Oral Oncology Reports,
Journal Year:
2024,
Volume and Issue:
11, P. 100591 - 100591
Published: June 29, 2024
Artificial
intelligence
(AI)
has
emerged
as
a
promising
tool
in
oral
oncology,
particularly
the
field
of
prediction.
This
review
provides
comprehensive
outlook
on
role
AI
predicting
cancer,
covering
key
aspects
such
data
collection
and
preprocessing,
machine
learning
techniques,
performance
evaluation
validation,
challenges,
future
prospects,
implications
for
clinical
practice.
Various
algorithms,
including
supervised
learning,
unsupervised
deep
approaches,
have
been
discussed
context
cancer
Additionally,
challenges
interpretability,
accessibility,
regulatory
compliance,
legal
are
addressed
along
with
research
directions
potential
impact
oncology
care.
Radiation Oncology,
Journal Year:
2024,
Volume and Issue:
19(1)
Published: March 30, 2024
Abstract
Background
Adaptive
radiation
therapy
(ART)
offers
a
dynamic
approach
to
address
structural
and
spatial
changes
that
occur
during
radiotherapy
(RT)
for
locally
advanced
head
neck
cancers.
The
integration
of
daily
ART
with
Cone-Beam
CT
(CBCT)
imaging
presents
solution
enhance
the
therapeutic
ratio
by
addressing
inter-fractional
changes.
Methods
We
evaluated
initial
clinical
experience
patients
cancer
using
an
online
adaptive
platform
intelligence-assisted
workflows
on
CBCT.
Treatment
included
auto-contour
structure
deformation
Organs
at
Risk
(OARs)
target
structures,
adjustments
treating
physician.
Two
plans
were
generated:
one
based
simulation
edited
structures
(scheduled)
re-optimized
plan
(adaptive).
Both
superior
approved
delivered.
Clinical
dosimetric
outcomes
reviewed.
Results
Twenty
two
cancers
(7
Nasopharynx,
6
Oropharynx,
1
oral
cavity,
8
larynx)
stages
I-IVA
treated
ART.
770
scheduled
generated.
703
(91.3%)
chosen.
Median
time
deliver
was
20
minutes
(range:
18-23).
compared
demonstrated
improved
mean
V95
values
PTV70,
PTV59.5,
PTV56
1.2%,
7.2%,
6.0%
respectively
1.4%
lower
maximum
dose
in
PTV70.
Fourteen
17
OARs
dosimetry
adaptation,
select
reaching
statistical
significance.
At
median
follow
up
14.1
months,
local
control
95.5%,
developed
metastatic
disease
four
died.
9.1%
had
acute
grade
3
dysphagia
13.6%
2
chronic
xerostomia.
Discussion
These
findings
provide
real
world
evidence
feasibility
benefit
incorporating
CBCT
treatment
cancer.
Prospective
study
is
needed
determine
if
these
improvements
translate
into
outcomes.
Cancers,
Journal Year:
2024,
Volume and Issue:
16(17), P. 2997 - 2997
Published: Aug. 28, 2024
Oral
squamous
cell
carcinoma
(OSCC)
is
the
most
common
head
and
neck
cancer.
Although
oral
cavity
an
easily
accessible
area
for
visual
examination,
OSCC
more
often
detected
at
advanced
stage.
The
global
prevalence
of
around
6%,
with
increasing
trends
posing
a
significant
health
problem
due
to
increase
in
morbidity
mortality.
microbiome
has
been
target
numerous
studies,
findings
highlighting
role
dysbiosis
developing
OSCC.
Dysbiosis
can
significantly
pathobionts
(bacteria,
viruses,
fungi,
parasites)
that
trigger
inflammation
through
their
virulence
pathogenicity
factors.
In
contrast,
chronic
bacterial
contributes
development
Pathobionts
also
have
other
effects,
such
as
impact
on
immune
system,
which
alter
responses
contribute
pro-inflammatory
environment.
Poor
hygiene
carbohydrate-rich
foods
risk
factors
mechanisms
are
not
yet
fully
understood
remain
frequent
research
topic.
For
this
reason,
narrative
review
concentrates
issue
potential
cause
OSCC,
well
underlying
involved.
Cell Reports Medicine,
Journal Year:
2024,
Volume and Issue:
5(3), P. 101447 - 101447
Published: March 1, 2024
There
is
an
unmet
clinical
need
for
a
non-invasive
and
cost-effective
test
oral
squamous
cell
carcinoma
(OSCC)
that
informs
clinicians
when
biopsy
warranted.
Human
beta-defensin
3
(hBD-3),
epithelial
cell-derived
anti-microbial
peptide,
pro-tumorigenic
overexpressed
in
early-stage
OSCC
compared
to
hBD-2.
We
validate
this
expression
dichotomy
situ
lesions
using
immunofluorescence
microscopy
flow
cytometry.
The
proportion
of
hBD-3/hBD-2
levels
non-invasively
collected
lesional
cells
contralateral
normal
cells,
obtained
by
ELISA,
generates
the
index
(BDI).
Proof-of-principle
blinded
discovery
studies
demonstrate
BDI
discriminates
from
benign
lesions.
A
multi-center
validation
study
shows
sensitivity
specificity
values
98.2%
(95%
confidence
interval
[CI]
90.3-99.9)
82.6%
CI
68.6-92.2),
respectively.
proof-of-principle
adaptable
point-of-care
assay
microfluidics.
propose
may
fulfill
major
low-socioeconomic
countries
where
pathology
services
are
lacking.
Oral Oncology Reports,
Journal Year:
2024,
Volume and Issue:
11, P. 100591 - 100591
Published: June 29, 2024
Artificial
intelligence
(AI)
has
emerged
as
a
promising
tool
in
oral
oncology,
particularly
the
field
of
prediction.
This
review
provides
comprehensive
outlook
on
role
AI
predicting
cancer,
covering
key
aspects
such
data
collection
and
preprocessing,
machine
learning
techniques,
performance
evaluation
validation,
challenges,
future
prospects,
implications
for
clinical
practice.
Various
algorithms,
including
supervised
learning,
unsupervised
deep
approaches,
have
been
discussed
context
cancer
Additionally,
challenges
interpretability,
accessibility,
regulatory
compliance,
legal
are
addressed
along
with
research
directions
potential
impact
oncology
care.
