Characterization of lesions via determination of vascular metrics using MRI data

US12423806B2 · kind B2 · utility

Assignees

• The Board of Regents of the University of Texas System · US
• THE UNIVERSITY OF CHICAGO · US

Inventors

• Thomas Yankeelov · Austin, US
• Gregory Karczmar · Crete, US
• Chengyue Wu · Austin, US
• David Hormuth · Austin, US
• Todd A. Oliver · Austin, US
• Robert D. Moser · Austin, US
• Federico Pineda · Chicago, US
• Ty Easley · Chicago, US
• Rina F. Barber · Chicago, US
• Byol Kim · Chicago, US
• Deepa Sheth · Chicago, US
• Aytekin Oto · Chicago, US
• Hiroyuki Abe · Chicago, US
• Milica Medved · Chicago, US
• Xiaobing Fan · Chicago, US
• Aritrick Chatterjee · Chicago, US
• Shiyang Wang · Chicago, US

Key dates

• Filing date: Oct 2, 2020
• Grant date: Sep 23, 2025
• Expiry date: Oct 2, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/30104
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

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.