U.S. patent application number 16/806677 was filed with the patent office on 2020-06-25 for method and system for facilitating physiological computations.
This patent application is currently assigned to HeartFlow, Inc.. The applicant listed for this patent is HeartFlow, Inc.. Invention is credited to Jin KIM, Michael SINGER.
Application Number | 20200202973 16/806677 |
Document ID | / |
Family ID | 49326853 |
Filed Date | 2020-06-25 |
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United States Patent
Application |
20200202973 |
Kind Code |
A1 |
KIM; Jin ; et al. |
June 25, 2020 |
METHOD AND SYSTEM FOR FACILITATING PHYSIOLOGICAL COMPUTATIONS
Abstract
A system for noninvasively determining at least one
physiological characteristic of a patient may include at least one
computer system configured to, using a three-dimensional surface
mesh model created using patient-specific imaging data, create a
three-dimensional combined surface and volume mesh model, including
at least a first model portion that has a different spatial
resolution than at least a second model portion. The computer
system may be further configured to input the three-dimensional
surface and volume mesh model into a fluid simulation system and
determine a measurement of the physiological characteristic, using
the fluid simulation system.
Inventors: |
KIM; Jin; (Daly City,
CA) ; SINGER; Michael; (Belmont, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
HeartFlow, Inc. |
Redwood City |
CA |
US |
|
|
Assignee: |
HeartFlow, Inc.
|
Family ID: |
49326853 |
Appl. No.: |
16/806677 |
Filed: |
March 2, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14988040 |
Jan 5, 2016 |
10622092 |
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16806677 |
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13625628 |
Sep 24, 2012 |
9262581 |
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14988040 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G16H 50/50 20180101;
G16B 5/00 20190201 |
International
Class: |
G16B 5/00 20060101
G16B005/00; G16H 50/50 20060101 G16H050/50 |
Claims
1-36. (canceled)
37. A system for noninvasively determining patient-specific
treatment options, the system comprising: at least one computer
system configured to, using a hardware processor of the at least
one computer system: obtaining and preprocessing patient-specific
anatomical data; creating a three-dimensional model of a patient's
anatomy based on the patient-specific anatomical data; determining
one or more boundary conditions of the three-dimensional model of
the patient's anatomy; preparing the three-dimensional model of the
patient's anatomy by trimming the three-dimensional model of the
patient's anatomy and incorporating the one or more boundary
conditions; processing the prepared three-dimensional model of the
patient's anatomy by converting at least a surface representation
of the three-dimensional model into a mesh discretizing a surface
or volume of the three-dimensional model; determining blood flow
information for the patient by analyzing the processed
three-dimensional model of the patient's anatomy; and determining
the patient-specific treatment options based on the determined
blood flow information.
38. The system of claim 37, wherein the patient-specific anatomical
data includes at least a portion of the aorta and a proximal
portion of main coronary arteries.
39. The system of claim 37, wherein the one or more boundary
conditions provide information about the three-dimensional model at
inflow boundaries, outflow boundaries, or vessel wall
boundaries.
40. The system of claim 39, wherein the inflow boundaries are
assigned with a prescribed value for velocity, flow rate, or
pressure.
41. The system of claim 40, wherein the prescribed value is
determined by noninvasively measuring physiologic characteristics
of the patient.
42. The system of claim 37, wherein the prepared three-dimensional
model of the patient's anatomy is a surface mesh model of one or
more patient-specific physiologic parameters.
43. The system of claim 42, wherein the one or more
patient-specific physiologic parameters include blood pressure,
patient height, patient weight, or myocardial mass.
44. The system of claim 38, wherein the patient-specific treatment
options include placing a coronary stent in one of the main
coronary arteries represented in the three-dimensional model.
45. A method for noninvasively determining patient-specific
treatment options using a computer system, the method comprising:
obtaining and preprocessing patient-specific anatomical data;
creating a three-dimensional model of a patient's anatomy based on
the patient-specific anatomical data; determining one or more
boundary conditions of the three-dimensional model of the patient's
anatomy; preparing the three-dimensional model of the patient's
anatomy by trimming the three-dimensional model of the patient's
anatomy and incorporating the one or more boundary conditions;
processing the prepared three-dimensional model of the patient's
anatomy by converting at least a surface representation of the
three-dimensional model into a mesh discretizing a surface or
volume of the three-dimensional model; determining blood flow
information for the patient by analyzing the processed
three-dimensional model of the patient's anatomy; and determining
the patient-specific treatment options based on the determined
blood flow information.
46. The method of claim 45, wherein the patient-specific anatomical
data includes at least a portion of the aorta and a proximal
portion of main coronary arteries.
47. The method of claim 45, wherein the one or more boundary
conditions provide information about the three-dimensional model at
inflow boundaries, outflow boundaries, or vessel wall
boundaries.
48. The method of claim 47, wherein the inflow boundaries are
assigned with a prescribed value for velocity, flow rate, or
pressure.
49. The method of claim 48, wherein the prescribed value is
determined by noninvasively measuring physiologic characteristics
of the patient.
50. The method of claim 45, wherein the prepared three-dimensional
model of the patient's anatomy is a surface mesh model of one or
more patient-specific physiologic parameters.
51. The method of claim 50, wherein the one or more
patient-specific physiologic parameters include blood pressure,
patient height, patient weight, or myocardial mass.
52. The method of claim 46, wherein the patient-specific treatment
options include placing a coronary stent in one of the main
coronary arteries represented in the three-dimensional model.
53. A non-transitory computer readable medium for use on at least
one computer system containing computer-executable programming
instructions for performing a method for noninvasively determining
patient-specific treatment options, the method comprising:
obtaining and preprocessing patient-specific anatomical data;
creating a three-dimensional model of a patient's anatomy based on
the patient-specific anatomical data; determining one or more
boundary conditions of the three-dimensional model of the patient's
anatomy; preparing the three-dimensional model of the patient's
anatomy by trimming the three-dimensional model of the patient's
anatomy and incorporating the one or more boundary conditions;
processing the prepared three-dimensional model of the patient's
anatomy by converting at least a surface representation of the
three-dimensional model into a mesh discretizing a surface or
volume of the three-dimensional model; determining blood flow
information for the patient by analyzing the processed
three-dimensional model of the patient's anatomy; and determining
the patient-specific treatment options based on the determined
blood flow information.
54. The non-transitory computer readable medium of claim 53,
wherein the patient-specific anatomical data includes at least a
portion of the aorta and a proximal portion of main coronary
arteries.
55. The non-transitory computer readable medium of claim 53,
wherein the one or more boundary conditions provide information
about the three-dimensional model at inflow boundaries, outflow
boundaries, or vessel wall boundaries.
56. The non-transitory computer readable medium of claim 55,
wherein the inflow boundaries are assigned with a prescribed value
for velocity, flow rate, or pressure.
Description
TECHNICAL FIELD
[0001] Embodiments include methods and systems for facilitating
computations of physiological characteristics. More specifically,
embodiments include methods and systems for processing computer
models to facilitate computations.
BACKGROUND
[0002] Modeling physiological characteristics in a human or animal
patient may be useful in a number of different situations. For
example, modeling coronary artery blood flows, pressures and other
characteristics may be used for assessing coronary artery disease
and evaluating treatment options. Various embodiments of a
noninvasive method and system for providing such physiological
modeling are described, for example, in U.S. patent application
Ser. No. 13/013,561, filed Jan. 25, 2011, and entitled "Method and
System for Patient-Specific Modeling of Blood Flow," which is
incorporated herein by reference in its entirety.
[0003] Using computation fluid dynamics and three-dimensional
models of various portions of a patient's anatomy to generate
physiological measurements from noninvasively generated
patient-specific data is a complex process. In order to be useful
in assessing a patient's disease and evaluating treatment options,
the computer models generated by such a process must be
sufficiently detailed to be accurate. At the same time, if the
models are too detailed, they may require unrealistic amounts of
computing power and/or take impractical amounts of time to create.
For example, in modeling the coronary arteries to assess blood
pressures and/or blood flows, as might be used in assessing the
need for an intervention such as placement of a stent or bypass
graft, computer models must be sufficiently detailed to allow for
computation of blood flow and/or blood pressure. At the same time,
to be useful, these computations must be provided to a physician in
a reasonable amount of time and must still be accurate.
[0004] Thus, a need exists for a method and system for assessing
coronary anatomy, myocardial perfusion, and coronary artery flow
noninvasively. Such a method and system must be sufficiently
accurate to promote confidence in the assessment of the patient's
physiology. At the same time, the method and system needs to be
practical from the standpoint of the time required to provide the
physiological data and the computing power required to do so.
[0005] The foregoing general description and the following detailed
description are exemplary and explanatory only and are not
restrictive of the disclosure.
SUMMARY
[0006] In one aspect, a system for noninvasively determining at
least one physiological characteristic of a patient may include at
least one computer system configured to: using a three-dimensional
surface mesh model created using patient-specific imaging data,
create a three-dimensional combined surface and volume mesh model,
including at least a first model portion that has a different
spatial resolution than at least a second model portion; input the
three-dimensional surface and volume mesh model into a fluid
simulation system; and determine a measurement of the physiological
characteristic, using the fluid simulation system.
[0007] In some embodiments, the computer system may be configured
to create the three-dimensional combined surface and volume model
by identifying at least a first portion of the surface mesh model
as having a first level of complexity, identifying at least a
second portion of the surface mesh model as having a second level
of complexity that is less than the first level, and creating the
surface and volume mesh model such that it includes at least one
high-resolution portion related to the first portion of the surface
model and at least one low-resolution portion related to the second
portion of the surface model. In one embodiment, the
high-resolution portion may include mesh elements that are smaller
than mesh elements of the low-resolution portion. In one
embodiment, identifying the first and second portions may involve
identifying first and second patterns of blood flow in a coronary
artery, where one of the patterns of blood flow is more complex
than the other.
[0008] In some embodiments, the computer system may be configured
to create the three-dimensional combined surface and volume mesh
model by forming multiple elongated shaped elements of the surface
and volume mesh model along a direction of fluid flow through the
surface and volume mesh model, where the first model portion
includes shaped elements that are elongated relative to shaped
elements of the second model portion. For example, in one
embodiment, the shaped elements may be tetrahedrons.
[0009] In some embodiments, the computer system may be configured
to create the three-dimensional combined surface and volume mesh
model by estimating, using the computer system and the surface mesh
model, a solution to at least one equation. In some embodiments,
the computer system may be further configured to estimate, using
the surface and volume mesh model, a solution to at least one
equation, before determining the measurement, wherein the solution
is input into the fluid simulation system along with the surface
and volume mesh model. In some embodiments, the surface and volume
mesh model may include separate surface and volume mesh models.
[0010] In some embodiments, the computer system may be configured
to provide data for use by the fluid simulation system in
determining the measurement. For example, the data may include, but
is not limited to, surface and volume mesh coordinates, surface and
volume element connectivities, model inlet and outlet coordinates
and connectivities, and boundary and initial conditions.
[0011] In some embodiments, the surface model and the surface and
volume mesh model may represent at least a portion of multiple
coronary arteries emanating from a portion of an aorta. In some
embodiments, the physiological characteristic may be fractional
flow reserve.
[0012] In another aspect, a method for noninvasively determining at
least one physiological characteristic of a patient using a
computer system may involve: creating, using the computer system
and the three-dimensional surface mesh model created using
patient-specific imaging data, a three-dimensional combined surface
and volume mesh model, including at least a first model portion
that has a different spatial resolution than at least a second
model portion; processing the surface and volume mesh model to
generate a refined surface and volume mesh model; inputting the
refined surface and volume mesh model into a fluid simulation
system of the computer system; and determining a measurement of the
physiological characteristic, using the fluid simulation system and
based on the refined surface and volume mesh model.
[0013] In some embodiments, creating the combined surface and mesh
model may include: identifying a high-complexity portion of the
surface mesh model; identifying a low-complexity portion of the
surface mesh model; and creating the surface and volume mesh model
such that the first model portion comprises a high-resolution
portion related to the high-complexity portion of the surface mesh
model and the second model portion comprises a low-resolution
portion related to the low-complexity portion of the surface mesh
model. In some embodiments, the method may further involve
processing the surface mesh model before the identifying steps to
generate a refined surface mesh model, where the identifying steps
are then performed on the refined surface mesh model. In some
embodiments, creating the combined surface and mesh model may
involve elongating multiple elements of the surface and volume mesh
model along a direction of fluid flow through the surface and
volume mesh model, where the first model portion includes elements
elongated relative to the second model portion.
[0014] In some embodiments, the method may further include, after
creating the surface and volume mesh model, generating at least one
solution to at least one equation based on the surface and volume
mesh model, and using linear interpolation to project the at least
one solution onto the surface and mesh model. Optionally, such
embodiments may further include processing the surface and volume
mesh model to generate a refined surface and mesh model, where the
step of using linear interpolation to project the solution is
performed on the refined surface and volume mesh model.
[0015] In some embodiments, creating the surface and mesh model may
involve identifying multiple mesh points that will be refined
during the method, where the identified mesh points reside in
portions of the surface and mesh model that are more complex than
other portions of the surface and mesh model. For example,
identifying the mesh points may involve determining whether each of
the mesh points is in or near a stenosed vessel of the surface and
mesh model, and the method may further involve prescribing a local
mesh element size based on a minimum cross-sectional area of the
stenosed vessel. As another example, identifying the mesh points
may involve determining whether each of the mesh points is in or
near an ostium of a coronary artery of the surface and mesh model
by determining if each of the mesh points is within a predetermined
distance from a centerline point of the surface and volume model
located in the ostium. Optionally, such embodiments may further
involve setting a mesh element size based on whether the mesh
points are in or near the ostium.
[0016] In some embodiments, the method may further include, before
the inputting step, generating at least one solution to at least
one equation, based on the combined surface and volume mesh model,
wherein the inputting step further comprises inputting the at least
one solution into the fluid simulation system. As mentioned
previously, in some embodiments, the surface model and the surface
and volume model may represent at least a portion of multiple
coronary arteries emanating from a portion of an aorta, and
determining the measurement may involve determining a fractional
flow reserve.
[0017] In another aspect non-transitory computer readable medium
may be configured for use on at least one computer system,
containing computer-executable programming instructions for
performing a method for noninvasively determining at least one
physiological characteristic of a patient. The method may involve:
creating, using the computer system and the three-dimensional
surface mesh model created using patient-specific imaging data, a
three-dimensional combined surface and volume mesh model, including
at least a first model portion that has a different spatial
resolution than at least a second model portion; generating at
least one solution to at least one equation, based on the combined
surface and volume mesh model; inputting the combined surface and
volume mesh model and the at least one solution into a fluid
simulation system of the computer system; and determining a
measurement of the physiological characteristic, using the fluid
simulation system and based on the combined surface and volume mesh
model and the at least one solution.
[0018] In some embodiments, creating the surface and mesh model may
involve identifying multiple mesh points that will be refined
during the method, where the identified mesh points reside in
portions of the surface and mesh model that are more complex than
other portions of the surface and mesh model. For example, in some
embodiments, identifying the mesh points may include reading a
model geometry of the surface and volume mesh model and solution
information computed by the computer system and generating
estimates of solution errors for each of the mesh points. In such
embodiments, identifying the mesh points may optionally further
involve: based on the solution errors, determining a desired mesh
size for the surface and volume mesh at each of the mesh points,
where the desired mesh size is configured to achieve a solution
error that is approximately uniform at approximately all mesh
points; and based on the desired mesh sizes, identifying the mesh
points that will be refined.
[0019] Additional embodiments and advantages will be set forth in
part in the description which follows, and in part will be obvious
from the description, or may be learned by practice of the
disclosure. The embodiments and advantages will be realized and
attained by means of the elements and combinations particularly
pointed out below.
BRIEF DESCRIPTION OF THE DRAWINGS
[0020] The accompanying drawings, which are incorporated in and
constitute a part of this specification, illustrate several
embodiments and together with the description, serve to explain the
principles of the disclosure.
[0021] FIG. 1 is a schematic diagram of a system for providing
information relating to coronary blood flow in a specific patient,
according to an exemplary embodiment;
[0022] FIG. 2 is a flow chart of a method for providing information
relating to blood flow in a specific patient, according to an
exemplary embodiment;
[0023] FIG. 3 shows an exemplary three-dimensional model generated
using noninvasively obtained imaging data;
[0024] FIG. 4A is a flow chart of a portion of the method
illustrated in FIG. 2, according to an exemplary embodiment;
[0025] FIG. 4B is a flow chart of a portion of the method
illustrated in FIG. 2, according to an alternative exemplary
embodiment;
[0026] FIG. 4C is a flow chart of a portion of the method
illustrated in FIG. 2, according to another alternative exemplary
embodiment;
[0027] FIG. 5 is a flow chart of substeps of one of the steps of
the method illustrated in FIGS. 4A-4C, according to an exemplary
embodiment;
[0028] FIG. 6 is a flow chart of substeps of one of the steps of
the method illustrated in FIGS. 4A-4C, according to an exemplary
embodiment;
[0029] FIG. 7 is a flow chart of substeps of one of the steps of
the method illustrated in FIGS. 4A and 4B, according to an
exemplary embodiment;
[0030] FIG. 8 is a flow chart of substeps of one of the steps of
the method illustrated in FIG. 4C, according to an exemplary
embodiment;
[0031] FIG. 9 is a flow chart of substeps of one of the steps of
the method illustrated in FIGS. 4A-4C, according to an exemplary
embodiment;
[0032] FIG. 10 shows unrefined and refined surface mesh models,
according to an exemplary embodiment; and
[0033] FIG. 11 shows unrefined and refined volume mesh models,
according to an exemplary embodiment.
DESCRIPTION OF THE EMBODIMENTS
[0034] Reference will now be made in detail to exemplary
embodiments, examples of which are illustrated in the accompanying
drawings. Wherever possible, the same reference numbers will be
used throughout the drawings to refer to the same or like
parts.
[0035] In an exemplary embodiment, a method and system may
determine information relating to blood flow in a specific patient
using information retrieved from the patient noninvasively. In some
embodiments, the information determined by the method and system
may relate to blood flow in the patient's coronary vasculature.
Alternatively, the determined information may relate to blood flow
in other areas of the patient's vasculature, such as carotid,
peripheral, abdominal, renal, and cerebral vasculature.
[0036] Referring to FIG. 3, an example of a three-dimensional
computer-generated model 220 of a portion of an aorta 2 and
coronary arteries 4 branching from the aorta 2 is provided. The
coronary vasculature includes a complex network of vessels, ranging
from large arteries to arterioles, capillaries, venules, veins,
etc. The coronary vasculature circulates blood to and within the
heart and includes the aorta 2, which supplies blood to multiple
main coronary arteries 4 (e.g., the left anterior descending (LAD)
artery, the left circumflex (LCX) artery, the right coronary (RCA)
artery, etc.), which may further divide into branches of arteries
or other types of vessels downstream from the aorta 2 and the main
coronary arteries 4. Thus, the exemplary method and system may
determine information relating to blood flow within the aorta, the
main coronary arteries, and/or other coronary arteries or vessels
downstream from the main coronary arteries. Although the aorta and
coronary arteries (and the branches that extend therefrom) are
discussed below, the disclosed method and system may also apply to
other types of vessels.
[0037] In an exemplary embodiment, the information determined by
the disclosed methods and systems may include, but is not limited
to, various blood flow characteristics or parameters, such as blood
flow velocity, pressure (or a ratio thereof), flow rate, and FFR at
various locations in the aorta, the main coronary arteries, and/or
other coronary arteries or vessels downstream from the main
coronary arteries. This information may be used to determine
whether a lesion is functionally significant and/or whether to
treat the lesion. This information may be determined using
information obtained noninvasively from the patient. As a result,
the decision whether to treat a lesion may be made without the cost
and risk associated with invasive procedures.
[0038] FIG. 1 shows aspects of a system for providing information
relating to coronary blood flow in a specific patient, according to
an exemplary embodiment. A three-dimensional model 10 of the
patient's anatomy may be created using data obtained noninvasively
from the patient as will be described below in more detail. Other
patient-specific information may also be obtained noninvasively. In
an exemplary embodiment, the portion of the patient's anatomy that
is represented by the three-dimensional model 10 may include at
least a portion of the aorta and a proximal portion of the main
coronary arteries (and the branches extending or emanating
therefrom) connected to the aorta.
[0039] Various physiological laws or relationships 20 relating to
coronary blood flow may be deduced, e.g., from experimental data as
will be described below in more detail. Using the three-dimensional
anatomical model 10 and the deduced physiological laws 20, multiple
equations 30 relating to coronary blood flow may be determined as
will be described below in more detail. For example, the equations
30 may be determined and solved using any numerical method, e.g.,
finite difference, finite volume, spectral, lattice Boltzmann,
particle-based, level set, finite element methods, etc. The
equations 30 may be solvable to determine information (e.g.,
pressure, velocity, FFR, etc.) about the coronary blood flow in the
patient's anatomy at various points in the anatomy represented by
the model 10.
[0040] The equations 30 may be solved using a computer 40. Based on
the solved equations, the computer 40 may output one or more images
or simulations indicating information relating to the blood flow in
the patient's anatomy represented by the model 10. For example, the
image(s) may include a simulated blood pressure model 50, a
simulated blood flow or velocity model 52, a computed FFR (FFRct)
model 54, etc., as will be described in further detail below. The
simulated blood pressure model 50, the simulated blood flow model
52, and the FFRct model 54 provide information regarding the
respective pressure, velocity, and FFRct at various locations along
three dimensions in the patient's anatomy represented by the model
10. FFRct may be calculated as the ratio of the blood pressure at a
particular location in the model 10 divided by the blood pressure
in the aorta, e.g., at the inflow boundary of the model 10, under
conditions of increased coronary blood flow, e.g., conventionally
induced by intravenous administration of adenosine.
[0041] In an exemplary embodiment, the computer 40 may include one
or more non-transitory computer-readable storage devices that store
instructions that, when executed by a processor, computer system,
etc., may perform any of the actions described herein for providing
information relating to blood flow in the patient. The computer 40
may include a desktop or portable computer, a workstation, a
server, a personal digital assistant, or any other computer system.
The computer 40 may include a processor, a read-only memory (ROM),
a random access memory (RAM), an input/output (I/O) adapter for
connecting peripheral devices (e.g., an input device, output
device, storage device, etc.), a user interface adapter for
connecting input devices such as a keyboard, a mouse, a touch
screen, a voice input, and/or other devices, a communications
adapter for connecting the computer 40 to a network, a display
adapter for connecting the computer 40 to a display, etc. For
example, the display may be used to display the three-dimensional
model 10 and/or any images generated by solving the equations 30,
such as the simulated blood pressure model 50, the simulated blood
flow model 52, and/or the FFRct model 54.
[0042] FIG. 2 shows aspects of a method for providing information
relating to blood flow in a specific patient, according to another
exemplary embodiment. The method may include obtaining
patient-specific anatomical data, such as information regarding the
patient's anatomy (e.g., at least a portion of the aorta and a
proximal portion of the main coronary arteries (and the branches
extending therefrom) connected to the aorta), and preprocessing the
data (step 100). The patient-specific anatomical data may be
obtained noninvasively, e.g., by CCTA.
[0043] A three-dimensional model of the patient's anatomy may be
created based on the obtained anatomical data (step 200). For
example, the three-dimensional model may be the three-dimensional
model 10 of the patient's anatomy described above in connection
with FIG. 1.
[0044] The three-dimensional model may be prepared for analysis and
boundary conditions may be determined (step 300). For example, the
three-dimensional model 10 of the patient's anatomy described above
in connection with FIG. 1 may be trimmed and discretized into a
volumetric mesh, e.g., a finite element or finite volume mesh. The
mathematical equations 30 described above in connection with FIG. 1
may be solved using the volumetric mesh.
[0045] Boundary conditions may also be assigned and incorporated
into the equations 30 described above in connection with FIG. 1.
The boundary conditions provide information about the
three-dimensional model 10 at its boundaries, e.g., inflow
boundaries, outflow boundaries, vessel wall boundaries, etc. The
inflow boundaries may include the boundaries through which flow is
directed into the anatomy of the three-dimensional model, such as
at an inlet of the aorta near the aortic root. Each inflow boundary
may be assigned, e.g., with a prescribed value or field for
velocity, flow rate, pressure, or other characteristic, by coupling
a heart model and/or a lumped parameter model to the boundary, etc.
The outflow boundaries may include the boundaries through which
flow is directed outward from the anatomy of the three-dimensional
model, such as at an outlet of the aorta near the aortic arch, and
the downstream ends of the main coronary arteries and the branches
that extend therefrom. Each outflow boundary can be assigned, e.g.,
by coupling a lumped parameter or distributed (e.g., a
one-dimensional wave propagation) model. The prescribed values for
the inflow and/or outflow boundary conditions may be determined by
noninvasively measuring physiologic characteristics of the patient,
such as, but not limited to, cardiac output (the volume of blood
flow from the heart), blood pressure, myocardial mass, etc. The
vessel wall boundaries may include the physical boundaries of the
aorta, the main coronary arteries, and/or other coronary arteries
or vessels of the three-dimensional model 10. IN various
embodiments, the vessel walls may be represented using a variety of
mathematical models, such as but not limited to rigid walls with
no-slip (i.e., zero velocity) boundary conditions, deformable walls
(e.g., elastically deformable), and/or the like.
[0046] As described in greater detail below, the prepared
three-dimensional model 10 may be processed (step 350) to
facilitate the computational analysis performed in the following
step 400. This additional processing step 350 may make the
computational analysis of step 400 more accurate and/or may reduce
the time and/or computing power required for the analysis. In some
embodiments, the step of preparing the model for analysis 300 and
the step of further processing the model 350 may be combined, and
in use these "steps" may flow together and be performed so quickly
and automatically that they are not discernible as discrete steps.
Therefore, the description of the discrete steps 300 and 350 is
provided herein for ease of description only and should not be
interpreted as a requirement of discrete and separate steps in
every embodiment. Again, the advantage provided by the processing
step 350 is that, by processing the model created in step 300,
subsequent analysis (step 400) can be performed more quickly, more
accurately and/or with less computing power. This advantage may be
quite significant in an overall process as complex as the one
described in the present application.
[0047] The computational analysis may be performed using the
prepared and processed three-dimensional model and the determined
boundary conditions (step 400) to determine blood flow information
for the patient. For example, the computational analysis may be
performed with the equations 30 and using the computer 40 described
above in connection with FIG. 1 to produce the images described
above in connection with FIG. 1, such as the simulated blood
pressure model 50, the simulated blood flow model 52, and/or the
FFRct model 54.
[0048] The method may also include providing patient-specific
treatment options using the results (step 500). For example, the
three-dimensional model 10 created in step 200 and/or the boundary
conditions assigned in step 300 may be adjusted to model one or
more treatments, e.g., placing a coronary stent in one of the
coronary arteries represented in the three-dimensional model 10 or
other treatment options. Then, the computational analysis may be
performed as described above in step 400 in order to produce new
images, such as updated versions of the blood pressure model 50,
the blood flow model 52, and/or the FFRct model 54. These new
images may be used to determine a change in blood flow velocity and
pressure if the treatment option(s) are adopted.
[0049] Steps 100, 200, 300, 400 and 500 are described in
significant detail in U.S. patent application Ser. No. 13/013,561,
which was previously incorporated herein by reference. Therefore,
these steps are not described in detail in the present application.
Step 350 is described in further detail below.
[0050] The systems and methods disclosed herein may be incorporated
into a software tool accessed by physicians to provide a
noninvasive means to quantify blood flow in the coronary arteries
and to assess the functional significance of coronary artery
disease. In addition, physicians may use the software tool to
predict the effect of medical, interventional, and/or surgical
treatments on coronary artery blood flow. The software tool may
prevent, diagnose, manage, and/or treat disease in other portions
of the cardiovascular system including arteries of the neck (e.g.,
carotid arteries), arteries in the head (e.g., cerebral arteries),
arteries in the thorax, arteries in the abdomen (e.g., the
abdominal aorta and its branches), arteries in the arms, or
arteries in the legs (e.g., the femoral and popliteal arteries).
The software tool may be interactive to enable physicians to
develop optimal personalized therapies for patients.
[0051] For example, the software tool may be incorporated at least
partially into a computer system, e.g., the computer 40 shown in
FIG. 1 used by a physician or other user. The computer system may
receive data obtained noninvasively from the patient (e.g., data
used to create the three-dimensional model 10, data used to apply
boundary conditions or perform the computational analysis, etc.).
For example, the data may be input by the physician or may be
received from another source capable of accessing and providing
such data, such as a radiology or other medical lab. The data may
be transmitted via a network or other system for communicating the
data, or directly into the computer system. The software tool may
use the data to produce and display the three-dimensional model 10
or other models/meshes and/or any simulations or other results
determined by solving the equations 30 described above in
connection with FIG. 1, such as the simulated blood pressure model
50, the simulated blood flow model 52, and/or the FFRct model 54.
Thus, the software tool may perform steps 100-500. In step 500, the
physician may provide further inputs to the computer system to
select possible treatment options, and the computer system may
display to the physician new simulations based on the selected
possible treatment options. Further, each of steps 100-500 shown in
FIG. 2 may be performed using separate software packages or
modules.
[0052] Alternatively, the software tool may be provided as part of
a web-based service or other service, e.g., a service provided by
an entity that is separate from the physician. The service provider
may, for example, operate the web-based service and may provide a
web portal or other web-based application (e.g., run on a server or
other computer system operated by the service provider) that is
accessible to physicians or other users via a network or other
methods of communicating data between computer systems. For
example, the data obtained noninvasively from the patient may be
provided to the service provider, and the service provider may use
the data to produce the three-dimensional model 10 or other
models/meshes and/or any simulations or other results determined by
solving the equations 30 described above in connection with FIG. 1,
such as the simulated blood pressure model 50, the simulated blood
flow model 52, and/or the FFRct model 54. Then, the web-based
service may transmit information relating to the three-dimensional
model 10 or other models/meshes and/or the simulations so that the
three-dimensional model 10 and/or the simulations may be displayed
to the physician on the physician's computer system. Thus, the
web-based service may perform steps 100-500 and any other steps
described below for providing patient-specific information. In step
500, the physician may provide further inputs, e.g., to select
possible treatment options or make other adjustments to the
computational analysis, and the inputs may be transmitted to the
computer system operated by the service provider (e.g., via the web
portal). The web-based service may produce new simulations or other
results based on the selected possible treatment options, and may
communicate information relating to the new simulations back to the
physician so that the new simulations may be displayed to the
physician.
[0053] One or more of the steps described herein may be performed
by one or more human operators (e.g., a cardiologist or other
physician, the patient, an employee of the service provider
providing the web-based service or other service provided by a
third party, other user, etc.), or one or more computer systems
used by such human operator(s), such as a desktop or portable
computer, a workstation, a server, a personal digital assistant,
etc. The computer system(s) may be connected via a network or other
method of communicating data.
[0054] With continued reference to FIG. 2, as mentioned above, in
some embodiments, the three-dimensional model provided in step 300
may be processed in step 350 to facilitate computational analysis
and generation of results (step 400). This further processing step
350, which in alternative embodiments may be combined with step
300, will now be described in greater detail.
[0055] In general, the further processing step 350 involves using
variable spatial resolution for patient-specific mathematical
modeling, such as modeling of fluid mechanics, solid mechanics,
fluid-structure interaction and/or the like. Variable spatial
resolution is used to process the model generated by step 300 of
the method to effectively initialize the equations used in step 400
to model the physiological characteristic(s) or measurement(s) of
interest. In general, a computer generated, unrefined surface mesh
is the output of step 300, and a refined mesh is the output of step
350. Typically, the refined mesh includes surface and volume mesh
data and allows for more effective initialization of the analysis
performed in step 400. The process of step 350 is performed by a
computer system, including computer software configured to perform
operations in sequence or in parallel.
[0056] For exemplary purposes, the system used to perform step 350
may be referred to herein as "the presolver," and the system used
to perform step 400 may be referred to herein as "the solver." The
presolver generally refines the model of step 300 to prepare it for
computational analysis by the solver (step 400). In some
embodiments, the presolver and the solver may run at the same time
for a given set of patient-specific data. Furthermore, in some
embodiments, data from the presolver may be output into the solver,
processed, and provided back to the presolver during step 350. In
other words, step 350 may include functionality of both the
presolver and the solver. Thus, the terms "presolver" and "solver"
are used primarily for ease of description and should not be
interpreted as limiting the scope of the embodiments to any
specific order of steps or operations.
[0057] At a high level, the presolver (step 350) converts a surface
representation (surface mesh with centerlines) of a physiologic
geometry into a specialized computational mesh that discretizes the
surface and volume of the geometry. The surface and volume meshes
(also referred to at the "surface and volume mesh model" or
"combined surface and volume mesh model") accurately represent the
underlying geometry of the patient's anatomy and are suitable for
rapidly solving equations throughout the entire computational
domain. In addition, step 350 prepares specialized pressure and
velocity fields that initialize the mathematical equation solver
(step 400) in order to accelerate solver convergence and increase
solver performance. In a typical embodiment, the input into step
350 is a surface mesh model, with centerlines, of the relevant
physiology and one or more patient-specific physiologic parameters,
such as but not limited to blood pressure, patient height, patient
weight and myocardial mass. The outputs from step 350 into step 400
are specialized surface and volume meshes and an initial solution
field used to rapidly and accurately solve mathematical equations
on the computational domain. Generally, step 350 is fully automated
and performs one or more sequences of operations. Due to the
automation, however, all of the sequences of operations described
below will typically be transparent to the user of the overall
system.
[0058] According to one embodiment, the method described by step
350 may involve: (1) using a three-dimensional surface mesh model
created using patient-specific imaging data to create a
three-dimensional combined surface and volume mesh model, including
at least a first model portion that has a different spatial
resolution than at least a second model portion; and (2) inputting
the three-dimensional surface and volume mesh model into a fluid
simulation system. The fluid simulation system, in step 400, then
performs computational analysis and generates results. In some
embodiments, method step 350 may include additional sub-steps. For
example, in some embodiments, the three-dimensional surface mesh
model that is the input into step 350 may be processed to provide a
refined surface mesh model, which is then used to create the
combined surface and volume mesh model. In some embodiments, the
surface and volume mesh model may be processed to generate a
refined surface and mesh model, and that refined surface and volume
mesh model may be input into the fluid simulation system. In some
embodiments, one or more solutions to one or more equations may be
produced as part of step 350, and the solutions may be used to
refine the surface and volume mesh model and/or may be input into
the fluid simulation system. Thus, step 350 may include any of a
number of suitable sub-steps, which will be described further
below.
[0059] Referring now to FIGS. 4A-4C, the model processing step 350
may include a number of different sequences of operations performed
in one of a number of different orders, according to various
embodiments. In some embodiments, two or more sequences may be
performed concurrently (FIGS. 4A and 4B), while in alternative
embodiments, all sequences may be performed sequentially (FIG. 4C).
Referring to FIG. 4A, for example, in one concurrent mode, the
unrefined surface mesh model of step 300 may be fed into a first
operational sequence 600, referred to as "presolver without mesh
refinement," and a third operational sequence 610, referred to as
"presolver with mesh refinement." First and third operational
sequences 600, 610, which are independent from one another, may be
started at the same time or approximately the same time. These two
sequences 600, 610 generate separate surface/volume meshes without
and with refinement, respectively. When sequence 600 completes
(i.e., the mesh without refinement is generated), a second
operational sequence 620 may be started (i.e., equations are solved
on the mesh without refinement). Note that sequence 620 may be
executed despite the possible incompletion of sequence 610. Upon
the completion of both sequence 620 and sequence 610, a refined
mesh is provided to the solver, for computational analysis step
400.
[0060] Referring now to FIG. 4B, in an alternative embodiment, step
350 may involve starting sequence 600 by itself. The resulting mesh
from sequence 600 may then be input into sequences 610 and 620
simultaneously. The results of sequences 610 and 620 are then
provided to the solver (step 400).
[0061] In another alternative embodiment, and with reference now to
FIG. 4C, all sequences may be performed successively (i.e.,
sequentially). In this embodiment, sequence 600 is run to
completion, the resulting data are then fed into sequence 620,
which is run to completion, the resulting data are then fed into an
alternate third sequence 615, referred to as "solution-based mesh
adaptation," which is run to completion, and the resulting refined
model is then provided to the solver 400. In this embodiment,
alternate third sequence 615 is used, rather than sequence 610,
since the sequences are run sequentially. It may be possible, in
other alternative embodiments, to run the various sequences in
other orders or configurations or to add further sequences. The
various sequences 600, 610, 615 and 620 will now be described in
further detail.
[0062] Referring now to FIG. 5, sequence 600 may be referred to as
a process of "presolver without mesh refinement." As illustrated in
FIG. 10, the input into sequence 600 includes a surface mesh model
700, for example a surface mesh model of a portion of an aorta and
coronary arteries branching from the aorta. The output from
sequence 600 includes a refined surface mesh 710, as well as a
volume mesh 720 (FIG. 11). A first operation 601 of sequence 600
involves inputting the patient-specific surface model 700 (from
step 300 of FIG. 2) and physiological parameters into the sequence
600. First operation 601 may initially involve, for a given patient
model, reading all required and optional patient-specific
parameters. In one embodiment, parameters used for generating the
mesh and setting boundary conditions may include, but are not
limited to, systolic blood pressure, diastolic blood pressure,
patient height, patient weight, myocardial mass, and a name of the
input geometry file. Optional additional parameters may include,
but are not limited to, patient hematorcrit, number of computer
processors on which the mathematical equations will be solved
and/or specialized mesh refinement parameters.
[0063] First operation 601 may also include initializing presolver
data structures and supporting libraries, including third party
libraries for parallel computing (e.g., OpenMPI), memory and array
management (e.g., boost), input/output streams (e.g., rapidxml),
and/or mesh generation (e.g., Simmetrix). Other libraries and
functionality, which may be selected based on the software
implementation of the presolver, may also be initialized. First
operation 601 may also include reading and parsing the surface mesh
model (from step 300). The surface mesh model contains a discrete
representation of the entire physiologic domain on which the
mathematical equations will be solved, and first operation 601
reads the discrete representation of the patient-specific model 700
and stores model information, such as but not limited to surface
coordinates, surface element connectivity, centerline points and
coordinates, vessel areas and normals at inlet/outlet points,
hierarchical information of the centerline tree structure, and
boundary information. These data are used to generate the
specialized surface and volume meshes and to prepare the initial
solution field for solving the equations.
[0064] A second operation 602 of sequence 600 may involve
identifying and labeling portions of the discrete model that will
receive specialized treatment by the presolver. For example,
certain regions of a coronary artery may be identified as having
relatively complex flow patterns compared to other regions of the
artery. Alternatively, or additionally, certain regions of a
coronary artery may be identified as having relatively simple flow
patterns compared to other regions of the artery. Such regions may
be identified during the second operation 602 so that they may be
treated differently during processing of the data. Specialized
treatment includes any mathematical, geometric or meshing operation
that is applied to a localized region of the model and not to the
model as a whole. Such operations may include, for example, the
generation of relatively high or low resolution meshes in selected
regions of the model, smoothing or blending of the model
surface(s), and cropping or trimming of the model surface.
[0065] A third operation 603 of sequence 600 may involve generating
a surface mesh based on the geometry to adequately capture the
input surface model. In this operation 603, a meshing library may
be used to create a specialized surface mesh that spatially
resolves the discrete physiological model. Adequate spatial
resolution of the model may comprise a surface mesh that captures
the complex morphology of the geometric surface to enable the
accurate solution of the equations used to model the physiological
phenomena of interest. In one embodiment, the specialized surface
mesh may be created by: (1) setting the mesh element sizes on all
model inlet and outlet surfaces to be a function of the
cross-sectional area of the respective inlet or outlet surface; (2)
setting the mesh element size to be relatively large on all
portions of the model that contain simple and slowly varying
topology, wherein the solutions to the mathematical equations do
not require high spatial resolution; (3) setting the mesh element
size to be relatively small on all portions of the model that
contain complex and rapidly varying topology, wherein the solutions
to the mathematical equations require high spatial resolution; and
(4) after all mesh element sizes are determined, using a mesh
generator to generate the surface mesh with the determined element
sizes.
[0066] The term "mesh elements" is used generally herein to
describe the multiple components or pieces that make up a mesh
model. Generally, these elements may take the form of shapes, with
typically many of the shapes making up the complete surface and/or
volume mesh models. For example, a surface or volume mesh model may
be made of multiple polyhedrons, such as tetrahedrons.
[0067] Once the surface mesh is generated, the fourth operation 604
of sequence 600 may involve using a meshing library to generate a
volume mesh.
[0068] Finally, operation 605 of sequence 600 may involve
outputting data and information required to solve the equations
step 620. Output data from sequence 600 may include, for example,
surface and volume mesh coordinates, surface and volume element
connectivities, model inlet and outlet coordinates and
connectivities, boundary and initial conditions, and geometric
model information required for solving the equations. In other
words, the output data includes a combined surface and volume mesh
without refinement. After operation 605, an optional step (not
shown in FIG. 5) may involve cleaning up computer memory and in
some instance exiting the presolver (such as when the solver is
used to solve the mathematical equations of step 620).
[0069] With reference now to FIG. 6, after the surface/volume mesh
is created in sequence 610, the mesh data is provided to sequence
620. In some embodiments, sequence 620 may be performed by what has
been referred to thus far as the solver. In other embodiments,
sequence 620 may be performed by software residing outside and
separate from the solver. In any case, sequence 620, for the
purposes of this description, is considered to be part of the
presolver method. Generally, sequence 620 involves solving
equations to obtain a solution that meets user-specified accuracy
requirements. In one embodiment, sequence 620 may involve a first
operation 621 that comprises assigning zero velocities and zero
pressure to the mesh from sequence 610. A second operation 622 may
then involve running the solver until the solutions converge.
Finally, a third operation 623 may involve outputting solutions
and/or generating reports, which may be used by a subsequent step
in the modeling process. Various additional details regarding
solving the equations of sequence 620 are described in detail in
U.S. patent application Ser. No. 13/013,561, which was previously
incorporated by reference.
[0070] Referring now to FIG. 7, in some embodiments (for example,
those illustrated in FIGS. 4A and 4B), the presolver step 350
includes sequence 610, involving applying a presolver with mesh
refinement. The first operation 611 of sequence 610 may involve
either inputting (or receiving) the mesh from sequence 600 (as in
FIG. 4B) or performing operations 601, 602, 603 and 604 of sequence
600 (as in FIG. 4A). The second operation 612 may involve
identifying and storing mesh points that should be refined. Mesh
points typically should be refined if they lie within regions of
the vessel geometry that contain complex solution features that
require additional spatial resolution (i.e., mesh elements) to
resolve adequately. In one embodiment, for example, presolver mesh
refinement may involve the following steps:
[0071] (1) Associating each mesh point with its nearest point on
the centerline tree of the model;
[0072] (2) Identifying and storing all mesh points on the model
that contain simple and slowly varying topology, wherein the
solutions to the equations do not require high spatial resolution.
These mesh points will not be refined. For example, in some
embodiments, this step may involve identifying and storing all mesh
points inside the aorta, because no complex flow features are
expected inside the aorta;
[0073] (3) Identifying and storing all mesh points of the model
that contain complex or rapidly varying topology, wherein the
solutions to the equations require high spatial resolution. These
points are marked for mesh refinement;
[0074] (4) At the points marked for mesh refinement, determining an
appropriate mesh size that accurately captures features of the
mathematical solution. A suitable mesh size may be determined by
factors such as but not limited to geometric topology of the model,
anticipated or computed solution profiles or gradients, modeling
constraints, and computer resource constraints. In some
embodiments, for example, this step may involve identifying and
storing all mesh points inside the coronary arteries that require
mesh refinement.
[0075] In one exemplary embodiment, the process of identifying and
storing mesh points for refinement, for example in the coronary
arteries, may include the following steps:
[0076] (1) For each centerline point in the coronary tree,
determine if the point is in or near a stenosed vessel. A
centerline point is in or near a stenosed vessel if at least one of
the following conditions is satisfied: [0077] a. the
cross-sectional area of a given centerline point is <1/2 the
average cross-sectional area of the centerline segment that
contains the given point; or [0078] b. a given centerline point is
within a user-specified distance downstream of a centerline point
that is identified as being inside a stenosed vessel
[0079] (2) For each mesh point of the model, determine if the mesh
point is in or near a stenosed vessel. In other words, for a given
mesh point, determine if the nearest centerline point is in or near
a stenosed vessel per the definitions stated above;
[0080] (3) If the given mesh point is in or near a stenosed vessel,
then prescribe a local mesh size that is based on the minimum
cross-sectional area of the stenosed vessel, i.e., the minimum
cross-sectional area of the centerline point in the stenosis.
Otherwise, prescribe a local element size based on the local
cross-sectional area of the vessel, i.e., the cross-sectional area
of the nearest centerline point;
[0081] (4) Identify and store mesh points that are located in one
of the ostia of the coronary arteries (i.e., the openings of the
coronary arteries into the aorta). A given mesh point is in an
ostium if the point is within a user-specified distance from a
centerline point that is in the ostium;
[0082] (5) If the given mesh point is in or near an ostium, then
ensure the local mesh size is below a user-specified tolerance. The
user-specified tolerance is a function of the local cross-sectional
area of the vessels. If the mesh size is above the user-specified
tolerance, then set the local mesh size to the user-specified
tolerance. Otherwise, use the existing local mesh size;
[0083] (6) If the given mesh point is not near the ostium (i.e.,
sufficiently distant from the ostium), then do not modify the local
mesh size;
[0084] (7) For mesh points that are marked for refinement, set
anisotropic size parameters of the mesh elements. Anisotropy
parameters (e.g., element skewness or stretching) are based on the
cross-sectional area and normal of the vessel as characterized by
the area and normal of the nearest centerline point.
[0085] The next operation 613 in sequence 610 involves adapting the
volume mesh anisotropically to capture the hemodynamics of the
model. This operation 613 involves using the meshing library to
refine the volume mesh based on the mesh element sizing method
described above. In some embodiments, mesh refinement may occur in
parallel, so different portions of the mesh are refined using
different computer processors to speed up the process of mesh
refinement.
[0086] The final operation 614 in sequence 610 involves adapting
outputting data and information required to solve the mathematical
equations of interest. Presolver output data may include, for
example, surface and volume mesh coordinates, surface and volume
element connectivities, model inlet and outlet coordinates and
connectivities, boundary and initial conditions, and geometric
model information required to solve the equations. Once sequence
610 is complete, in some embodiments, the method may include
cleaning up computer memory, and exiting the presolver.
[0087] With reference now to FIG. 8, in some embodiments (such as
that illustrated in FIG. 4C), the presolver method may include the
sequence 615--a solution-based mesh adaptation. In one embodiment,
sequence 615 may include a first operation 616 of inputting (or
receiving) the mesh from sequence 600 and the solutions
(corresponding error fields) from sequence 620. This operation 616
may include reading the model geometry (of the mesh) from sequence
600 and the solution information computed from sequence 620 and
computing estimates of solution errors at each mesh point.
[0088] A second operation 617 may involve, based on the solution
errors computed above, computing a desired mesh size at every mesh
point. The desired mesh size is generally one configured to achieve
a solution error that is approximately uniform at all (or
approximately all) mesh points. Based on the desired, computed mesh
sizes, operation 617 may also include identifying and marking mesh
points that require refinement or coarsening.
[0089] A third operation 618 may involve adapting the volume mesh
anisotropically to obtain uniform error fields after mesh
adaptation. Some embodiments may include using a meshing library to
refine the volume mesh based on the mesh element sizings determined
in step 617. Mesh refinement may occur in parallel, so different
portions of the mesh may be refined using different computer
processors to speed up the process of mesh refinement.
[0090] A fourth operation 619 may involve outputting data and
information required to solve the mathematical equations of
interest. Presolver output data may include, for example, surface
and volume mesh coordinates, surface and volume element
connectivities, model inlet and outlet coordinates and
connectivities, boundary and initial conditions, and geometric
model information for solving the equations. In some embodiments,
after the fourth step, the method may include cleaning up computer
memory and exiting the presolver.
[0091] Referring now to FIG. 9, step 400 of performing
computational analysis and outputting results may include several
operations in some embodiments. For example, a first operation 631
may involve assigning initial conditions by projecting solutions
from sequence 620 onto the mesh from sequence 610 or sequence 615.
In other words, operation 613 may involve using linear
interpolation to project the solution field computed in sequence
620 onto the refined mesh created in sequence 610 or sequence
615.
[0092] Next, a second operation 632 may use the projected solution
field and the refined mesh created in 610 or 615 to solve the
equations that govern the mathematical model to obtain a fully
converged solution on the refined mesh. Finally, a third operation
633 may involve outputting solutions and generating reports, based
on the solved mathematical equations. Such solutions may include,
for example, any of a number of various blood flow characteristics
or parameters, such as blood flow velocity, blood pressure (or a
ratio thereof), flow rate, and FFR at various locations in the
aorta, the main coronary arteries, and/or other coronary arteries
or vessels downstream from the main coronary arteries. As mentioned
previously, additional details regarding the step of performing
computational analysis and outputting results are provided in U.S.
patent application Ser. No. 13/013,561, which was previously
incorporated by reference.
[0093] Any aspect set forth in any embodiment may be used with any
other embodiment set forth herein. Every device and apparatus set
forth herein may be used in any suitable medical procedure, may be
advanced through any suitable body lumen and body cavity, and may
be used for imaging any suitable body portion.
[0094] Various modifications and variations can be made in the
disclosed systems and processes without departing from the scope of
the disclosure. Other embodiments will be apparent to those skilled
in the art from consideration of the specification and practice of
the disclosure disclosed herein. It is intended that the
specification and examples be considered as exemplary only, with a
true scope and spirit of the disclosure being indicated by the
following claims.
* * * * *