Intratumoral microbiota-aided fusion radiomics model for predicting tumor response to neoadjuvant chemoimmunotherapy in triple-negative breast cancer
Journal of Translational Medicine,
Journal Year:
2025,
Volume and Issue:
23(1)
Published: March 20, 2025
Neoadjuvant
chemoimmunotherapy
(NACI)
has
emerged
as
the
standard
treatment
for
early-stage
triple-negative
breast
cancer
(TNBC).
However,
reliable
biomarkers
identifying
patients
who
are
likely
to
benefit
from
NACI
lacking.
This
study
aims
develop
an
intratumoral
microbiota-aided
radiomics
model
predicting
pathological
complete
response
(pCR)
in
with
TNBC.
Intratumoral
microbiota
characterized
by
16S
rDNA
sequencing
and
quantified
through
experimental
assays.
Single-cell
RNA
is
performed
analyze
tumor
microenvironment
of
tumors
various
responses
NACI.
Radiomics
features
extracted
regions
on
longitudinal
magnetic
resonance
images
(MRIs)
scanned
before
after
training
set.
On
basis
(pCR
or
non-pCR)
scoring,
we
select
key
construct
a
fusion
integrating
multi-timepoint
(pre-NACI
post-NACI)
MRI
predict
efficacy
immunotherapy,
followed
independent
external
validation.
A
total
124
enrolled,
88
set
36
validation
Tumors
achieves
pCR
present
significantly
greater
load
than
achieve
non-pCR
(p
<
0.05).
Additionally,
group
exhibit
infiltration
tumor-associated
SPP1+
macrophages,
which
negatively
correlated
load.
17
use
them
model.
The
highest
AUC
0.945
set,
outperforming
pre-NACI
(AUC
=
0.875)
post-NACI
0.917)
models.
In
this
maintains
superior
0.873,
surpassing
those
0.769)
0.802)
Clinically,
distinguishes
do
not
accuracy
77.8%.
Decision
curve
analysis
demonstrates
net
clinical
across
varying
risk
thresholds.
Our
could
serve
powerful
noninvasive
tool
TNBC
Language: Английский
Synthetic imaging for research and education in nuclear medicine: Who’s afraid of the black box?
European Journal of Nuclear Medicine and Molecular Imaging,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 22, 2025
Language: Английский
Dual-region MRI radiomic analysis indicates increased risk in high-risk breast lesions: bridging intratumoral and peritumoral radiomics for precision decision-making
BMC Cancer,
Journal Year:
2025,
Volume and Issue:
25(1)
Published: May 6, 2025
To
evaluate
the
clinical
utility
of
dynamic
contrast-enhanced
magnetic
resonance
imaging
(DCE-MRI)-derived
clinicoradiological
characteristics
and
intratumoral/peritumoral
radiomic
features
in
predicting
pathological
upgrades
(malignant
transformation)
high-risk
breast
lesions.
Retrospectively
collected
data
174
patients
with
lesions
who
underwent
preoperative
MRI
examinations
were
confirmed
by
biopsy
pathology
Shenzhen
People's
Hospital
between
January
1,
2019
2024.
The
dataset
was
randomly
divided
into
a
training
set
(n
=
121)
test
53)
at
ratio
7:3.
Initially,
during
second
stage
DCE-MRI,
region
interest
(ROI)
delineated
along
maximum
cross-section
lesion,
then
automatically
expanded
outward
3
mm,
5
7
mm
as
peritumoral
ROIs.
intratumoral,
each
peritumoral,
combined
intratumoral
models
established
respectively.
Independent
risk
factors
predictive
malignant
identified
through
univariate
multivariable
logistic
regression
analyses,
which
subsequently
incorporated
characteristics.
Finally,
model
integrating
features.
performance
analyzed
using
receiver
operating
characteristic
(ROC)
curves,
area
under
curve
(AUC)
calculated.
radiomics
achieved
highest
diagnostic
among
all
models,
AUC
values
0.704
0.654
for
sets,
In
set,
showed
(AUC
0.883),
superior
to
that
0.745,
P
0.003),
0.791,
0.027),
0.704,
0.001),
0.830,
0.004).
also
0.851).
constructed
had
best
performance,
sensitivity,
specificity,
accuracy
79.4%,
82.7%,
81.8%
72.7%,
85.7%,
83.0%
model,
integrates
data,
exhibited
strong
clinically
applicable
nomogram
stratify
individualized
upgrade
risk,
assisting
clinicians
making
more
precise
decisions.
Language: Английский