U.S. patent application number 12/505983 was filed with the patent office on 2009-11-12 for systems and methods for designing energy efficient microfluidic channel devices.
This patent application is currently assigned to DTherapeutics, LLC. Invention is credited to Ghassan S. Kassab.
Application Number | 20090281650 12/505983 |
Document ID | / |
Family ID | 39645052 |
Filed Date | 2009-11-12 |
United States Patent
Application |
20090281650 |
Kind Code |
A1 |
Kassab; Ghassan S. |
November 12, 2009 |
SYSTEMS AND METHODS FOR DESIGNING ENERGY EFFICIENT MICROFLUIDIC
CHANNEL DEVICES
Abstract
In at least one embodiment, a method for diagnosing vascular
disease is provided, the method comprising the steps of obtaining a
vessel image showing a vasculature of a vessel identifying at least
two measurements from the vasculature of the vessel, the
measurements relating to at least two parameters, calculating a
relationship between the at least two parameters from the at least
two measurements to generate one or more vasculature data points,
and comparing the one or more vasculature data points to data
relative to a model vasculature to determine the extent of vascular
disease. In an another embodiment, a method for diagnosing vascular
disease in a patient's vascular tree is provided, the method
comprising the steps of generating a model vascular tree from a
minimum energy hypothesis calculation, and comparing the patient's
vascular tree with the model vascular tree to determine the extent
of vascular disease.
Inventors: |
Kassab; Ghassan S.;
(Zionsville, IN) |
Correspondence
Address: |
ICE MILLER LLP
ONE AMERICAN SQUARE, SUITE 3100
INDIANAPOLIS
IN
46282-0200
US
|
Assignee: |
DTherapeutics, LLC
Zionsville
IN
|
Family ID: |
39645052 |
Appl. No.: |
12/505983 |
Filed: |
July 20, 2009 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12522350 |
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PCT/US2008/000762 |
Jan 22, 2008 |
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12505983 |
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60881833 |
Jan 23, 2007 |
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Current U.S.
Class: |
700/103 ;
703/1 |
Current CPC
Class: |
A61B 5/055 20130101;
A61B 5/026 20130101; A61B 6/504 20130101; A61B 5/02007 20130101;
A61B 5/7246 20130101; A61B 6/03 20130101 |
Class at
Publication: |
700/103 ;
703/1 |
International
Class: |
G06F 17/50 20060101
G06F017/50 |
Claims
1. A method to design an energy efficient microfluidic channel
device, comprising the steps of: identifying at least two
parameters relating to a desired microfluidic channel device;
calculating a relationship between the at least two parameters to
generate at least two measurements; and utilizing the at least two
measurements to design the microfluidic channel device.
2. The method of claim 1, wherein the at least two parameters
comprise parameters relating to volume and length of a desired
microfluidic channel device.
3. The method of claim 3, wherein the step of calculating a
relationship between the at least two parameters is performed using
a volume-length relation.
4. The method of claim 3, wherein the step of calculating a
relationship between the at least two parameters is performed using
a resistance-length and volume relation.
5. The method of claim 1, wherein the at least two parameters
comprise parameters relating to diameter and length.
6. The method of claim 5, wherein the step of calculating a
relationship between the at least two parameters is performed using
a diameter-length relation.
7. The method of claim 1, wherein the at least two parameters
comprise parameters relating to flow rate and diameter.
8. The method of claim 7, wherein the step of calculating a
relationship between the at least two parameters is performed using
a flow rate-diameter relation.
9. The method of claim 1, wherein the at least two parameters
comprise parameters relating to resistance, length, and volume.
10. The method of claim 9, wherein the step of calculating a
relationship between the at least two parameters is performed using
a resistance-length and volume relation.
11. The method of claim 1, wherein the at least two parameters
comprise parameters relating to flow rate and length.
12. The method of claim 11 wherein the step of calculating a
relationship between the at least two parameters is performed using
a flow rate-length relation.
13. The method of claim 1, further comprising the step of utilizing
the at least two measurements to fabricate the microfluidic channel
device.
14. A method to design an energy efficient microfluidic channel
device, comprising the steps of: identifying at least two
parameters relating to a desired microfluidic channel device;
calculating a relationship between the at least two parameters to
generate at least two measurements, wherein at least two of the at
least two parameters are chosen from parameters relating to volume,
length, resistance, diameter, and flow rate; utilizing the at least
two measurements to design the microfluidic channel device; and
utilizing the at least two measurements to fabricate the
microfluidic channel device.
15. An energy efficient microfluidic channel device, the device
designed and fabricated based upon the identification of at least
two parameters relating to a desired microfluidic channel device,
the calculation of a relationship between the at least two
parameters to generate at least two measurements, and the
utilization of the at least two measurements to design and
fabricate the energy efficient microfluidic channel device.
16. The device of claim 15, wherein the at least two parameters
comprise parameters relating to volume and length of a desired
microfluidic channel device, and wherein the calculation of the
relationship between the at least two parameters is performed using
a volume-length relation.
17. The device of claim 15, wherein the at least two parameters
comprise parameters relating to relating to diameter and length of
a desired microfluidic channel device, and wherein the calculation
of the relationship between the at least two parameters is
performed using a diameter-length relation.
18. The device of claim 15, wherein the at least two parameters
comprise parameters relating to relating to flow rate and diameter
of a desired microfluidic channel device, and wherein the
calculation of the relationship between the at least two parameters
is performed using a flow rate-diameter relation.
19. The device of claim 15, wherein the at least two parameters
comprise parameters relating to relating to resistance, length, and
volume of a desired microfluidic channel device, and wherein the
calculation of the relationship between the at least two parameters
is performed using a resistance-length and volume relations
20. The device of claim 15, wherein the at least two parameters
comprise parameters relating to relating to flow rate and length of
a desired microfluidic channel device, and wherein the calculation
of the relationship between the at least two parameters is
performed using a flow rate-length relations.
Description
[0001] The present application is a continuation patent application
that is related to, and claims the priority benefit of, U.S. patent
application Ser. No. 12/522,350, filed Jul. 7, 2009, which is
related to, claims the priority benefit of, and is a U.S. national
stage patent application of; International Patent Application
Serial No. PCT/US2008/000762, filed Jan. 22, 2008, which is related
to, and claims the priority benefit of, U.S. Provisional Patent
Application Ser. No. 60/881,833, filed Jan. 23, 2007. The contents
of each of these applications are hereby incorporated by reference
in their entirety into this disclosure.
[0002] The disclosure of the present application relates generally
to diagnosis of vascular disease, in particular relating to using
morphological features of the coronary artery tree to diagnose
coronary artery disease.
[0003] Diffuse coronary artery disease (DCAD), a common form of
atherosclerosis, is difficult to diagnose because the arterial
lumen cross-sectional area is diffusely reduced along the length of
the vessels. Typically, for patients with even mild segmental
stenosis, the lumen cross-sectional area is diffusely reduced by 30
to 50%. The failure of improved coronary flow reserve after
angioplasty may mainly be due to the coexistence of diffuse
narrowing and focal stenosis. Whereas angiography has been regarded
as the "gold standard" in the assessment of focal stenosis of
coronary arteries, its viability to diagnose DCAD remains
questionable. The rationale of conventional angiography in the
assessment of coronary artery disease is to calculate the percent
lumen diameter reduction by comparison of the target segment with
the adjacent `normal` reference segment. In the presence of DCAD,
however, an entire vessel may be diffusely narrowed so that no true
reference (normal) segment exists. Therefore, in the presence of
DCAD, standard angiography significantly underestimates the
severity of the disease.
[0004] To overcome the difficulty of using angiography in the
diagnosis of DCAD, intravascular ultrasound (IVUS) has been the
subject of extensive studies. IVUS has the advantage of directly
imaging the cross-sectional area along the length of the vessel
using a small catheter. The disadvantage of IVUS, however, is that
its extensive interrogation of diseased segments may pose a risk
for plaque rupture.
[0005] What is needed is an improved approach to diagnosis and
prognosis of vascular disease and its symptoms that avoid intrusive
and expensive methods while improving accuracy and efficacy.
BRIEF SUMMARY
[0006] The disclosure of the present application addresses the need
in multiple applications by the application of derived equations
that can be used to diagnose disease as well as aid in the
efficient fabrication of micro-fluidic channel devices.
[0007] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the method
comprises the steps of obtaining a vessel image showing a
vasculature of a vessel, identifying at least two measurements from
the vasculature of the vessel, the measurements relating to at
least two parameters, calculating a relationship between the at
least two parameters from the at least two measurements to generate
one or more vasculature data points, and comparing the one or more
vasculature data points to data relative to a model vasculature to
determine the extent of vascular disease. In another embodiment,
the vessel image is an image selected from the group consisting, of
an angiograph, a CT image, and an MRI. In yet another embodiment,
the at least two parameters comprise parameters relating to volume
and length from the vasculature of the vessel.
[0008] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the step of
calculating a relationship between the at least two parameters is
performed using a volume-length relation. In another embodiment,
the step of calculating a relationship between the at least two
parameters is performed using a resistance-length and volume
relation. In yet another embodiment, the at least two parameters
comprise parameters relating to diameter and length from the
vasculature of the vessel. In an additional embodiment, the step of
calculating a relationship between the at least two parameters is
performed using a diameter-length relation.
[0009] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to flow rate and
diameter from the vasculature of the vessel. In another embodiment,
the step of calculating a relationship between the at least two
parameters is performed using a flow rate-diameter relation. In yet
another embodiment, the at least two parameters comprise parameters
relating to resistance, length, and volume from the vasculature of
the vessel. In an additional embodiment, the step of calculating a
relationship between the at least two parameters is performed using
a resistance-length and volume relation.
[0010] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to flow rate and length
from the vasculature of the vessel. In another embodiment, the step
of calculating a relationship between the at least two parameters
is performed using a flow rate-length relation. In yet another
embodiment, the step of comparing the one or more vasculature data
points to data relative to a model vasculature is performed by
graphically comparing said data points to data relative to a model
vasculature to determine the extent of vascular disease by
identifying graphical differences between said data points to data
relative to a model vasculature. In an additional embodiment, the
step of comparing the one or more vasculature data points to data
relative to a model vasculature is performed by comparing said data
points to data relative to a model vasculature in table form to
determine the extent of vascular disease by identifying numerically
calculated differences between said data points to data relative to
a model vasculature.
[0011] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure the method
comprises the steps of generating a model vascular tree from a
minimum energy hypothesis calculation, and comparing the patient's
vascular tree with the model vascular tree to determine the extent
of vascular disease. In another embodiment, the step of generating
a model vascular tree from a minimum energy hypothesis calculation
further comprises the step of calculating a relationship between at
least two parameters from at least two measurements to generate one
or more model vasculature data points within the model vascular
tree. In yet another embodiment, the at least two parameters
comprise parameters relating to volume and length. In an additional
embodiment, the step of calculating a relationship between the at
least two parameters is performed using a volume-length relation.
In a further embodiment, the step of calculating a relationship
between the at least two parameters is performed using a
resistance-length and volume relation.
[0012] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to diameter and length.
In another embodiment, the step of calculating a relationship
between the at least two parameters is performed using a
diameter-length relation. In yet another embodiment, the at least
two parameters comprise parameters relating to flow rate and
diameter. In an additional embodiment, the step of calculating a
relationship between the at least two parameters is performed using
a flow rate-diameter relation.
[0013] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to resistance, length,
and volume. In another embodiment, the step of calculating a
relationship between the at least two parameters is performed using
a resistance-length and volume relation. In yet another embodiment,
the at least two parameters comprise parameters relating to flow
rate and length. In an additional embodiment, the step of
calculating a relationship between the at least two parameters is
performed using a flow rate-length relation.
[0014] In at least one embodiment of a method for diagnosing
vascular disease according to the present disclosure, the step of
comparing the patient's vascular tree with the model vascular tree
to determine the extent of vascular disease is performed by
graphically comparing the patient's vascular tree with the model
vascular tree to determine the extent of vascular disease by
identifying graphical differences between the patient's vascular
tree with the model vascular tree. In another embodiment, the step
of comparing the patient's vascular tree with the model vascular
tree to determine the extent of vascular disease is performed by
comparing the patient's vascular tree with the model vascular tree
in table form to determine the extent of vascular disease by
identifying numerically calculated differences between the
patient's vascular tree with the model vascular tree.
[0015] In at least one embodiment of a system for diagnosing
vascular disease according to the present disclosure, the system
comprises a processor, a storage medium operably connected to the
processor, the storage medium capable of receiving and storing data
relative of measurements from a vasculature of a vessel, wherein
the processor is operable to obtain a vessel image showing a
vasculature of a vessel, identify at least two measurements from
the vasculature of the vessel, the measurements relating to at
least two parameters, calculate a relationship between the at least
two parameters from the at least two measurements to generate one
or more vasculature data points, and compare the one or more
vasculature data points to data relative to a model vasculature to
determine the extent of vascular disease. In another embodiment,
the vessel image is an image selected from the group consisting of
an angiograph, a CT image, and an MRI. In yet another embodiment,
the at least two parameters comprise parameters relating to volume
and length from the vasculature of the vessel. In an additional
embodiment, the calculation of a relationship between the at least
two parameters is performed using a volume-length relation.
[0016] In at least one embodiment of a system for diagnosing
vascular disease according to the present disclosure, the step of
calculating a relationship between the at least two parameters is
performed using a resistance-length and volume relation. In another
embodiment, the at least two parameters comprise parameters
relating to diameter and length from the vasculature of the vessel.
In yet another embodiment, the calculation of a relationship
between the at least two parameters is performed using a
diameter-length relation.
[0017] In at least one embodiment of a system for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to flow rate and
diameter from the vasculature of the vessel. In another embodiment,
the calculation of a relationship between the at least two
parameters is performed using a flow rate-diameter relation. In yet
another embodiment, the at least two parameters comprise parameters
relating to resistance, length, and volume from the vasculature of
the vessel. In an additional embodiment, the calculation of a
relationship between the at least two parameters is performed using
a resistance-length and volume relation.
[0018] In at least one embodiment of a system for diagnosing
vascular disease according to the present disclosure, the at least
two parameters comprise parameters relating to flow rate and length
from the vasculature of the vessel. In another embodiment, the
calculation of a relationship between the at least two parameters
is performed using a flow rate-length relation. In yet another
embodiment, the comparison of the one or more vasculature data
points to data relative to a model vasculature is performed by
graphically comparing said data points to data relative to a model
vasculature to determine the extent of vascular disease by
identifying graphical differences between said data points to data
relative to a model vasculature. In an additional embodiment, the
comparison of the one or more vasculature data points to data
relative to a model vasculature is performed by comparing said data
points to data relative to a model vasculature in table form to
determine the extent of vascular disease by identifying numerically
calculated differences between said data points to data relative to
a model vasculature.
[0019] In at least one embodiment of a system for diagnosing
vascular disease according to the present disclosure, the system
further comprises a program stored upon the storage medium, said
program operable by the processor upon data relative of
measurements from a vasculature of a vessel. In another embodiment,
the system comprises a user system and a server system, and wherein
the user system and the server system are operably connected to one
another.
[0020] In at least one embodiment of a system for diagnosing
vascular disease in a patient's vascular tree according to the
present disclosure, the system comprises a processor and a storage
medium operably connected to the processor, the storage medium
capable of receiving and storing data relative of measurements from
a vasculature of a vessel, wherein the processor is operable to,
generate a model vascular tree from a minimum energy hypothesis
calculation, and compare the patient's vascular tree with the model
vascular tree to determine the extent of vascular disease. In
another embodiment, the generation of a model vascular tree from a
minimum energy hypothesis calculation is performed by calculating a
relationship between at least two parameters from at least two
measurements to generate one or more model vasculature data points
within the model vascular tree. In at least one embodiment of a
system for diagnosing vascular disease in a patient's vascular tree
according to the present disclosure, the at least two parameters
comprise parameters relating to volume and length. In another
embodiment, the calculation of a relationship between the at least
two parameters is performed using a volume-length relation. In yet
another embodiment, the calculation of a relationship between the
at least two parameters is performed using a resistance-length and
volume relation.
[0021] In at least one embodiment of a system for diagnosing
vascular disease in a patient's vascular tree according to the
present disclosure, the at least two parameters comprise parameters
relating to diameter and length. In another embodiment, the
calculation of a relationship between the at least two parameters
is performed using a diameter-length relation. In yet another
embodiment, the at least two parameters comprise parameters
relating to flow rate and diameter. In an additional embodiment,
the calculation of a relationship between the at least two
parameters is performed using a flow rate-diameter relation.
[0022] In at least one embodiment of a system for diagnosing
vascular disease in a patient's vascular tree according to the
present disclosure, the at least two parameters comprise parameters
relating to resistance, length, and volume. In another embodiment,
the calculation of a relationship between the at least two
parameters is performed using a resistance-length and volume
relation. In yet another embodiment, the at least two parameters
comprise parameters relating to flow rate and length. In an
additional embodiment, the calculation of a relationship between
the at least two parameters is performed using a flow rate-length
relation.
[0023] In at least one embodiment of a system for diagnosing
vascular disease in a patient's vascular tree according to the
present disclosure, the comparison of the patient's vascular tree
with the model vascular tree to determine the extent of vascular
disease is performed by graphically comparing the patient's
vascular tree with the model vascular tree to determine the extent
of vascular disease by identifying graphical differences between
the patient's vascular tree with the model vascular tree. In
another embodiment, the comparison of the patient's vascular tree
with the model vascular tree to determine the extent of vascular
disease is performed by comparing the patient's vascular tree with
the model vascular tree in table form to determine the extent of
vascular disease by identifying numerically calculated differences
between the patient's vascular tree with the model vascular tree.
In yet another embodiment, the system further comprises a program
stored upon the storage medium, said program operable by the
processor upon data relative of measurements from a vasculature of
a vessel. In an additional embodiment, the system comprises a user
system and a server system, and wherein the user system and the
server system are operably connected to one another.
[0024] In at least one embodiment of a program having a plurality
of program steps to be executed on a computer having a processor
and a storage medium to analyze data relative of measurements from
a vasculature of a vessel according to the present disclosure, the
program is operable to obtain a vessel image showing a vasculature
of a vessel, identify at least two measurements from the
vasculature of the vessel, the measurements relating to at least
two parameters, calculate a relationship between the at least two
parameters from the at least two measurements to generate one or
more vasculature data points, and compare the one or more
vasculature data points to data relative to a model vasculature to
determine the extent of vascular disease.
[0025] In at least one embodiment of a program having a plurality
of program steps to be executed on a computer having a processor
and a storage medium to analyze data relative of measurements from
a vasculature of a vessel according to the present disclosure, the
program is operable to generate a model vascular tree from a
minimum energy hypothesis calculation, and compare the patient's
vascular tree with the model vascular tree to determine the extent
of vascular disease.
[0026] In at least one embodiment of a method to design an energy
efficient microfluidic channel device according to the present
disclosure, the method comprises the steps of identifying at least
two parameters relating to a desired microfluidic channel device,
calculating a relationship between the at least two parameters to
generate at least two measurements, and utilizing the at least two
measurements to design the microfluidic channel device. In another
embodiment, the at least two parameters comprise parameters
relating to volume and length of a desired microfluidic channel
device. In yet another embodiment, the step of calculating a
relationship between the at least two parameters is performed using
a volume-length relation. In an additional embodiment, the step of
calculating a relationship between the at least two parameters is
performed using a resistance-length and volume relation.
[0027] In at least one embodiment of a method to design an energy
efficient microfluidic channel device according to the present
disclosure, the at least two parameters comprise parameters
relating to diameter and length. In another embodiment, the step of
calculating a relationship between the at least two parameters is
performed using a diameter-length relation. In yet another
embodiment, the at least two parameters comprise parameters
relating to flow rate and diameter. In an additional embodiment,
the step of calculating a relationship between the at least two
parameters is performed using a flow rate-diameter relation.
[0028] In at least one embodiment of a method to design an energy
efficient microfluidic channel device according to the present
disclosure, the at least two parameters comprise parameters
relating to resistance, length, and volume. In another embodiment,
the step of calculating a relationship between the at least two
parameters is performed using a resistance-length and volume
relation. In yet another embodiment, the at least two parameters
comprise parameters relating to flow rate and length. In an
additional embodiment, the step of calculating a relationship
between the at least two parameters is performed using a flow
rate-length relation.
[0029] In at least one embodiment of a method to design an energy
efficient microfluidic channel device according to the present
disclosure, the method further comprises the step of utilizing the
at least two measurements to fabricate the microfluidic channel
device.
[0030] A model vascular tree was derived from examining many normal
patients, thereby establishing a normal trend, and then diagnosing
disease as a function of variation from the statistical norm of
this model vascular tree.
BRIEF DESCRIPTION OF THE DRAWINGS
[0031] FIG. 1 shows the relation between normalized cumulative
arterial volume and corresponding normalized cumulative arterial
length for each crown on a log-log plot, according to at least one
embodiment of the present disclosure;
[0032] FIG. 2 shows the presence of DCAD at locations along the
mean trend lines for normal (solid) and DCAD vasculature (broken)
according to at least one embodiment of the present disclosure;
and
[0033] FIG. 3 shows a diagnostic system according to at least one
embodiment of the present disclosure.
DETAILED DESCRIPTION
[0034] The disclosure of the present application applies concepts
from biomimetics and microfluidics to analyze vascular tree
structure, thus improving the efficacy and accuracy of diagnostics
involving vascular diseases such as DCAD. Scaling laws are
developed in the form of equations that use the relationships
between arterial volume, cross-sectional area, blood flow and the
distal arterial length to quantify moderate levels of diffuse
coronary artery disease. For the purposes of promoting an
understanding of the principles of the present disclosure,
reference will now be made to the embodiments illustrated in the
drawings, and specific language will be used to describe the same.
It will nevertheless be understood that no limitation of the scope
of the present disclosure is thereby intended.
[0035] Biomimetics (also known as bionics, biognosis, biomimicry,
or bionical creativity engineering) is defined as the application
of methods and systems found in nature to the study and design of
engineering systems and modern technology. The mimic of technology
from nature is based on the premise that evolutionary pressure
forces natural systems to become highly optimized and efficient.
Some examples include (1) the development of dirt- and
water-repellent paint from the observation that the surface of the
lotus flower plant is practically unsticky, (2) hulls of boats
imitating the thick skin of dolphins, and (3) sonar, radar, and
medical ultrasound imaging imitating the echolocation of bats.
[0036] Microfluidics is the study of the behavior, control and
manipulation of microliter and nanoliter volumes of fluids. It is a
multidisciplinary field comprising physics, chemistry, engineering
and biotechnology, with practical applications to the design of
systems in which such small volumes of fluids may be used.
Microfluidics is used in the development of DNA chips,
micro-propulsion, micro-thermal technologies, and lab-on-a-chip
technology.
[0037] Regarding the minimum energy hypothesis, the architecture
(or manifolds) of the transport network is essential for transport
of material in microfluid channels for various chips. The issue is
how to design new devices, and more particularly, how to fabricate
microfluidic channels that provide a minimum cost of operation.
Nature has developed optimal channels (or transport systems) that
utilize minimum energy for transport of fluids. The utility of
nature's design of transport systems in engineering applications is
an important area of biomimetics.
[0038] Biological trees (for example, vascular trees) are either
used to conduct fluids such as blood, air, bile or urine. Energy
expenditure is required for the conduction of fluid through a tree
structure because of frictional losses. The frictional losses are
reduced when the vessel branches have larger diameters. This comes
with a cost, however, for the metabolic construction and
maintenance of the larger volume of the structure. The question is
what physical or physiological factors dictate the design of
vascular trees. The answer is that the design of vascular trees
obeys the "minimum energy hypothesis", i.e., the cost of
construction and operation of the vascular system appears to be
optimized.
[0039] The disclosure of the present application is based on a set
of scaling laws determined from a developed minimum energy
hypothesis. Equation #1 (the "volume-length relation") demonstrates
a relationship between vessel volume, the volume of the entire
crown, vessel length, and the cumulative vessel length of the
crown:
V V max = ( L L max ) 5 ' + 1 ( 1 ) ##EQU00001##
[0040] In Equation #1, V represents the vessel volume, V.sub.max
the volume of the entire crown, L represents the vessel length,
L.sub.max represents the cumulative vessel length of the entire
crown, and .epsilon.' represents the crown flow resistance, which
is equal to the ratio of metabolic to viscous power
dissipation.
[0041] Equation #2 (the "diameter-length relation") demonstrates a
relationship between vessel diameter, the diameter of the most
proximal stem, vessel length, and the cumulative vessel length of
the crown:
D D max = ( L L max ) 3 ' - 2 4 ( ' + 1 ) ( 2 ) ##EQU00002##
[0042] In Equation #2, D represents the vessel diameter, D.sub.max
represents the diameter of the most proximal stem, L represents the
vessel length, L.sub.max represents the cumulative vessel length of
the entire crown, and .epsilon.' represents the crown flow
resistance, which is equal to the ratio of metabolic to viscous
power dissipation.
[0043] Equation #3 (the "flow rate-diameter relation") demonstrates
a relationship between the flow rate of a stem, the flow rate of
the most proximal stem, vessel diameter, and the diameter of the
most proximal stem:
Q Q max = ( D D max ) 4 ( ' + 1 ) 3 ' - 2 ( 3 ) ##EQU00003##
[0044] In Equation #3, Q represents flow rate of a stem, Q.sub.max
represents the flow rate of the most proximal stem, V represents
vessel diameter, V.sub.max represents the diameter of the most
proximal stem, and .epsilon.' represents the crown flow resistance,
which is equal to the ratio of metabolic to viscous power
dissipation.
[0045] Regarding the aforementioned Equations, a vessel segment is
referred to as a "stem," and the entire tree distal to the stem is
referred as a "crown."The aforementioned parameters relate to the
crown flow resistance and is equal to the ratio of maximum
metabolic-to-viscous power dissipation.
[0046] Two additional relations were found for the vascular trees.
Equation #4 (the "resistance-length and volume relation")
demonstrates a relationship between the crown resistance, the
resistance of the entire tree, vessel length, the cumulative vessel
length of the crown, vessel volume, and the volume of the entire
crown:
R c R max = ( L / L max ) 3 ( V / V max ) '' ( 4 ) ##EQU00004##
[0047] In Equation #4, R.sub.c represents the crown resistance,
R.sub.max represents the resistance of the entire tree, L
represents vessel length, L.sub.max, represents the cumulative
vessel length of the entire crown, V represents vessel volume,
V.sub.max represents the volume of the entire crown, and .epsilon.'
represents the crown flow resistance, which is equal to the ratio
of metabolic to viscous power dissipation. Resistance, as
referenced herein, is defined as the ratio of pressure differenced
between inlet and outlet of the vessel.
[0048] Equation #5 (the "flow rate-length relation") demonstrates a
relationship between the flow rate of a stem, the flow rate of the
most proximal stem, vessel length, the cumulative vessel length of
the entire crown:
Q Q max = L L max ( 5 ) ##EQU00005##
[0049] In Equation #5, Q represents flow rate of a stem, Q.sub.max
represents the flow rate of the most proximal stem, L represents
vessel length, and L.sub.max represents the cumulative vessel
length of the entire crown.
[0050] In at least one embodiment of the disclosure of the present
application, the application of one or more of the aforementioned
Equations to acquired vessel data may be useful diagnose and/or aid
in the diagnosis of disease.
[0051] By way of example, the application of one or more of the
aforementioned Equations are useful to diagnose DCAD. For such a
diagnosis, the applications of Equations #1-#3 may provide the
"signatures" of normal vascular trees and impart a rationale for
diagnosis of disease processes. The self-similar nature of these
laws implies that the analysis can be carried out on a partial tree
as obtained from an angiogram, a computed tomography (CT) scan, or
an magnetic resonance imaging (MRI). Hence, the application of
these Equations to the obtained images may serve for diagnosis of
vascular disease that affect the lumen dimension, volume, length
(vascularity) or perfusion (flow rate). Additionally, the
fabrication of the microfluidic channels can be governed by
Equations #1-#5 to yield a system that requires minimum energy of
construction and operation. Hence, energy requirements will be at a
minimum to transport the required microfluidics.
[0052] In one exemplary embodiment, the application of the
volume-length relation Equation #1) to actual obtained images is
considered as shown in FIG. 1. First, images (angiograms in this
example) of swine coronary arties were obtained. The application of
Equation #1 on various volumes and lengths from the angiograms
resulted in the individual data points shown within FIG. 1 (on a
logarithmic scale). The line depicted within FIG. 1 represents the
mean of the data points (the best fit) among the identified data
points.
[0053] In FIG. 2, the mean of the data (solid line) is compared to
an animal with diffuse disease at three different vessel sizes:
proximal (1), middle (2), and distal (3). The reductions in volume
shown on FIG. 2 correspond to approximately 40% stenosis, which is
typically undetectable with current methodologies. At each diffuse
stenosis, the length remains constant but the diameter
(cross-sectional, and hence, volume) changes. The length is
unlikely to change unless the flow becomes limiting (more than
approximately 80% stenosis) and the vascular system experiences
vessel loss (rarefication) and remodeling. It is clear that a 40%
stenosis deviates significantly from the y-axis (as determined by
statistical tests) from the normal vasculature, and as such, 40%
stenosis can be diagnosed by the system and method of the
disclosure of the present application. It can be appreciated that
the disclosure of the present application can predict
inefficiencies as low as about 10%, compared to well-trained
clinicians who can only predict inefficiencies at about 60% at
best.
[0054] This exemplary statistical test compares the deviation of
disease to normality relative to the variation within normality.
The location of the deviation along the x-axis corresponds to the
size of the vessel. The vessel dimensions range as
proximal>mid>distal. Hence, by utilizing the system and
method of the disclosure of the present application, the diagnosis
of the extent of disease and the dimension of the vessel branch is
now possible. Similar embodiments with other scaling relations as
described herein can be applied similarly to model and actual
vascular data.
[0055] The techniques disclosed herein have tremendous application
in a large number of technologies. For example, a software program
or hardware device may be developed to diagnose the percentage of
inefficiency (hence, occlusion) in a circulatory vessel or
system.
[0056] Regarding the computer-assisted determination of such
diagnoses, an exemplary system of the disclosure of the present
application is provided. Referring now to FIG. 3, there is shown a
diagrammatic view of an embodiment of diagnostic system 300 of the
present disclosure. In the embodiment shown in FIG. 3, diagnostic
system 300 comprises user system 302. In this exemplary embodiment,
user system 302 comprises processor 304 and one or more storage
media 306. Processor 304 operates upon data obtained by or
contained within user system 302 Storage medium 306 may contain
database 308, whereby database 308 is capable of storing and
retrieving data. Storage media 306 may contain a program
(including, but not limited to, database 308), the program operable
by processor 304 to perform a series of steps regarding data
relative of vessel measurements as described in further detail
herein.
[0057] Any number of storage media 306 may be used with diagnostic
system 300 of the present disclosure, including, but not limited
to, one or more of random access memory, read only memory, EPROMS,
hard disk drives, floppy disk drives, optical disk drives,
cartridge media, and smart cards, for example. As related to user
system 302, storage media 306 may operate by storing data relative
of vessel measurements for access by a user and/or for storing
computer instructions. Processor 304 may also operate upon data
stored within database 308.
[0058] Regardless of the embodiment of diagnostic system 300
referenced herein and/or contemplated to be within the scope of the
present disclosure, each user system 302 may be of various
configurations well known in the art. By way of example, user
system 302, as shown in FIG. 3, comprises keyboard 310, monitor
312, and printer 314. Processor 304 may further operate to manage
input and output from keyboard 310, monitor 312, and printer 314.
Keyboard 310 is an exemplary input device, operating as a means for
a user to input information to user system 302. Monitor 312
operates as a visual display means to display the data relative of
vessel measurements and related information to a user using a user
system 302. Printer 314 operates as a means to display data
relative of vessel measurements and related information. Other
input and output devices, such as a keypad, a computer mouse, a
fingerprint reader, a pointing device, a microphone, and one or
more loudspeakers are contemplated to be within the scope of the
present disclosure. It can be appreciated that processor 304,
keyboard 310, monitor 312, printer 314 and other input and output
devices referenced herein may be components of one or more user
systems 302 of the present disclosure.
[0059] It can be appreciated that diagnostic system 300 may further
comprise one or more server systems 316 in bidirectional
communication with user system 302, either by direct communication
(shown by the single line connection on FIG. 3), or through a
network 318 (shown by the double line connections on FIG. 3) by one
of several configurations known in the art. Such server systems 316
may comprise one or more of the features of a user system 302 as
described herein, including, but not limited to, processor 304,
storage media 306, database 308, keyboard 310, monitor 312, and
printer 314, as shown in the embodiment of diagnostic system 300
shoe, in FIG. 3. Such server systems 316 may allow bidirectional
communication with one or more user systems 302 to allow user
system 302 to access data relative of vessel measurements and
related information from the server systems 316. It can be
appreciated that a user system 302 and/or a server system 316
referenced herein may be generally referred to as a "computer."
[0060] The disclosure of the present application also relates to
the design and fabrication of micro-fluidic chambers for use in
research and development, thereby designing a chamber that
maximizes flow conditions while minimizing the amount of material
needed to construct the chamber. Many other uses are also possible
and within the scope of the disclosure of the present
application.
[0061] The foregoing disclosure of the exemplary embodiments of the
present application has been presented for purposes of illustration
and description and can be further modified within the scope and
spirit of this disclosure. It is not intended to be exhaustive or
to limit the present disclosure to the precise forms disclosed.
This application is therefore intended to cover any variations,
uses, or adaptations of a device, system and method of the present
application using its general principles. Further, this application
is intended to cover such departures from the present disclosure as
may come within known or customary practice in the art to which
this system of the present application pertains. Many variations
and modifications of the embodiments described herein will be
apparent to one of ordinary skill in the art in light of the above
disclosure. The scope of the present disclosure is to be defined
only by the claims appended hereto, and by their equivalents.
[0062] Further, in describing representative embodiments of the
present disclosure, the specification may have presented the method
and/or process of the present disclosure as a particular sequence
of steps. However, to the extent that the method or process does
not rely on the particular order of steps set forth herein, the
method or process should not be limited to the particular sequence
of steps described. As one of ordinary skill in the art would
appreciate, other sequences of steps may be possible. Therefore,
the particular order of the steps set forth in the specification
should not be construed as limitations on the claims. In addition,
the claims directed to the method and/or process of the present
disclosure should not be limited to the performance of their steps
in the order written, and one skilled in the art can readily
appreciate that the sequences may be varied and still remain within
the spirit and scope of the present disclosure.
* * * * *