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Abstract #4743

Improving estimation of cell size distribution using Fourier expansion-based deconvolution for microstructural parameters mapping (FED-MPM)

Diwei Shi1, Sisi Li2, Yishi Wang3, Li Chen1, Xiaoyu Jiang4,5, Junzhong Xu4,5,6,7, Quanshui Zheng1, and Hua Guo2
1Center for Nano and Micro Mechanics, Department of Engineering Mechanics, Tsinghua University, Beijing, China, 2Center for Biomedical Imaging Research, Tsinghua University, Beijing, China, 3Philips Healthcare, Beijing, China, 4Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, 5Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, 6Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States, 7Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States


Cellular microstructural parameters mapping can provide quantitative information for tumor diagnosis and treatment monitoring. Particularly, voxel-wise cell size distribution may provide critical clinical biomarkers to characterize heterogeneity of tumors. Currently, MRI-cytometry may measure such a distribution, but it “blurs” the distribution peaks and prevents differentiating different cell populations with different cell sizes. In this work, we develop a new approach to improve this and hence make it more practical to distinguish different cells. Detection of T cell infiltration for assessment of early response to immunotherapy may be a potential application of this method.

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