Abstract #0322
Investigating tissue microstructure of prostate cancer using Linear Multi-scale Modeling of diffusion MRI data
Barbara Daria Wichtmann1, Niklas Westhoff2, Cleo-Aron Weis3, Ralph Strecker4, Thorsten Feiweier5, Steffen Albert6,7, Moritz Wolter8, Frank Zöllner6,7, Bettina Baeßler9, Aapo Nummenmaa10, Qiuyun Fan10,11, Susie Huang10,12, and Ulrike Attenberger1
1Diagnostic and Interventional Radiology, University Hospital Bonn, Bonn, Germany, 2Department of Urology and Urosurgery, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 3Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany, Heidelberg, Germany, 4EMEA Scientific Partnerships, Siemens Healthcare GmbH, Erlangen, Germany, 5MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany, 6Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 7Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany, 8High Performance Computing & Analytics Lab, University Bonn, Bonn, Germany, 9Institute of Diagnostic and Interventional Radiology, University Hospital Würzburg, Würzburg, Germany, 10A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States, 11Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China, 12Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
Synopsis
Keywords: Prostate, CancerLinear Multi-scale Modeling (LMM) is an advanced diffusion-weighted imaging(DWI) technique that uses multi-shell, multi-diffusion-time DWI data to estimate tissue microstructure parameters, including volume fractions of restricted and hindered water compartments over a range of length scales and orientation distribution information. Here,we apply the LMM framework to characterize prostate cancer(PCa) lesions and correlate our results with histology. Within the histopathologically proven cancerous lesions we observed a significantly increased fraction of restricted diffusion, particularly within the 2μm and 7μm sized water compartments. LMM may enable the development of distinct diffusion microstructural signatures of PCa to facilitate diagnosis of clinically significant PCa lesions.
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