METHOD AND SYSTEM FOR IMAGE PROCESSING AND PATIENT-SPECIFIC MODELING OF BLOOD FLOW

• US 20160364859A1
• Filed: 08/25/2016
• Published: 12/15/2016
• Est. Priority Date: 08/12/2010
• Status: Active Grant

• Current Assignee: Heartflow Inc.
• Original Assignee: Heartflow Inc.
• Inventors: TAYLOR, Charles A.
• Granted Patent: US 10,441,361 B2
• Time in Patent Office: Days
• US Class Current: 1/1
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Abstract

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient'"'"'s heart, and create a three-dimensional model representing at least a portion of the patient'"'"'s heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient'"'"'s heart and determine a fractional flow reserve within the patient'"'"'s heart based on the three-dimensional model and the physics-based model.

Claims

1-184. -184. (canceled)

185. A method processing images for planning treatment for arterial stenotic lesions, comprising:

identifying a set of stenotic lesions in a patient'"'"'s coronary arteries from medical image data of the patient;

generating a plurality of treatment options for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented; and

calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

186. The method of claim 185, further comprising:

determining an optimum treatment option from the plurality of treatment options based on the predicted hemodynamic metrics calculated for each of the plurality of treatment options for the set of stenotic lesions.

187. The method of claim 185, wherein calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option comprises:

calculating, for each of the plurality of treatment options, predicted fractional flow reserve (FFR) values for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

188. The method of claim 187, wherein calculating, for each of the plurality of treatment options, predicted fractional flow reserve (FFR) values for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option comprises:

determining a pressure loss model for the one or more of the stenotic lesions that are stented in the corresponding stenting configuration;

simulating blood flow and pressure in the coronary arteries of the patient with the pressure loss model for the one or more of the stenotic lesions that are stented; and

calculating FFR values for each of the set of stenotic lesions based on the simulated blood flow and pressure in the coronary arteries of the patient.

189. The method of claim 185, further comprising:

displaying, for each of the plurality of treatment options, a respective figure showing results of calculating the predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

190. The method of claim 186, further comprising:

displaying a plurality of results of calculating the predicted hemodynamic metrics resulting from the stenting configuration corresponding to each of the plurality of treatment options for the set of stenotic lesions.

191. The method of claim 185, further comprising:

displaying a model of the patient'"'"'s coronary arteries; and

in response to a user selecting one of a plurality of treatment options, displaying the stenting configuration corresponding to the selected treatment option and the hemodynamic metrics calculated resulting from the stenting configuration corresponding to the selected treatment option for the set of stenotic lesions.

192. The method of claim 185, further comprising:

displaying a model of the patient'"'"'s coronary arteries; and

in response to a user selection of one or more stent locations on the model of the patient'"'"'s coronary arteries, displaying the hemodynamic metrics calculated for the set of stenotic lesions for a treatment option corresponding to the stenting configuration indicated by the user selection of the one or more stent locations.

193. The method of claim 185, wherein identifying a set of stenotic lesions in a patient'"'"'s coronary arteries from medical image data of the patient comprises:

extracting a patient-specific anatomical model of the coronary arteries from the medical image data;

detecting a plurality of stenotic lesions in the coronary arteries using the patient-specific anatomical model of the coronary arteries;

estimating a hemodynamic metric for each of the plurality of stenotic lesions; and

identifying a set of hemodynamically relevant stenotic lesions from the plurality of stenotic lesions based on the hemodynamic metric estimated for each of the plurality of stenotic lesions.

194. The method of claim 193, wherein estimating a hemodynamic metric for each of the plurality of stenotic lesions comprises:

simulating blood flow and pressure in the coronary arteries using a computational model of coronary circulation; and

estimating the hemodynamic metric for each of the plurality of stenotic lesions based on a simulated pressure change across each of the plurality of stenotic lesions.

195. The method of claim 193, wherein estimating a hemodynamic metric for each of the plurality of stenotic lesions comprises:

estimating a fractional flow reserve (FFR) value for each of the plurality of stenotic lesions.

196. An apparatus for processing images for planning treatment for arterial stenotic lesions, the apparatus executing a method comprising:

identifying a set of stenotic lesions in a patient'"'"'s coronary arteries from medical image data of the patient;

generating a plurality of treatment options for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented; and

calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

197. The apparatus of claim 196, further comprising:

determining an optimal treatment option from the plurality of treatment options based on the predicted hemodynamic metrics calculated for each of the plurality of treatment options for the set of stenotic lesions.

198. The apparatus of claim 196, wherein calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option comprises:

calculating, for each of the plurality of treatment options, predicted fractional flow reserve (FFR) values for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

199. The apparatus of claim 198, wherein calculating, for each of the plurality of treatment options, predicted fractional flow reserve (FFR) values for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option comprises:

adjusting a pressure drop simulated for the one or more of the stenotic lesions that are stented in the corresponding stenting configuration;

simulating blood flow and pressure in the coronary arteries of the patient with the adjusted pressure drop for the one or more of the stenotic lesions that are stented; and

calculating FFR values for each of the set of stenotic lesions based on the simulated blood flow and pressure in the coronary arteries of the patient.

200. The apparatus of claim 196, wherein the plurality of treatment options comprises a respective treatment option corresponding to each possible stenting configuration of one or more of the set of stenotic lesions.

201. The apparatus of claim 196, further comprising:

displaying, for each of the plurality of treatment options, a respective figure showing results of calculating the predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.

202. The apparatus of claim 197, further comprising:

displaying a plurality of results of calculating the predicted hemodynamic metrics resulting from the stenting configuration corresponding to each of the plurality of treatment options for the set of stenotic lesions.

203. The apparatus of claim 196, wherein identifying a set of stenotic lesions in a patient'"'"'s coronary arteries from medical image data of the patient comprises:

extracting a patient-specific anatomical model of the coronary arteries from the medical image data;

detecting a plurality of stenotic lesions in the coronary arteries using the patient-specific anatomical model of the coronary arteries;

estimating a hemodynamic metric for each of the plurality of stenotic lesions; and

identifying a set of hemodynamically relevant stenotic lesions from the plurality of stenotic lesions based on the hemodynamic metric estimated for each of the plurality of stenotic lesions.

204. A non-transitory computer readable medium storing computer program instructions for processing images for planning treatment for arterial stenotic lesions, the computer program instructions when executed by a processor causes the processor to perform operations comprising:

identifying a set of stenotic lesions in a patient'"'"'s coronary arteries from medical image data of the patient;

generating a plurality of treatment options for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented; and

calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option.