US 12,376,750 B2
Tumor characterization and outcome prediction through quantitative measurements of tumor-associated vasculature
Anant Madabhushi, Shaker Heights, OH (US); and Nathaniel Braman, Bethel Park, PA (US)
Assigned to Case Western Reserve University, Cleveland, OH (US); and The United States Government as Represented by The Department of Veteran Affairs, Washington, DC (US)
Filed by Case Western Reserve University, Cleveland, OH (US); and The United States Government as Represented by The Department of Veteran Affairs, Washington, DC (US)
Filed on Oct. 27, 2023, as Appl. No. 18/495,821.
Application 18/495,821 is a continuation of application No. 17/116,319, filed on Dec. 9, 2020, granted, now 11,896,349.
Claims priority of provisional application 62/945,310, filed on Dec. 9, 2019.
Prior Publication US 2024/0057874 A1, Feb. 22, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 5/02 (2006.01); A61B 5/00 (2006.01); A61B 5/08 (2006.01); G06T 7/00 (2017.01); G06T 7/12 (2017.01)
CPC A61B 5/02007 (2013.01) [A61B 5/0035 (2013.01); A61B 5/004 (2013.01); A61B 5/08 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G06T 7/0012 (2013.01); G06T 7/12 (2017.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/20036 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30101 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method, comprising:
accessing data derived from one or more routine clinical medical imaging scans including a lesion in which the lesion and associated vasculature are segmented in a three-dimensional segmentation;
extracting at least two features, the at least two features including at least one feature indicative of a morphology of the associated vasculature or a portion thereof, and at least one feature indicative of a function of the associated vasculature or a portion thereof, the at least one feature indicative of the morphology extracted from the three-dimensional segmentation of the associated vasculature, and the at least one feature indicative of the function being a pharmacokinetic measurement extracted from a region of tissue in the one or more routine clinical imaging scans that is perfused by the associated vasculature;
providing the at least two features, and/or one or more statistics of the at least two features, to a machine learning model trained to make a prediction concerning the lesion; and
receiving, from the machine learning model, the prediction concerning the lesion.