Proceedings of the Southwest State University Series IT Management Computer Science Computer Engineering Medical Equipment Engineering,
Journal Year:
2024,
Volume and Issue:
14(3), P. 104 - 120
Published: Nov. 15, 2024
The
purpose
of
the
research
is
to
analyze
efficiency
U-net
neural
network
architecture
in
decision
support
systems
for
glioma
diagnostics
and
segmentation
brain
areas
affected
by
it
on
MRI
images.
Methods.
To
conduct
experimental
studies,
a
training
dataset
was
generated
data
normalized.
A
software
implementation
U-Net
performed
using
Keras
framework
Python
programming
language.
model
trained.
Results.
series
experiments
were
conducted,
during
which
error
classification
matrices
obtained,
trained
"Tumor"
"No
tumor"
classes
assessed
metrics
such
as
Recall,
Precision
F1-measure,
quality
glioma-affected
test
set
assessed.
IoU
metric,
reflects
ratio
bounding
boxes
used
assess
accuracy
spatial
correspondence
predicted
segmented
highlighted
masks.
Based
results
testing
solving
problem
segmenting
glioma,
average
value
metric
0.812,
an
acceptable
result.
Conclusion.
showed
that
based
able
effectively
diagnose
presence
with
values
metrics,
indicates
possibility
this
medical
diagnostics,
well
its
However,
advisable
refine
reduce
number
false
negative
results,
critically
important
diagnostics.
Applied Neuropsychology Child,
Journal Year:
2025,
Volume and Issue:
unknown, P. 1 - 8
Published: March 15, 2025
Brain
tumors
are
the
most
common
type
of
pediatric
cancer,
significantly
impacting
children's
health-related
quality
life
(HRQoL).
This
study
aimed
to
adapt
PedsQL™-BTM
Turkish
culture
and
evaluate
its
psychometric
properties,
including
reliability,
validity,
cross-cultural
consistency.
A
total
108
children
with
brain
(mean
age:
9.1
±
4.99
years)
120
parents
participated
in
study.
The
translation
process
included
forward-backward
translation,
reconciliation,
cognitive
debriefing,
pilot
testing.
Internal
consistency
(Cronbach's
alpha),
test-retest
reliability
(ICC),
exploratory
confirmatory
factor
analysis
were
conducted
properties.
Correlations
between
Generic
Core
Scales
examined
for
criterion
validity.
Cronbach's
alpha
ranged
from
0.83
0.97,
indicating
excellent
internal
Test-retest
was
robust,
ICC
values
exceeding
0.80
subscales.
EFA
explained
84.2%
variance
parent
reports
80.4%
child
reports,
while
CFA
confirmed
six-factor
structure
(child-reported
outcomes:
RMSEA
=
0.069,
90%
CI:
0.061-0.076;
TLI
0.862;
NFI
0.92;
χ2
(147)
1875,
p
<
0.001;
parent-reported
0.063,
0.059-0.069;
0.858;
0.93;
(153)
1912,
0.001).
BTM
subscales
demonstrated
strong
validity
(e.g.
Cognitive
Problems
correlated
School
Functioning:
r
0.831,
0.05).
is
a
reliable
valid
tool
assessing
HRQoL
tumors.
Science Advances,
Journal Year:
2024,
Volume and Issue:
10(47)
Published: Nov. 22, 2024
Glioblastoma
(GBM)
cells
are
highly
heterogeneous
and
invasive,
leading
to
treatment
resistance
relapse.
However,
the
molecular
regulation
in
distal
tumors
remains
elusive.
Here,
we
collected
paired
tissues
from
tumor
core
(TC)
peritumoral
brain
(PTB)
for
integrated
snRNA-seq
snATAC-seq
analyses.
Tumor
infiltrating
PTB
TC
behave
more
like
oligodendrocyte
progenitor
than
astrocytes
at
transcriptome
level.
Dual-omics
analyses
further
suggest
that
regulatory
regions
genome
specific
transcription
factors
potential
determinants
of
regional
heterogeneity.
Notably,
while
activator
protein
1
(AP-1)
is
active
all
GBM
states,
its
activity
declines
PTB,
with
another
factor,
BACH1,
showing
opposite
trend.
Combined
inhibition
AP-1
BACH1
efficiently
attenuates
progression
mice
prolongs
survival
either
single-target
treatment.
Together,
our
work
reveals
marked
alterations
infiltrated
a
synergy
combination
therapy
targeting
intratumor
heterogeneity
GBM.
Neuro-Oncology,
Journal Year:
2024,
Volume and Issue:
27(1), P. 13 - 32
Published: Sept. 13, 2024
Abstract
Adolescents
and
young
adults
(AYAs;
ages
15–39
years)
are
a
vulnerable
population
facing
challenges
in
oncological
care,
including
access
to
specialized
transition
of
unique
tumor
biology,
poor
representation
clinical
trials.
Brain
tumors
the
second
most
common
type
AYA,
with
malignant
brain
being
cause
cancer-related
death.
The
2021
WHO
Classification
for
central
nervous
system
(CNS)
Tumors
highlights
importance
integrated
molecular
characterization
histologic
diagnosis
several
relevant
AYA
population.
In
this
position
paper
from
Society
Neuro-Oncology
(SNO),
management
CNS
is
reviewed,
focusing
on
types
population,
namely
glioma,
medulloblastoma,
ependymoma,
germ
cell
tumor.
Current
future
directions
specific
also
highlighted.
Finally,
possible
solutions
address
barriers
care
patients
discussed,
emphasizing
need
multidisciplinary
collaborative
approaches
that
span
pediatric
adult
paradigms
incorporating
advanced
testing,
targeted
therapy,
AYA-centered
care.
Aging,
Journal Year:
2024,
Volume and Issue:
unknown
Published: July 5, 2024
The
objective
is
to
investigate
the
prognostic
factors
associated
with
gliomas
and
develop
assess
a
predictive
nomogram
model
connected
survival
that
may
serve
as
an
additional
resource
for
clinical
management
of
glioma
patients.
Current Opinion in Oncology,
Journal Year:
2024,
Volume and Issue:
36(6), P. 554 - 559
Published: Aug. 28, 2024
Purpose
of
review
In
this
review,
we
investigated
the
role
European
oncological
networks
on
management
and
care
patients
with
central
nervous
system
(CNS)
malignancies.
Recent
findings
Within
universe
tumors,
malignancies
represent
a
challenge
because
several
reasons
such
as
biological
complexity,
need
dedicated
experienced
physicians
(surgeons,
pathologists,
radiologists
neuro-oncologists)
tertiary
healthcare
providers.
Limits
to
development
effective
innovative
are
represented
by
rarity
these
tumors
their
extreme
heterogeneity
in
terms
clinical
presentation,
course
disease,
genetic
assessments
site
presentation.
The
societies
or
associations,
which
make
possible
connect
patients,
scientists,
doctors
researchers
together
allowing
obtain
improvements.
Summary
Oncological
can
cooperate
increase
accrual
rate
speed
trials,
share
data
about
CNS
malignancy
improve
knowledge
toward
class
within
health
operators
promoting
equity
high
standard
care.
