cobelli C. Nonlinear stochastic regularization to characterize tissue residue function in bolus-tracking MRI: assessment and comparison with SVD, block-Circulant SVD and Tikhonov. IEEE Transaction on Biomedical Engineering, 2009; 56(5): 1287-1297.