U.S. patent application number 13/045966 was filed with the patent office on 2015-07-02 for visceral fat measurement.
The applicant listed for this patent is Thomas L. Kelly, Kevin E. Wilson. Invention is credited to Thomas L. Kelly, Kevin E. Wilson.
Application Number | 20150182180 13/045966 |
Document ID | / |
Family ID | 44656544 |
Filed Date | 2015-07-02 |
United States Patent
Application |
20150182180 |
Kind Code |
A9 |
Kelly; Thomas L. ; et
al. |
July 2, 2015 |
VISCERAL FAT MEASUREMENT
Abstract
Dual-energy absorptiometry is used to estimate visceral fat
metrics and display results, preferably as related to normative
data. The process involves deriving x-ray measurements for
respective pixel positions related to a two-dimensional projection
image of a body slice containing visceral fat as well as
subcutaneous fat, at least some of the measurements being
dual-energy x-ray measurements, processing the measurements to
derive estimates of metrics related to the visceral fat in the
slice, and using the resulting estimates. Processing the
measurements includes an algorithm which places boundaries of
regions, e.g., a large "abdominal" region and a smaller "abdominal
cavity" region. Two boundaries of the "abdominal cavity" region are
placed at positions associated with the left and right innermost
extent of the abdominal muscle wall by identifying inflection of %
Fat values. The regions are combined in an equation that is highly
correlated with VAT measured by quantitative computed tomography in
order to estimate VAT.
Inventors: |
Kelly; Thomas L.;
(Groveland, MA) ; Wilson; Kevin E.; (Acton,
MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Kelly; Thomas L.
Wilson; Kevin E. |
Groveland
Acton |
MA
MA |
US
US |
|
|
Prior
Publication: |
|
Document Identifier |
Publication Date |
|
US 20110235886 A1 |
September 29, 2011 |
|
|
Family ID: |
44656544 |
Appl. No.: |
13/045966 |
Filed: |
March 11, 2011 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12730051 |
Mar 23, 2010 |
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13045966 |
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10958107 |
Oct 4, 2004 |
7725153 |
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12730051 |
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Current U.S.
Class: |
378/62 ;
382/132 |
Current CPC
Class: |
G06K 9/46 20130101; G06T
2207/10116 20130101; A61B 6/5294 20130101; G01N 2223/419 20130101;
G16H 50/30 20180101; A61B 6/50 20130101; G06T 7/11 20170101; A61B
6/461 20130101; A61B 6/032 20130101; G01N 23/046 20130101; A61B
5/4872 20130101; A61B 6/482 20130101; A61B 6/5217 20130101; G06T
7/0012 20130101; G01N 2223/612 20130101; G06K 2009/4666
20130101 |
International
Class: |
G06K 9/00 20060101
G06K009/00; G01N 23/04 20060101 G01N023/04 |
Claims
1. A method comprising: acquiring x-ray measurements for respective
pixel positions related to a two-dimensional projection image of a
portion of a subject's abdomen, wherein at least some of the
measurements are dual-energy x-ray measurements; placing a
plurality of regions of the image; computer processing to combine
the plurality of regions to provide an estimate of visceral fat;
and providing and displaying selected results related to said
estimate of visceral.
2. The method of claim 1 including combining the plurality of
regions in a linear equation using constants that provide
correlation between DXA VAT and VAT measured by computed
tomography.
3. The method of claim 1 including combining the plurality of
regions using polynomial expansion.
4. The method of claim 1 including placing a first region of the
image which extends from a first side of the abdomen to a second
side of the abdomen, and placing a second region which extends
across an inner abdominal cavity from the first side to the second
side between innermost extents of an abdominal muscle wall.
5. The method of claim 1 including placing a first region of the
image which extends from a first side of the abdomen to a second
side of the abdomen, placing a second region which extends across
an inner abdominal cavity from the first side to the second side
between innermost extents of an abdominal muscle wall but exclusive
of a third region which is placed where bone is present and percent
fat cannot be directly measured.
6. The method of claim 1 including computer processing at least
some of the x-ray measurements for placing at least one region of
the image.
7. The method of claim 4 including using an anatomical landmark and
a preselected region of interest line for placing the first region
of the image.
8. The method of claim 4 including computer processing at least
some of the x-ray measurements for placing the second region of the
image.
9. The method of claim 8 including identifying a left and a right
innermost extent of abdominal muscle wall by identifying inflection
of adipose tissue values for placing the second region of the
image.
10. The method of claim 4 including combining the first region and
the second region in a linear equation that is correlated with VAT
measured by quantitative computed tomography for processing the
first and second regions to provide an estimate of visceral
fat.
11. The method of claim 10 including calculating visceral fat as:
J*second region Mass-K*(first region Mass-second region
Mass)+b.
12. The method of claim 11 including selecting constants J and K
that provide correlation between DXA VAT and VAT measured by
computed tomography, and wherein b is an intercept term.
13. The method of claim 11 including selecting a value for at least
one of J, K and b for the subject.
14. The method of claim 13 including selecting a value for at least
one of J, K and b based on at least one of age, gender, ethnicity,
weight, height, body mass index, waist circumference, and other
anthropomorphic variables of the subject.
15. Apparatus comprising: a data acquisition unit including a
scanner that acquires x-ray measurements for respective pixel
positions related to a two-dimensional projection image of a
portion of a subject's abdomen, wherein at least some of the
measurements are dual-energy x-ray measurements; a memory in which
is placed a plurality of regions of the image; a processing unit
that computer-processes the regions to provide an estimate of
visceral fat; and a display unit that provides and displays
selected results related to visceral fat of the subject.
16. The apparatus of claim 15 wherein the processing unit combines
the plurality of regions in a linear equation using constants that
provide correlation between DXA VAT and VAT measured by computed
tomography.
17. The apparatus of claim 15 wherein the processing unit combines
the plurality of regions using polynomial expansion.
18. The apparatus of claim 15 wherein a first region and a second
region are stored in memory, the first region extending from a
first side of the abdomen to a second side of the abdomen, and the
second region extending across an inner abdominal cavity wall from
the first side to the second side between innermost extents of an
abdominal muscle wall.
19. The apparatus of claim 15 wherein a first region, a second
region, and a third region are stored in memory, the first region
extending from a first side of the abdomen to a second side of the
abdomen, the second region extending across an inner abdominal
cavity from the first side to the second side between innermost
extents of an abdominal muscle wall but exclusive of a third region
which is placed where bone is present and percent fat cannot be
directly measured.
20. The apparatus of claim 18 wherein the processing unit places
the first region of the image by computer-processing at least some
of the x-ray measurements.
21. The apparatus of claim 20 wherein the processing unit uses an
anatomical landmark and a preselected region of interest line to
place the first region of the image.
22. The apparatus of claim 18 wherein the processing unit places
the second region of the image by computer-processing at least some
of the x-ray measurements.
23. The apparatus of claim 22 wherein the processing unit uses an
algorithm to identify a left and a right innermost extent of
abdominal muscle wall by identifying inflection of adipose tissue
values for placing the second region of the image.
24. The apparatus of claim 18 wherein the processing unit combines
the first region and the second region using a linear equation
which is correlated with VAT measured by quantitative computed
tomography.
25. The apparatus of claim 24 wherein the processing unit
calculates visceral fat as: J*second region Mass-K*(first region
Mass-second region Mass)+b.
26. The apparatus of claim 25 wherein constants J and K are
selected based on correlation between DXA VAT and VAT measured by
computed tomography, and wherein b is an intercept term.
27. The apparatus of claim 25 wherein at least one of J, K and b
are selected for the subject.
28. The apparatus of claim 27 wherein at least one of J, K and b
are selected based on at least one of age, gender, ethnicity,
weight, height, body mass index, waist circumference, and other
anthropomorphic variables of the subject.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation-in-part of U.S. patent
application Ser. No. 12/730,051, titled ESTIMATING VISCERAL FAT BY
DUAL-ENERGY X-RAY ABSORPTIOMETRY, filed Mar. 23, 2010, which is
incorporated by reference.
BACKGROUND OF THE INVENTION
[0002] Obesity can be generally predictive of morbidities such as
coronary artery disease and diabetes, and the anatomical
distribution of adipose tissue (fat) can be a strong independent
predictor of these and other medical conditions and outcomes. For
example, overweight subjects with a larger proportion of fat stored
as visceral adipose tissue (VAT) are believed to be at a higher
risk than similarly overweight individuals with a larger percentage
of fat stored as subcutaneous adipose tissue (SAT). Studies have
shown that VAT levels are a predictor of cardiovascular risk
factors, e.g. HDL, LDL, triglyceride levels, and hypertension.
Because of the predictive and other values of visceral fat as
distinguished from general obesity and subcutaneous fat, it is
believed desirable to find a way to efficiently and effectively
measure or estimate VAT.
[0003] It is known in the art to measure or estimate VAT by
differentiating it from SAT in abdominal cross-sections or slices
using computerized tomography (CT) and magnetic resonance imaging
(MRI). Measurements can be made at the level of the umbilicus,
where SAT and VAT volumes typically are identified by an image
thresholding algorithm. However, the relatively high cost of both
examinations and the high radiation dosage of CT can discourage the
use of these techniques as a screening tool for VAT levels.
Further, the thresholding method lacks specificity because areas or
volumes above the threshold can have different amounts of % fat,
and areas or volumes below the threshold may not be fat-free. Thus,
systematic errors can be introduced by assumptions of % fat in
areas or volumes above or below the threshold.
[0004] Dual-energy x-ray absorptiometry (DXA) exams are widely
available, rapid, relatively low dose, and much less costly than CT
and MRI exams. Further, DXA is capable of measuring both global and
regional fat mass because, for tissue paths that are projected as
pixels in the x-ray image, a given dual-energy x-ray measurements
pertains to a unique combination of fat and lean mass. However, the
ability of DXA to distinguish between VAT and SAT has been limited
because DXA is a two-dimensional projection technique.
SUMMARY OF THE INVENTION
[0005] In accordance with one non-limiting aspect of the invention
a method comprises acquiring x-ray measurements for respective
pixel positions related to a two-dimensional projection image of a
portion of a subject's abdomen, wherein at least some of the
measurements are dual-energy x-ray measurements; placing a
plurality of regions of the image; computer processing to combine
the plurality of regions to provide an estimate of visceral fat;
and providing and displaying selected results related to said
estimate of visceral.
[0006] In accordance with another non-limiting aspect of the
invention a method comprises: acquiring x-ray measurements for
respective pixel positions related to a two-dimensional projection
image of a portion of a subject's abdomen, wherein at least some of
the measurements are dual-energy x-ray measurements; placing a
first region of the image which extends from a first side of the
abdomen to a second side of the abdomen; placing a second region
which extends across an inner abdominal cavity wall from the first
side to the second side between innermost extents of an abdominal
muscle wall; computer processing the first and second regions to
provide an estimate of visceral fat; and providing and displaying
selected results related to said estimate of visceral fat.
[0007] In accordance with another non-limiting aspect of the
invention an apparatus comprises a data acquisition unit including
a scanner that acquires x-ray measurements for respective pixel
positions related to a two-dimensional projection image of a
portion of a subject's abdomen, wherein at least some of the
measurements are dual-energy x-ray measurements; a memory in which
is placed a plurality of regions of the image; a processing unit
that computer-processes the regions to provide an estimate of
visceral fat; and a display unit that provides and displays
selected results related to visceral fat of the subject.
[0008] In accordance with another non-limiting aspect of the
invention an apparatus comprises: a data acquisition unit including
a scanner that acquires x-ray measurements for respective pixel
positions related to a two-dimensional projection image of a
portion of a subject's abdomen, wherein at least some of the
measurements are dual-energy x-ray measurements; a memory in which
is placed a first region of the image which extends from a first
side of the abdomen to a second side of the abdomen, and a second
region which extends across an inner abdominal cavity wall from the
first side to the second side between innermost extents of an
abdominal muscle wall; a processing unit that computer-processes
the first and second regions to provide an estimate of visceral
fat; and a display unit that provides and displays selected results
related to visceral fat of the subject.
[0009] In various non-limiting alternatives one or more functions
can be automated or partially automated with computer processing.
For example, the first region can be automatically placed by a
software tool using various anatomical landmarks and the position
of an upper region of interest line delineating the pelvis for
reference. Further, the software tool may automatically place the
second region based on % Fat inflection which is indicative of the
innermost extent of the abdominal muscle wall. Further,
measurements of total adipose tissue in a fixed thickness region
across the entire width of the subject, e.g., just above the pelvis
at the level of the 4.sup.th lumbar vertebrae, can be combined with
a measurement of the adipose tissue in the same thickness region of
the abdominal cavity plus whatever subcutaneous fat is present
above and below the cavity region using a linear equation that is
correlated with VAT measured by quantitative computed tomography in
order to estimate VAT.
BRIEF DESCRIPTION OF THE FIGURES
[0010] FIG. 1 is a simplified and schematic cross-sectional
elevation illustrating a fan-shaped distribution of x-rays in a DXA
system in which the visceral fat analysis described herein can be
practiced.
[0011] FIG. 2a illustrates a PA projection image of a patient taken
with a DXA system, and FIG. 2b is an enlarged view of the portion
of the image corresponding to the body slice indicated by a broken
line rectangle in FIG. 2a.
[0012] FIG. 3 illustrates a cross-sectional image of a body
slice.
[0013] FIG. 4 illustrates placement of a large "abdominal" region
and a smaller "abdominal cavity" region.
[0014] FIG. 5 illustrates a % fat profile and inflection points
used for placement of the abdominal cavity region.
[0015] FIG. 6 is a block diagram of a DXA system useful for
estimating visceral adipose tissue.
[0016] FIG. 7 is a cross-sectional image of a body slice which
illustrates use of more than two regions.
DETAILED DESCRIPTION
[0017] Referring to FIG. 1, a DXA system 10 includes a patient
table 12 having a support surface 14 that can be considered
horizontal and planar in this simplified explanation and
illustration which is not necessarily accurate in scale or
geometry, and which is used here solely to illustrate and explain
certain principles of operation. A human subject 26 is supine on
surface 14. The length of the patient is along a horizontal
longitudinal axis defined as the y-axis and the patient's arms are
spaced from each other along the x-axis. A C-arm 16 has portions
16a and 16b extending below and above table 10, respectively, and
is mounted in suitable structure (not shown expressly) for moving
at least parallel to the y-axis along the length of patient 26.
Lower portion 16a of the C-arm carries an x-ray source 20 that can
emit x-rays limited by an aperture 22 into a fan-shaped
distribution 24 conforming to a plane perpendicular to the y-axis.
The energy range of the x-rays can be relatively wide, to allow for
the known DXA dual-energy x-ray measurements, or can be filtered or
generated in a narrower range to allow for single energy x-ray
measurements. The x-ray distribution can be continuous within the
angle thereof or can be made up, or considered to be made up, of
individual narrower beams. The x-ray distribution 24 can encompass
the entire width of the patient as illustrated, or it can have a
narrower angle so the entire patient can be covered only by several
passes along the y-axis and the x-ray measurements from the several
passes can be combined as is known in the art to simulate the use
of a wider fan beam, as typical in current commercial DXA systems.
Alternatively, a single, pencil-like beam of x-rays can be used to
scan selected regions of the patient's body, e.g. in a raster
pattern. The x-rays impinge on x-ray detector 28, which can
comprise one or more linear arrays of individual x-ray elements 30,
each linear array extending in the x-direction, or a continuous
detector where measurements for different positions along the
detector can be defined in some manner known in the art, or can be
another form of detector of x-rays. C-arm 16 can move at least
along the y-axis, or can be maintained at any desired position
along that axis. For any one position, or any one unit of
incremental travel in the y-direction of arm 16, detector 28 can
produce one or several lines of raw x-ray data. Each line can
correspond to a row of pixels in a resulting image, which row
extends in a direction corresponding to the x-direction. Each line
corresponds to a particular position, or range of positions, of the
C-arm in its movement along the y-axis and/or a particular linear
detector, and comprises a number of individual measurements, each
for a respective detector element position in the line, i.e.,
represents attenuation that the x-rays have suffered in traveling
from source 20 to a respective detector element position over a
specified time interval. A DXA system takes a higher x-ray energy
measurement H and a lower x-ray energy measurement L from each
detector element position, and carries out initial processing known
in the art to derive, from the raw x-ray data, a set of pixel
values for a projection image. Each pixel value comprises a high
energy value H and a low energy value L. This can be achieved by
rapidly alternating the energy level of the x-rays from source 20
between a higher and a lower range of x-ray energies, for example
by rapidly rotating or otherwise moving a suitable filter in or out
of the x-rays before they reach patient 26, or by controlling the
x-ray tube output, and/or by using an x-ray detector 28 that can
discriminate between energy ranges to produce H and L measurements
for each pixel position, e.g. by having a low energy and a high
energy detector element side-by-side or on top of each other for
respective positions in the detector array. The H and L x-ray
measurements for the respective pixel positions are
computer-processed as known in the art to derive estimates of
various parameters, including, if desired, body composition (total
mass, fat mass, and lean mass).
[0018] A PA projection image taken with the DXA system is
illustrated in FIG. 2a. FIG. 2b is an enlarged view of the
projection image of the relatively thick slice of the body
indicated by the broken line rectangle in FIG. 2a. As suggested by
FIGS. 2a and 2b, pixel values are derived from x-ray measurements
for a body slice that is along the z-x plane and has a thickness
(w) in the y-direction. For example, several hundred pixel values
in the x-direction and a several pixel values in the y-direction
are derived from the raw x-ray data. Typically but not necessarily,
the body slice thickness w along the y-direction is several mm,
e.g. 10-15 mm.
[0019] FIG. 3 illustrates an x-ray image of a section or slice
parallel to a z-x plane through the abdominal region of an obese
patient taken with a CT system. The image shows a ring 200
(non-circular) of subcutaneous adipose tissue (SAT) and regions 202
of visceral adipose tissue (VAT).
[0020] Referring to FIG. 3 and FIG. 4, in accordance with one
embodiment of the invention % VAT is estimated with a DXA system
using an empirical technique. A region of interest (ROI) is placed
on a DXA scan to delineate various anatomical regions, e.g. arms,
trunk, legs, etc. in accordance with the instructions in the User's
Guide for the Hologic DXA scanner. After the ROI has been placed on
the scan, a large "abdominal" region 302 and a smaller "abdominal
cavity" region 304, both rectangular in shape and 4 scan lines (5
cm) high, are placed on the subject's abdomen 1-2 scan lines
(1.5-2.5 cm) above the top of the pelvis region at the level of
vertebral body L4. The large "abdominal" region 302 is defined by
boundaries 306, 308, 310, 312, and extends completely across the
abdomen from one side to the other. The smaller "abdominal cavity"
region 304 is defined by boundaries 300, 301, 306, 308, centered
within the large region, and extends across the inner abdominal
cavity. The large "abdominal" region can be placed by the user
based on visual inspection of the image. However, in accordance
with an embodiment of the invention the "abdominal" region is
automatically placed by a software tool that is stored in
non-transitory computer readable memory and run by processing
hardware. For example, the software tool may place the "abdominal"
region using various anatomical landmarks and the position of the
upper ROI line delineating the pelvis for reference.
[0021] Referring to FIGS. 3 through 5, the software tool may also
automatically place the smaller "abdominal cavity" region 304
within the larger region 302. In one embodiment this is
accomplished with an algorithm which places boundaries based on %
Fat inflection. The upper and lower boundaries 306, 308 of the
"abdominal cavity" region are superimposed over the larger region
such that the upper and lower coordinates of both regions are
identical. The left and right boundaries 300, 301 of the "abdominal
cavity" region are then placed by the algorithm. In particular, the
algorithm initially operates on percent fat profile data
corresponding to a position inside the left and right boundaries
310, 312 of the large abdominal region, e.g., at the point where
the subcutaneous fat layer ends, and proceeds by operating on data
corresponding to an adjacent set of pixels moving in toward the
center the body from the left and right sides. Initially, % Fat
decreases steadily as the x-ray beam enters the abdominal muscle
band 314. Typically after one or two cm (10-20 pixels) the trend of
decreasing % Fat reverses as the DXA beam exits the abdominal
muscle wall and enters the inner visceral cavity. At this point the
% Fat values start to increase. This inflection point, which is
indicative of the innermost extent of the abdominal muscle wall, is
detected by the algorithm, e.g., by identifying that the % Fat
values of two consecutive pixels are higher than the preceding
pixel. The "abdominal cavity" region boundaries 300, 301 are set at
the inflection point.
[0022] In practice the abdominal cavity can be located easily on
one side of the body but may be difficult to find on the other. In
this case the size and location of the cavity wall that was found
can be mirrored to the other side by taking advantage of the
presence of bilateral symmetry in the DXA anterior-posterior
projection of the human body.
[0023] A linear regression technique that accounts for SAT between
the boundaries of the "abdominal cavity" region is used to estimate
VAT. The large "abdominal" region defined by boundaries 306, 308,
310, 312 provides a measurement of total adipose tissue in a 5 cm
wide region across the entire width of the subject just above the
pelvis at the level of the 4.sup.th lumbar vertebrae. The smaller
"abdominal cavity" region defined by boundaries 300, 301, 306, 308
provides a measurement of the adipose tissue in the same 5 cm wide
region of the abdominal cavity plus whatever subcutaneous fat is
present above (at region 320) and below (at region 322) the cavity
region in the two dimensional DXA projection. Constant percent fat
values at the center of the plot in FIG. 5 indicate image pixels
where bone is present and percent fat cannot be directly measured.
However, techniques for estimating percent fat values for the
region where bone is present and percent fat cannot be directly
measured are known. The measurement (Abd. Adipose Mass) of total
adipose tissue in a 5 cm wide region across the entire width of the
subject just above the pelvis at the level of the 4.sup.th lumbar
vertebrae and the measurement (Cavity Adipose Mass) of the adipose
tissue in the same 5 cm wide region of the abdominal cavity plus
whatever subcutaneous fat is present above and below the cavity
region in the two dimensional DXA projection is combined in a
linear equation that is highly correlated with VAT measured by
quantitative computed tomography in order to estimate VAT as:
DXA VAT=J*Cavity Adipose Mass-K*(Abd. Adipose Mass-Cavity Adipose
Mass)+b Eq. 1
where J and K are constants that optimize the correlation between
DXA VAT and VAT measured by computed tomography, and b is the
intercept term of the linear equation. It should be noted that the
values of J, K and b are not necessarily that same for all
subjects. For example, values of J, K and b can be dependent upon
age, gender, ethnicity, weight, height, body mass index, waist
circumference, and other anthropomorphic variables. Those skilled
in the art will understand how to determine those constants in view
of this disclosure.
[0024] The results of the processes described above can be in
various forms and can be used for a variety of purposes. For
example, displays of numerical values can be used in assessing the
health, treatment options, or treatments of a patient by a health
professional. As another example, such numerical values or
estimates derived therefrom can be used as inputs to automated
systems for similar assessment or for treatment planning. As yet
another example, parameters related to fat metrics can be displayed
and recorded or printed as a part of an otherwise typical report
including x-ray images and other DXA-produced information for a
patient.
[0025] Estimates of visceral fat derived as discussed above can be
shown in a variety of ways. They can be displayed alone, or in
combination with known or expected ranges of comparable estimates
for populations believed to be "normal" or "healthy," which ranges
can be matched to the estimates for a patient by some
characteristic such as age, sex, and/or ethnicity. The normal or
healthy ranges for such characteristics can be obtained by
retrospective analysis of already completed studies and/or from new
studies to obtain the data. A VAT metric for a patient can be
compared with a VAT metric for the same patient taken at a
different time to estimate the change and/or the rate of change,
for example to see if visceral fat parameters have improved or have
deteriorated over some period of time or in relation to some
treatment or regimen. Such changes also can be matched to expected
or known or estimated ranges to see if the change or rate of change
for a patient is statistically significant as distinguished from a
change within the precision range of the estimate. The VAT
estimates derived as discussed above, or metrics based on such
estimates, can be used in other ways as well. One non-limiting
example is to produce reports similar to those produced for BMD
(bone mineral density) in current commercial bone densitometry
(DXA) systems but for metrics of visceral fat (VAT) rather than BMD
estimates.
[0026] FIG. 6 illustrates in block diagram form a DXA system
carrying out the processes described above for estimating VAT. The
system can be one of the current DXA systems offered commercially
by the assignee programmed to carry out the disclosed processes,
using programming that a person of ordinary skill in the art can
apply to a particular commercially available DXA system without
undue experimentation, given the teachings in this patent
specification. The system includes a scanner 60, computer
processing unit 62, user interface 66, and a results presentation
unit 64. The scanner may include an x-ray source and x-ray
detector. Scanner 60 also includes appropriate other components
known in the art, such as power and control units, and operates to
generate dual energy or single energy x-ray measurements of the
selected region or slice of a patient's body. The computer
processing unit 62 includes processing hardware and non-transitory
computer readable memory for controlling scanner 60 and processing
x-ray measurements obtained thereby in accordance with the
techniques described above under corresponding programming. A
results presentation unit 64 displays, prints, stores, and/or sends
for further processing or storage, results such as in the form of
images and/or curves and/or numeric results indicative of VAT or %
VAT, or some other parameter related to visceral fat or other
parameter discussed above, including in the immediately preceding
paragraph. Units 62 and 64 communicate interactively with a user
input unit 66. The actual physical arrangement of system components
may differ from the functional illustration in FIG. 6.
[0027] The disclosure above is mainly in terms of SAT and VAT of
human patients, but it should be clear that its approach is
applicable in other fields as well, such as in analysis of other
subjects, such as live animals and carcasses. Finally, while a
currently preferred embodiment has been described in detail above,
it should be clear that a variation that may be currently known or
later developed or later made possible by advances in technology
also is within the scope of the appended claims and is contemplated
by and within the spirit of the detailed disclosure.
[0028] FIG. 7 is a cross-sectional image of a body slice which
illustrates an alternative embodiment utilizing more than two
regions. The large "abdominal" region defined by boundaries 306,
308, 310, 312 provides a measurement of total adipose tissue in a 5
cm wide region across the entire width of the subject just above
the pelvis at the level of the 4.sup.th lumbar vertebrae. A smaller
"cavity" region which includes a first portion defined by
boundaries 300, 700, 306, 308 and a second portion defined by
boundaries 702, 301, 306, 308 provides a measurement of the adipose
tissue in the same 5 cm wide region of the abdominal cavity,
exclusive of the spinal region, and plus whatever subcutaneous fat
is present above (at region 320) and below (at region 322) the
cavity region in the two dimensional DXA projection. The "spinal"
region defined by boundaries 700, 306, 702, 308 provides a
measurement of adipose tissue where bone is present and percent fat
cannot be directly measured. A generalized linear equation for
combining the measurements of adipose tissue in order to estimate
VAT with three regions can be represented as:
DXA VAT=J*Region1+K*Region2+L*Regionb 3+b, Eq. 2
where J, K and L are constants that optimize the correlation
between DXA VAT and VAT measured by computed tomography, and b is
the intercept term of the linear equation. As in the previously
described embodiment, the values of the constants (here J, K, and
L) and intercept b are not necessarily that same for all subjects.
For example, values of J, K, L and b can be dependent upon age,
gender, ethnicity, weight, height, body mass index, waist
circumference, and other anthropomorphic variables. Those skilled
in the art will understand how to determine those constants in view
of this disclosure. Furthermore, the two region and three region
embodiments are merely exemplary, and any number of regions could
be defined and utilized to estimate VAT.
[0029] In an alternative embodiment polynomial expansion is used to
estimate VAT. A generalized equation for combining the measurements
of adipose tissue using polynomial expansion in order to estimate
VAT can be represented as:
DXA VAT=J1(Region1)+J2(Region1).sup.2+J3(Region1).sup.2+ . . . Eq.
3
where Jn and constants associated with the polynomial expansion of
the other regions (eg. K.sub.n and L.sub.n) optimize the
correlation between DXA VAT and VAT measured by computed
tomography. As in the previously described embodiment, the values
of the constants are not necessarily that same for all subjects,
and can be dependent upon age, gender, ethnicity, weight, height,
body mass index, waist circumference, and other anthropomorphic
variables.
[0030] While the invention is described through the above exemplary
embodiments, it will be understood by those of ordinary skill in
the art that modification to and variation of the illustrated
embodiments may be made without departing from the inventive
concepts herein disclosed. Moreover, while the preferred
embodiments are described in connection with various illustrative
structures, one skilled in the art will recognize that the system
may be embodied using a variety of specific structures.
Accordingly, the invention should not be viewed as limited except
by the scope and spirit of the appended claims.
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