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 Jiang^4,5, Junzhong Xu^4,5,6,7, 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

Synopsis

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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