US 11,728,039 B2
Methods and systems for predicting sensitivity of blood flow calculations to changes in anatomical geometry
Sethuraman Sankaran, Palo Alto, CA (US); Leo Grady, Millbrae, CA (US); and Charles A. Taylor, Atherton, CA (US)
Assigned to HeartFlow, Inc., Redwood City, CA (US)
Filed by HeartFlow, Inc., Redwood City, CA (US)
Filed on Nov. 26, 2019, as Appl. No. 16/695,489.
Application 16/695,489 is a continuation of application No. 15/298,964, filed on Oct. 20, 2016, granted, now 10,522,254.
Application 15/298,964 is a continuation of application No. 14/596,622, filed on Jan. 14, 2015, granted, now 9,501,622, issued on Nov. 22, 2016.
Claims priority of provisional application 61/948,325, filed on Mar. 5, 2014.
Prior Publication US 2020/0098481 A1, Mar. 26, 2020
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 50/50 (2018.01); G06T 7/00 (2017.01); G06N 3/00 (2023.01); A61B 6/00 (2006.01); A61B 5/00 (2006.01); G06F 17/18 (2006.01); A61B 5/026 (2006.01)
CPC G16H 50/50 (2018.01) [A61B 5/7267 (2013.01); A61B 6/00 (2013.01); A61B 6/507 (2013.01); A61B 6/5217 (2013.01); G06F 17/18 (2013.01); G06N 3/00 (2013.01); G06T 7/0012 (2013.01); A61B 5/026 (2013.01); A61B 2576/02 (2013.01); G06T 2207/30104 (2013.01)] 20 Claims
 
1. A computer-implemented method of determining a sensitivity of a patient's blood flow characteristic to uncertainty in a geometric model of a patient's vascular system, the method comprising:
obtaining, for each of a plurality of individuals, a geometric model of at least a portion of a vascular system of each individual and at least one sensitivity of a blood flow characteristic to at least one uncertainty in geometry in the geometric model;
mapping, in a machine learning database, a plurality of features of each geometric model to the obtained sensitivities;
obtaining a geometric model of at least part of a patient's vascular system;
determining, for the patient, at least one value of uncertainty in geometry in the geometric model of at least part of the patient's vascular system; and
determining a sensitivity of a blood flow characteristic of the patient to at least one value of uncertainty in geometry in the geometric model of at least part of the patient's vascular system, using (i) the machine learning database in which the plurality of features are mapped to the obtained sensitivities and/or (ii) the mapped plurality of features.