非参数统计
盒内非相干运动
细胞仪
乳房磁振造影
流式细胞术
磁共振弥散成像
磁共振成像
生物医学工程
计算机科学
医学
乳腺癌
放射科
癌症
统计
数学
乳腺摄影术
内科学
免疫学
作者
Junzhong Xu,Xiaoyu Jiang,Sean P. Devan,Lori R. Arlinghaus,Eliot T. McKinley,Jingping Xie,Zhongliang Zu,Qing Wang,A. Bapsi Chakravarthy,Yong Wang,John C. Gore
摘要
Purpose This report introduces and validates a new diffusion MRI‐based method, termed MRI‐cytometry , which can noninvasively map intravoxel, nonparametric cell size distributions in tissues. Methods MRI was used to acquire diffusion MRI signals with a range of diffusion times and gradient factors, and a model was fit to these data to derive estimates of cell size distributions. We implemented a 2‐step fitting method to avoid noise‐induced artificial peaks and provide reliable estimates of tumor cell size distributions. Computer simulations in silico, experimental measurements on cultured cells in vitro, and animal xenografts in vivo were used to validate the accuracy and precision of the method. Tumors in 7 patients with breast cancer were also imaged and analyzed using this MRI‐cytometry approach on a clinical 3 Tesla MRI scanner. Results Simulations and experimental results confirm that MRI‐cytometry can reliably map intravoxel, nonparametric cell size distributions and has the potential to discriminate smaller and larger cells. The application in breast cancer patients demonstrates the feasibility of direct translation of MRI‐cytometry to clinical applications. Conclusion The proposed MRI‐cytometry method can characterize nonparametric cell size distributions in human tumors, which potentially provides a practical imaging approach to derive specific histopathological information on biological tissues.
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