IP Library › Granted Patent US 11,672,468
Granted Patent B2
US 11,672,468 · App. 16/097,457 · Granted Jun 13, 2023

System and method for multi-modality quantification of neuroinflammation in central nervous system diseases

Inventors: Yong Wang (St. Louis, MO); Qing Wang (St. Louis, MO); Tammie Benzinger (St. Louis, MO)
Assignee: Washington University
A61B5/4088A61B5/055A61B5/4064G01R33/4806G01R33/56341G01R33/5616G01R33/5617G01R33/56509
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Quick Facts
Patent No.
US 11,672,468
App. No.
16/097,457
Granted
Jun 13, 2023
Kind
B2
Abstract

Methods and systems for diagnosing a condition of a central nervous system are provided. A method includes providing a DBSI-MRI data set obtained from the central nervous system of the subject, and transforming the DBSI-MRI data set to obtain at least one DBSI biomarker value. The method further includes comparing each DBSI biomarker value to at least one corresponding threshold value from a diagnostic database to obtain a relation between each DBSI biomarker value and the at least one corresponding threshold value, and diagnosing the condition according to at least one diagnostic rule, wherein each diagnostic rule defines a candidate condition in terms of the relations between the at least one DBSI biomarker value and the at least one corresponding threshold value.

Claims (55)

1. A method for diagnosing at least one condition of a central nervous system in a subject, the method comprising:

receiving, via a computing device including a processor, a diffusion basis spectrum imaging—magnetic resonance imaging (DBSI-MRI) data set obtained from the central nervous system of the subject;

transforming, via the computing device, the DBSI-MRI data set to obtain at least one DBSI biomarker value including a cellularity diffusivity based on a DBSI signal model;

generating maps of the at least one DBSI biomarker value derived from the transformation;

comparing, via the computing device, each of the at least one DBSI biomarker value to at least one corresponding threshold value from a diagnostic database to obtain a relation between each of the at least one DBSI biomarker value and the at least one corresponding threshold value, wherein the at least one corresponding threshold value each is a DBSI biomarker value;

diagnosing, via the computing device, the at least one condition according to at least one diagnostic rule, wherein each of the at least one diagnostic rule defines a candidate condition of the central nervous system in terms of the relations between the at least one DBSI biomarker value and the at least one corresponding threshold value, and

verifying the at least one DBSI biomarker by correlating the at least one DBSI biomarker with at least one cerebrospinal fluid (CSF) neural injury marker,

wherein the at least one condition is selected from the group consisting of a healthy condition, a preclinical Alzheimer's disease (AD) condition, and an early symptomatic AD condition, and the at least one DBSI biomarker is selected from the group consisting of: the cellularity diffusivity, a fractional anisotropy, and a radial diffusivity; and

wherein the at least one corresponding threshold value includes a plurality of threshold values, and the diagnostic database comprises a plurality of entries, the plurality of entries comprising a first entry corresponding to the healthy condition, a second entry corresponding to the pre-clinical AD condition, and a third entry corresponding to the early symptomatic AD condition, wherein each entry of the plurality of entries comprises the plurality of threshold values, wherein the plurality of threshold values for each entry comprise a lower cellularity diffusivity threshold value, an upper cellularity diffusivity threshold value, a lower fractional anisotropy threshold value, an upper fractional anisotropy threshold value, a lower radial diffusivity threshold value, and an upper radial diffusivity threshold value, wherein the plurality of threshold values are means of relating biomarker values to one condition selected from the group consisting of the healthy condition, the preclinical AD condition, and the early symptomatic AD condition, and

wherein the at least one diagnostic rule comprises:

diagnosing the healthy condition if the cellularity diffusivity value is less than the corresponding upper cellularity diffusivity threshold value from the first entry;

diagnosing the pre-clinical AD condition if the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the second entry; and

diagnosing the early symptomatic AD condition if:

the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the third entry;

the fractional anisotropy value is less than the corresponding upper fractional anisotropy threshold value from the third entry; and

the radial diffusivity value is greater than the corresponding lower radial diffusivity threshold value from the third entry.

2. The method in accordance with claim 1 , wherein transforming the DBSI-MRI data set comprises selecting the at least one DBSI biomarker value from a portion of the DBSI-MRI data set corresponding to at least one white matter tract of the subject, wherein the at least one white matter tract is selected from the group consisting of: corpus callosum, internal capsule, corona radiate, external capsule, cingulate gyrus, hippocampus, superior longitudinal fasciculus, and superior fronto-occipital fasciculus.

3. A central nervous system diagnosis computing device for providing a diagnosis of at least one condition of a central nervous system in a subject, said computing device including a processor in communication with a memory, said processor programmed to:

retrieve a diffusion basis spectrum imaging—magnetic resonance imaging (DBSI-MRI) data set obtained from the central nervous system of the subject from the memory;

transform the DBSI-MRI data set to obtain at least one DBSI biomarker value including a cellularity diffusivity based on a DBSI signal model;

generate maps of the at least one DBSI biomarker value derived from the transformation;

retrieve a diagnostic database comprising at least one corresponding threshold value from the memory;

compare each of the at least one DBSI biomarker value to at least one corresponding threshold value from the retrieved diagnostic database to obtain a relation between each of the at least one DBSI biomarker value and the at least one corresponding threshold value, wherein the at least one corresponding threshold value each is a DBSI biomarker value; and

diagnose the at least one condition according to at least one diagnostic rule, wherein each of the at least one diagnostic rule defines a candidate condition of the central nervous system in terms of the relations between the at least one DBSI biomarker value and the at least one corresponding threshold value,

wherein the at least one condition is selected from the group consisting of a healthy condition, a preclinical Alzheimer's disease (AD) condition and an early symptomatic AD condition, and the at least one DBSI biomarker is selected from the group consisting of: the cellularity diffusivity, a fractional anisotropy, and a radial diffusivity,

wherein said processor is further programmed to:

verify the at least one DBSI biomarker by correlating the at least one DBSI biomarker with at least one cerebrospinal fluid (CSF) neural injury marker,

wherein the at least one corresponding threshold value includes a plurality of threshold values, and the diagnostic database comprises a plurality of entries, the plurality of entries comprising a first entry corresponding to the healthy condition, a second entry corresponding to the preclinical AD condition, and a third entry corresponding to the early symptomatic AD condition, wherein each entry of the plurality of entries comprises the plurality of threshold values, wherein the plurality of threshold values are means of relating biomarker values to one condition selected from the group consisting of the healthy condition, the preclinical AD condition, and the early symptomatic AD condition,

wherein the plurality of threshold values for each entry comprise a lower cellularity diffusivity threshold value, an upper cellularity diffusivity threshold value, a lower fractional anisotropy threshold value, an upper fractional anisotropy threshold value, a lower radial diffusivity threshold value, and an upper radial diffusivity threshold value, and

wherein the at least one diagnostic rule comprises:

diagnosing the healthy condition if the cellularity diffusivity value is less than the corresponding upper cellularity diffusivity threshold value from the first entry;

diagnosing the pre-clinical AD condition if the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the second entry; and

diagnosing the early symptomatic AD condition if:

the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the third entry;

the fractional anisotropy value is less than the corresponding upper fractional anisotropy threshold value from the third entry; and

the radial diffusivity value is greater than the corresponding lower radial diffusivity threshold value from the third entry.

4. The computing device in accordance with claim 3 , wherein said processor is further configured to select the at least one DBSI biomarker value from a portion of the DBSI-MRI data set corresponding to at least one white matter tract of the subject, wherein the at least one white matter tract is selected from the group consisting of: corpus callosum, internal capsule, corona radiate, external capsule, cingulate gyrus, hippocampus, superior longitudinal fasciculus, and superior fronto-occipital fasciculus.

5. At least one non-transitory computer-readable storage media for providing a diagnosis of at least one condition of a central nervous system in a subject, the at least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein, when executed by at least one processor, the computer-executable instructions cause the at least one processor to:

transform a diffusion basis spectrum imaging—magnetic resonance imaging (DBSI-MRI) data set to obtain at least one DBSI biomarker value, wherein the DBSI-MRI data set is obtained from the central nervous system of the subject including a cellularity diffusivity based on a DBSI signal model;

generate maps of the at least one DBSI biomarker value derived from the transformation;

compare each of the at least one DBSI biomarker value to at least one corresponding threshold value from a stored diagnostic database to obtain a relation between each of the at least one DBSI biomarker value and the at least one corresponding threshold value, wherein the at least one corresponding threshold value each is a DBSI biomarker value; and

diagnose the at least one condition according to at least one diagnostic rule, wherein each of the at least one diagnostic rule defines a candidate condition of the central nervous system in terms of the relations between the at least one DBSI biomarker value and the at least one corresponding threshold value,

wherein the at least one condition is selected from the group consisting of a healthy condition, a preclinical Alzheimer's disease (AD) condition and an early symptomatic AD condition, and the at least one DBSI biomarker is selected from the group consisting of: the cellularity diffusivity, a fractional anisotropy, and a radial diffusivity,

wherein the computer-executable instructions further cause the at least one processor to:

verify the at least one DBSI biomarker by correlating the at least one DBSI biomarker with at least one cerebrospinal fluid (CSF) neural injury marker,

wherein the at least one corresponding threshold value includes a plurality of threshold values, and the diagnostic database comprises a plurality of entries, the plurality of entries comprising a first entry corresponding to the healthy condition, a second entry corresponding to the pre-clinical AD condition, and a third entry corresponding to the early symptomatic AD condition, wherein each entry of the plurality of entries comprises the plurality of threshold values, wherein the plurality of threshold values are means of relating biomarker values to one condition selected from the group consisting of the healthy condition, the preclinical AD condition, and the early symptomatic AD condition,

wherein the plurality of threshold values for each entry comprise a lower cellularity diffusivity threshold value, an upper cellularity diffusivity threshold value, a lower fractional anisotropy threshold value, an upper fractional anisotropy threshold value, a lower radial diffusivity threshold value, and an upper radial diffusivity threshold value, and

wherein the at least one diagnostic rule comprises:

diagnosing the healthy condition if the cellularity diffusivity value is less than the corresponding upper cellularity diffusivity threshold value from the first entry;

diagnosing the pre-clinical AD condition if the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the second entry; and

diagnosing the early symptomatic AD condition if:

the cellularity diffusivity value is between the corresponding lower cellularity diffusivity threshold value and upper cellularity diffusivity threshold value from the third entry;

the fractional anisotropy value is less than the corresponding upper fractional anisotropy threshold value from the third entry; and

the radial diffusivity value is greater than the corresponding lower radial diffusivity threshold value from the third entry.

6. The at least one non-transitory computer-readable storage media in accordance with claim 5 , wherein the computer-executable instructions cause the at least one processor to transform the DBSI-MRI data set by selecting the at least one DBSI biomarker value from a portion of the DBSI-MRI data set corresponding to at least one white matter tract of the subject, wherein the at least one white matter tract is selected from the group consisting of: corpus callosum, internal capsule, corona radiate, external capsule, cingulate gyrus, hippocampus, superior longitudinal fasciculus, and superior fronto-occipital fasciculus.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 4, 2019
From: WANG, YONG; WANG, QING; BENZINGER, TAMMIE LEE SMITH
To: WASHINGTON UNIVERSITY
Reel/Frame 048233/0928 →
Continuity (4)
Provisional Application 62353159 · Jun 22, 2016
Provisional Application 62329633 · Apr 29, 2016
Related Publication 20190150822A1 · May 23, 2019
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