Carlo Pierpaoli, M.D., Ph.D.
Quantitative Medical Imaging Lab
Building 13, Room 3W16
13 South Drive
Bethesda, MD 20892
Biomarkers are of fundamental importance for any research endeavor aimed at improving human health. The main objective of the Section on Quantitative Medical Imaging is to research quantitative markers obtained with non-invasive imaging techniques, primarily MRI, encompassing methods development, biologic validation, and clinical application. We have been particularly focused on MRI of the normal brain and of neurologic disorders, but we are expanding our investigation to other organs.
We hope that our work will lead to improved accuracy, reliability, and interpretability of clinical MRI. The imaging methods we develop enable the creation of reliable normative databases and provide a framework for accurate phenotyping in personalized medicine. The quantitative nature of the novel biomarkers we investigate provides data suitable to be analyzed with artificial intelligence approaches for addressing clinical questions.
Quantitative MRI markers rely on the quality, accuracy and reliability of MRI data, which presents a major challenge for acquisitions, such as diffusion MRI (dMRI), that are vulnerable to artifacts. However, if we can understand the source and behavior of these factors then we can design approaches that are highly effective for correcting images during the post-acquisition processing stage.
Our lab has made contributions in imaging research which encompass the full quantitative imaging spectrum including: acquisition, processing, analysis, and clinical interpretation of findings. The tools we develop are publicly available in the TORTOISE software suite (www.tortoisedti.org) which currently includes artifact and distortion correction strategies, sophisticated multi-subject registration and a combined voxelwise analysis paradigm to detect microstructural and morphometric abnormalities in a robust and bias-free manner.
Because the ultimate goal of our research effort is to advance medical care, we have established several projects with intramural and extramural collaborators including both clinical and pre-clinical studies. Our current projects include probing the neurobiological underpinnings of the diffusion MRI signal, identifying MRI markers of pathology in experimental animal models of brain disorders, characterizing diffusion and morphometric brain changes during childhood and determining the presence and nature of abnormalities in human disorders such as stroke, traumatic brain injury, Down syndrome, Hereditary Spastic Paraparesis, and Moebius syndrome. We are also developing imaging strategies useful for prostate cancer assessment.
Dr. Pierpaoli received his M.D. at the university of Milan, Italy, followed by a specialization in Neurology, and a Ph.D. in Neuroscience. His early research experience was in neuropharmacology with an internship at the Institute for Pharmacological Research "Mario Negri" in Milan, Italy. Dr. Pierpaoli has spent most of his scientific career at the NIH, first at the National Institute of Neurological Disorders and Stroke (NINDS), then at the National Institute of Child Health and Human Development (NICHD), and currently in the Quantitative Medical Imaging Section, National Institute of Biomedical Imaging and Bioengineering (NIBIB). Dr. Pierpaoli's research is aimed at extracting accurate and reproducible biomarkers from data acquired with non-invasive imaging techniques, primarily Magnetic Resonance Imaging (MRI). He is mainly known for his contributions in the field of diffusion MRI applied to brain studies. Dr. Pierpaoli is a fellow of the International Society of Magnetic Resonance and received the NIH Award of Merit for performing the first diffusion tensor imaging studies of the human brain.
Irfanoglu MO, Nayak A, Jenkins J, Hutchinson EB, Sadeghi N, Thomas CP, Pierpaoli C. DR-TAMAS: Diffeomorphic Registration for Tensor Accurate Alignment of Anatomical Structures. Neuroimage. 2016;132:439-454.
Walker L, Chang LC, Nayak A, Irfanoglu MO, Botteron KN, McCracken J, McKinstry RC, Rivkin MJ, Wang DJ, Rumsey J, Pierpaoli C, Brain Development Cooperative Group.. The diffusion tensor imaging (DTI) component of the NIH MRI study of normal brain development (PedsDTI). Neuroimage. 2016;124(Pt B):1125-1130.
Irfanoglu MO, Sarlls J, Nayak A, Pierpaoli C. Evaluating corrections for Eddy-currents and other EPI distortions in diffusion MRI: methodology and a dataset for benchmarking. Magn Reson Med. 2019;81(4):2774-2787.
Hutchinson EB, Schwerin SC, Radomski KL, Sadeghi N, Komlosh ME, Irfanoglu MO, Juliano SL, Pierpaoli C. Detection and Distinction of Mild Brain Injury Effects in a Ferret Model Using Diffusion Tensor MRI (DTI) and DTI-Driven Tensor-Based Morphometry (D-TBM). Front Neurosci. 2018;12:573.
Thomas C, Sadeghi N, Nayak A, Trefler A, Sarlls J, Baker CI, Pierpaoli C. Impact of time-of-day on diffusivity measures of brain tissue derived from diffusion tensor imaging. Neuroimage. 2018;173:25-34.
Related Scientific Focus Areas
Biomedical Engineering and Biophysics
This page was last updated on August 31st, 2019