U.S. patent application number 16/396087 was filed with the patent office on 2019-08-15 for systems and methods for providing personalized estimates of bioheat transfer.
This patent application is currently assigned to HeartFlow, Inc.. The applicant listed for this patent is HeartFlow, Inc.. Invention is credited to Leo GRADY, Charles A. TAYLOR, Christopher K. ZARINS.
Application Number | 20190247123 16/396087 |
Document ID | / |
Family ID | 55802465 |
Filed Date | 2019-08-15 |
United States Patent
Application |
20190247123 |
Kind Code |
A1 |
GRADY; Leo ; et al. |
August 15, 2019 |
SYSTEMS AND METHODS FOR PROVIDING PERSONALIZED ESTIMATES OF BIOHEAT
TRANSFER
Abstract
Systems and methods are disclosed for providing personalized
estimates of bioheat transfer through a patient's body or a portion
of a patient's body. One method includes receiving a
patient-specific vascular model of a patient's anatomy, including
at least one vessel of the patient; receiving a patient-specific
tissue model including at least a portion of tissue of the
patient's anatomy; receiving an estimate of heat content of the
portion of tissue of the patient-specific tissue model or tissue
surrounding the portion of tissue; determining an estimate of heat
distribution of the portion of tissue of the patient-specific
tissue model or tissue surrounding the portion of tissue based on
the vascular model, the tissue model, or the received estimate of
heat content; and output the determined estimate of heat
distribution to a storage medium or user display.
Inventors: |
GRADY; Leo; (Millbrae,
CA) ; TAYLOR; Charles A.; (Atherton, CA) ;
ZARINS; Christopher K.; (Menlo Park, MA) |
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Applicant: |
Name |
City |
State |
Country |
Type |
HeartFlow, Inc. |
Redwood City |
CA |
US |
|
|
Assignee: |
HeartFlow, Inc.
|
Family ID: |
55802465 |
Appl. No.: |
16/396087 |
Filed: |
April 26, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15088626 |
Apr 1, 2016 |
10314655 |
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16396087 |
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62141911 |
Apr 2, 2015 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61B 34/10 20160201;
A61B 18/12 20130101; A61N 7/02 20130101; A61B 2018/00577 20130101;
A61F 7/00 20130101; A61B 2034/104 20160201; A61B 34/00 20160201;
A61B 18/02 20130101; G16H 50/50 20180101 |
International
Class: |
A61B 34/10 20060101
A61B034/10; A61B 34/00 20060101 A61B034/00; G16H 50/50 20060101
G16H050/50 |
Claims
1-20. (canceled)
21. A computer-implemented method of providing personalized
estimates of bioheat transfer through a patient's body or a portion
of a patient's body, the method comprising: receiving an estimate
of heat content of a portion of a patient's tissue; receiving blood
flow information associated with the portion of the patient's
tissue; computing an estimate of heat transfer through the portion
of the patient's tissue based on the received estimate of heat
content and the received blood flow information; computing an
estimate of heat distribution of the portion of the patient's
tissue or tissue surrounding the portion of the patient's tissue
based on the determined estimate of heat transfer; and outputting
the determined estimate of heat distribution to a storage medium or
user display.
22. The computer-implemented method of claim 21, wherein the
display includes renderings of heat distribution simulations,
treatments, and/or interactive options or prompts to adjust
circulation, temperature, patient tissue geometry, time frames to
display.
23. The computer-implemented method of claim 21, wherein the
estimate of heat content is estimated as a homogenous value.
24. The computer-implemented method of claim 23, further
comprising: determining an introduction of a temperature source in
a location of the tissue model or vascular model, wherein the
estimate of heat content is homogenous except for the location of
the temperature source.
25. The computer-implemented method of claim 24, wherein the
temperature source is associated with ablation, a heating
apparatus, or a cooling apparatus.
26. The computer-implemented method of claim 21, further
comprising: determining, using the vascular model, blood flow
demand of the tissue model.
27. The computer-implemented method of claim 21, wherein the
estimate of heat content of the portion of tissue comprises the
heat content of the portion of tissue or the surrounding tissue at
a first point of time; and wherein the estimate of heat
distribution comprises heat distribution at a second point of time
different from the first point of time.
28. The computer-implemented method of claim 21, further
comprising: receiving a patient-specific vascular model of a
patient's anatomy, including at least one vessel of the patient; or
receiving a patient-specific tissue model including at least a
portion of tissue of the patient's anatomy; wherein the estimate of
heat transfer or the estimate of heat distribution is based on the
received patient-specific vascular model and/or the receive
patient-specific tissue model.
29. A system for providing personalized estimates of bioheat
transfer through a patient's body or a portion of a patient's body,
the system comprising: a data storage device storing instructions
of providing personalized estimates of bioheat transfer through a
patient's body or a portion of a patient's body; and a processor
configured to execute the instructions to perform a method
including: receiving an estimate of heat content of a portion of a
patient's tissue; receiving blood flow information associated with
the portion of the patient's tissue; computing an estimate of heat
transfer through the portion of the patient's tissue based on the
received estimate of heat content and the received blood flow
information; computing an estimate of heat distribution of the
portion of the patient's tissue or tissue surrounding the portion
of the patient's tissue based on the determined estimate of heat
transfer; and outputting the determined estimate of heat
distribution to a storage medium or user display.
30. The system of claim 29, wherein the display includes renderings
of heat distribution simulations, treatments, and/or interactive
options or prompts to adjust circulation, temperature, patient
tissue geometry, time frames to display.
31. The system of claim 29, wherein the estimate of heat content is
estimated as a homogenous value.
32. The system of claim 31, wherein the system is further
configured for: determining an introduction of a temperature source
in a location of the tissue model or vascular model, wherein the
estimate of heat content is homogenous except for the location of
the temperature source.
33. The system of claim 32, wherein the temperature source is
associated with ablation, a heating apparatus, or a cooling
apparatus.
34. The system of claim 29, wherein the system is further
configured for: determining, using the vascular model, blood flow
demand of the tissue model.
35. The system of claim 29, wherein the estimate of heat content of
the portion of tissue comprises the heat content of the portion of
tissue or the surrounding tissue at a first point of time; and
wherein the estimate of heat distribution comprises heat
distribution at a second point of time different from the first
point of time.
36. The system of claim 29, wherein the system is further
configured for: receiving a patient-specific vascular model of a
patient's anatomy, including at least one vessel of the patient; or
receiving a patient-specific tissue model including at least a
portion of tissue of the patient's anatomy; wherein the estimate of
heat transfer or the estimate of heat distribution is based on the
received patient-specific vascular model and/or the receive
patient-specific tissue model.
37. A non-transitory computer readable medium for use on a computer
system containing computer-executable programming instructions for
performing a method of providing personalized estimates of bioheat
transfer through a patient's body or a portion of a patient's body,
the method comprising: receiving an estimate of heat content of a
portion of a patient's tissue; receiving blood flow information
associated with the portion of the patient's tissue; computing an
estimate of heat transfer through the portion of the patient's
tissue based on the received estimate of heat content and the
received blood flow information; computing an estimate of heat
distribution of the portion of the patient's tissue or tissue
surrounding the portion of the patient's tissue based on the
determined estimate of heat transfer; and outputting the determined
estimate of heat distribution to a storage medium or user
display.
38. The non-transitory computer readable medium of claim 37,
wherein the display includes renderings of heat distribution
simulations, treatments, and/or interactive options or prompts to
adjust circulation, temperature, patient tissue geometry, time
frames to display.
39. The non-transitory computer readable medium of claim 37,
wherein the estimate of heat content is estimated as a homogenous
value.
40. The non-transitory computer readable medium of claim 39, the
method further comprising: determining an introduction of a
temperature source in a location of the tissue model or vascular
model, wherein the estimate of heat content is homogenous except
for the location of the temperature source.
Description
RELATED APPLICATION(S)
[0001] This application claims priority to U.S. Provisional
Application No. 62/141,911 filed Apr. 2, 2015, the entire
disclosure of which is hereby incorporated herein by reference in
its entirety.
FIELD OF THE DISCLOSURE
[0002] Various embodiments of the present disclosure relate
generally to disease assessment, treatment planning, and related
methods. More specifically, particular embodiments of the present
disclosure relate to systems and methods of providing personalized
estimates of bioheat transfer through a patient's body or a portion
of a patient's body.
BACKGROUND
[0003] The human body has a refined homeostatic mechanism for
maintaining constant body temperature, but it nevertheless may be
sensitive to external temperature. Some temperature changes may
affect the whole body and cause conditions that may be potentially
life-threatening, for example, hypothermia, hyperthermia, heat
stroke, and/or heat exhaustion. These conditions may be treated
through a variety of methods, for example, rewarming, fluid
ingestion, immersion in warm/cool water, or by more advanced
mechanisms. Other temperature changes may be applied focally as
therapeutics, for example, applying radiofrequency (RF) ablation or
cryoablation to treat cancer or to treat atrial fibrillation or
ventricular tachycardia. In these cases, extreme temperatures may
be used to deliberately damage pathological tissue while trying to
preserve surrounding healthy tissue. However, heat transfer in the
human body may be complex and difficult to predict since heat
transfer may be contingent on a variety of factors including, for
example, heat diffusion through multiple different materials (e.g.,
tissue, fluid, bone), the convection of the vascular system, and/or
temperatures external to the body. In addition, individuals' bodies
may vary in their abilities to adjust or regulate temperatures,
which may cause people to vary in how prone they are to
heat-related illness or how sensitive they are to treatment.
[0004] Thus, a desire exists for understanding bioheat transfer
specific to an individual. For example, a desire exists to model
bioheat (e.g., heat transfer or heat distribution) in an
individual's entire body and/or in isolated organs and body parts.
Furthermore, a desire exists to evaluate effectiveness of
temperature-related treatments.
[0005] The foregoing general description and the following detailed
description are exemplary and explanatory only and are not
restrictive of the disclosure.
SUMMARY
[0006] According to certain aspects of the present disclosure,
systems and methods are disclosed providing personalized estimates
of bioheat transfer through a patient's body or a portion of a
patient's body.
[0007] One method includes: receiving a patient-specific vascular
model of a patient's anatomy, including at least one vessel of the
patient; receiving a patient-specific tissue model including at
least a portion of tissue of the patient's anatomy; receiving an
estimate of heat content of the portion of tissue of the
patient-specific tissue model or tissue surrounding the portion of
tissue; determining an estimate of heat distribution of the portion
of tissue of the patient-specific tissue model or tissue
surrounding the portion of tissue based on the vascular model, the
tissue model, or the received estimate of heat content; and output
the determined estimate of heat distribution to a storage medium or
user display.
[0008] In accordance with another embodiment, a system for
providing personalized estimates of bioheat transfer through a
patient's body or a portion of a patient's body comprises: a data
storage device storing instructions for providing personalized
estimates of bioheat transfer through a patient's body or a portion
of a patient's body; and a processor configured for: receiving a
patient-specific vascular model of a patient's anatomy, including
at least one vessel of the patient; receiving a patient-specific
tissue model including at least a portion of tissue of the
patient's anatomy; receiving an estimate of heat content of the
portion of tissue of the patient-specific tissue model or tissue
surrounding the portion of tissue; determining an estimate of heat
distribution of the portion of tissue of the patient-specific
tissue model or tissue surrounding the portion of tissue based on
the vascular model, the tissue model, or the received estimate of
heat content; and output the determined estimate of heat
distribution to a storage medium or user display.
[0009] In accordance with another embodiment, a non-transitory
computer readable medium for use on a computer system containing
computer-executable programming instructions for performing a
method of providing personalized estimates of bioheat transfer
through a patient's body or a portion of a patient's body, the
method comprising: receiving a patient-specific vascular model of a
patient's anatomy, including at least one vessel of the patient;
receiving a patient-specific tissue model including at least a
portion of tissue of the patient's anatomy; receiving an estimate
of heat content of the portion of tissue of the patient-specific
tissue model or tissue surrounding the portion of tissue;
determining an estimate of heat distribution of the portion of
tissue of the patient-specific tissue model or tissue surrounding
the portion of tissue based on the vascular model, the tissue
model, or the received estimate of heat content; and output the
determined estimate of heat distribution to a storage medium or
user display.
[0010] Additional objects and advantages of the disclosed
embodiments will be set forth in part in the description that
follows, and in part will be apparent from the description, or may
be learned by practice of the disclosed embodiments. The objects
and advantages of the disclosed embodiments will be realized and
attained by means of the elements and combinations particularly
pointed out in the appended claims.
[0011] It is to be understood that both the foregoing general
description and the following detailed description are exemplary
and explanatory only and are not restrictive of the disclosed
embodiments, as claimed.
BRIEF DESCRIPTION OF THE DRAWINGS
[0012] The accompanying drawings, which are incorporated in and
constitute a part of this specification, illustrate various
exemplary embodiments, and together with the description, serve to
explain the principles of the disclosed embodiments.
[0013] FIG. 1 is a block diagram of an exemplary system and network
for providing personalized estimates of bioheat transfer through a
patient's body or a portion of a patient's body, according to an
exemplary embodiment of the present disclosure.
[0014] FIG. 2 is a flow diagram of an exemplary method of providing
personalized estimates of bioheat transfer through a patient's body
or a portion of a patient's body, according to an exemplary
embodiment of the present disclosure.
[0015] FIG. 3 is a flow diagram of an exemplary method of
generating personalized examples of heat transfer in a patient's
body, according to an exemplary embodiment of the present
disclosure.
[0016] FIG. 4 is a flow diagram of an exemplary method of
generating personalized examples of heat transfer in a patient's
body involving rapid changes in body temperature, according to an
exemplary embodiment of the present disclosure.
[0017] FIG. 5A is a flow diagram of an exemplary method of
analyzing heat transfer in a patient's myocardium as a result of
ablation, according to an exemplary embodiment of the present
disclosure.
[0018] FIG. 5B is a flow diagram of an exemplary method of
analyzing heat transfer in a patient's tissue as a result of
ablation, according to an exemplary embodiment of the present
disclosure.
[0019] FIG. 6 is a flow diagram of an exemplary method of analyzing
heat transfer in musculoskeletal tissue, according to an exemplary
embodiment of the present disclosure.
DESCRIPTION OF THE EMBODIMENTS
[0020] Reference will now be made in detail to the exemplary
embodiments of the disclosure, 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.
[0021] As described above, a desire exists for understanding
bioheat transfer specific to an individual. For example, the
capability to model bioheat (e.g., heat transfer or heat
distribution) in a patient's body may improve an evaluation of the
severity of disease and of the appropriateness of treatment.
[0022] This disclosure describes systems and methods for
determining bioheat transfer in a patient by modeling the effects
of blood flow, tissue, and the external environment on the
distribution of heat in the patient's body. For example, the
systems and methods may address both bioheat modeling throughout
the patient's body and/or the modeling of bioheat transfer in
isolated organs and body parts. It should be appreciated that any
of the following techniques and descriptions should be construed to
include analysis of heat transfer through a patient's entire body,
an entire organ of the patient's body, or one or more parts of the
body or organs. The embodiments of this disclosure may permit
planning and assessing the effectiveness of temperature-related
treatments for a patient, e.g., in the relief of whole body
temperature conditions or focally-applied therapeutics. By
extension, the embodiments of this disclosure provide assessments
or recommendations of effective temperature-related treatment and
aid the design and development of new temperature-related
treatments and devices.
[0023] Referring now to the figures, FIG. 1 depicts a block diagram
of an exemplary system 100 and network for providing personalized
estimates of bioheat transfer through a patient's body or a portion
of a patient's body, according to an exemplary embodiment.
Specifically, FIG. 1 depicts a plurality of physicians 102 and
third party providers 104, any of whom may be connected to an
electronic network 101, such as the Internet, through one or more
computers, servers, and/or handheld mobile devices. Physicians 102
and/or third party providers 104 may create or otherwise obtain
images of one or more patients' anatomy. The physicians 102 and/or
third party providers 104 may also obtain any combination of
patient-specific information, e.g., age, medical history, blood
pressure, blood viscosity, body temperature, patient activity or
exercise level, etc. Physicians 102 and/or third party providers
104 may transmit the anatomical images and/or patient-specific
information to server systems 106 over the electronic network 101.
Server systems 106 may include storage devices for storing images
and data received from physicians 102 and/or third party providers
104. Server systems 106 may also include processing devices for
processing images and data stored in the storage devices. For the
purposes of the disclosure, "patient" may refer to any individual
or person for whom diagnosis or treatment analysis is being
performed, or any individual or person associated with the
diagnosis or treatment analysis of one or more individuals.
[0024] FIG. 2 depicts a general embodiment of a method for
estimating a heat distribution in a target tissue. FIG. 3 and FIG.
4 depict exemplary methods for evaluating heat transfer throughout
a patient's entire body or portions thereof. For example, FIG. 3
shows an exemplary method for analyzing thermoregulation of a
patient's body. FIG. 4 shows an exemplary method of analyzing a
body's thermoregulation in association with a therapy that may
include rapid cooling or heating in a portion of a patient's body.
FIGS. 5A, 5B, and 6 depict exemplary methods for evaluating heat
transfer in particular portions of a patient's body. For example,
FIGS. 5A and 5B show exemplary methods for analyzing heat transfer
from ablation in a patient's myocardium and/or in a patient's
tissue, respectively. FIG. 6 depicts an exemplary method for heat
transfer in musculoskeletal tissue, e.g., from a heating or cooling
apparatus externally applied to a patient's skin. Heating or
cooling apparatuses may include heating packs/pads or cooling
packs, or electrical or other medical devices.
[0025] Any of the embodiments depicted in FIGS. 2-6 may be
modified, for example, to include variations or changes of
circulation, blood flow temperature, and/or patient anatomy.
Changes in circulation may reflect scenarios where a physician may
temporarily increase or decrease circulation locally (e.g., via a
tourniquet, balloon catheter, hyperbaric chamber, etc.) in order to
better control heat transfer in a patient and/or increase the
safety of a procedure. In such an embodiment, any of the above
methods may be modified to account for this increased or decreased
circulation, e.g., by adjusting the blood flow simulation boundary
conditions to reflect the modified circulation. Modified
circulation may further include temporary stops to blood flow. For
example, some surgery may involve halting blood flow for a period
of time, e.g., inducing deep systemic hypothermia for
cerebral/cardiac protection during the surgery. The disclosed
systems and methods may be modified to model and assess any range
of changes to circulation.
[0026] Another modification may include a modeling a bolus of
heat/cold injected into the bloodstream, e.g., to change the local
environment. This type of change may allow safer/more effective
application or introduction of heat/cold to a patient's body. Such
an embodiment may be computed, e.g., by introducing a differential
heat/cold in the blood over a period of time when solving the
advection-diffusion equation.
[0027] Furthermore, any of the exemplary methods depicted in FIGS.
2-6 may be used in conjunction with a modified patient model,
including but not limited to a patient model modified to reflect
revascularization or target tissue change in the patient's anatomy
and/or a change in the parameters of the advection-diffusion
equation.
[0028] FIG. 2 is a flow diagram of an exemplary method 200 of
providing personalized estimates of bioheat transfer through a
patient's body or a portion of a patient's body, according to an
exemplary embodiment. The method of FIG. 2 may be performed by
server systems 106, based on information, images, and data received
from physicians 102 and/or third party providers 104 over
electronic network 101.
[0029] In one embodiment, step 201 may include receiving an
estimate of blood flow demand in at least a portion of a patient's
body. For example, step 201 may include receiving a
patient-specific vascular model in an electronic storage medium
(e.g., hard drive, network drive, cloud drive, mobile phone,
tablet, etc.) of the server systems 106. Specifically, receiving
the patient-specific vascular model may include either generating
the patient-specific vascular model at the server system 106, or
receiving one over electronic network (e.g., electronic network
101). The vasculature may be obtained, for example, via imaging,
including computed tomography (CT) or magnetic resonance (MR)
imaging. The patient-specific vascular model may include an
estimate of blood flow demand in one or more portions of the
vascular model.
[0030] In one embodiment, step 203 may include receiving a
patient-specific tissue model of at least the tissue in which heat
transfer may be estimated. In one embodiment, the patient-specific
tissue model may be received in an electronic storage medium. The
tissue model and/or the tissue in which heat transfer may be
estimated, may be referred to as, "target tissue."
[0031] In one embodiment, step 205 may include receiving an
estimate of heat content, e.g., temperature, of one or more areas
of the target tissue and/or surrounding environment (e.g.,
anatomical environment or patient environment). In one embodiment,
a patient environment may include the surrounding environment may
include an environment surrounding a target tissue, e.g., an
environment around a patient's heart or brain that may influence
temperature(s) within the patient's heart or brain). In one
embodiment, the estimate of heat content may include a temperature
of one or more areas of the target tissue and/or surrounding
environment at one instant in time. For example, the instant in
time may serve as an initial time (e.g., T.sub.0). The temperature
estimate of step 205 may include an initial temperature of the
surrounding anatomical environment, e.g., as given by a (systemic)
core heat. Such core heat may be derived from body temperature,
activity level, etc.
[0032] In one embodiment, step 207 may include determining an
estimate of the heat distribution of the target tissue and/or blood
at a second instant in time based on the vascular model, target
tissue model, and/or initial estimate of heat content. Step 207 may
be performed using a processor (e.g., laptop, desktop, cloud
computing architecture, graphics processing unit (GPU), digital
signal processor (DSP), mobile phone, tablet, etc.).
[0033] In one embodiment, step 209 may include outputting the
estimate of the heat distribution (e.g., of step 207) to an
electronic storage medium and/or a user display (e.g., monitor,
mobile phone, tablet). The user display may include rendering
estimated heat distribution of the patient-specific vascular model
and/or rendering estimated heat distribution of the target tissue
(e.g., the tissue model). Step 209 may further include features
comprising one or more of: simulations of heat distribution through
the tissue model (e.g., color-coded temperature maps), interactive
options or prompts to adjust circulation, temperature, or model
geometry at any location in rendered vascular and/or tissue models,
menu selections associated with various treatments to apply for
modeling (including temperature-based and non-temperature-based
treatments), options or suggestions to adjust time frames for heat
distribution (e.g., recommendations of time intervals or times at
which to perform follow-up assessments of bioheat changes),
comparisons of various modeled bioheat scenarios (for a single
patient and comparisons between patients), etc. Displays for
comparisons may include overlays and/or side-by-side panels
displaying various portions of the patient-specific vascular and/or
tissue model.
[0034] FIGS. 3 and 4 depict analyses of heat transfer in a
patient's body. In other words, the methods shown in FIGS. 3 and 4
may be relevant for studying thermoregulation. Thermoregulation is
a metabolic function that may be challenged by conditions including
hypothermia, hyperthermia, heat stroke, and/or heat exhaustion. An
analysis of heat transfer in the patient's entire body may help
evaluate the effectiveness of therapy to address one of these
conditions or to develop new therapeutic methods for addressing
these conditions. FIG. 3 shows an exemplary method of such an
analysis of heat transfer. FIG. 4 shows an exemplary method of such
an analysis of heat transfer in a patient's entire body, where the
analysis may involve treating one or more of the metabolic
conditions by, at least, employing a therapy that may apply rapid
cooling and/or heating to a portion of the patient's body.
[0035] FIG. 3 is a flow diagram of an exemplary method 300 of
analyzing heat transfer in a patient's body, according to an
exemplary embodiment. The method of FIG. 3 may be performed by
server systems 106, based on information, images, and data received
from physicians 102 and/or third party providers 104 over
electronic network 101.
[0036] In one embodiment, step 301 may include receiving a
patient-specific vascular model of the patient's whole-body
vasculature in an electronic storage medium (e.g., hard drive,
network drive, cloud drive, mobile phone, tablet, etc.). This model
may include large vessels (e.g., obtained via imaging, including CT
and/or MR) and/or microvasculature perfusing the tissue. The
microvasculature may be measured or simulated (e.g., generated via
a constrained constructive optimization). The vascular model may
include arteries, veins, or some combination of arteries and
veins.
[0037] In one embodiment, step 303 may include receiving a
patient-specific model of the patient's tissue, including organs
and muscles (e.g., the target tissue) in an electronic storage
medium. This model may be extracted from a medical imaging scan
(e.g., via CT or MR imaging).
[0038] In one embodiment, step 305 may include receiving an
estimate of heat content in one or more areas of the target tissue
at one instant in time. In one embodiment, the target tissue may be
estimated or modeled as homogeneous at a reduced (hypothermia)
temperature and/or a raised (hyperthermia) temperature. Deep organs
known to source heat during thermoregulation (e.g., liver, brain,
and/or heart) may be initialized with a temperature closer to the
patient's homeostatic temperature (e.g., 37.degree. Celsius).
[0039] In one embodiment, step 307 may include determining an
estimate of the heat distribution of the target tissue at a second
instant in time based on the cardiovascular model, target tissue
model, and/or initial estimate of heat content. In one embodiment,
step 307 may include using a processor (e.g., laptop, desktop,
cloud computing architecture, GPU, DSP, mobile phone, tablet, etc.)
to determine the estimate of the heat distribution in the target
tissue at the second instant in time.
[0040] For example, step 307 may include estimating the heat
distribution by determining the blood flow in the vascular model
(e.g., from step 301). Estimating blood flow may include an
analysis involving 3D computational fluid dynamics, a reduced order
model, and/or estimation from a database (e.g., using machine
learning). Estimating blood flow may also include determining blood
flow demand. For instance, step 307 may include performing a
patient-specific estimate of blood flow in the patient's
vasculature based on an estimate of blood flow demand (e.g., from
the target tissue mass or total vascular volume). Blood flow demand
may include volumetric flow are, blood flow velocity, or velocity
field (e.g., in a cross-section of a segment of a vessel or a
portion of the target tissue). Blood flow demand may include the
amount of blood flow sufficient for an organ to meet metabolic
needs, e.g. the amount of blood flow provided by the myocardium to
meet oxygen requirements during physical activity. Blood flow
demand may be represented as a flow rate per unit of tissue or
organ, and blood flow demand may be met by the flow rate through
the vasculature supplying that tissue or organ. In other words, one
embodiment of step 307 may include estimating blood flow demand of
a tissue mass or vascular volume, determining blood flow to the
tissue mass or through the vascular volume (given the blood flow
demand of the respective tissue or vasculature), and estimating
heat distribution through the tissue or vasculature from the
determined blood flow.
[0041] One embodiment of determining heat distribution using blood
flow may include arteriolar vasodilation and/or vasoconstriction
modeling to reflect patient blood flow under various patient
physiological states or external conditions. For example, the
arteriolar vasodilation and/or vasoconstriction modeling may
include modeling an increase the skin perfusion in hyperthermic
conditions or modeling a decrease skin perfusion in hypothermic
conditions. The modeling of arteriolar vasodilation and/or
vasoconstriction may be performed by reducing or increasing the
resistance in a boundary condition model at one or more outlets of
the supplying arterial system or, alternatively or in addition, by
changing the caliber of an explicit microcirculation network model
within the tissue itself, based on the temperature in the tissue or
organ.
[0042] Heat distribution may be determined from blood flow by way
of advection-diffusion equations. For example, step 307 may include
determining patient-specific heat transfer by solving an
advection-diffusion equation for the temperature in which an
estimated blood flow velocity field (e.g., from an estimated blood
flow and/or blood flow demand) may be assumed to provide advection
of heat in the target tissue.
[0043] In some embodiments, patient heat transfer properties (e.g.
conductivity) may be assigned from data acquired from imaging
sources or literature. Another option may include assuming uniform
material properties in the target tissue. Boundary conditions for
modeling patient-specific heat transfer may be applied at the skin
boundaries (e.g., using Dirichlet boundary conditions for the room
temperature and modeling a loss at the skin boundary due to sweat
evaporation during hyperthermic conditions). In some cases, the
heat transfer equation (advection-diffusion equation) may be solved
for a fixed time (e.g., several seconds) or for a steady-state
solution to produce an estimated heat distribution at one or more
additional time instants.
[0044] In one embodiment, step 309 may include outputting the one
or more estimated heat distributions in the target tissue, e.g., to
an electronic storage medium or a user display (e.g., monitor,
mobile phone, tablet, etc.).
[0045] FIG. 4 is a flow diagram of an exemplary method 400 of
analyzing heat transfer in a patient's body where body temperature
may rapidly change, according to an exemplary embodiment. The
method of FIG. 4 may be performed by server systems 106, based on
information, images, and data received from physicians 102 and/or
third party providers 104 over electronic network 101.
[0046] In one embodiment, step 401 may include receiving a
patient-specific vascular model of the whole-body vasculature in an
electronic storage medium (e.g., hard drive, network drive, cloud
drive, mobile phone, tablet, etc.). This model may include large
vessels (e.g., obtained via imaging such as CT or MR) and/or
microvasculature perfusing the tissue. The microvasculature may be
measured and/or simulated (e.g., via a constrained constructive
optimization). The vascular model may include arteries, veins, or
some combination of arteries and veins.
[0047] In one embodiment, step 403 may include receiving a
patient-specific model of the patient tissue, including organs and
muscles (the target tissue) in an electronic storage medium. This
model may be extracted from a medical imaging scan (e.g., CT or
MR).
[0048] In one embodiment, step 405 may include receiving an
estimate of heat content in one or more areas of the target tissue
at one instant in time. In one embodiment, the target tissue may be
estimated or modeled as homogeneous at a reduced (hypothermia)
temperature and/or at a raised (hyperthermia) temperature. Deep
organs known to source heat during thermoregulation (e.g., liver,
brain and heart) may be initialized with a temperature closer to
the homeostatic temperature (e.g., 37.degree. Celsius).
[0049] In one embodiment, step 407 may include determining an
estimate of the heat distribution in the target tissue at a second
instant in time based on the cardiovascular model, target tissue
model, and/or initial estimate of heat content. In one embodiment,
step 407 may include using a processor (e.g., laptop, desktop,
cloud computing architecture, GPU, DSP, mobile phone, tablet, etc.)
to determine the estimate of the heat distribution in the target
tissue at the second instant in time.
[0050] The estimate of blood flow may be determined by first
determining the blood flow in the cardiovascular model in a
simulated physiological state. For instance, step 407 may include
performing a patient-specific estimate of blood flow in the
patient's vasculature using an estimate of the patient's blood flow
demand (e.g., from the target tissue mass or total vascular
volume). Estimating blood flow may include analyzing 3D
computational fluid dynamics, a reduced order model, or blood flow
estimates from a database (e.g., using machine learning). One
embodiment of determining heat distribution using blood flow may
include arteriolar vasodilation and/or vasoconstriction modeling to
reflect patient blood flow under various patient physiological
states or external conditions. For example, the arteriolar
vasodilation and/or vasoconstriction modeling may include modeling
an increase the skin perfusion in hyperthermic conditions or
modeling a decrease skin perfusion in hypothermic conditions.
[0051] In one embodiment, a patient-specific heat transfer may be
determined by solving an advection-diffusion equation. For example,
step 407 may include solving an advection-diffusion equation for
the concentration of heat in which the estimated blood flow
velocity field (e.g., from an estimated blood flow and/or blood
flow demand) may be assumed to provide advection in the target
tissue.
[0052] Step 407 of estimating the heat distribution may include
setting one or more conditions for determining the estimate. For
example, patient heat transfer properties (e.g., diffusivity) may
be assigned from data acquired from imaging sources or literature.
Another option for setting conditions to estimate heat distribution
may include assuming uniform material properties in the target
tissue. Boundary conditions may be applied at the skin boundaries
(e.g., using Dirichlet boundary conditions for the room temperature
and modeling a loss at the skin boundary due to sweat evaporation
during hyperthermic conditions). In particular, the applied
heat/cooling source may be virtually applied as a Dirichlet
boundary condition fixing a constant temperature (e.g., hot or
cold, depending on the device) over the portion of skin affected by
the source. The heat transfer equation may be solved for a fixed
time (e.g., several seconds) or for a steady-state solution to
produce an estimated heat distribution at one or more additional
time instants.
[0053] In one embodiment, step 409 may include outputting the one
or more estimated heat distributions in the target tissue, e.g., to
an electronic storage medium or a user display (e.g., monitor,
mobile phone, tablet, etc.).
[0054] FIGS. 5A, 5B, and 6 include exemplary analyses of local heat
transfer in, at least, portions of a patient's body. For example,
exemplary methods of FIGS. 5A and 5B include analyses of heat
transfer in connection with ablation in various parts of a
patient's body. FIG. 5A includes an exemplary method for analyzing
heat transfer in the myocardium associated with ablation. An
analysis of heat transfer in the myocardium may assess the
effectiveness of an RF ablation or cryoablation procedure (e.g.,
for treating left ventricular tachycardia, supraventricular
tachycardia, Wolff-Parkinson-White syndrome, atrial tachycardia,
multifocal atrial tachycardia or atrial fibrillation) and/or to
determine preferable or optimal settings for the ablation. FIG. 5B
includes an exemplary method for analyzing heat transfer in tissue
(e.g., organ tissue) associated with ablation. An analysis of heat
transfer in organ tissue may help assess the effectiveness of an RF
ablation, cryoablation, ablation performed using external beam
radiation or high frequency ultrasound (HIFU), cryogenic, and/or
cryotherapy treatment procedure (e.g., for treating cancer of the
liver, bone, lung, spleen, skin, prostate or kidney by destroying
tumors or lesions). The exemplary method described in FIG. 6
includes analyses of heat transfer in musculoskeletal tissue. An
analysis of heat transfer in the musculoskeletal tissue may be
useful, e.g., in sports medicine to assess the effectiveness of
heat transfer from a heating or cooling apparatus applied to the
exterior of the skin to a patient's muscles. Such an analysis may
help determine settings for heating/cooling apparatus size,
temperature, and/or location as well as assist in the design of
more effective heating/cooling apparatuses.
[0055] FIG. 5A is a flow diagram of an exemplary method 500 of
analyzing heat transfer in a patient's myocardium associated with
ablation, according to an exemplary embodiment. The method of FIG.
5A may be performed by server systems 106, based on information,
images, and data received from physicians 102 and/or third party
providers 104 over electronic network 101.
[0056] In one embodiment, step 501 may include receiving a
patient-specific coronary vascular model in an electronic storage
medium (e.g., hard drive, network drive, cloud drive, mobile phone,
tablet, etc.). This model may include large coronary vessels (e.g.,
obtained via imaging, including CT and/or MR) and/or include
microvasculature perfusing the tissue. The microvasculature may be
measured or simulated (e.g., via a constrained constructive
optimization). The vascular model may include arteries, veins, or
some combination of arteries and veins.
[0057] In one embodiment, step 503 may include receiving a
patient-specific model of the patient tissue, including the
myocardium (or epicardium, atrial wall, etc.) as the target tissue
in an electronic storage medium. This model may be extracted from a
medical imaging scan (e.g., CT and/or MR).
[0058] In one embodiment, step 505 may include receiving an
estimate of heat content in one or more areas of the target tissue
at one instant in time. In one embodiment, the target tissue may be
estimated or modeled as homogeneous at body temperature, except for
the location of an ablation catheter which may be set to a
prespecified temperature in a localized area (e.g., at a
temperature of 50.degree. Celsius in an area of 4 mm for RF
ablation or a temperature of -10.degree. to -70.degree. Celsius for
cryoablation). The ablation catheter location in the target tissue
may be represented virtually (e.g., for pre-procedure simulation
and planning) or may be represented in its actual location during a
procedure (e.g., using positioning on the catheter tip).
[0059] In one embodiment, step 507 may include determining an
estimate of the heat distribution in the target tissue and/or blood
at a second instant in time based on the cardiovascular model,
target tissue model, and/or initial estimate of heat content. In
one embodiment, step 507 may include using a processor (e.g.,
laptop, desktop, cloud computing architecture, GPU, DSP, mobile
phone, tablet, etc.) to determine the estimate of the heat
distribution in the target tissue at the second instant in
time.
[0060] The estimate may be determined by first determining the
blood flow in the cardiovascular model in a simulated physiological
state. For instance, step 507 may include performing a
patient-specific estimate of blood flow in the patient's coronaries
using an estimate of the patient's blood flow demand. The blood
flow demand may include the blood flow demand from the total
vascular volume or the myocardial mass (e.g., the mass of the
target tissue). Estimating blood flow may include analyzing 3D
computational fluid dynamics, a reduced order model, or blood flow
estimates from a database (e.g., using machine learning).
[0061] In one embodiment, a patient-specific heat transfer may be
determined by solving an advection-diffusion equation. For example,
step 507 may include solving an advection-diffusion equation for
the concentration of heat in which the estimated blood flow
velocity field (e.g., from an estimated blood flow and/or blood
flow demand) may be assumed to provide advection in the target
tissue.
[0062] Step 507 of estimating the heat distribution may include
setting one or more conditions for determining the estimate. For
example, patient heat transfer properties (e.g., diffusivity) may
be assigned from data acquired from imaging sources or literature.
Another option may including assuming uniform material properties
in the target tissue. Boundary conditions may be applied at the
endocardial and epicardial surfaces using empirically-derived
values (e.g., using Dirichlet boundary conditions with a
homeostatic temperature for the endocardium and epicardium) and/or
by coupling to another computational model (e.g., a heat-transfer
model in the whole body or a pulsatile blood flow model in a
dynamic heart). The heat transfer equation may be solved for a
fixed time (e.g., several seconds) or for a steady-state solution
to produce an estimated heat distribution, e.g., at one or more
additional time instants.
[0063] In one embodiment, step 509 may include outputting the one
or more estimated heat distributions in the target tissue, e.g., to
an electronic storage medium or a user display (e.g., monitor,
mobile phone, tablet, etc.).
[0064] FIG. 5B is a flow diagram of an exemplary method 520 of
analyzing heat transfer in tissue associated with ablation,
according to an exemplary embodiment. The method of FIG. 5B may be
performed by server systems 106, based on information, images, and
data received from physicians 102 and/or third party providers 104
over electronic network 101.
[0065] In one embodiment, step 521 may include receiving a
patient-specific vascular model of the vasculature in the target
tissue and/or surrounding tissue in an electronic storage medium
(e.g., hard drive, network drive, cloud drive, mobile phone,
tablet, etc.). This model may include large vessels (e.g., obtained
via imaging such as CT or MR) and/or include microvasculature
perfusing the tissue. The microvasculature may be measured or
simulated (e.g., via a constrained constructive optimization). The
vascular model may include arteries, veins, or some combination of
arteries and veins.
[0066] In one embodiment, step 523 may include receiving a
patient-specific model of target ablation tissue (e.g., the tissue
containing a tumor or lesion) as the target tissue in an electronic
storage medium. In some embodiments, the tissue may include organ
tissue, e.g., liver tissue, lung tissue, and/or kidney tissue. This
model may be extracted from a medical imaging scan (e.g., CT or
MR).
[0067] In one embodiment, step 525 may include receiving an
estimate of heat content in one or more areas of the target tissue
at one instant in time. In one embodiment, the target tissue may be
estimated or modeled as homogeneous at body temperature, except for
the location of an ablation catheter which is set to a prespecified
temperature in a localized area (e.g., at a temperature of
50.degree. Celsius in an area of 4 mm for RF ablation or a
temperature of -10.degree. to -70.degree. Celsius for
cryoablation). The temperature at which the body may be modeled,
may be derived from the ambient temperature and/or via a systemic
temperature controlled to make the localized heating/cooling safer
for the patient. The ablation catheter location in the target
tissue may be represented virtually (e.g., for pre-procedure
simulation and planning) or may be represented in its actual
location during a procedure (e.g., using positioning on the
catheter tip).
[0068] In one embodiment, step 527 may include determining an
estimate of the heat distribution in the target tissue and/or blood
at a second instant in time based on the vascular model, target
tissue model, and/or initial estimate of heat content. In one
embodiment, step 527 may include using a processor (e.g., laptop,
desktop, cloud computing architecture, GPU, DSP, mobile phone,
tablet, etc.) to determine the estimate of the heat distribution in
the target tissue at the second instant in time.
[0069] The estimate of the heat distribution may be determined by
determining the blood flow in the vascular model in a simulated
physiological state. For instance, step 527 may include performing
a patient-specific estimate of blood flow in the patient's
vasculature using an estimate of the patient's blood flow demand
(e.g., from the target tissue mass or total vascular volume).
Estimating blood flow may include analyzing 3D computational fluid
dynamics, a reduced order model, or blood flow estimates from a
database (e.g., using machine learning).
[0070] In one embodiment, a patient-specific heat transfer may be
determined by solving an advection-diffusion equation. For example,
step 527 may include solving an advection-diffusion equation for
the concentration of heat in which the estimated blood flow
velocity field (e.g., from an estimated blood flow and/or blood
flow demand) may be assumed to provide advection in the target
tissue.
[0071] Step 527 of estimating the heat distribution may include
setting one or more conditions for determining the estimate. For
example, patient heat transfer properties (e.g. diffusivity) may be
assigned from data acquired from imaging sources or literature.
Another option may include assuming uniform material properties in
the target tissue. Boundary conditions may be applied at the
endocardial and epicardial surfaces using empirically-derived
values (e.g., using Dirichlet boundary conditions with a
homeostatic temperature for the target tissue surface) and/or by
coupling to another computational model (e.g., a heat-transfer
model in the whole body including multiple organs, fat, fluid,
bone, etc.). The heat transfer equation may be solved for a fixed
time (e.g., several seconds) or for a steady-state solution to
produce an estimated heat distribution, e.g., at one or more
additional time instants.
[0072] In one embodiment, step 529 may include outputting the one
or more estimated heat distributions in the target tissue, e.g., to
an electronic storage medium or a user display (e.g., monitor,
mobile phone, tablet, etc.).
[0073] FIG. 6 is a flow diagram of an exemplary method 600 of
analyzing heat transfer in musculoskeletal tissue, according to an
exemplary embodiment. The method of FIG. 6 may be performed by
server systems 106, based on information, images, and data received
from physicians 102 and/or third party providers 104 over
electronic network 101.
[0074] In one embodiment, step 601 may include receiving a
patient-specific peripheral vascular model in an electronic storage
medium (e.g., hard drive, network drive, cloud drive, mobile phone,
tablet, etc.). This model may include one or more of the large
peripheral vessels (e.g., obtained via imaging such as CT or MR)
and/or including microvasculature perfusing the target muscle
tissue and/or microvasculature perfusing the body exterior (e.g.,
skin). The microvasculature may be measured or simulated (e.g., via
a constrained constructive optimization). The vascular model may
include arteries, veins, or some combination of arteries and
veins.
[0075] In one embodiment, step 603 may include receiving a
patient-specific model of target muscle tissue (e.g., the
quadriceps femoris or any other arm, leg, hip, hand or foot muscle)
as the target tissue in an electronic storage medium. This model
may be extracted from a medical imaging scan (e.g., CT or MR). For
a more comprehensive model, the target tissue may be taken as a
particular muscle and the surrounding muscle, bone, fat, and fluid.
The initial temperature of the surrounding muscle, bone, fat, and
fluid may be given by a (systemic) core heat derived from body
temperature, activity level, etc.
[0076] In one embodiment, step 605 may include receiving an
estimate of heat content in one or more areas of the target tissue
at one instant in time. In one embodiment, the target tissue may be
estimated or modeled as homogeneous at body temperature, except for
the location of the heating/cooling apparatus in a localized area
of the body exterior. The heating/cooling apparatus location in the
target tissue may be represented virtually (e.g., for
pre-application simulation and planning) or may be represented in
its actual location during an application (e.g., using positioning
on the catheter tip). In one embodiment, the temperature at which
the body may be modeled may be derived from the ambient
temperature.
[0077] In one embodiment, step 607 may include determining an
estimate of the heat distribution in the target tissue at a second
instant in time based on the vascular model, target tissue model,
and/or initial estimate of heat content. In one embodiment, step
607 may include using a processor (e.g., laptop, desktop, cloud
computing architecture, GPU, DSP, mobile phone, tablet, etc.) to
determine the estimate of the heat distribution in the target
tissue at the second instant in time.
[0078] The estimate may be determined by determining the blood flow
in the cardiovascular model in a simulated physiological state. For
instance, step 607 may include performing a patient-specific
estimate of blood flow in the patient's coronaries using an
estimate of the patient's blood flow demand (e.g., from the target
muscle mass or total vascular volume). Estimating blood flow may
include analyzing 3D computational fluid dynamics, a reduced order
model, and/or blood flow estimates from a database (e.g., using
machine learning).
[0079] In one embodiment, a patient-specific heat transfer may be
determined by solving an advection-diffusion equation. For example,
step 607 may include solving an advection-diffusion equation for
the concentration of heat in which the estimated blood flow
velocity field (e.g., from an estimated blood flow and/or blood
flow demand) may be assumed to provide advection in the target
tissue.
[0080] Step 607 of estimating the heat distribution may include
setting one or more conditions for determining the estimate. For
example, patient heat transfer properties (e.g., diffusivity) may
be assigned from data acquired from imaging sources or literature.
Another option may including assuming uniform material properties
in the target tissue. Boundary conditions may be applied at the
target tissue surface using empirically-derived values and/or
estimated values, e.g., based on core temperature, activity levels,
and/or coupling to another computational model (e.g., a
heat-transfer model in the whole body or a pulsatile blood flow
model in a dynamic heart). Alternatively or in addition, boundary
conditions may be applied in a wider field of view (e.g., applied a
homeostatic body temperature boundary condition at the borders of a
larger anatomical model encompassed, for example, by the entire
field of view of a medical image). The heat transfer equation may
be solved for a fixed time (e.g., several seconds) and/or for a
steady-state solution. One or more solutions from the heat transfer
equation may be used to produce an estimated heat distribution at
one or more additional time instants.
[0081] In one embodiment, step 609 may include outputting the one
or more estimated heat distributions in the target tissue, e.g., to
an electronic storage medium or a user display (e.g., monitor,
mobile phone, tablet, etc.).
[0082] The ability of bodies to regulate temperature or respond to
temperature changes may vary between individuals.
Temperature-related conditions may negatively impact a patient
(e.g., causing hypothermia or hyperthermia), or temperature may be
used to treat a patient (e.g., in treating hypothermia/hyperthermia
or in ablation). Different patients may respond to temperature and
treatment differently, depending on the unique ways that each
patient's body may conduct bioheat transfer. The present disclosure
includes systems and methods for determining bioheat transfer
specific to an individual. For example, the disclosure includes
systems and methods for modeling bioheat transfer specifically for
the individual's anatomy, as extracted from patient-specific
imaging. For instance, the present disclosure includes an exemplary
embodiment of modeling patient-specific bioheat transfer by
estimating heat diffusion from blood flow through the patient's
anatomy. An understanding of patient-specific bioheat transfer may
improve treatment efficacy for temperature-related ailments and
treatments.
[0083] Other embodiments of the invention will be apparent to those
skilled in the art from consideration of the specification and
practice of the invention disclosed herein. It is intended that the
specification and examples be considered as exemplary only, with a
true scope and spirit of the invention being indicated by the
following claims.
* * * * *