METHOD FOR QUANTIFYING BRAIN INJURIES

• US 20150379713A1
• Filed: 10/15/2013
• Published: 12/31/2015
• Est. Priority Date: 10/17/2012
• Status: Active Grant

• Current Assignee: Assistance Publique - Hopitaux De Paris
• Original Assignee: Assistance Publique - Hopitaux De Paris
• Inventors: PUYBASSET, Louis, GALANAUD, Damien, BENALI, Habib, PERLBARG, Vincent, LEHERICY, Stephane
• Granted Patent: US 10,176,578 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2576/026 for the brain
• CPC Class Codes: A61B 5/0042 for the brain
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/4064 Evaluating the brain A61B5/031, A61B5/369, A61B5/14553 take precedence
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G01R 33/56341 Diffusion imaging
• CPC Class Codes: G06F 18/22 Matching criteria, e.g. proximity measures
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06T 2207/10088 Magnetic resonance imaging [MRI]
• CPC Class Codes: G06T 2207/30016 Brain
• CPC Class Codes: G06T 7/0012 Biomedical image inspection
• CPC Class Codes: G06T 7/0014 using an image reference approach
• CPC Class Codes: G06T 7/238 using non-full search, e.g. three-step search
• CPC Class Codes: G16H 30/40 for processing medical images, e.g. editing
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

The invention relates to an ex vivo method for detecting and/or quantifying brain injuries. The invention also relates to an ex vivo method for monitoring the evolution of a brain injury, and to an ex vivo method for predicting when a patient will come out of a coma. The invention is particularly applicable in the field of medicine and in the field of clinical studies.

Claims

1. An ex-vivo method for detecting and/or quantifying brain injuries of a test subject comprising the following steps:

a) measurement of the fractional anisotropy FA₁ in at least one first region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of a test subject,

b) measurement of the axial diffusivity DA₁ in at least one second region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

c) measurement of the radial diffusivity DR₁ in at least one third region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

d) determination of the ratios SFA, SDA, SDR as defined below by comparison of the measured values FA₁, DA₁, DR₁ to normal regional values from a reference group of healthy subjects of fractional anisotropy FA_n, of axial diffusivity DA_n and of radial diffusivity RD_n, for said regions according to the following formulae;

SFA=(FA₁/FA_n)

SDA=(DA₁/DA_n)

SDR=(DR₁/DR_n)

said region of the brain being injured if the value of SFA, SDA and/or SDR is greater than or less than 1 plus or minus two times the standard deviation of the regional measurements from the reference group of healthy subjects respectively of the reference fractional anisotropy, axial diffusivity, radial diffusivity in said region of interest.

4. The method as claimed in claim 1, in which the method further comprises a step f) of determination of the intensity of the injuries by measurement of the variation against the average of the reference values.

5. The method as claimed in claim 1, in which the method further comprises a step f) of determination of the intensity of the injuries by regions (I_les) according to the following formula:

I_les=(((FA₁−

FA_ref)×

100)/FA_ref)+(((DA₁−

DA_ref)×

100)/DA_ref)+(((DR₁−

DR_ref)×

100)/DR_ref).

6. The method as claimed in claim 1, in which the reference regional values are of the reference average values measured in at least one identical or different reference patient.

8. The method as claimed in claim 1, in which the measurements of fractional anisotropy, axial diffusivity, radial diffusivity are performed in at least one of the regions of the brain selected from the middle cerebellar peduncle (ICBM #1), the anterior brain stem (ICBM #2,7,8), the posterior brain stem (ICBM #9,10,11,12,13,14), the genu of the corpus callosium (ICBM #3), the body of the corpus callosium (ICBM #4), the splenium of the corpus callosium (ICBM #5), the right cerebral peduncle (ICBM #15), the left cerebral peduncle (ICBM #16), the right sagittal stratum (ICBM #21,29,31,47), the left sagittal stratum (ICBM #22,30,32,48), the right superior longitudinal fasciculus (ICBM #41), the left superior longitudinal fasciculus (ICBM #42), the anterior limb of the right internal capsule (ICBM #17), the anterior limb of the left internal capsule (ICBM #18), the posterior limb of the right internal capsule (ICBM #19), the posterior limb of the left internal capsule (ICBM #20), the right external capsule (ICBM #33), the left external capsule (ICBM #34), the right corona radiata (ICBM #23,25,27), the left corona radiata (ICBM #24,26,28).

9. The method as claimed in claim 1, in which the measurements of fractional anisotropy, axial diffusivity, radial diffusivity are performed in all the following regions of the brain:

the middle cerebellar peduncle (ICBM #1), the anterior brain stem (ICBM #2,7,8), the posterior brain stem (ICBM #9,10,11,12,13,14), the genu of the corpus callosium (ICBM #3), the body of the corpus callosium (ICBM #4), the splenium of the corpus callosium (ICBM #5), the right cerebral peduncle (ICBM #15), the left cerebral peduncle (ICBM #16), the right sagittal stratum (ICBM #21,29,31,47), the left sagittal stratum (ICBM #22,30,32,48), the right superior longitudinal fasciculus (ICBM #41), the left superior longitudinal fasciculus (ICBM #42), the anterior limb of the right internal capsule (ICBM #17), the anterior limb of the left internal capsule (ICBM #18), the posterior limb of the right internal capsule (ICBM #19), the posterior limb of the left internal capsule (ICBM #20), the right external capsule (ICBM #33), the left external capsule (ICBM #34), the right corona radiata (ICBM #23,25,27), the left corona radiata (ICBM #24,26,28).

15. The method as claimed in claim 1, in which the measurements of the fractional anisotropy, axial diffusivity and radial diffusivity are performed on an MRI image taken on a test subject having suffered a cranial and/or brain trauma.

16. The method as claimed in claim 1, in which the measurements of the fractional anisotropy, axial diffusivity and radial diffusivity are performed on an MRI image taken on a test subject having suffered a brain injury, a meningeal hemorrhage, an aneurismal meningeal hemorrhage, an ischemic attack, an intraparenchymal hemorrhagic attack, a cerebral anoxia.

2. An ex-vivo method for monitoring the trend of a brain injury in a test subject comprising the following steps at a time t₀ and at a time t₁:

a) measurements of the fractional anisotropy FA₁ at t₀ and FA₂ at t₁ in at least one first region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of a test subject,

b) measurements of the axial diffusivity DA₁ at t₀ and DA₂ at t₁ in at least one second region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

c) measurements of the radial diffusivity DR₁ at t₀ and DR₂ at t₁ in at least one third region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

d) determination of the ratios S_FA1, S_DA1, S_RD1, S_FA2, S_DA2, and S_RD2 as defined below by comparison of the measured values FA₁, DA₁, DR₁, FA₂, DA₂, DR₂ against normal regional values of fractional anisotropy FA_n, of axial diffusivity DA_n and of radial diffusivity DR_n, for said regions according to the following formulae;

S_FA1=(FA₁/FA_n)

S_DA1=(DA₁/DA_n)

S_DR1=(DR₁/DR_n)

S_FA2=(FA₂/FA_n)

S_DA2=(DA₂/DA_n)

S_DR2=(DR₂/DR_n)

e) determination of the variation Δ

S_FA, Δ

S_DA, Δ

S_DR according to the following formulae;

Δ

S_FA=S_FA2−

S_FA1

Δ

S_DA=S_DA2−

S_DA1

Δ

S_DR−

S_RD2−

S_RD1

a negative variation of at least one value Δ

S_FA, Δ

S_DA, indicating an aggravation of the injury, a positive variation of at least one value Δ

S_FA, Δ

S_DA, indicating a recovery, a negative variation of Δ

S_DR indicating a recovery, a positive variation of Δ

S_DR indicating an aggravation of the injury.

7. The method as claimed in claim 2, in which the reference patient is identical to the test subject.

3. An ex-vivo method for predicting outcome from coma, from the vegetative state or from the state of minimal consciousness of a test subject comprising the following steps:

a) measurement of the fractional anisotropy FA₁ in at least one first region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of a test subject,

b) measurement of the axial diffusivity DA₁ in at least one second region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

c) measurement of the radial diffusivity DR₁ in at least one third region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of said test subject,

d) determination of the diffusion ratios S_FAp, S_DAp, S_DRp by comparison of the measured values FA₁, DA₁, DR₁ against normal regional values of fractional anisotropy FA_n, of axial diffusivity DA_n and of radial diffusivity DR_n of a reference group of healthy subjects, for said regions according to the following formulae;

S_FAp=(FA₁/FA_n)

S_DAp=(DA₁/DA_n)

S_DRp=(DR₁/DR_n)

e) determination of a predictive algorithm F from the diffusion ratio S_FAref;

S_DAref, S_DRref of determined regions of the brain of a reference group of subjects as in the abovementioned steps a) to d) and of supervised classification software, the supervised classification software making it possible to classify the data S_FAref;

S_DAref, S_DRref as a function of the states of outcome of the patients of the subjects of the reference group of subjects;

f) calculation of a prediction value sDTI of the patient by application of the algorithm F determined in the step e) and of the values S_FAp, S_DAp, S_DRp obtained in the step d);

g) determination of at least two prediction value ranges by application of the algorithm F to the diffusion ratios S_FAref, S_DAref, S_DRref, a positive range and a negative range, the positive range delimiting the values for which prediction of outcome from coma, from the vegetative state or from the state of minimal consciousness is favorable, the negative range the reverse,

h) comparison of the prediction value of the step f) with said at least two ranges determined in the step g).

10. The method as claimed in claim 3, in which the measurement of the fractional anisotropy of the step a) is performed in at least one of the regions of the brain selected from the middle cerebellar peduncle (ICBM #1), the anterior brain stem (ICBM #2,7,8), the posterior brain stem (ICBM #9,10,11,12,13,14), the genu of the corpus callosium (ICBM #3), the body of the corpus callosium (ICBM #4), the splenium of the corpus callosium (ICBM #5), the right cerebral peduncle (ICBM #15), the left cerebral peduncle (ICBM #16), the sagittal stratum, the anterior limb of the right internal capsule (ICBM #17), the anterior limb of the left internal capsule (ICBM #18).

11. The method as claimed in claim 3, in which the measurement of the axial diffusivity of the step b) is performed in the regions of the brain selected from the posterior brain stem (ICBM #10), the genu of the corpus callosium (ICBM #3), the splenium of the corpus callosium (ICBM #5), the left cerebral peduncle (ICBM #16), the posterior limb of the left internal capsule (ICBM #20).

12. The method as claimed in claim 3, in which the measurement of the radial diffusivity of the step c) is performed in the regions of the brain selected from the cerebellar peduncle, the anterior brain stem (ICBM #2,7,8), the posterior brain stem (ICBM #10), the genu of the corpus callosium (ICBM #3), the body of the corpus callosium (ICBM #4), the right cerebral peduncle (ICBM #15), the left cerebral peduncle (ICBM #16), the anterior limb of the left internal capsule (ICBM #18), the posterior limb of the right internal capsule (ICBM #19), the posterior limb of the left internal capsule (ICBM #20).

13. The method as claimed in claim 3, in which the measurements of the fractional anisotropy, axial diffusivity and radial diffusivity are performed on an MRI image taken on a patient in a coma, in a vegetative state or in a state of minimal consciousness.

14. The method as claimed in claim 3, in which the supervised classification method is selected from the neural network methods, decision trees, the k closest neighbors method, the support vector machines.

17. The use of supervised classification software to construct an ex-vivo diagnostic reference base for predicting outcome from coma, from the vegetative state or from the state of minimal consciousness of a patient.

18. The use of a reference base obtained by means of supervised classification software in an ex-vivo diagnostic method for predicting outcome from coma, from the vegetative state or from the state of minimal consciousness of a test subject.

19. An ex-vivo method for predicting outcome from coma, from the vegetative state or from the state of minimal consciousness of a test subject comprising the following steps:

a) measurement of the fractional anisotropy FA in at least one first region of the brain on an image obtained by magnetic resonance imaging (MRI) of the brain of a test subject,

b) measurement of a score according to the following formula;

20. The method as claimed in claim 19, in which said beta_o and beta_i values are real numbers as described in the following table: