International Journal for Numerical Methods in Biomedical Engineering,
Год журнала:
2024,
Номер
40(12)
Опубликована: Ноя. 11, 2024
ABSTRACT
Reported
in
this
paper
is
a
cutting‐edge
computational
investigation
into
the
influence
of
geometric
characteristics
on
abdominal
aortic
aneurysm
(AAA)
rupture
risk,
beyond
traditional
measure
maximum
diameter.
A
Comprehensive
fluid–structure
interaction
(FSI)
analysis
was
employed
to
assess
risk
factors
range
patient
scenarios,
with
use
three‐dimensional
(3D)
AAA
models
reconstructed
from
patient‐specific
data
and
finite
element
method.
Wall
shear
stress
(WSS),
its
derivatives
such
as
time‐averaged
WSS
(TAWSS),
oscillatory
index
(OSI),
relative
residence
time
(RRT)
transverse
(transWSS)
offer
insights
force
dynamics
acting
wall.
Emphasis
placed
these
WSS‐based
metrics
seven
key
indices.
By
correlating
discrepancies
biomechanical
phenomena,
study
highlights
novel
profound
impact
geometry
prediction.
This
demonstrates
necessity
multidimensional
assessment
approach,
future
efforts
should
complement
findings
experimental
validations
for
an
applicable
approach
clinical
use.
Background:
Abdominal
aortic
aneurysms
(AAAs)
present
a
formidable
public
health
concern
due
to
their
propensity
for
localized,
anomalous
expansion
of
the
abdominal
aorta.
These
insidious
dilations,
often
in
early
stages,
mask
life-threatening
potential
rupture,
which
carries
grave
prognosis.
Understanding
hemodynamic
intricacies
governing
AAAs
is
paramount
predicting
aneurysmal
growth
and
imminent
risk
rupture.
Objective:
Our
extensive
investigation
delves
into
this
complex
environment
intrinsic
AAAs,
utilizing
comprehensive
numerical
analyses
physiological
pulsatile
blood
flow
realistic
boundary
conditions
explore
multifaceted
dynamics
influencing
aneurysm
rupture
risk.
study
introduces
novel
elements
by
integrating
these
parameters
overall
context
pathophysiology,
thus
advancing
our
understanding
intricate
mechanics
evolution
Methods:
Conservation
mass
momentum
equations
are
used
model
an
solved
using
finite
volume-based
ANSYS
Fluent
solver.
Resistance
pressure
outlets
following
three-element
Windkessel
were
imposed
at
each
outlet
accurately
AAAs’
shear
stress.
Results:
results
uncover
elevated
velocities
within
aneurysm,
suggesting
augmented
future
increased
stress
wall.
During
systole
phase,
high
wall
(WSS)
was
observed,
typically
associated
with
lower
while
low
oscillatory
index
(OSI)
noted,
correlating
decreased
expansion.
Conversely,
during
diastole
WSS
OSI
identified,
potentially
weakening
wall,
thereby
promoting
Conclusion:
underscores
indispensable
role
computational
fluid
dynamic
(CFD)
techniques
diagnostic,
therapeutic,
monitoring
realms
AAAs.
This
body
research
significantly
advances
offering
pivotal
insights
underpinning
progression
informing
clinical
interventions
enhancing
patient
care.
Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials,
Год журнала:
2024,
Номер
160, С. 106760 - 106760
Frontiers in Bioengineering and Biotechnology,
Год журнала:
2025,
Номер
13
Опубликована: Март 21, 2025
Hemodynamic
analysis
based
on
computational
fluid
dynamics
(CFD)
modelling
is
expected
to
improve
risk
stratification
for
patients
with
aortic
aneurysms
and
dissections.
However,
the
parameter
settings
in
CFD
simulations
involve
considerable
variability
uncertainty.
Additionally,
exact
relationship
between
hemodynamic
features
disease
progression
remains
unclear.
These
challenges
limit
clinical
application
of
models.
This
review
presents
a
detailed
overview
workflow
CFD-based
analysis,
focus
recent
advancements
field.
We
also
conducted
systematic
27
studies
large
sample
sizes
(n
>
5)
that
examine
characteristics
Some
identified
consistent
relationships
progression,
reinforcing
potential
limitations
such
as
small
oversimplified
patient-specific
models
remain.
findings
emphasize
need
larger,
more
refine
strategies,
strengthen
connection
hemodynamics
diseases,
ultimately
facilitate
use
management.
Bioengineering,
Год журнала:
2025,
Номер
12(5), С. 437 - 437
Опубликована: Апрель 22, 2025
Research
on
abdominal
aortic
aneurysms
(AAAs)
primarily
focuses
developing
a
clear
understanding
of
the
initiation,
progression,
and
treatment
AAA
through
improved
model
accuracy.
High-fidelity
hemodynamic
biomechanical
predictions
are
essential
for
clinicians
to
optimize
preoperative
planning
minimize
therapeutic
risks.
Computational
fluid
dynamics
(CFDs),
finite
element
analysis
(FEA),
fluid-structure
interaction
(FSI)
widely
used
simulate
hemodynamics
biomechanics.
However,
accuracy
these
simulations
depends
utilization
realistic
sophisticated
boundary
conditions
(BCs),
which
properly
integrating
with
rest
cardiovascular
system.
Recent
advances
in
machine
learning
(ML)
techniques
have
introduced
faster,
data-driven
surrogates
modeling.
These
approaches
can
accelerate
segmentation,
predict
biomechanics,
assess
disease
progression.
their
reliability
high-quality
training
data
derived
from
CFDs
FEA
simulations,
where
BC
modeling
plays
crucial
role.
Accurate
BCs
enhance
ML
predictions,
increasing
clinical
applicability.
This
paper
reviews
existing
models,
discussing
limitations
technical
challenges.
Additionally,
recent
advancements
explored,
current
states,
future
directions,
common
algorithms,
limitations.
