Inter-Subject Coherence in Dt-Mri

• US 20070273373A1
• Filed: 04/06/2005
• Published: 11/29/2007
• Est. Priority Date: 04/14/2004
• Status: Active Grant

• Current Assignee: Mclean Hospital (Mass General Brigham, Inc.)
• Original Assignee: Mclean Hospital (Mass General Brigham, Inc.)
• Inventors: Lange, Nicholas
• Granted Patent: US 7,570,049 B2
• Time in Patent Office: Days
• US Class Current: 324/307
• CPC Class Codes: G01R 33/56341 Diffusion imaging

Abstract

A method for estimating a value of a diffusion tensor includes obtaining, from a plurality of test subjects, DT-MRI data from which an initial estimate of the tensor can be derived. Values indicative of intra-subject variation and inter-subject variation in the data are then determined. These values are used to determine a subject-specific additive offset for adjusting the DT-MRI data.

Claims

1. A method for estimating a value of a diffusion tensor, said method comprising:

obtaining, from a plurality of test subjects, DT-MRI data from which an initial estimate of the tensor can be derived;

determining a first value indicative of intra-subject variation in said data;

determining a second value indicative of inter-subject variation in said data; and

at least in part on the basis of said first and second values, determining a subject-specific additive offset for adjusting said DT-MRI data.

2. The method of claim 1, further comprising generating adjusted data by adjusting said DT-MRI data by said offset.

3. The method of claim 2, further comprising generating a bowtie plot from said adjusted data.

4. The method of claim 1, further comprising selecting said DT-MRI data to represent an initial estimate of said diffusion tensor value.

5. The method of claim 1, further comprising selecting said DT-MRI data to represent echo data from which an initial estimate of the diffusion tensor can be derived.

6. The method of claim 1, wherein determining a first value comprises determining an average intra-subject variance.

7. The method of claim 1, wherein determining a second value comprises determining an inter-subject variance.

8. A computer-readable medium having encoded thereon software for estimating a value of a diffusion tensor, said software comprising instructions for:

obtaining, from a plurality of test subjects, DT-MRI data from which an initial estimate of the tensor can be derived;

determining a first value indicative of intra-subject variations in said data;

determining a second value indicative of inter-subject variation in said data; and

at least in part on the basis of said first and second values, determining a subject-specific additive offset for adjusting said DT-MRI data.

9. The computer-readable medium of claim 8, wherein the software further comprises instructions for generating adjusted data by adjusting said DT-MRI data by said offset.

10. The computer-readable medium of claim 9, wherein the software further comprises instructions for generating a bowtie plot from said adjusted data.

11. The computer-readable medium of claim 8, wherein the software further comprises instructions for selecting said DT-MRI data to represent an initial estimate of said diffusion tensor value.

12. The computer-readable medium of claim 8, wherein the software further comprises instructions for selecting said DT-MRI data to represent echo data from which an initial estimate of the diffusion tensor can be derived.

13. The computer-readable medium of claim 8, wherein the instructions for determining a first value comprise instructions for determining an average intra-subject variance.

14. The computer-readable medium of claim 8, wherein the instructions for determining a second value comprise instructions for determining an inter-subject variance.

15. A system for estimating a value of a diffusion tensor, said system comprising:

an MRI machine;

a processor in data communication with the MRI machine;

a computer-readable medium in data communication with the processor, the computer-readable medium having encoded thereon software as recited in claim 9.

16. A method for estimating the evolution of a diffusion tensor, the method comprising:

obtaining, from each of a plurality of test subjects, DT-MRI representing a time series of diffusion tensors associated with each test subject;

reducing the DT-MRI data to determine individual data descriptive of the evolution of tensor values for each of the test subjects;

reducing the individual data to determine data descriptive of the evolution of a diffusion tensor associated with the plurality of test subjects.

17. The method of claim 16, wherein reducing the individual data comprises:

determining a plurality of individual mean functions, each of which corresponds to a test subject; and

determining a plurality of individual covariance matrices, each of which corresponds to a test subject.

18. The method of claim 16, wherein reducing at least one of the collective data and the individual data comprises determining a growth model.

19. The method of claim 18, determining a growth model comprises selecting a growth model from the group consisting of a parametric growth-model, a semi-parametric growth-model, and a non-parametric growth-model.

20. The method of claim 16, wherein reducing at least one of the collective data and the individual data comprises determining a longitudinal model.