Edema invariant tractography
AssigneeThe Trustees of the University of Pennsylvania
InventorsRagini Verma, Luke Macyszyn, Emmanuel Caruyer, Jeremy Lecoeur, Mark Elliot, Steven Brem
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Abstract
Edema invariant tractography methods are provided. The methods include acquiring data using a multishell, high angular resolution diffusion imaging sequence; (ii) modeling the data using a multi-compartment model; and (iii) reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
Claims40
An edema invariant tractography method comprising, with a processor:
- acquiring data from a patient using a 3-shell, high angular resolution diffusion imaging sequence, wherein:
- the first shell as a b-value of about 300 s/mm2 and a gradient direction of about 15, the second shell has a b-value of about 800 s/mm2 and a gradient direction of about 30, and the third shell has a b-value of about 2000 s/mm2 and a gradient direction of about 64;
- (ii) modeling said data using a multi-compartment model;
- and
- (iii) reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
An edema invariant tractography method comprising, with a processor:
- acquiring data from a patient using a multishell, high angular resolution diffusion imaging sequence;
- (ii) modeling said data using a multi-compartment model comprising a free water compartment;
- and
- (iii) reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
A method of identifying tracts in an edematous brain of a patient, said method comprising, with a processor:
- acquiring data from said patient using a 3-shell, high angular resolution diffusion imaging sequence, wherein:
- the first shell as a b-value of about 300 s/mm2 and a gradient direction of about 15, the second shell has a b-value of about 800 s/mm2 and a gradient direction of about 30, and the third shell has a b-value of about 2000 s/mm2 and a gradient direction of about 64;
- (ii) modeling said data using a multi-compartment model;
- and
- (iii) reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
A method of identifying tracts in an edematous brain of a patient, said method comprising, with a processor:
- acquiring data from a patient using a multishell, high angular resolution diffusion imaging sequence;
- (ii) modeling said data using a multi-compartment model comprising a free water compartment;
- and
- (iii) reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
The method according to 3, wherein a tumor is present in said brain.
A tractography electronic device comprising:
- (a) code for performing a 3-shell, high angular resolution diffusion imaging sequence, wherein:
- the first shell as a b-value of about 300 s/mm2 and a gradient direction of about 15, the second shell has a b-value of about 800 s/mm2 and a gradient direction of about 30, and the third shell has a b-value of about 2000 s/mm2 and a gradient direction of about 64;
- (b) code for performing a multi-compartment model;
- (c) code for reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm;
- and
- (d) at least one processing unit for executing said code of (a)-(c).
A tractography electronic device comprising:
- (a) code for performing a multishell, high angular resolution diffusion imaging sequence;
- (b) code for performing a multi-compartment model comprising a free water compartment;
- and
- (c) code for reconstructing the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm;
- and
- (d) at least one processing unit for executing said code of (a)-(c).
A tractography electronic device, said device comprising at least one processing unit configured to:
- acquire data using a multishell, high angular resolution diffusion imaging sequence;
- model said data using a multi-compartment model comprising a free water compartment;
- and
- reconstruct the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
A computer program product, stored on a computer readable medium, said product comprising instructions for configuring a computer to:
- acquire data using a 3-shell, high angular resolution diffusion imaging sequence, wherein:
- the first shell as a b-value of about 300 s/mm2 and a gradient direction of about 15, the second shell has a b-value of about 800 s/mm2 and a gradient direction of about 30, and the third shell has a b-value of about 2000 s/mm2 and a gradient direction of about 64;
- model said data using a multi-compartment model;
- and
- reconstruct the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
A computer program product, stored on a computer readable medium, said product comprising instructions for configuring a computer to:
- acquire data using a multishell, high angular resolution diffusion imaging sequence;
- model said data using a multi-compartment model comprising a free water compartment;
- and
- reconstruct the fibers through a probabilistic tracking algorithm using a fiber orientation distribution which has streamlines fitted to the output of said probabilistic tracking algorithm.
Dependencies are inferred from the claim text.