Method for post-processing liver MRI images to obtain a reconstructed map of the internal magnetic susceptibility

Patent metadata

Field	Value
Publication number	US-11403752-B2
Application number	US-201716332749-A
Country	US
Kind code	B2
Filing date	Sep 12, 2017
Priority date	Sep 13, 2016
Publication date	Aug 2, 2022
Grant date	Aug 2, 2022

Abstract

In the field of obesity related disease, identification of patients with nonalcoholic steatohepatitis (NASH) would be useful to counsel them more intensively on diet and lifestyle changes and propose new pharmacological treatments. As a consequence, the inventors worked on a method for post-processing images of a region of interest of the liver for reconstructing a map of the internal magnetic susceptibility by using a Bayesian regularization approach to inverse the internal magnetic field. Such method can be implemented on computer and provides better results than other known methods for obesity related disease. This method may be applied for predicting that a subject is at risk of suffering from such disease, diagnosing a disease, identifying a therapeutic or a biomarker and screening compounds useful as a medicine.

First claim

The invention claimed is:

1. A method for post-processing images of a region of interest (ROI) of the liver of a subject to obtain determined parameters, the images being acquired with a magnetic resonance imaging technique, the magnetic resonance imaging technique involving successive echoes of a multiple-gradient echo sequence, each image associating to each pixel of the image the amplitude of the measured signal in the magnetic resonance imaging technique and the phase of the measured signal in the magnetic resonance imaging technique, the method for post-processing comprising at least the step of:
obtaining in each image the heterogeneous magnetic field, the heterogeneous magnetic field being the sum of an internal magnetic field and an external magnetic field, by:
unwrapping the phase of each image, to obtain unwrapped images,
extracting the first-order phase from the unwrapped images,
calculating the heterogeneous magnetic field based on the extracted first-order phase,
separating the internal magnetic field from the external magnetic field in the heterogeneous magnetic field by:
calculating the external magnetic field by decomposing the heterogeneous magnetic field into a field generated by dipoles outside the region of interest (ROI); and
subtracting the calculated external magnetic field from the heterogeneous magnetic field using a projection onto dipole field method, to obtain the internal magnetic field,
reconstructing a map of the internal magnetic susceptibility based on the internal magnetic field by using a Bayesian regularization approach to inverse the internal magnetic field, the reconstructed map being a determined parameter, and
displaying the reconstructed map.

2. A method for post-processing images according to claim 1 , wherein said decomposing of the heterogeneous magnetic field comprises using a projection in Hilbert space and minimizing a distance between the field generated by dipoles outside the region of interest and the heterogeneous magnetic field.

3. A method for post-processing images according to claim 2 , wherein the distance is pondered by a normal distribution.

4. A method for post-processing images according to claim 1 , wherein the Bayesian regularization approach comprises a first regularization term taking into account the signal to noise ratio of each images.

5. A method for post-processing images according to claim 1 , wherein the Bayesian regularization approach comprises a second regularization term taking into account the boundary conditions of the region of interest.

6. A method for post-processing images according to claim 1 , wherein the Bayesian regularization approach comprises a third regularization term depending from the inverse of the amplitude image gradient.

7. A method for post-processing images according to claim 1 , wherein the steps of separating and reconstructing both implies a minimization, the minimization being carried out by using a conjugate gradient technique.

8. A method for post-processing images according to claim 1 , wherein the method for post-processing further comprises the step of determining fat characterization parameters, the fat characterization parameters being determined parameters and the step of determining comprises:
extracting a real signal over echo time for at least one pixel of the unwrapped images, to obtain at least one extracted real signal,
calculating fat characterization parameters by using a fitting technique applied on a model,
the model being a function which associates to a plurality of parameters each extracted real signal, the plurality of parameters comprising at least two fat characterization parameters and at least one parameter obtained by a measurement,
the fitting technique being a non-linear least-square fitting technique using pseudo-random initial conditions.

9. A method for predicting that a subject is at risk of suffering from an obesity related disease, the method for predicting at least comprising the step of:
carrying out the steps of a method for post-processing images of the subject, to obtain determined parameters, the method for post-processing images being according to claim 1 ,
predicting that the subject is at risk of suffering from the obesity related disease based on the determined parameters.

10. A method for diagnosing an obesity related disease, the method for diagnosing at least comprising the step of:
carrying out the steps of a method for post-processing images of the subject, to obtain determined parameters, the method for post-processing images being according to claim 1 , and
diagnosing the obesity related disease based on the determined parameters.

11. A method for identifying a therapeutic target for preventing or treating an obesity related disease, the method comprising the steps of:
carrying out the steps of a method for post-processing images of a first subject, to obtain first determined parameters, the method for post-processing images being according to claim 1 and the first subject being a subject suffering from the obesity related disease,
carrying out the steps of the method for post-processing images of a second subject, to obtain second determined parameters, the method for post-processing images being according to claim 1 and the second subject being a subject not suffering from the obesity related disease,
selecting a therapeutic target based on the comparison of the first and second determined parameters.

12. A method for identifying a biomarker, the biomarker being a diagnostic biomarker of an obesity related disease, a prognostic biomarker of an obesity related disease or a predictive biomarker in response to the treatment of an obesity related disease, the method comprising the steps of:
carrying out the steps of a method for post-processing images of a first subject, to obtain first determined parameters, the method for post-processing images being according to claim 1 and the first subject being a subject suffering from the obesity related disease,
carrying out the steps of the method for post-processing images of a second subject, to obtain second determined parameters, the method for post-processing images being according to claim 1 and the second subject being a subject not suffering from the obesity related disease,
selecting a biomarker based on the comparison of the first and second determined parameters.

13. A non-transitory computer-readable medium on which is stored a computer program product comprising instructions for carrying out the steps of a method according to claim 1 when said computer program product is executed on a computer device.

14. A device for analyzing a region of interest of the liver of a subject, the device comprising a processor adapted to carry out a method according to claim 1 .

Assignees

• Inst Nat Sante Rech Med
• Univ Paris Diderot—Paris 7
• Centre Nat Rech Scient
• Assist Publique—Hopitaux De Paris
• Univ Versailles Saint Quentin En Yvelines

Inventors

• LEPORQ Benjamin
• Lambert Simon
• Van Beers Bernard

Classifications

• A61B5/4244

  liver · CPC title

• A61B5/4872

  Body fat · CPC title

• G01R33/5608

  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

• G01R33/56536 Primary

  due to magnetic susceptibility variations · CPC title

• G06T7/0012 Primary

  Biomedical image inspection · CPC title