Modelling midline shift and ventricle collapse in cerebral oedema following acute ischaemic stroke
PLoS Computational Biology,
Journal Year:
2024,
Volume and Issue:
20(5), P. e1012145 - e1012145
Published: May 28, 2024
In
ischaemic
stroke,
a
large
reduction
in
blood
supply
can
lead
to
the
breakdown
of
blood-brain
barrier
and
cerebral
oedema
after
reperfusion
therapy.
The
resulting
fluid
accumulation
brain
may
contribute
significant
rise
intracranial
pressure
(ICP)
tissue
deformation.
Changes
level
ICP
are
essential
for
clinical
decision-making
therapeutic
strategies.
However,
measurement
is
constrained
by
techniques
obtaining
exact
values
has
proven
challenging.
this
study,
we
propose
first
computational
model
simulation
following
acute
stroke
investigation
midline
shift
(MLS)
relationship.
consists
three
components
healthy
flow,
occluded
flow
oedema,
respectively.
utilized
obtain
core
geometry
then
imported
into
growth.
results
compared
with
data
from
97
traumatic
injury
patients
validation
major
parameters.
Midline
been
widely
used
diagnosis,
decision-making,
prognosis
patients.
Therefore,
focus
on
quantifying
relationship
between
identify
factors
that
affect
ICP-MLS
Three
investigated,
including
geometry,
damage
severity
types
(including
rare
oedema).
Meanwhile,
two
(stress
tension/compression)
mechanical
also
presented
differences
stress,
tension,
compression
intraparenchymal
periventricular
regions
discussed.
This
work
helps
predict
precisely
therefore
provides
improved
guidance
treatment
oedema.
Language: Английский
Poroelastic modelling of brain tissue swelling and decompressive craniectomy treatment in ischaemic stroke
Computer Methods in Biomechanics & Biomedical Engineering,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 11
Published: March 10, 2024
Brain
oedema
or
tissue
swelling
that
develops
after
ischaemic
stroke
can
cause
detrimental
effects,
including
brain
herniation
and
increased
intracranial
pressure
(ICP).
These
effects
be
reduced
by
performing
a
decompressive
craniectomy
(DC)
operation,
in
which
portion
of
the
skull
is
removed
to
allow
swollen
expand
outside
skull.
In
this
study,
poroelastic
model
used
investigate
effect
infarct
size
location
on
severity
swelling.
Furthermore,
will
also
evaluate
effectiveness
DC
surgery
as
treatment
for
ischaemia.
The
consists
two
equations:
one
describing
elasticity
other
changes
interstitial
pressure.
applied
an
idealized
geometry,
it
found
infarcts
with
radius
larger
than
approximately
14
mm
located
near
lateral
ventricle
produce
worse
midline
shift,
measured
through
compression.
able
show
positive
reducing
shift
allowing
part
opening.
However,
does
not
decrease
during
treatment.
Further
improvement
validation
could
enhance
capability
proposed
predicting
occurrence
post
Language: Английский
AI-assisted In-silico Trial for the Optimization of Osmotherapy following Ischaemic Stroke
Xi Chen,
No information about this author
Lei Lü,
No information about this author
Tamás Józsa
No information about this author
et al.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 23, 2024
Abstract
Over
the
past
few
decades,
osmotherapy
has
commonly
been
employed
to
reduce
intracranial
pressure
in
post-stroke
oedema.
However,
evaluating
effectiveness
of
challenging
due
difficulties
clinical
measurement.
As
a
result,
there
are
no
established
guidelines
regarding
selection
administration
protocol
parameters.
Considering
that
infusion
osmotic
agents
can
also
give
rise
various
side
effects,
remained
subject
debate.
In
previous
studies,
we
proposed
first
mathematical
model
for
investigation
and
validated
with
data.
The
physiological
parameters
vary
among
patients
such
variations
result
failure
osmotherapy.
Here,
propose
an
AI-assisted
in-silico
trial
further
optimisation
protocols.
deep
neural
network
predicts
evolution
over
episodes.
effects
choice
dose
investigated
using
model.
addition,
stratifications
related
brain
time
treatment
different
patient
groups.
This
provides
alternative
approach
tackle
challenges
trials
supported
by
both
mathematical/physical
laws
patient-specific
biomedical
information.
Language: Английский
Hybrid weights structure model based on Lagrangian principle to handle big data challenges for identification of oil well production: A case study on the North Basra oilfield, Iraq
Engineering Applications of Artificial Intelligence,
Journal Year:
2024,
Volume and Issue:
138, P. 109465 - 109465
Published: Oct. 18, 2024
Language: Английский