Characterizing fluid flows in breast tumor DCE-MRI studies using unbalanced regularized optimal mass transport methods Conference Paper


Authors: Chen, X.; Huang, W.; Tannenbaum, A. R.; Deasy, J. O.
Title: Characterizing fluid flows in breast tumor DCE-MRI studies using unbalanced regularized optimal mass transport methods
Conference Title: SPIE Medical Imaging 2024: Image Processing
Abstract: Tumor vasculature varies widely among patients and is an important factor in disease progression and treatment response. Characterizing tumor fluid flows, often using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), is therefore a key component of disease assessment. In our work, we applied a computational fluid dynamical model we have developed, called the unbalanced regularized optimal mass transport (urOMT) method, to quantify and visualize fluid flow behaviors in breast tumors. Unlike the popular Tofts model, the urOMT model includes cross-voxel transport by solving an advection-diffusion equation. The urOMT outputs can reveal time-varying changes of physical transport properties at a local voxel level and can also visualize directional trend of the cross-voxel flows. Results for DCE-MRI studies of ten breast cancer patients each at four time points during neoadjuvant chemotherapy indicate that urOMT-produced metrics, flux, influx and efflux are potentially valuable biomarkers for evaluating therapeutic responses. © 2024 SPIE.
Keywords: chemotherapy; magnetic resonance imaging; biomarkers; breast cancer; molecular imaging; tumors; disease progression; biomarker; microfluidics; dynamic contrast-enhanced magnetic resonance imaging; diseases; dce-mri; disease treatment; tumor vasculature; flow of fluids; fluid-flow; optimal mass transport; advection; breast tumour; computational fluid dynamics; diffusion in liquids; transport method; tumor dynamics
Journal Title Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume: 12926
Conference Dates: 2024 Feb 19-22
Conference Location: San Deigo, CA
ISBN: 1605-7422
Publisher: SPIE  
Date Published: 2024-01-01
Start Page: 129261T
Language: English
DOI: 10.1117/12.3005382
PROVIDER: scopus
DOI/URL:
Notes: Conference paper -- Source: Scopus
Altmetric
Citation Impact
BMJ Impact Analytics
MSK Authors
  1. Joseph Owen Deasy
    524 Deasy
  2. Xinan Chen
    5 Chen