The University of Texas System

The University of Chicago

Milica Medved

Robert D Moser

Hiroyuki Abe

Aytekin Oto

Byol Kim

Todd A Oliver

Thomas Yankeelov

Federico Pineda

Rina F Barber

Chengyue Wu

Gregory Karczmar

Ty Easley

Aritrick Chatterjee

Xiaobing Fan

Deepa Sheth

David Hormuth

Shiyang Wang

Disclosed are approaches to non-invasively characterize a tumor or other lesion in a region of interest (ROI) based on various analyses of magnetic resonance imaging (MRI) data. The MRI data may correspond to ultrafast dynamic contrast enhanced MRI (DCE-MRI) and high spatial resolution DCE-MRI scans, and diffusion-weighted MRI (DW-MRI) scans of the ROI. Vasculature metrics may be determined, and tumor-associated blood flow velocity and/or tumor interstitial pressure may be obtained using the vasculature metrics as inputs to a computational fluid dynamics model. A combination of morphological vascular metrics and functional vascular metrics may be used to characterize the tumor. Malignancy, aggressiveness, treatment response, and other features of tumors or other lesions, in the breast or other regions of a patient, may be characterized through disclosed analyses of MRI data.

Characterization of lesions via determination of vascular metrics using MRI data

Growing community of inventors

Chicago, IL, United States of America

Milica Medved