Quantitative Medical Imaging

The Section on Quantitative Medical Imaging develops methods to derive biomarkers from data acquired by non-invasive imaging techniques (such as Magnetic Resonance Imaging, MRI) that are informative about anatomy and physiology and that provide new, accurate and reliable tools for assessment of various medical conditions.

group photo of Pierpaoli's lab members
Left to right: Okan Irfanoglu, Ph.D., Anand Shunmugavel, Ph.D., Neda Sadeghi, Ph.D., Laura D. Reyes, Ph.D., Amritha Nayak, M.A., Angela Bissoli, M.D., Carlo Peirpaoli, M.D./Ph.D. (lab PI), Chung Mah Moon, Ph.D.  
Photo: C. Chang for NIBIB

Biomarkers1 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, and 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.

Perspective

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.

Methods Development

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.

Clinical Translation

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.

Conclusion

Our work aims at improving the quality, 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.

 

1. A biomarker is defined as: a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.

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