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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5522_Библиотеки_им_академика_М_И_Перельмана.pdf
Imaging in Particle Therapy
from online to real-time 4D treatments, as time-resolved 3D data provides the
information needed for lateral beam adjustments and energy adaption in PT (Mori
et al 2018). AI can also improve models for image acquisition and reconstruction as
well as investigate correlations with corresponding dose distributions in in-vivo
range verification or implement classification and prediction models to stratify
patients and predict treatment outcome. Recently, AI has been exploited as a tool,
together with radiomics (and dosiomics), to extract relevant quantitative features
from images (and dose maps) for tumour aggressiveness and treatment outcome
prediction (Lambin et al 2017, Morelli et al 2022). Nevertheless, although the
potential of AI is very promising, its use in the clinical practice must be regulated to
provide interpretable results with a quantifiable level of uncertainty.
Finally, another fundamental topic of interest in the near future and demanding
for further research, is quantitative imaging (Q-imaging) (O’Connor et al 2017,
Gurney-Champion et al 2020). Up to now Q-imaging is mainly limited to improve
contouring in PT planning, but its potential in providing biological, microstructural
and physiological features must be exploited. Q-imaging allows clinicians and
researchers to account not only for tumour geometry but also for tumour biology
and to better understand the biological properties at the basis of a PT treatment.
Knowing and modelling the tumour characteristics and the mechanisms of PT, will
help in defining optimal and individual dose schemes, as well as sculpting the dose
according to each patient. In this way, the implementation of personalized and
biologically-guided PT treatments will make the most of PT benefits.
Within this scenario, different working groups are currently working on the
standardization of imaging protocols and on advancing imaging capabilities in PT,
such as PTCOG (https://www.ptcog.site/), EPTN (Grau et al 2018, 2020) and
AAPM (https://www.aapm.org/). These, together with the entire scientific community, also supported by dedicated conferences (MICCAI, BIGART, ICCR, 4D
treatment workshop, as few examples), will continuously advance image guidance
in PT towards accurate treatments and improved patient care.
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