U.S. patent application number 13/494429 was filed with the patent office on 2012-12-20 for methods and apparatus for assessing activity of an organ and uses thereof.
Invention is credited to Robert G. Carroll.
Application Number | 20120323108 13/494429 |
Document ID | / |
Family ID | 47353701 |
Filed Date | 2012-12-20 |
United States Patent
Application |
20120323108 |
Kind Code |
A1 |
Carroll; Robert G. |
December 20, 2012 |
METHODS AND APPARATUS FOR ASSESSING ACTIVITY OF AN ORGAN AND USES
THEREOF
Abstract
Methods and apparatus are provided for imaging activity of an
organ of a subject for diagnosis and prognosis of pathology or
injury to the organ, where unaffected portions of the organ are
used as a reference for assessing activity of afflicted areas of
the organ.
Inventors: |
Carroll; Robert G.; (Largo,
FL) |
Family ID: |
47353701 |
Appl. No.: |
13/494429 |
Filed: |
June 12, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13494262 |
Jun 12, 2012 |
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13494429 |
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61498243 |
Jun 17, 2011 |
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Current U.S.
Class: |
600/407 ;
345/419 |
Current CPC
Class: |
G06T 7/0012 20130101;
G06T 2207/10104 20130101; G06T 7/0014 20130101; G06T 7/136
20170101; G06T 2207/30016 20130101 |
Class at
Publication: |
600/407 ;
345/419 |
International
Class: |
A61B 6/00 20060101
A61B006/00; G06T 15/00 20110101 G06T015/00 |
Claims
1. A system for assessing the activity of an organ in a subject
comprising: a) an imaging system comprising: i) an imaging device
for generating a quantitative three-dimensional image of the organ
that is represented as voxels, wherein each voxel contains
information about the activity of a portion of the organ; and ii) a
computing device operatively connected to the imaging device and to
a first display device; and b) one or more computers operatively
connected to the imaging system, comprising one or more processors,
a memory unit, and a computer-readable storage medium including
computer-readable code that is read by the one or more processors
to perform a method comprising the steps of: i) receiving by the
one or more computers the generated three-dimensional organ image;
ii) calculating by the one or more computers a mean of the activity
represented by the voxels, wherein voxels representing values at
upper and lower extremes are excluded from calculation of the mean;
iii) calculating by the one or more computers a standard deviation
of the mean obtained in step ii), wherein voxels representing
activity above a certain standard deviation of the mean indicate
areas of the organ having increased activity and wherein voxels
representing activity below a certain standard deviation of the
mean indicate areas of the organ having reduced activity; and iv)
generating by the one or more computers a representation of the
organ showing areas of the organ having increased activity and/or
reduced activity.
2. The system of claim 1, wherein the method performed by the one
or more processors comprises displaying by the one or more
computers the generated representation of the organ on a second
display device operatively connected to the one or more
computers.
3. The system of claim 1, wherein the method performed by the one
or more processors comprises transmitting from the one or more
computers the generated representation of the organ to the imaging
system so as to be displayed on the first display device.
4. The system of claim 1, wherein in step ii) voxels are excluded
from the calculation of the mean if the voxels represent values at
the upper and lower 5% of the values.
5. The system of claim 1, wherein standard deviation (SD) is
calculated in 0.1 SD units between 3.0 SD units below the mean to
3.0 SD units above the mean.
6. The system of claim 1, wherein voxels representing activity
above 1.5 SD units above the mean indicate areas of the organ
having increased activity and wherein voxels representing activity
below 1.5 SD units below the mean indicate areas of the organ
having reduced activity.
7. The system of claim 1, wherein voxels from the one side of an
organ are compared with corresponding voxels from an opposite side
of the same organ.
8. The system of claim 1, wherein voxels from an organ on one side
of the body are compared with corresponding voxels from the
corresponding organ on the opposite side of the body.
9. The system of claim 1, wherein the image of the organ is
obtained using positron emission tomography (PET), functional
magnetic resonance imaging (fMRI), diffusion tensor magnetic
resonance imaging, magnetic resonance imaging of any form, single
photon emission computed tomography (SPECT) magnetic source imaging
or optical imaging.
10. The system of claim 1, wherein three dimensional imaging of the
organ is obtained using positron emission tomography (PET) in
connection with a computed tomography (CT) X-ray scan.
11. The system of claim 1, wherein the image of the organ is
obtained using positron emission tomography (PET) in connection
with any magnetic resonance scan.
12. The system of claim 1, wherein areas of increased or reduced
activity in the organ indicate a disease, an injury, a response to
an injury, or functional changes in areas that have been
disconnected from the remainder of the brain or spinal cord because
of injury to connective structures.
13. The system of claim 12, wherein the disease or injury is a
tumor, stroke, infection, demyelinating disease, degenerative
disease, dementia, ischemia, traumatic injury, shock wave injury,
or primary or metastatic cancer.
14. The system of claim 12, wherein the organ is the brain and
areas of reduced activity in the organ represent diffuse axonal
injury.
15. The system of claim 1 comprising determining a ratio of a
number of voxels showing increased activity to a number of voxels
showing decreased activity within an area of disease or injury.
16. The system of claim 1 comprising determining a ratio of a
number of voxels showing increased activity to a number of voxels
showing decreased activity at a border region between an area of
disease or injury and normal tissue.
17. The system of claim 1, wherein an image of the organ is
obtained and analyzed at a plurality of time points.
18. The system of claim 17, wherein images at different time points
are used to evaluate effectiveness of a course of treatment of a
subject or to evaluate progression of disease.
19. A system for assessing the activity of an organ in a subject
comprising: one or more computing devices comprising one or more
processors, a memory unit, and a computer-readable storage medium
including computer-readable code that is read by the one or more
processors to perform a method comprising the steps of: i)
obtaining by the one or more computing devices a quantitative
three-dimensional image of the organ that is represented as voxels,
wherein each voxel contains information about the activity of a
portion of the organ generated by an imaging device; ii)
transmitting the generated three-dimensional organ image to one or
more analysis computing devices; iii) obtaining a representation of
the organ from the one or more analysis computing devices, wherein
the representation shows areas of the organ having increased
activity and/or reduced activity; and iv) displaying the obtained
representation on the display device.
20. The system of claim 19, wherein the representation of the organ
was generated using the transmitted three-dimensional organ image
at the one or more analysis computers by a method comprising the
steps of: i) calculating a mean of the activity represented by the
voxels of the three-dimensional organ image, wherein voxels
representing values at upper and lower extremes are excluded from
calculation of the mean; and ii) calculating a standard deviation
of the mean obtained in step i), wherein voxels representing
activity above a certain standard deviation of the mean indicate
areas of the organ having increased activity and wherein voxels
representing activity below a certain standard deviation of the
mean indicate areas of the organ having reduced activity.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] This application claims the benefit of U.S. Provisional
Patent Application No. 61/498,243, filed on Jun. 17, 2011, the
content of which is incorporated herein by reference in its
entirety.
FIELD
[0002] This invention relates to methods and apparatus for imaging
activity of an organ of a subject for diagnosis and prognosis of
pathology or injury to the organ, where unaffected portions of the
organ are used as a reference for assessing activity of afflicted
areas of the organ.
BACKGROUND
[0003] Throughout this application various publications are
referred to in parenthesis. Full citations for these references may
be found at the end of the specification immediately preceding the
claims. The disclosures of these publications are hereby
incorporated by reference in their entireties into the subject
application to more fully describe the art to which the subject
application pertains.
[0004] Nuclear medicine involves the noninvasive quantification of
physiological processes. In the case of positron emission
tomography (PET), fluorine-18 deoxyglucose (FDG) has proven to be a
remarkably good way of tracing the level of physiological glucose
metabolism in living cells. Uptake of fluorine-18 deoxyglucose is
proportional to the number of glucose transporter 1 (GLUT1)
receptors expressed on the cell surface. The number of GLUT1
receptors on the surface is regulated by the cell in accord with
its level of internally sensed demand for glucose. Once FDG glucose
enters the cell, further metabolism is prevented by the lack of
oxygen within the constructor. Thus, one has an ideal physiological
tracer for glucose uptake, separated from further intracellular
stages of glucose metabolism. New and improved PET scanners
continue to be developed (e.g., Shiga et al., 2009).
[0005] Imaging studies have been used between groups of subjects to
demonstrate evidence of injuries or pathologies (e.g., Kato et al.,
2007; Zhang et al., 2010). Three dimensional images can be
represented using voxels. A voxel is a data point on a regular grid
in three dimensional space. A voxel, i.e., a volumetric pixel, is
analogous to a pixel, which represents two dimensional image data.
The data point can consist of a single piece of datum or multiple
pieces of data. Voxel-based morphometry is an imaging analysis
technique that can be used to investigate focal differences in, for
example, the brain between two groups of subjects (e.g., Ashburner
and Friston, 2000). Voxel-based morphometry studies have been
carried out by comparing patients with controls, for example in
studies of dementia (Mummery et al., 2000) and traumatic brain
injury (Garcia-Panach et al., 2011).
[0006] The need for control groups can impede the use of imaging
for diagnosis. This is especially the case since there are, for
example, gender-specific cerebral areas of age-associated changes
of FDG uptake (Kim et al., 2009). For example, accurate diagnosis
of diffuse axonal injury is severely limited by requirements for
adequate age- and gender-matched control groups. One widely used
software program has only 4 patients below age 55; and only 37
patients in the 56-75 year age range as baseline controls. Other
databases are even more lacking. Thus, it is impossible to
objectively measure brain injury in those groups of individuals
most prone to brain injury, i.e., infants, children, adolescents,
athletes of age 15 to 30 and motor vehicle accident survivors aged
15 to 55. Data in those younger than 15 are very scarce.
[0007] The prevent invention address the need for a method of
imaging injuries and pathologies that does not require comparison
of a patient to a control group of subjects.
SUMMARY
[0008] In exemplary embodiments, the present invention makes use of
the normal portions of a patient's own organ to calculate baseline
physiological function. Using the patient as its own control
creates far more powerful imaging and measurement statistics as
well as greater reliability for the relevance of the measurements
for the patient's own situation. With use of the individual as its
own control, the available precision of measurement is vastly
improved because one is not required to have a reference population
of the same age or gender, or same manufacture or same generation
of equipment, or precisely the same protocol of imaging in a
reference population. Thus, the present invention can provide
improved technical features over the art.
[0009] In exemplary embodiments, the invention provides methods for
assessing the activity of an organ in a subject with the aid of a
digital computer comprising: a) accessing by one or more computers
a quantitative three-dimensional image of the organ that is
represented as voxels, wherein each voxel contains information
about the activity of a portion of the organ; b) calculating by the
one or more computers a mean of the activity represented by the
voxels, wherein voxels representing values at upper and lower
extremes are excluded from calculation of the mean; c) calculating
by the one or more computers a standard deviation of the mean
obtained in step b), wherein voxels representing activity above a
certain standard deviation of the mean indicate areas of the organ
having increased activity and wherein voxels representing activity
below a certain standard deviation of the mean indicate areas of
the organ having reduced activity; and d) outputting by the one or
more computers to an output device a representation of the organ
showing areas of the organ having increased activity and/or reduced
activity. In some exemplary embodiments, the method may further
comprise outputting by the one or more computers to the output
device a representation of the organ showing areas of the organ
having neither increased activity and/or reduced activity.
[0010] In exemplary embodiments, the invention also provides
systems for assessing the activity of an organ in a subject
comprising one or more processors, a memory unit, and a
computer-readable storage medium including computer-readable code
that is read by the one or more processors to perform a method
comprising the steps of: a) accessing by one or more computers a
quantitative three-dimensional image of the organ that is
represented as voxels, wherein each voxel contains information
about the activity of a portion of the organ; b) calculating by the
one or more computers a mean of the activity represented by the
voxels, wherein voxels representing values at upper and lower
extremes are excluded from calculation of the mean; c) calculating
by the one or more computers a standard deviation of the mean
obtained in step b), wherein voxels representing activity above a
certain standard deviation of the mean indicate areas of the organ
having increased activity and wherein voxels representing activity
below a certain standard deviation of the mean indicate areas of
the organ having reduced activity; and d) outputting by the one or
more computers to an output device a representation of the organ
showing areas of the organ having increased activity and/or reduced
activity.
[0011] In exemplary embodiments, the invention further provides
systems for assessing the activity of an organ in a subject
comprising: a) an imaging system comprising: i) an imaging device
for generating a quantitative three-dimensional image of the organ
that is represented as voxels, wherein each voxel contains
information about the activity of a portion of the organ; and ii) a
computing device operatively connected to the imaging device and to
a first display device; and b) one or more computers operatively
connected to the imaging system, comprising one or more processors,
a memory unit, and a computer-readable storage medium including
computer-readable code that is read by the one or more processors
to perform a method comprising the steps of: i) receiving by the
one or more computers the generated three-dimensional organ image;
ii) calculating by the one or more computers a mean of the activity
represented by the voxels, wherein voxels representing values at
upper and lower extremes are excluded from calculation of the mean;
iii) calculating by the one or more computers a standard deviation
of the mean obtained in step ii), wherein voxels representing
activity above a certain standard deviation of the mean indicate
areas of the organ having increased activity and wherein voxels
representing activity below a certain standard deviation of the
mean indicate areas of the organ having reduced activity; and iv)
generating by the one or more computers a representation of the
organ showing areas of the organ having increased activity and/or
reduced activity.
[0012] In exemplary embodiments, the invention still further
provides systems for assessing the activity of an organ in a
subject comprising: a) one or more computing devices comprising one
or more processors, a memory unit, and a computer-readable storage
medium including computer-readable code that is read by the one or
more processors to perform a method comprising the steps of: i)
obtaining by the one or more computing devices a quantitative
three-dimensional image of the organ that is represented as voxels,
wherein each voxel contains information about the activity of a
portion of the organ generated by an imaging device; ii)
transmitting the generated three-dimensional organ image to one or
more analysis computing devices; iii) obtaining a representation of
the organ from the one or more analysis computing devices, wherein
the representation shows areas of the organ having increased
activity and/or reduced activity; and iv) displaying the obtained
representation on the display device.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The features and advantages of the disclosure can be more
fully understood with reference to the following description of the
disclosure when taken in conjunction with the accompanying figures,
wherein:
[0014] FIG. 1 is a flow chart illustrating an exemplary method for
identifying voxels having inactivity and/or compensatory activity
in comparison to a baseline of the normal portions of the entire
brain according to an exemplary embodiment of the present
disclosure.
[0015] FIG. 2 is a schematic representation illustrating a imaging
system operatively connected to one or more computing devices
according to an exemplary embodiment of the present disclosure.
[0016] FIG. 3 is a flow chart illustrating an exemplary method for
assessing the activity of an organ in a subject according to an
exemplary embodiment of the present disclosure.
[0017] FIGS. 4A-4D are exemplary charts showing results of various
psychometrics tests performed with a subject over a one year
period.
[0018] FIG. 5A-5B show comparative quantitative PET images showing
significant improvement in Case Study #1 from May 2011 (A) to
February 2012 (B) consistent with improved cognitive scores.
DETAILED DESCRIPTION
[0019] In exemplary embodiments, the invention may provide a method
for assessing the activity of an organ in a subject with the aid of
a digital computer comprising:
[0020] a) accessing by one or more computers a quantitative
three-dimensional image of the organ that is represented as voxels,
wherein each voxel contains information about the activity of a
portion of the organ;
[0021] b) calculating by the one or more computers a mean of the
activity represented by the voxels, wherein voxels representing
values at upper and lower extremes are excluded from calculation of
the mean;
[0022] c) calculating by the one or more computers a standard
deviation of the mean obtained in step b), wherein voxels
representing activity above a certain standard deviation of the
mean indicate areas of the organ having increased activity and
wherein voxels representing activity below a certain standard
deviation of the mean indicate areas of the organ having reduced
activity; and
[0023] d) outputting by the one or more computers to an output
device a representation of the organ showing areas of the organ
having increased activity and/or reduced activity.
[0024] In exemplary embodiments, the method may comprise outputting
by the one or more computers to the output device a representation
of the organ showing areas of the organ having neither increased
activity and/or reduced activity.
[0025] In exemplary embodiments, the invention may provide a system
for assessing the activity of an organ in a subject comprising one
or more processors, a memory unit, and a computer-readable storage
medium including computer-readable code that is read by the one or
more processors to perform a method comprising the steps of:
[0026] a) accessing by one or more computers a quantitative
three-dimensional image of the organ that is represented as voxels,
wherein each voxel contains information about the activity of a
portion of the organ;
[0027] b) calculating by the one or more computers a mean of the
activity represented by the voxels, wherein voxels representing
values at upper and lower extremes are excluded from calculation of
the mean;
[0028] c) calculating by the one or more computers a standard
deviation of the mean obtained in step b), wherein voxels
representing activity above a certain standard deviation of the
mean indicate areas of the organ having increased activity and
wherein voxels representing activity below a certain standard
deviation of the mean indicate areas of the organ having reduced
activity; and
[0029] d) outputting by the one or more computers to an output
device a representation of the organ showing areas of the organ
having increased activity and/or reduced activity.
[0030] In exemplary embodiments, the system may comprise outputting
by the one or more computers to the output device a representation
of the organ showing areas of the organ having neither increased
activity and/or reduced activity.
[0031] Various values can be selected for use in excluding voxels
representing values at upper and lower extremes from the
calculation of the mean. As non-limiting examples, voxels can be
excluded from calculation of the mean if the voxels represent
values at the upper and lower 1%, 5% or 10% of the values.
[0032] In exemplary embodiments, other methods of excluding vowels
that represent outlier values may be used. As one example, a first
mean can be calculated of the activity represented by all the
voxels. Then, voxels representing values at the upper and lower
values can be excluded, either if the values are above or below a
certain percentage of all values or if the values are above or
below a certain standard deviation of the first mean. The voxels
that are not excluded are then used to calculate a new mean of
normal voxels.
[0033] Another method of excluding vowels that represent outlier
values is to construct a histogram of values represented by all
voxels, then fitting a curve to the histogram, and excluding voxels
that deviate above or below the curve. These procedures can be
performed by the one or more computers that calculated a mean of
the activity represented by the voxels where voxels representing
values at upper and lower extremes are excluded from calculation of
the mean.
[0034] Standard deviation (SD) of the mean can be expressed, for
example in 1SD, 0.1 SD or 0.01 SD units. For example, SD can be
calculated in 0.01 or 0.1 SD units between 3.0, 3.5, 4.0 or 4.5 SD
units below the mean to 3.0, 3.5, 4.0 or 4.5 SD units above the
mean. As a further example, in one embodiment, standard deviation
(SD) is calculated in 0.1 SD units between 4.0 SD units below the
mean to 4.0 SD units above the mean.
[0035] In exemplary embodiments, different thresholds can be
established for classifying voxels as representing increased
activity or decreased activity. For example, a threshold can be set
at 1.0 SD, 1.5 SD, 1.65 SD, 2.0 SD, 2.5 SD, 3.0, 3.5, 4.0 or 4.5 SD
units above or below the mean. As a further example, in one
embodiment, voxels representing activity above 1.5 SD units above
the mean indicate areas of the organ having increased activity and
voxels representing activity below 1.5 SD units below the mean
indicate areas of the organ having reduced activity. Other
variations can be used consistent with the letter and spirit of the
present disclosure.
[0036] The organ from which the image is obtained can be, for
example, brain, heart, lung, kidney, liver, pancreas, bladder,
salivary glands, esophagus, stomach, gallbladder, intestines,
colon, rectum, thyroid, parathyroid, adrenal gland, ureter,
bladder, urethra, tonsils, adenoids, thymus, spleen, ovary,
fallopian tube, uterus, vagina, mammary gland, testes, vas
deferens, seminal vesicle, prostate, penis, pharynx, larynx,
trachea, bronchi or lung, to name a few.
[0037] In exemplary embodiments, voxels from the one side of an
organ can be compared with corresponding voxels from an opposite
side of the same organ. For organs that occur on both sides of the
body, such as for example, brain, lung or kidney, in exemplary
embodiments, voxels from an organ on one side of the body can be
compared with corresponding voxels from the corresponding organ on
the opposite side of the body.
[0038] In exemplary embodiments, the image of the organ can be
obtained using, for example, positron emission tomography (PET),
functional magnetic resonance imaging (fMRI), any type or sequence
of magnetic resonance imaging (MRI) including diffusion tensor
magnetic resonance imaging, single photon emission computed
tomography (SPECT), magnetic source imaging or optical imaging, to
name a few. For example, three dimensional imaging of the organ can
be obtained using positron emission tomography (PET) in connection
with a computed tomography (CT) X-ray scan, or may be obtained
using positron emission tomography (PET) in connection with any
magnetic resonance scan.
[0039] Dedicated brain-only solid-state PET scanners are being
developed by Hitachi. Such units may provide essential
physiological information for a much lower patient radiation dose
than existing PET CT machines. A PET CT general-purpose machine may
generate a CT dose 10 times the radiation dose from a 15 milicurie
FDG injection. The dedicated machine entirely does away with the CT
dose and drops the required FDG dose by factor of five to about 3
mCi. In exemplary embodiments, such dedicated machines and the like
can be used.
[0040] In exemplary embodiments, areas of increased or reduced
activity in an organ can indicate a disease, an injury, a response
to an injury, or functional changes in areas that have been
disconnected from the remainder of the brain or spinal cord because
of injury to connective structures. Non-limiting examples of such
diseases or injuries include a tumor, stroke, infection,
demyelinating disease, degenerative disease, dementia, ischemia,
traumatic injury, shock wave injury, or primary or metastatic
cancer, to name a few. For example, if the organ is the brain,
areas of reduced activity can represent diffuse axonal injury,
and/or represent areas of the brain disconnected from their source
of workload. Functional connectivity MRI can be used to show which
parts of the brain are communicating.
[0041] In exemplary embodiments, areas of disease or injury can be
further analyzed by determining a ratio of a number of voxels
showing increased activity to a number of voxels showing decreased
activity within the area of disease or injury. Further analysis can
include determining a ratio of a number of voxels showing increased
activity to a number of voxels showing decreased activity within
the entirety of a diseased area and/or at a border region between
an area of disease or injury and normal tissue.
[0042] In exemplary embodiments, an image of the organ can be
obtained and analyzed at a plurality of time points. Images
obtained at different time points can be used, for example, to
evaluate effectiveness of a course of treatment of a subject or to
evaluate progression of disease.
[0043] For example, an image of the brain can be obtained and
analyzed at a plurality of time points during neurological surgery
or during neurological intensive care. Frequent serial brain PET
studies can be used to guide neurological surgery and neurological
intensive care of brain injured patients. In exemplary embodiments,
periodic, or non-periodic repeated assessments may provide a tool
for demonstrating response to therapy in a timely manner. By way of
non-limiting example, studies may be repeated, e.g., a minimal
interval of about three hours to a more common interval of daily,
weekly, monthly, to name a few, to document brain glucose
metabolism, brain oxygen metabolism, brain blood flow, and other
vital parameters, to name a few. Some neurological surgery
procedures have operating room durations in excess of 10 hours.
Neurological intensive care can last for months.
[0044] As another example, an image of the heart can be obtained
and analyzed at a plurality of time points during cardiac surgery,
during cardiac interventional procedures, and/or during cardiac
intensive care. In exemplary embodiments, frequent serial heart PET
studies can be used to guide cardiac surgery and cardiac
interventional intensive care of heart injured patients. Periodic
and/or non-periodic repeated assessments may provide a tool for
demonstrating response to therapy in a timely manner. Studies may
be repeated, e.g., a minimal interval of about 5 minutes to a more
common interval of daily, weekly, monthly, to name a few, to
document cardiac nutritional blood flow using rubidium 82, cardiac
FDG metabolism using fluorine 18; cardiac oxygen metabolism using
oxygen 15, and other vital parameters, to name a few.
[0045] Voxels within an area of disease or injury in the organ can
be analyzed at a plurality of time points, and a ratio of a number
of voxels within the area showing increased activity over time to a
number of voxels within the area showing decreased activity over
time can be used as a measure of whether the disease or injury is
improving or not improving. For example, if the disease is cancer,
a decrease in the ratio of the number of voxels within the area of
disease showing increased activity over time to the number of
voxels within the area of disease showing decreased activity over
time is indicative of a favorable outcome. As another example, if
the disease is reduced blood flow to the area, an increase in the
ratio of the number of voxels within the area showing increased
activity over time to the number of voxels within the area showing
decreased activity over time is indicative of a favorable
outcome.
[0046] In exemplary embodiments, the subject can be any living
organism, including any type of animals, such as humans.
[0047] The methods disclosed herein can comprise imaging the
subject to obtain an image of the organ.
[0048] In exemplary embodiments, a system for assessing the
activity of an organ in a subject may comprise:
[0049] a) an imaging system comprising:
[0050] i) an imaging device for generating a quantitative
three-dimensional image of the organ that is represented as voxels,
wherein each voxel contains information about the activity of a
portion of the organ; and
[0051] ii) a computing device operatively connected to the imaging
device and to a first display device; and
[0052] b) one or more computers operatively connected to the
imaging system, comprising one or more processors, a memory unit,
and a computer-readable storage medium including computer-readable
code that is read by the one or more processors to perform a method
comprising the steps of:
[0053] i) receiving by the one or more computers the generated
three-dimensional organ image;
[0054] ii) calculating by the one or more computers a mean of the
activity represented by the voxels, wherein voxels representing
values at upper and lower extremes are excluded from calculation of
the mean;
[0055] iii) calculating by the one or more computers a standard
deviation of the mean obtained in step ii), wherein voxels
representing activity above a certain standard deviation of the
mean indicate areas of the organ having increased activity and
wherein voxels representing activity below a certain standard
deviation of the mean indicate areas of the organ having reduced
activity; and
[0056] iv) generating by the one or more computers a representation
of the organ showing areas of the organ having increased activity
and/or reduced activity.
[0057] In exemplary embodiments, the method performed by the one or
more processors can comprise displaying by the one or more
computers the generated representation of the organ on a second
display device operatively connected to the one or more computers.
The method performed by the one or more processors can also
comprise transmitting from the one or more computers the generated
representation of the organ to the imaging system so as to be
displayed on the first display device.
[0058] In exemplary embodiments, the image of the organ can
obtained using, e.g., positron emission tomography (PET),
functional magnetic resonance imaging (fMRI), any type or sequence
of magnetic resonance imaging including diffusion tensor imaging
(MRI); magnetic source imaging, optical imaging, computed
tomography (CT) X-ray scan, or combinations thereof, to name a few.
In some exemplary embodiments, the image of the organ may be
obtained using positron emission tomography (PET), alone, or in
combination with CT or MRI.
[0059] In exemplary embodiments, a system for assessing the
activity of an organ in a subject comprising one or more computing
devices may comprise one or more processors, a memory unit, and a
computer-readable storage medium including computer-readable code
that is read by the one or more processors to perform a method
comprising the steps of:
[0060] i) obtaining by the one or more computing devices a
quantitative three-dimensional image of the organ that is
represented as voxels, wherein each voxel contains information
about the activity of a portion of the organ generated by an
imaging device;
[0061] ii) transmitting the generated three-dimensional organ image
to one or more analysis computing devices; iii) obtaining a
representation of the organ from the one or more analysis computing
devices, wherein the representation shows areas of the organ having
increased activity and/or reduced activity; and
[0062] iv) displaying the obtained representation on the display
device.
[0063] In exemplary embodiments, the representation of the organ
can be generated using the transmitted three-dimensional organ
image at the one or more analysis computers by a method comprising,
e.g., the steps of:
[0064] i) calculating a mean of the activity represented by the
voxels of the three-dimensional organ image, wherein voxels
representing values at upper and lower extremes are excluded from
calculation of the mean; and
[0065] ii) calculating a standard deviation of the mean obtained in
step i), wherein voxels representing activity above a certain
standard deviation of the mean indicate areas of the organ having
increased activity and wherein voxels representing activity below a
certain standard deviation of the mean indicate areas of the organ
having reduced activity.
[0066] In exemplary embodiments, a voxel analysis of the patient's
own organ can be used to establish mean voxel values. Median and
mode voxel values can also be determined. The fundamental
principles of voxel-based morphometric (VBM) methods are well
known.
[0067] In exemplary embodiments, a histogram may be provided,
ranging from -4 standard deviations to +4 standard deviations, for
example, in 0.1 standard deviation steps illustrating the
distribution of voxels within the boundaries of the organ being
examined. This histogram display of voxels can be used to select
those voxels which will be statistically analyzed and graphically
displayed. In a normal organ one expects a Gaussian distribution of
voxels.
[0068] In exemplary embodiments, voxels can be analyzed using, for
example, commercially available software such as provided by MIM
Software Inc. (Cleveland, Ohio).
[0069] In exemplary embodiments, volumetric three-dimensional
outlines of clusters can be viewed in a cinematic mode, for
example, proceeding from -4 standard deviations toward -1 standard
deviation thereby showing areas of each degree of damage. Similarly
a cinematic review of +3 standard deviation volumetric
three-dimensional outlines allows demonstration of compensatory
increase in neuronal function of undamaged structures and other
recruited pathways. Such analysis can further verify the reality of
damaged tissue by demonstrating the reality of compensatory
mechanisms.
[0070] Where clusters of inactivity or compensatory activity are
found, in exemplary embodiments, different indicia such as color
overlays, text labels, boundary outlines or the like may be applied
to the visual display output. The display output can be a computer
monitor but may also be high resolution printers as well, or other
display devices. Three-dimensional volumetric displays of medical
data are becoming increasingly available.
[0071] According to an exemplary embodiment, the invention may
include the ability to generate a short, cycling presentation of
the identified voxels (inactive and/or compensatory) at a plurality
of standard deviations. This cycling presentation or animation may
be presented in three-dimensional contours of the organ.
Three-dimensional contours of details of degree of metabolism
within areas of damage can be simultaneously displayed.
[0072] In exemplary embodiments, the number of voxels within the
three-dimensional boundaries defined by standard deviations, such
as, for example, 3, 2.5, 2.0, 1.5, and 1.0 standard deviations
above or below the mean of non-involved tissue within that patients
organ can be mapped over time to provide a very sensitive analysis
of response to therapy versus progression of disease.
[0073] In an exemplary embodiment, the brain quantitative analysis
program may automatically cycle from the lowest transaxial slice to
the highest transaxial slice. In some exemplary embodiments, the
thickness of the slice can be adjusted from 4 mm to 20 mm.
[0074] Exemplary embodiments of the present disclosure may be
applicable to a large range of noninvasive imaging modalities that
can be used to address and quantitate changes in tissue physiology
repair and disease processes over time.
[0075] In exemplary embodiments, clusters of voxels may be defined
by deviants from the mean and can clearly show both the epicenter,
the umbra and the penumbra of any imaginable physiological deviance
within any organ, and may be measured by any modality that is
voxel-based. For example, imaging MRI, functional MRI, diffusion
tensor MRI, and other experimental MRI sequences may be candidates
for such analysis. In exemplary embodiments, such modalities may
include positron emission tomography, magnetic resonance imaging,
single photon emission computed tomography, CT, volumetric
ultrasound, optical tissue imaging, and all other means of
noninvasive volumetric imaging of living tissues.
[0076] In exemplary embodiments, symmetrical organs such as brain
and kidneys, comparison can be made with the corresponding area in
the contralateral side, bearing in mind that within the brain, the
contralateral structure may be up-regulated to compensate for
decreased function in the injured structure.
[0077] In exemplary embodiments, diffuse axonal injuries in the
brain may generally appear as scattered small areas of decreased
glucose metabolism on the gyri of the cerebral cortex. These
lesions may be almost impossible to visually identify because of
their location on a variable terrain. In some exemplary
embodiments, voxel-based threshold imaging may clearly identify
small scattered lesions.
[0078] In exemplary embodiments, objective quantification of the
number, size, severity, and location of, for example, areas of
decreased glucose metabolism within the brain may be possible
without the need of a control group. Thus, possible artifacts
generated by arbitrary brain deformation may be avoided. In some
exemplary embodiments, serial quantification of number, size,
severity and location of injured areas may provide objective
documentation of quantitative response to therapy. For example,
therapies such as drug intervention and rehabilitation intervention
can be compared with the spontaneous natural history of the
untreated pathological process.
[0079] Within the brain, amyloid protein is commonly deposited at
areas of injury, potentially leading to progressively greater
injury over time due to amyloid toxicity. In exemplary embodiments,
amyloid brain imaging may be a natural adjunct to fluorine 18
deoxyglucose brain imaging in traumatic brain injury.
[0080] There may be multiple patterns of injury following trauma to
the brain including coup-contrecoup contusion of brain surfaces,
axonal damage by propagation of shear forces resulting in Wallerian
degeneration and death of widely distributed neurons whose axons
assembled into a tract within the path of shear forces.
[0081] In exemplary embodiments, baseline measurements may be made
on individuals involved in contact sports who can be tracked season
by season. In exemplary embodiments, the present invention can be
used to identify the vulnerable post-concussion time during which
repeated trauma can produce disproportionate severe damage.
[0082] Military personnel can be screened for susceptibility to
additional blast injury predeployment, potentially decreasing the
total number of individuals whose cumulative brain damage renders
them nonfunctional. Most individuals have a degree of cognitive
reserve which masks the behavioral and neurological signs and
symptoms of lesser degrees of brain injury.
[0083] According to exemplary embodiments, in any area of diseased
tissue, adjacent voxels may include volumes of cells with improving
metabolism adjacent to volumes of cells with declining metabolism.
In some exemplary embodiments, the ratio of voxels advancing to
voxels declining may be a measure of whether the overall physiology
is favoring regeneration or death. In some exemplary embodiments,
whether the process is cancer where one wants the decline to be
predominant or areas of blocked blood flow where one wants the
advance to be predominant, progress of the local physiological
condition can be objectively measured in a timely fashion to allow
therapeutic intervention with near real-time monitoring of the
results. This may allow one to measure the status of the region,
intervene therapeutically, and then remeasure.
[0084] In exemplary embodiments, each patient, and each area of
brain hypometabolism may require frequent monitoring to detect the
local advance decline ratio. For example, each patient and each
area of brain hypometabolism may have differing dose response
curves for any therapeutic intervention.
[0085] In exemplary embodiments, the ratio of the number of voxels
improving/number of voxels worsening in an anatomical area can
provide a unique measure of overall disease progression and
treatment effectiveness over time. In addition to the injured or
diseased area itself, the border between normal and abnormal tissue
areas may be another region of interest.
[0086] In exemplary embodiments, the number of voxels in each
degree of deviance from the mean may be obtained, and serial images
may be displayed, such as, for example, starting with those voxels
that are most negative (-4 standard deviations). Further, the
obtained voxels may be summed with all interval voxels to a
selected endpoint, such as, for example, -1.65 standard deviations.
This may produce a quantitative three-dimensional volumetric map of
the range of disease. This map may be electronically saved on any
suitable computer-readable storage device and subsequently used to
quantitatively compare with a second volumetric map obtained after
therapy in accordance with the expected time course of disease
resolution. For example, the second map may be obtained one to
three months after therapy relating to chronic conditions. In other
situations, the second map may be obtained one to three days after
therapy relating to acute conditions.
[0087] In exemplary embodiments, the quantitative disease
assessment taking place at regular intervals may serve as an
objective measurement of the efficacy of any drug or interventional
therapy. For example, in a laboratory or a clinical research
setting more frequent observations can document the physiology of
the repair sequence. Thus surrogate markers for pharmacological
intervention trials may be validated. These can be of immense help
in drug discovery. These can also be of immense help in determining
whether an individual patient is benefiting from the intervention.
Non-responders can be spared potential toxicity that is not offset
by benefit.
[0088] In some exemplary embodiments, a histogram display of all of
the voxels within the defined boundaries of a disease process
within a specific anatomical area may be provided. For example, an
area of traumatic brain injury in the right frontal lobe may
contain 500,000 voxels. 100,000 of these voxels may be located
within plus and minus 1 millimeter of the transition zone from
affected tissue to normal tissue, the apparent visual boundary of
the disease process. The 100,000 voxels in the transition zone will
be expected to display a wide range of metabolic uptake values. The
voxels which are more centrally located will also be expected to
exhibit a wide range of metabolic uptake values. All of the voxels
within the visual boundary of the disease process are likely to
change metabolic uptake over time as the cells improve or die.
[0089] In an exemplary embodiment, a software product may be used
for detecting diffuse axonal injuries in a brain. The software
product may be any suitable computer-readable storage media that
contains instructions, that when executed, cause one or more
computers to perform the steps: accessing a digital brain scan of a
subject's entire brain; quantitatively identifying voxels having
inactivity of, e.g., -1.65 standard deviations or less from that of
the entire brain, or activity of, e.g. +1.65 standard deviations or
more; establishing a threshold value for localizing one or more
clusters of said identified voxels; applying a clustering algorithm
to localize said one or more clusters; generating a revised digital
brain scan image with visually perceptible indicia associated with
said one or more clusters localized; and displaying said revised
digital brain scan image on an output device.
[0090] FIG. 1 shows, according to an exemplary embodiment, a method
for detecting diffuse axonal injuries. At step 105, a volumetric
digital brain scan image of a subject's entire brain may be
obtained or accessed. At step 110, voxels may be quantitatively
identified which are, e.g., -1.5 standard deviations or less from
that of the entire brain which may indicate inactivity and/or are,
e.g., +1.5 standard deviations or more from the entire brain which
may indicate compensatory activity. At step 115, one or more
threshold values may be established for localizing one or more
clusters of said identified voxels. At step 120, a clustering
algorithm may be applied to localize said one or more clusters
using the one or more threshold values. For example, the clustering
algorithm may be applied to the identified voxels above or below
the 1.5 standard deviations from the brain. At step 125, one or
more indicias may be generated with respect to the one or more sets
of identified clusters. Using the generated indicias, at step 130,
a revised digital brain scan image with visually perceptible
indicia associated may be generated. At step 135, a revised digital
brain scan image may be displayed on an output device. At step 140,
based on the generated image, alternative pathways to and from the
areas of identified areas of compensatory activity may be
stimulated.
[0091] In some exemplary embodiments, the method as illustrated in
FIG. 1 may further comprise the steps of: accessing a digital brain
scan image of a subject's entire brain; quantitatively identifying
voxels having inactivity of at a plurality of standard deviations
less than, e.g., -1.0; establishing a threshold value for
localizing one or more clusters of said identified voxels; applying
a clustering algorithm to localize said one or more clusters;
sequentially generating a plurality of revised digital brain scan
images with visually perceptible indicia associated with said one
or more clusters localized at each standard deviation value; and
displaying said revised digital brain scan image on an output
device.
[0092] According to an exemplary embodiment, diffuse axonal
injuries may be detected in a brain by implementing a method
comprising the steps of: accessing a digital brain scan image of a
subject's entire brain; quantitatively identifying voxels having
compensatory activity of at a plurality of standard deviations
greater than, e.g., 1.0; establishing a threshold value for
localizing one or more clusters of said identified voxels; applying
a clustering algorithm to localize said one or more clusters;
sequentially generating a plurality of revised digital brain scan
images with visually perceptible indicia associated with said one
or more clusters localized at each standard deviation value; and
displaying said revised digital brain scan images on an output
device. In some exemplary embodiments, the revised digital brain
scan images may be presented in three-dimensional contours.
[0093] According to another exemplary embodiment, FIG. 2 shows an
imaging system, generally designated by number 5. The imaging
system 5 may include one or more imaging devices designated by
number 10, that may be operatively connected to one or more
computing devices generally designated by number 20. The imaging
device 10 may generate an quantitative three-dimensional image of
an organ, such as, for example, a brain, heart, lung, kidney,
liver, pancreas, bladder, salivary glands, esophagus, stomach,
gallbladder, intestines, colon, rectum, thyroid, parathyroid,
adrenal gland, ureter, bladder, urethra, tonsils, adenoids, thymus,
spleen, ovary, fallopian tube, uterus, vagina, mammary gland,
testes, vas deferens, seminal vesicle, prostate, penis, pharynx,
larynx, trachea, bronchi and lung, to name a few. In exemplary
embodiments, the image of the organ may be generated using positron
emission tomography (PET), computed tomography (CT) X-ray scan,
functional magnetic resonance imaging (fMRI), magnetic source
imaging or optical imaging, or combinations thereof. For example,
the three-dimensional imaging maybe obtained using a PET scan in
connection with a CT X-ray scan.
[0094] In exemplary embodiments, the imaging system 10, and by
extension, any one of its components, may be operatively connected
to one or more computer networks 50, such as, for example, the
Internet, or any other suitable network, via, by way of example, a
set of routers and/or networking switches. The imaging system 10
may be connected to an imaging analysis system 30 or any one of its
components. For example, the imaging analysis system 30 may include
one or more analysis computers, designated by number 40. The
analysis computers 40 may include one or more processors, computer
readable storage media, and memory units. The one or more
processors may read and execute software embodied as instructions
stored on the computer readable storage media, according to
exemplary embodiments herein.
[0095] In exemplary embodiments, the analysis system 30 may be used
to assess the activity of organ. Referring to FIG. 2, at step 205,
the analysis computers 40 may obtain a image scan of an organ. The
organ may be from an animal, including a human. The image scan data
generated by the imaging device 10 may be sent directly or
indirectly to the analysis system 30.
[0096] The obtained image scan may be a quantitative
three-dimensional image of the organ. This image or image scan may
include voxels or voxel data, wherein each voxel contains
information about the activity of a portion of the imaged organ. In
one exemplary embodiment, the imaging device 10 may generate a PET
scan of the organ in a Digital Imaging and Communications in
Medicine (DICOM) format. In this regard, the image or scan data may
contain at least four elements as follows: an x coordinate, a y
coordinate, a z coordinate, and a value measured at the x, y, and z
coordinates. Since DICOM is a standard covering both data formats
and protocols for communications, the image scan/data may be
obtained several ways. See DICOM at:
http://en.wikipedia.org/wiki/DICOM.
[0097] At step 210, the obtained image scan may be used by the
analysis computers 40 to calculate activity using the voxels. For
example, the mean of the activity represented by the voxels may be
calculated. In some exemplary embodiments, voxels representing
extreme upper and lower values may be excluded. Voxels representing
values at the upper and/or lower 1%, 5%, 10%, or any other
appropriate voxels representing values in an extreme range may be
excluded.
[0098] At step 215, the analysis computers 40 may further, based on
the calculated mean, calculate one or more voxel threshold values.
In an exemplary embodiment, the analysis computers 40 may calculate
a standard deviation using the calculated mean. For example, the
standard deviation may be calculated in 0.1 standard deviation (SD)
units between 4.0 SD units below the mean to 4.0 SD units above the
mean. In some exemplary embodiments, the standard deviation may be
calculated in 0.01 standard deviation (SD) units. In some
embodiments, the standard deviation may be calculated in units
between 3.0 SD units below the mean to 3.0 SD units above the
mean.
[0099] At step 220, the analysis computers may determine voxels are
outside or beyond the calculated threshold values. The analysis
computers 40 may determine voxels which are a specified standard
deviation above or below the mean, as such voxels may respectively
indicate areas of the organ with increased or decreased activity.
For example, voxels representing activity 1.65 SD units above or
below the mean may indicate, respectively, increased or decreased
activity. In some exemplary embodiments, other standard deviation
unit values may be used to indicate activity/inactivity. For
example, voxels representing activity anywhere from 1.00-4.00 SD
units above or below the mean may indicate increased or decreased
activity.
[0100] At step, 225, the calculated data regarding the voxels may
be stored, such as in databases 35, for future use. At step 230, a
representation of the organ, based on the calculations performed by
the analysis computers 40, may be outputted to an output device to
show the areas of the organ with increased and/or decreased
activity. For example, the analysis computers 40 may be connected
to a display device to display the representation of the organ. In
some exemplary embodiments, the displayed representation may be a
histogram.
[0101] In some exemplary embodiments, software such as the MIMneuro
may be used at least by the analysis computers 40 to perform one or
more of the calculations and generate a representative output based
on such calculations, such as for example a histogram.
[0102] In some exemplary embodiments, the representation of the
output representation of the organ showing increased/decreased
activity may be sent from the analysis computers 40 to the imaging
system 10. For example, the output representation may be displayed
a on a display operatively connected to the computer 20. The
imaging device 10 and/or computer may be located any suitable
locations, such as, for example, a doctor's office, a hospital, a
clinic, to name a few.
[0103] The output representation and associated calculations
related to the organ may be used by a physician. In an exemplary
embodiment, a physician may observe a representation, such as
histogram of the organ scan. For example, the physician may select
a range of histogram bars representing voxel values that are a
certain amount of standard deviations away from the mean for the
entire organ scan, such as for example, 1.5 SD units, 1.65 units,
to an name a few. In this regard, such a selection may be
symmetrical about the mean. For instance, if a large count of
voxels (i.e. a spike) occurs at -1.3 standard deviations, then
something less than 1.3 standard deviations will be selected as the
"normal range" both above the mean and below the mean, and
equidistant from the mean. Further, the physician may perform a
visual verification of the normal area. Further, the analysis
computers 40 or computer 20 may be used to display a visual map of
the scan data that highlights the "normal area" as a result the
physician's selection. If the selection verifies, then the mean,
median and mode may be calculated and stored for future
comparisons.
[0104] In exemplary embodiments, areas of increased or reduced
activity in the organ indicate a disease or an injury, such as, for
example, a tumor, stroke, infection, demyelinating disease,
degenerative disease, dementia, ischemia, traumatic injury, or
primary or metastatic cancer, to name a few. For example, with
respect to the brain, areas of reduced activity in the organ may
represent diffuse axonal injury.
[0105] Further processing regarding the voxels may include
rescaling the voxels and calculating an advance/decline ratio. The
voxels may be rescaled so as to eliminate any biases, with any
scaled data and/or scaling factors may be stored for future
reference. The advanced/decline ratio may also be stored for future
reference. In addition, depending on the type of organ imaged, the
voxels from one side of the imaged organ may be compared with the
corresponding voxels on the opposite side of the same organ.
Similarly, voxels from one organ on side of the body may be
compared with corresponding voxels on the corresponding organ on
the opposite side of the body.
[0106] Analyses preformed using the voxels may include determining
a ratio of a number of voxels showing increased activity to a
number of voxels showing decreased activity at a border region
between an area of disease or injury and normal tissue.
[0107] The process of accessing organ activity as illustrated in
FIG. 2 may be repeated over a period of time at certain intervals
so as to determine any changes in activity. In this regard, an
image of the organ may obtained and analyzed at a plurality of time
points. The images obtained at different time points may be used to
evaluate effectiveness of a course of treatment of a subject or to
evaluate progression of disease. The voxels within an area of
disease or injury in the organ may be analyzed at a plurality of
time points and a ratio of a number of voxels within the area
showing increased activity over time to a number of voxels within
the area showing decreased activity over time may be a measure of
whether the disease or injury is improving or not improving.
[0108] In the case of a human brain being imaged/scanned,
psychometric tests may be used in addition or in conjunction with
to assess and/evaluate the brain and its activity.
[0109] In situations where a brain is being analyzed or accessed, a
plurality of psychometric tests may also be administered with
respect to the patient over the same period of time. In any event,
after the process is repeated various things may be tracked, such
as for example, the absolute number of voxels, the advanced/decline
ratio, and the percentage of activity change in certain areas, to
name a few. FIGS. 4A-4B, shows results of various psychometric
tests that may administered over a 1 year time period.
[0110] It will be seen that the advantages set forth above, and
those made apparent from the foregoing description, are efficiently
attained and since certain changes may be made in the above
construction without departing from the scope of the invention, it
is intended that all matters contained in the foregoing description
or shown in the accompanying drawings shall be interpreted as
illustrative and not in a limiting sense. This invention will be
better understood from the Experimental Details, which follow.
However, one skilled in the art will readily appreciate that the
specific methods and results discussed are merely illustrative of
the invention as described more fully in the claims that follow
thereafter.
EXPERIMENTAL DETAILS
Case Study #1
Quantitative Evaluation Post Hyperbaric Oxygen Therapy
[0111] History:
[0112] RM, a 46 year old male suffered traumatic brain injury when
he fell on his head from a loft, a distance of 8 feet in February
1997. The patient was severely incapacitated, declared totally and
permanently disabled by Social Security and was evaluated at Mayo
Clinic Jacksonville. With remarkable persistence in a self-directed
rehabilitation program, he was able to resume gainful employment
after several years. Subsequently, the patient reported hitting his
head from a major bicycle accident and hitting his head when he
walked into an obstruction at a warehouse. Patient self-referred in
May 2011 with complaints of anxiety, depression, intermittent
dissociation, decreased ability to concentrate, and memory loss. At
the time of referral, the patient had been self-medicating with
alcohol and had stopped self-directed rehabilitation.
[0113] Care Plan:
[0114] The patient was advised to abstain from self-medicating with
alcohol. Rx 50 mg Trazadone at night. Self-directed 45 hours of 1.3
atmospheric pressure 90% oxygen.
[0115] PET Studies:
[0116] Upon referral (May 3, 2011) patient received a Quantitative
PET brain study and underwent multiple cognitive and self-reporting
psychometric testing during the following 12 month period. On Aug.
18, 2011 (75 days later) the patient received a second Quantitative
PET brain study and continued cognitive and psychometric testing.
The PET studies were analyzed using a custom neurological software
package.
[0117] Referring to FIGS. 5A and 5B, Comparative Quantitative
Imaging showed significant improvement from May 2011 to February
2012 consistent with improved Cognitive scores (Table 1).
Significant improvement is noted especially in frontal lobes.
Referring to FIG. 5A, the patient's brain is imaged showing areas
501, 502, 503, 504, and 505 with decreased activity. FIG. 5B shows
the imaged brain in February 2012, with improvement in those same
areas.
[0118] RM has had about seventy 1.3 atmosphere hyperbaric
treatments since November, 2011. Patient reports mediation 3 to 5
times a week, no drinking, and consistent vitamin B complex use
since Nov. 26, 2011. His family and economic stress level are twice
as high as compared to a year ago. RM has shown remarkable
improvement in frontal lobe PET scan hypometabolism, remarkable
improvement in Processing Speed, and significant improvement in
Neurocognitive Index.
TABLE-US-00001 TABLE 1 A. Cognitive changes over time for Case
Study #1 03- 12- 17- 21- 10- 15- 17- 25- 30- 09- 24- May Jul Jul
Jul Aug Aug Aug Aug Aug Nov Jan NC 63 68 66 73 81 87 82 93 90 77 70
index Comp 21 40 63 30 45 75 50 90 34 61 55 M Verbal 12 30 58 63 12
55 63 79 30 37 63 M Visual 45 53 66 13 81 81 37 90 45 75 45 M Psych
86 84 34 96 96 96 98 96 99 94 90 motor speed RT 42 45 70 58 93 95
86 86 93 66 32 CA 82 82 63 63 58 58 58 70 77 77 82 CF 70 81 87 90
86 90 96 96 97 78 82 Proc 5 5 13 40 18 34 27 75 53 18 4 speed Exec
68 84 86 95 88 93 98 96 97 81 81 func Total 494 572 606 621 658 764
695 871 715 664 604 B. Cognitive changes over time for Case Study
#1 (Continuation of Table 1A) 31- 04- 06- 04- 11- 21- 26- 18- 23-
02- Jan Feb Feb Mar Mar Mar Jan Apr Apr May NC 63 82 82 90 90 84 91
93 93 95 1713 index Comp 12 70 40 79 70 61 82 70 61 61 1170 M
Verbal 16 79 30 90 90 73 63 63 73 63 1142 M Visual 18 53 53 53 37
45 86 68 45 53 1142 M Psych 95 99 99 99 99 99 99 99 99 99 1955
motor speed RT 58 70 79 73 81 68 82 86 75 75 1513 CA 77 70 82 82 82
70 77 70 82 82 1544 CF 66 79 87 94 93 81 95 96 96 98 1838 Proc 25
53 77 53 63 92 75 97 96 99 1022 speed Exec 66 79 86 95 93 79 96 96
96 98 1851 func Total 496 734 715 808 798 752 846 838 816 823 NC
index--Neuro-cognitive index, Comp M--Composite memory, Verbal
M--Verbal memory, Visual M--Visual Memory, Psych motor
speed--Psycho-motor speed, RT--Reaction time, CA--Complex
attention, C--Cognitive flexibility, Proc speed--Processing speed,
Exec func--Executive function
Case Study #2
NFL Player
[0119] Clinical Diagnosis:
[0120] Traumatic brain injury with persistent symptoms: severe
headaches, memory loss requiring constant notations in a diary,
difficulties with anger and rage, difficulty sleeping,
sleepwalking, talking in his sleep, "terrible" "horrible"
short-term memory, and perceptions of space closing in on him,
especially in crowds.
[0121] He experiences significant visual impairment, as well as
severe dizziness if he bends over after exercise. He finds a 45
minute trip on the interstate very difficult. He is chronically
frustrated and upset. He is in marital counseling. He has just
experienced the third anniversary of his second marriage. He has
children by his first marriage ages 24 and 18. He divorced in 2008.
He is currently unemployed; applying for social security
disability.
[0122] Summary of Brain Surface Visual Findings:
[0123] Cortical confluent hypometabolic areas are seen at the base
of the brain centering on the brainstem, pons, cerebellar vermis
and cerebellar peduncles. The inferior aspects of cortical and
subcortical regions of both temporal lobes are hypometabolic; the
medial aspects of both cerebellar hemispheres are involved; there
is also significant spotty cortical and subcortical hypometabolism
of the inferior aspects of the frontal lobes. Midline images of the
brain demonstrate severe extensive hypometabolism of the basal
ganglia and midbrain.
[0124] Right Frontal Lobe:
[0125] There is a severely hypometabolic right frontal lobe area
measuring 4.9 cm in height by 1.4 cm in width by 1.25 cm in
anterior-posterior dimension involving most of the right superior
frontal gyms. There is a large area of hypometabolism involving the
right inferior frontal gyms pars triangularis measuring 2.5 cm in
height by 1.4 cm in width by 1.9 cm in anterior-posterior
dimension. The right frontal gyms is hypometabolic; right superior
frontal gyrusis hypometabolic; right middle frontal gyms is
hypometabolic; right orbitofrontal region including the medial
orbital gyms is hypometabolic. Right supplementary motor area is
extensively hypometabolic. Right precentral gyms contains a
hypometabolic area measuring 2 cm in height by 1.8 cm in width. The
right superiormedial frontal gyms is severely hypometabolic
measuring 2.8 cm in length by1.5 cm in width.
[0126] Left Frontal Lobe:
[0127] There is a mirror image hypometabolic area measuring 2.3 cm
in height by 0.7 cm in width involving much of the left superior
frontal gyms. Hypometabolism is extensive in the left orbitofrontal
region including the medial orbital gyms. The left anteriororbital
gyms is hypometabolic. The right inferior medial frontal gyms is
hypometabolic; left superior frontal gyms measuring 0.7 cm diameter
is severely hypometabolic, left middle frontal gyms is
hypometabolic. Left supplementary motor area is extensively
hypometabolic. Left middle frontal gyms is hypometabolic. Left
superior frontal gyms is hypometabolic; left precentral gyms is
hypometabolic; left superior frontal gyms is hypometabolic. The
left superior medial frontal gyms is severely hypometabolic
measuring 2 cm in anterior-posterior dimension and about 1.5 cm in
width.
[0128] Insula:
[0129] There is focal hypometabolism within the right insula.
[0130] Right Temporal Lobe:
[0131] Hypometabolism of the inferior aspects of the right temporal
lobe extending into the medial area. The right fusiform gyms is
extensively hypometabolic; right hippocampus is extensively
hypometabolic measuring 2.9 cm in height by 1.3 cm in width by 4.4
cm in oblique anterior-posterior length. Right temporal pole is
hypometabolic.
[0132] Left Temporal Lobe:
[0133] Hypometabolism of the inferior aspects of the left temporal
lobe extending into the medial area as is the left fusiform gyms.
The left temporal pole is hypometabolic; the left fusiform gyms is
involved. The left hippocampus is significantly hypometabolic.
[0134] Right Parietal Lobe:
[0135] The right rolandic operculum is hypometabolic; The right
super marginal gyms is hypometabolic. The right precentral gyms is
hypometabolic. The right posterior cingulate gyms is hypometabolic.
The right superior parietal lobule is extensively hypometabolic.
The right precentral gyms is hypometabolic. The right superior
parietal lobule is extensively and severely hypometabolic. The
right angular gyms is hypometabolic as is the right supra-marginal
gyms.
[0136] Left Parietal Lobe:
[0137] The left rolandic operculum is hypometabolic. The left super
marginal gyms is hypometabolic; the left precentral gyms is
hypometabolic; the left postcentral gyms is hypometabolic; left
superiorparietal lobule is hypometabolic; the left pre-post central
gyms is hypometabolic; the left superior parietal lobule is very
extensively and severely hypometabolic. Left supra marginal gyms is
hypometabolic. Left angular gyms is hypometabolic.
[0138] Basal Ganglia:
[0139] The putamen is hypometabolic bilaterally. The globis
pallidus bilaterally is extensively hypometabolic.
[0140] Thalamus:
[0141] The right thalamus is severely hypometabolic measuring about
3 cm in height by 2.1 cm in anterior-posterior dimension. Left
thalamus is severely hypometabolic measuring 4.2 cm in height by
2.2 cm in width.
[0142] Right Occipital Lobe:
[0143] The right superior occipital gyms shows extensive
hypometabolism. There is definite involvement of the right primary
visual cortex. The right lingual gyms inferior to the right primary
visual cortex is also severely hypometabolic.
[0144] Left Occipital Lobe:
[0145] There is definite involvement of the left primary visual
cortex measuring 2.3 cm in height by 1.3 cm in width, by 2.6 cm in
anterior-posterior dimension. There is very extensive involvement
of the left primary visual cortex. The left superior occipital gyms
has extensive hypometabolism. Adjacent structures in the left
occipital lobe are also hypometabolic. The left lingual gyms is
hypometabolic and the right superior occipital gyms is
hypometabolic; the right fusiform gyms is hypometabolic. The left
fusiform gyms and left inferior occipital gyms are focally
hypometabolic
[0146] Cerebellum:
[0147] There is extensive hypometabolism involving the right
inferior and superior cerebellar peduncles. There is moderately
extensive hypometabolism of the left inferior and superior
cerebellar peduncles. The midline cerebellar vermis is extensively
hypometabolic measuring 2.4 cm in width by 1.14 cm
anterior-posterior.
[0148] Quantitative Findings:
[0149] Areas of the brain where the hypometabolism is so severe and
extensive that the average metabolic rate of the entire structure
is statistically depressed.
TABLE-US-00002 TABLE 2 Areas of extensive hypometabolism in Case
Study #2. Structure Midline Left Right base of po -2.4 SD globis
pallidus -2.2 SD -2.2 SD superior cerebellar -0.9 SD -2.1 SD
peduncle middle cerebellar -1.0 SD -1.5 SD peduncle inferior
cerebellar -0.7 SD -1.8 SD peduncle brainstem -1.4 SD thalamus -1.3
SD -1.4 SD primary visual cortex -1.3 SD -1.2 SD lingual gyrus -1.0
SD -1.2 SD amygdala -1.2 SD -0.6 SD
Example
[0150] -2 SD means 97.5% of people function better.
TABLE-US-00003 TABLE 3 Percentages of regions of brain showing
hypometabolism. Max Min Volume % Contour (z-score) (z-score) (ml)
Volume WHOLE BRAIN 4.21 -4.91 2417.8 WHOLE BRAIN HYPO -1.65 -4.91
123.9 5.1% Frontal Lobe 4.21 -4.91 576.9 Frontal Lobe Hypo -1.65
-4.91 32.1 5.6% Occipital Lobe 3.66 -3.94 225.7 Occipital Lobe Hypo
-1.65 -3.94 15.3 6.8% Parietal Lobe 3.71 -4.77 341.8 Parietal Lobe
Hypo -1.65 -4.77 23.7 6.9% Temporal Lobe 3.66 3.94 307.3 Temporal
Lobe Hypo -1.65 -3.94 9.8 3.2% Hypo: hypometabolism.
[0151] Impressions:
[0152] This patient demonstrates extensive severe traumatic brain
injury in both the right and left sides of his brain. Very severe
memory impairment is directly traceable to hypometabolism in both
hippocampi, and bilaterally in the thalamus. Visual difficulties
are directly traceable to bilateral hypometabolism in the primary
visual cortex. Difficulties with emotional self-regulation are
directly correlated with hypometabolism in both amygdala, as well
as extensive areas of hypometabolism in the frontal cortex
bilaterally.
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