IP Library Granted Patent US 10,524,686
Granted Patent B2
US 10,524,686 · App. 14/956,149 · Granted Jan 7, 2020

Diffusion reproducibility evaluation and measurement (DREAM)-MRI imaging methods

Inventor: Benjamin M. Ellingson (Los Angeles, CA)
Assignee: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
A61B5/055A61B5/7207G01R33/56341G01R33/561G01R33/56518
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Quick Facts
Patent No.
US 10,524,686
App. No.
14/956,149
Granted
Jan 7, 2020
Kind
B2
Abstract

Methods for quickly estimating apparent diffusion coefficient probability density functions (ADC PDFs) for each image voxel are provided using a “diffusion reproducibility evaluation and measurement” (DREAM) magnetic resonance sequence. Non-diffusion-weighted (reference) images collected simultaneously have blood oxygenation level dependent (BOLD) sensitivity that can be used for resting-state fMRI data to measure functional connectivity, an unbiased parameter reflecting neurological integrity. ADC coefficient of variation (ADC CV) measurements can be used to isolate and label regions of non-enhancing tumor and predict future enhancement independent of FLAIR, T2, or average ADC maps. Functional diffusion mapping (fDMs) using voxel-wise changes in ADC PDFs can be used to spatially visualize and statistically quantify response to treatment. Additionally, the temporal (time-resolved) diffusivity information can be used for real-time MR thermometry, which is useful for cancer treatment monitoring, and for microperfusion quantification, and tumor/tissue characterization.

Claims (55)

1. A method for tissue evaluation, the method comprising:

(a) rapidly acquiring a number of diffusion weighted magnetic resonance images over a scan time using an acquisition able to time-resolve apparent diffusion coefficient (ADC) measurement variations;

(b) approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions for voxels from the acquired diffusion weighted magnetic resonance images;

(c) mapping the probability density at each ADC value for each image voxel to generate and display a final ADC-PDF map;

(d) collecting ADC coefficient of variation (ADC CV) measurements for a region of interest of a subject tissue;

(e) labeling regions of non-enhancing tumor; and

(f) predicting future contrast enhancement of areas of tissue.

2. A method for tissue evaluation, the method comprising:

(a) rapidly acquiring a number of diffusion weighted magnetic resonance images over a scan time using an acquisition able to time-resolve apparent diffusion coefficient (ADC) measurement variations;

(b) approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions for voxels from the acquired diffusion weighted magnetic resonance images;

(c) mapping the probability density at each ADC value for each image voxel to generate and display a final ADC-PDF map; and

wherein the diffusion weighted magnetic resonance images are acquired with a single-shot echo polar (SS-EPI) sequence with parallel imaging and partial Fourier encoding.

3. The method of claim 2 , further comprising:

increasing speed of image acquisition using a spiral pulse sequence.

4. The method of claim 2 , further comprising:

increasing speed of image acquisition with compressed sensing.

5. A method for tissue evaluation, the method comprising:

(a) rapidly acquiring a number of diffusion weighted magnetic resonance images over a scan time using an acquisition able to time-resolve apparent diffusion coefficient (ADC) measurement variations;

(b) approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions for voxels from the acquired diffusion weighted magnetic resonance images;

(c) mapping the probability density at each ADC value for each image voxel to generate and display a final ADC-PDF map;

wherein said approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions comprises:

acquiring weighted magnetic resonance images data at 2 b-values;

correcting data of eddy current and motion artifacts;

calculating ADC for each pair of b-values (b 1 and b 2 ) that are acquired;

collecting voxel-wise ADC calculated values over the entire scan time; and

collapsing the ADC calculated values into a histogram and then dividing the values by the total number of acquisitions to produce a final ADC PDF map reflecting the probability density at each ADC value for each image voxel.

6. A method for tissue evaluation, the method comprising:

(a) rapidly acquiring a number of diffusion weighted magnetic resonance images over a scan time using an acquisition able to time-resolve apparent diffusion coefficient (ADC) measurement variations;

(b) approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions for voxels from the acquired diffusion weighted magnetic resonance images;

(c) mapping the probability density at each ADC value for each image voxel to generate and display a final ADC-PDF map;

further comprising:

collecting simultaneously non-diffusion weighted magnetic resonance images; and

measuring functional connectivity with resting-state fMRI data using the collected images.

7. The method of claim 6 , wherein said resting-state fMRI data is based on blood oxygen level-dependent (BOLD) contrast.

8. A method for tumor imaging in tissue, the method comprising:

(a) acquiring, with a repetition time (TR) of less than 2.4 seconds, a number of diffusion weighted magnetic resonance images of at least two b-values over a short scan time;

(b) calculating apparent diffusion coefficient values for said b-values from the acquired images;

(c) approximating apparent diffusion coefficient probability density function (ADC-PDF) distributions for each voxel;

(d) mapping (ADC-PDF) distributions of the probability density at each ADC value for each image voxel to generate a (ADC-PDF) distribution map; and

(e) identifying areas of comparatively lower ADC values within tissue regions of interest from the map.

9. The method of claim 8 , further comprising:

comparing ADC-PDF maps from serial scans; and

identifying decreases in ADC in voxels of contrast enhancing regions of said maps as an indicator of tumor recurrence.

10. The method of claim 8 , further comprising:

collecting ADC coefficient of variation (ADC CV) measurements for a region of interest of a subject tissue;

labeling regions of non-enhancing tumor; and

predicting future contrast enhancement of areas of tissue.

11. The method of claim 8 , further comprising:

collecting simultaneously non-diffusion weighted magnetic resonance images; and

measuring functional connectivity with resting-state fMRI data using the collected images.

12. The method of claim 11 , wherein said resting-state fMRI data is based on blood oxygen level-dependent (BOLD) contrast.

13. The method of claim 8 , wherein said diffusion weighted magnetic resonance images are acquired with a single-shot echo polar (SS-EPI) sequence with parallel imaging and partial Fourier encoding.

14. The method of claim 8 , wherein said mapping apparent diffusion coefficient probability density function (ADC-PDF) distributions comprises:

collecting voxel-wise ADC calculated b-values values over the entire scan time; and

collapsing the ADC calculated values into a histogram and then dividing the values by the total number of acquisitions to produce a final ADC PDF map reflecting the probability density at each ADC value for each image voxel.

Assignments (2)
CONFIRMATORY LICENSE Recorded Jan 31, 2017
From: UNIVERSITY OF CALIFORNIA LOS ANGELES
To: NATIONAL INSTITUTES OF HEALTH (NIH), U.S. DEPT. OF HEALTH AND HUMAN SERVICES (DHHS), U.S. GOVERNMENT
Reel/Frame 041566/0315 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 18, 2015
From: ELLINGSON, BENJAMIN M.
To: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Reel/Frame 037329/0309 →
Continuity (2)
Provisional Application 62085715 · Dec 1, 2014
Related Publication 20160157746A1 · Jun 9, 2016