Lung ventillation measurements using ultrasound

• US 9,211,110 B2
• Filed: 03/17/2014
• Issued: 12/15/2015
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Original Assignee: Board of Regents of the University of Michigan (University of Michigan)
• Inventors: Rubin, Jonathan, Fowlkes, J. Brian, Kripfgans, Oliver D., Hamilton, James
• Primary Examiner(s): REMALY, MARK DONALD
• Application Number:
  US14/216,738
• Publication Number:
  US 20140316266A1
• Time in Patent Office: 638 Days
• US Class Current: 1/1
• CPC Class Codes: A61B 8/08 Detecting organic movements or changes, e.g. tumours, cysts, swellings A61B8/02 - A61B8/06 take precedence
• CPC Class Codes: A61B 8/0858 involving measuring tissue layers, e.g. skin, interfaces
• CPC Class Codes: A61B 8/461 Displaying means of special interest
• CPC Class Codes: A61B 8/483 involving the acquisition of a 3D volume of data
• CPC Class Codes: A61B 8/485 involving measuring strain or elastic properties
• CPC Class Codes: A61B 8/5223 for extracting a diagnostic or physiological parameter from medical diagnostic data for algorithms to analyse biomedical images G06T7/0012
• CPC Class Codes: A61B 8/5253 combining overlapping images, e.g. spatial compounding
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

An ultrasound-based system determines dynamic strain measurements over a surface using ultrasound speckle analysis that allows for accurate measurement of surface area displacement. The system additionally determines an approximate displacement along a third axis, the z-axis. From these, an estimation of a local volume change is determined. In this way, a volume change can be determined for the lung or any other region of interest.

Claims

1. A method of determining change in volume of a target sample, the method comprising:

receiving, at an imaging processing machine, ultrasound images of a two-dimensional area corresponding to the target sample, where a first ultrasound image is taken at a first time period and a second ultrasound image is taken at a second time period after the first time period;

determining, at the imaging processing machine, a change in strain value of the target sample over the two-dimensional area, wherein the strain value is determined from comparing the first ultrasound image to the second ultrasound image, wherein the first ultrasound image and the second ultrasound image are speckle-containing images;

determining, at the imaging processing machine, and from the change in strain value, an xy-plane change in area of the target sample between the first time period and the second time period;

determining, at the imaging processing machine, an approximate physical z-axis displacement over the two-dimensional area by approximating a change in local curvature of the two-dimensional area between the first time period and the second time period; and

determining, at the imaging processing machine, a volume displacement of the target sample from the approximate physical z-axis displacement and change in strain value.

2. The method of claim 1, wherein determining an approximate physical z-axis displacement further comprises:

defining at least one osculating circle at a region of the two-dimensional area of the target sample;

determining an initial radius of the at least one osculating circle at the first time period and a second radius of the at least one osculating circle at the second time period; and

determining the approximate physical z-axis displacement from a change between the initial radius and the second radius.

3. The method of claim 2, further comprising:

defining a plurality of osculating circles at for the two-dimensional area of the target sample;

determining for each of the osculating circles changes in radii between the first time period and the second time period; and

determining the approximate physical z-axis displacement as a mean of the determined changes in radii for the plurality of osculating circles.

4. The method of claim 3, wherein the plurality of osculating circles have the same initial radius of curvature at the first time period.

5. The method of claim 3, wherein at least some of the plurality of osculating circles have a different initial radius of curvature at the first time period.

6. The method of claim 3, wherein osculating circles corresponding to a central region of the two-dimensional area have a larger initial radius of curvature than osculating circles corresponding to a peripheral region of the two-dimensional area.

7. The method of claim 3, wherein the osculating circles are defined along two orthogonal directions of the two-dimensional area, wherein the each osculating circle is defined by a principal curvature determined from an ultrasound image of a two-dimensional area corresponding to the target sample.

8. The method of claim 3, further comprising performing a statistically significant analysis of the determined changes in radii for the plurality of osculating circles to identify a subset of significance for the changes in radii, the method comprising determining the approximate physical z-axis displacement as mean of the subset of significance for the changes in radii.

9. The method of claim 8, wherein the statistically significant analysis comprises a averaging data, high and/or low threshold filtering, skewness analysis, kurtosis analysis, or a combination thereof.

10. The method of claim 3, further comprising:

determining a plurality of approximate physical z-axis displacements over the two-dimensional area; and

mapping the plurality of approximate physical z-axis displacements onto an ultrasound image of the two-dimensional area for display.