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Abstract #4186

Animal Imaging Using L1-Regularized Quantitative Susceptibility Mapping

Ildar Khalidov1, Tian Liu1, Xiaoyue Chen2, Moonso Jin2, Ali S. Arbab3, Quan Jiang3, Martin Prince1, Yi Wang1

1Radiology, Weill Cornell Medical College, NYC, NY, United States; 2Biomedical Engineering, Cornell University, Ithaca, NY, United States; 3Neurology, Henry Ford Hospital, Detroit, MI, United States

Quantitative susceptibility mapping (QSM) is a technique that uses phase data from an MRI image to estimate the susceptibility distribution in the object. It has been demonstrated that QSM is able to correctly estimate the magnetic moment of specimen differing in susceptibility to the surrounding tissue [1]. We would like to exploit this ability to perform quantitative imaging of biomarkers in animal imaging. However, animal imaging presents additional challenges: the need for higher resolution suggests lower SNR; mixes of several tissues can create significant artifacts that impede quantification. In this work, we estimated the susceptibility change induced by SPIO nanoparticles that are targeted to specific cells. In experiment (1), we scan a rat brain after stroke injected with neural progenitor cells (NPCs) incubated in a solution containing a suspension of ferumoxide-protamine sulfate. In experiment (2), we image a mouse injected with SPIO nanoparticles that target the intercellular adhesion molecule ICAM-1, which is induced in response to inflammation. We use total-variation based regularization to circumvent the problems with low SNR and the streaking artifacts.