MRI tractography based transit time determination for nerve fibers

Patent metadata

Field	Value
Publication number	US-10996303-B2
Application number	US-201214345219-A
Country	US
Kind code	B2
Filing date	Sep 14, 2012
Priority date	Sep 16, 2011
Publication date	May 4, 2021
Grant date	May 4, 2021

Abstract

Magnetic resonance methods comprise tractographically establishing a path along a structure in a specimen and finding a distribution of structure radii or cross-sectional areas along the path. Based on the distribution and the path, end-to-end functional characteristics of the structure are estimated. For example, nerve transit times or distributions of transit times can be estimated for a plurality of nervous system locations such as Brodmann areas. Comparison of estimated transit times or distributions thereof between reference values or other values from the same structure can be used to assess specimen health.

First claim

I claim:

1. A method of evaluating magnetic resonance images to characterize specimen structures, comprising:
applying a plurality of magnetic resonance (MR) pulse sequences to a specimen and obtaining corresponding MR signals and MR images;
obtaining directions of an axis of a specimen structure based on the MR images;
establishing a path along a specimen structure based on the directions of the specimen axis at a plurality of locations;
calculating a geometrical characteristic of the specimen structure along the established path at the plurality of path locations, wherein the geometrical characteristic is a cross-sectional area or a linear dimension associated with the cross-section;
calculating contributions to a specimen functional value for the plurality of path locations based on the geometrical characteristic; and
providing a specimen functional value estimate by combining the calculated contributions along the path, wherein the specimen includes a nerve fiber, a nerve fiber bundle, an axon, an axon bundle, or brain white matter and the specimen functional value is a moment of a velocity distribution.

2. The method of claim 1 , wherein the geometrical characteristic is a linear dimension that corresponds to an effective diameter of the fiber cross section.

3. The method of claim 1 , wherein the cross-sectional area or the linear dimension associated with the cross-section are determined based on at least one of hindered or restricted diffusion in the nerve fiber, the nerve fiber bundle, the axon, the axon bundle, or brain white matter at a plurality of path increments.

4. The method of claim 1 , wherein contributions to signal transit time along the path are determined as proportional to nerve fiber diameter.

5. The method of claim 1 , further comprising:
comparing signal transit time moments between a plurality of locations; and
providing an assessment based on the comparison.

6. The method of claim 1 , wherein the signal transit time moments are mean transit times.

7. A non-transitory computer-readable medium, comprising computer-executable instructions for performing a method that comprises:
applying a plurality of magnetic resonance (MR) pulse sequences to a specimen and obtaining corresponding MR signals and MR images;
obtaining directions of an axis of a specimen structure based on the MR images;
establishing a path along a specimen structure based on the directions of the specimen axis at a plurality of locations;
calculating a geometrical characteristic of the specimen structure along the established path at the plurality of path locations, wherein the geometrical characteristic is a cross-sectional area or a linear dimension associated with the cross-section;
calculating contributions to a specimen functional value for the plurality of path locations based on the geometrical characteristic; and
providing a specimen functional value estimate by combining the estimated contributions along the path, wherein the specimen includes a nerve fiber, a nerve fiber bundle, an axon, an axon bundle, or brain white matter and the specimen functional value is a moment of a velocity distribution.

8. An apparatus, comprising:
a magnetic resonance imaging system configured to obtain and record a set of translational diffusion-weighted magnetic resonance signals associated with a plurality of diffusion-weighted field gradient strengths and a plurality of diffusion-weighted field gradient directions along a path along an axis of a nerve fiber, a nerve fiber bundle, an axon, or a bundle of axons in a specimen, and produce magnetic resonance (MR) images based on the recorded translational diffusion-weighted magnetic resonance signals; and
a processor configured to:
obtain directions of an axis of a specimen structure based on the MR images;
establish a path along a specimen structure based on the directions of the specimen axis at a plurality of locations;
estimate a geometrical characteristic of the specimen structure along the established path at the plurality of path locations, wherein the geometrical characteristic is a cross-sectional area or a linear dimension associated with the cross-section;
estimate contributions to a specimen functional value for the plurality of path locations based on the geometrical characteristic; and
provide a specimen functional value estimate by combining the estimated contributions along the path, wherein the specimen includes a nerve fiber, a nerve fiber bundle, an axon, an axon bundle, or brain white matter and the specimen functional value is a moment of a velocity distribution.

9. The apparatus of claim 8 , further comprising a display coupled to the processor and configured to display an image corresponding to the established path and the specimen.

10. The apparatus of claim 9 , wherein the display is further configured to display path increments.

11. The apparatus of claim 8 , wherein the processor is configured to establish the path based on at least one principal diffusion axis associated with the restricted compartment.

12. A method of evaluating magnetic resonance images to characterize specimen structures, comprising:
applying a plurality of magnetic resonance (MR) pulse sequences to a specimen and obtaining corresponding MR signals and MR images;
obtaining directions of an axis of a specimen structure based on the MR images;
establishing paths along a specimen structure based on the directions of the specimen axis at a plurality of locations;
calculating a geometrical characteristic of the specimen structure along the established paths at the plurality of path locations, wherein the geometrical characteristic is a cross-sectional area or a linear dimension associated with the cross-section;
calculating contributions to specimen functional values for the plurality of path locations based on the geometrical characteristic;
providing specimen functional value estimates by combining the calculated contributions along the respective paths, wherein the specimen includes a nerve fiber, a nerve fiber bundle, an axon, an axon bundle, or brain white matter and the specimen functional value is a signal transit time; and
arranging the signal transit times as a transit time matrix, wherein the transit time matrix indicates unconnected specimen locations.

13. A method of evaluating magnetic resonance images to characterize specimen structures, comprising:
applying a plurality of magnetic resonance (MR) pulse sequences to a specimen and obtaining corresponding MR signals and MR images;
obtaining directions of an axis of a specimen structure based on the MR images;
establishing paths along a specimen structure based on the directions of the specimen axis at a plurality of locations;
calculating a geometrical characteristic of the specimen structure along the established path at the plurality of path locations, wherein the geometrical characteristic is a cross-sectional area or a linear dimension associated with the cross-section;
calculating contributions to a specimen functional value for the plurality of path locations based on the geometrical characteristic;
providing specimen functional value estimates by combining the calculated contributions along the path, wherein the specimen includes a nerve fiber, a nerve fiber bundle, an axon, an axon bundle, or brain white matter and the specimen functional values are higher order moments of signal transit times between the plurality of locations; and
arranging the higher order moments of the signal transit times as a transit time matrix.

14. The method of claim 13 , further comprising displaying an image corresponding to th

Assignees

• Basser Peter J
• Us Health

Inventors

• Basser Peter J

Classifications

• A61B5/055

  involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging · CPC title

• G01R33/56341

  Diffusion imaging · CPC title

• G01R33/5608 Primary

  Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels (image data processing or generation, in general G06T) · CPC title

• A61B5/40

  Detecting, measuring or recording for evaluating the nervous system (for sleep A61B5/4806; for anaesthesia A61B5/4821; for pain A61B5/4824) · CPC title