Добавил:
Sekretar
kiopkiopkiop18@yandex.ru
t.me/Prokururor I Вовсе не секретарь, но почту проверяю
Опубликованный материал нарушает ваши авторские права? Сообщите нам.
Вуз:
Предмет:
Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5522_Библиотеки_им_академика_М_И_Перельмана.pdf
Imaging in Particle Therapy
conventional scanners by acquiring fast imaging sequences such as bSSFP, T2weighted turbo spin echo and spoiled gradient echo, the navigator slice approach or
k-space based sorting require proper implementation in the MR scanner. To
improve spatial resolution while respecting a clinically feasible total acquisition
time of a few minutes or less, parallel imaging and under-sampling schemes
(Mickevicius and Paulson 2017b) can be utilized, as well as deep learning solutions
to speed up reconstruction time (Terpstra et al 2020, Freedman et al 2021).
In time-resolved MRI instead, image acquisition is reduced to 2D information
but continuously performed at sub-second frame rates (down to 125 ms; Kim et al
2021) with the so-called 2D cine MRI sequences, such as bSSFP or spoiled gradient
echo, to capture cycle-to-cycle variations. 2D cine MRI, representing the state of the
art for MRI-linacs, can be acquired either on a single plane or multiple planes
(commonly in the sagittal direction), or in an orthogonal sagittal/coronal interleaved
fashion centered in the tumour to achieve pseudo 3D information (Paganelli et al
2018b, Kurz et al 2020, Keall et al 2022).
7.3 In-beam MRI-guided proton therapy
As previously mentioned, MRI is currently adopted offline in PT, but the
implementation of real-time MRI guidance with an integrated MRI scanner at
the treatment isocenter is under investigation for proton therapy (Oborn et al 2017,
Schellhammer et al 2018, Hoffmann et al 2020, Pham et al 2022). The availability of
such a system would enable in-room time-resolved imaging able to directly monitor
the internal anatomy just before and during treatment (i.e., to perform online
adaptation and gating at first instance) coupled with better dose conformality
provided by the proton beam. This configuration by nature means that the MRI
scanner is expected to be operational while the proton beams are being delivered.
This immediately introduces various complexities or additional requirements to the
proton therapy. The most important requirements are listed in table 7.1 with a brief
summary and discussed below in the following paragraphs.
7.3.1 Beam delivery, MR design and magnetic compatibility
One of the most important considerations for in-beam MRI-guided proton therapy
is that the proton beam delivery must be pencil beam scanning (PBS; Oborn et al
2015). A passively scattered beam will lose its volumetric dose conformity after
traversing through a magnetic field. This is due to the polyenergetic nature of the
beams containing protons with energies that range over many MeV, i.e., the
difference between the deepest and the most shallow Bragg peak for a given
treatment field. Each of these protons will undergo a different magnetic deflection
before coming to rest inside the patient. Therefore, the integrated MRI proton
therapy system will need to be PBS based instead, and so dose planning, which needs
to account for the magnetic field induced beam deflection, can be performed on a
monoenergetic spot-by-spot basis.
As discussed in Hoffmann et al (2020) and Pham et al (2022), the magnet design
either needs to be open or split-bore style, such that the proton beam has direct
7-5
Imaging in Particle Therapy
Table 7.1. A summary of the unique requirements of a real-time MRI-guided proton therapy system.
Feature/requirement Description
Beam delivery method Pencil beam scanning is required. Passive scattering methods break down
due to spatial degradation of polyenergetic beams during transport
through the complex 3D spatially varying MRI magnetic fringe field
(Oborn et al 2015).
Proton path to MRI
isocenter
Magnetic
compatibility
Treatment planning The Treatment Planning System (TPS) must be able to account for the
Dosimetry Dosimetry should be conducted in the presence of the magnetic field of
A clear path for the proton beam to reach the patient located inside an
MRI scanner is required. This is possible with open or split-bore style
MRI scanners (Burigo and Oborn 2022, Burigo and Oborn 2019).
There must be no detrimental impact on the MRI scanner operation by
the proton beam and vice versa (Gantz et al 2020). This could be
achieved via magnetic decoupling using magnetic shielding between
the two systems.
transport of the proton beam through the MRI fringe field, as well as
the calculation of proton beam dose in the presence of the main MRI
field (Padilla-Cabal et al 2018, Padilla-Cabal et al 2020).
the MRI. Thus, the detectors and their performance must be evaluated
and possibly modified to operate successfully in this environment.
Magnetic field effects on their dose response can be accounted for via
correction factors (Causer et al 2020, Fuchs et al 2021a).
access to the patient. For best practice, at least a partial gantry (e.g., 220° rotation) is
required for beam access from any gantry angle (when coupled with a reversible
patient couch). In a system with an almost complete split-gap the beam direction
would be perpendicular to the main magnetic field (Oborn et al 2015). Alternatively,
an open magnet design with a C-shaped or U-shaped rotating magnet could be
integrated in the proton gantry, which requires the beam to pass through one of the
magnet poles.
At least two research groups have already created prototype systems that have
brought together a portable, open MRI scanner with a C-shaped permanent magnet
design and a PBS assembly. At OncoRay in Dresden, Germany, three configurations
using a compact MRI scanner for extremity imaging have been investigated
(figure 7.3). These include (i) a 0.22 T MRI located at the end of a horizontal fixed
proton beam line (Schellhammer et al 2018); (ii) the same 0.22 T MRI positioned at
the end of a horizontal clinical-quality PBS assembly (non-gantry PBS; Gantz et al
2020); (iii) and a 0.32 T MRI scanner at the end of the same PBS assembly (Gebauer
et al 2023). At the DKFZ in Heidelberg, Germany, a 0.25 T MRI has been
integrated at the end of a PBS assembly with the potential for multiple ion species
(Debus 2021). Finally, a dedicated 0.5 T bi-directional, whole-body MRI scanner
using a cryogen-free superconducting magnet technology has been installed in late
7-6
Imaging in Particle Therapy
Figure 7.3. The preclinical MRI-integrated proton therapy systems at OncoRay, Dresden, Germany.
Figure 7.4. The 0.5 T bi-directional, whole-body in-beam MRI scanner installed at the horizontal proton PBS
research beam line at OncoRay, Dresden, Germany.
2023 to serve as the next prototype at OncoRay. This system will allow for proton
beam access either through a portal hole in the magnet yoke of the scanner or
through the gap between the MRI cryostat halves. Figure 7.4 presents an impression
of the proposed system with the proton beam incident from the perpendicular
orientation. This system was installed at the end of 2023 and is currently being
commissioned for first experimental use.
When integrating an MRI with a proton beam, electromagnetic interference
effects between the PBS process and the MRI system are present. This primarily
manifests itself as a strong ghosting image artefact present in the MR images during
concurrent irradiation (Gantz et al 2020). The mechanism is linked to the magnetic
fringe field of the PBS assembly slightly altering the B
field strength of the MRI
0
scanner, all occurring with a frequency corresponding to the PBS dose delivery
process. This ghosting is clearly a threat to the whole purpose of using the MRI to
guide the treatment process in real-time. The most obvious approach for eliminating
this concern is to magnetically decouple the PBS from the MRI scanner. Passive
magnetic shielding of the PBS assembly would appear the simplest option. It is also
worth considering software-based solutions to filter distorted images from the
7-7
Imaging in Particle Therapy
correct images, remembering that a combined system would allow for shared
timestamps across the image construction and PBS spot settings. For example,
reconstructing images from k-space information obtained between the delivery of
PBS energy layers (i.e., when the MRI field is not impacted) would inherently
produce accurate images.
7.3.2 Proton therapy dose calculation and dosimetry in a magnetic field
Considerable work has been conducted in the area of dose calculation of proton
beams in the presence of magnetic fields, which is a necessary requirement for inbeam MRI-PT systems. In 2008, the deflection of a PBS broad proton beam
incident on a phantom with uniform magnetic fields was calculated with Monte
Carlo methods (Raaymakers et al 2008). In 2012, an analytical method was
derived to calculate the e xpected proton beam deflections in uniform, transverse
magnetic fields (Wolf and Bortfeld 2012). In 2014 and 2015, the dosimetric effects
induced by uniform, transverse magnetic fields were assessed in patient treatment
planning studies, showing that clinical grade treatment plans can be calculated in
the presence of 0.5 and 1.5 T magnetic fields (Moteabbed et al 2014, Hartman et al
2015). Also in 2015, the transport of a proton beam towards a realistic MRI
scanner was modelled (Oborn et al 2015), showing that the full 3D magnetic fringe
field needs to be taken into account for treatment planning. In 2017, a fast and
accurate numerical model was presented to predict and compensate for magnetic
field induced beam deflections (Schellhammer and Hoffmann 2017). Fuchs et al
(2017) next studied the changes to proton and carbon pencil beams incident on
water phantoms using Monte Carlo methods: magnetic fields of up to 3 T were
studied, and the concept of a beam retraction (or shallower Bragg peak depth) was
first introduced. Padilla-Cabal and colleagues (Padilla-Cabal et al 2018)next
investigated a pencil beam algorithm for prediction of the changes to a proton
pencil beam in magnetic fields. In 2019, a small (up to 8% local dose increase)
electron return effect produced by proton beams at 0.95 T was investigated
experimentally and with Monte Carlo simulations (Lühr et al 2019). Also in
2019, pencil beam dose planning that accounts for inline magnetic fields was
explored (Burigo and Oborn 2019). In 2020, a Monte Carlo-based dose calculation
algorithm was investigated for use in proton beams in magnetic fields (PadillaCabal et al 2020). In 2021, the response and performance of various radiation
detectors exposed to proton beams in the presence of magnetic fields was studied
(Fuchs
et al 2021b). Dose planning in the presence of perpendicular magnetic fields
that accounts for the MRI fringe field has also been shown with success (Burigo
and Oborn 2022). In 2023, the OncoRay group measured the effect of the MRI
magnetic field (both fringe field and imaging field) on the proton beam path, dose
spot pattern, dose spot form for their 0.32 T in-beam MRI scanner at the PBS
beam line and quantified the lateral beam deflection, radiation field shape
deformation and dose spot distortion as a function of beam energy and distance
to the beam and MRI isocenter (Gebauer et al 2023). This data is valuable for the
7-8
Imaging in Particle Therapy
commissioning and evaluation of future treatment planning systems taking into
account the full 3D magnetic field map of the in-beam MRI scanner.
As such, a wide range of both experimental and modelling based studies have
been conducted in the field of dose calculation and dosimetry for the unique
conditions that will be present in real-time MRI-guided proton beam therapy. So
far, there have been no concerning findings; proton beam radiotherapy dose
planning optimization and dosimetry that accounts for the presence of MR magnetic
fields appears completely feasible.
7.4 MRI-guided PT workflow
Currently in PT, MRI can be adopted as an off-line modality to acquire ionizing dosefree repeated imaging to support treatment planning and, eventually, adaptation, and
to perform follow-up examinations; but with future integrated systems, online
adaptation is envisioned. Figure 7.5 shows the potential use of MRI in a current PT
workflow and the optional treatment style of using integrated real-time MRI-guidance.
7.4.1 Treatment planning
One step towards maximal tumour control with minimal toxicity in PT is when highresolution imaging is used for tumour and OARs contouring in treatment planning.
CT remains the clinical standard in PT treatment planning as it provides high spatial
resolution and does not suffer from geometric distortion, providing electron density
information for different tissues. However, low soft-tissue contrast and large
interobserver and intra-observer variations have been reported in the delineation
of most solid tumours, potentially leading to marginal misses or suboptimal organ
sparing or both (Dirix et al 2014). To overcome this, MR images can be fused on the
planning CT images for accurate target and organs at risk delineation, providing
more consistent and more accurate information than CT images alone, when
Figure 7.5. Potential use of MRI in an off-line and online workflow. The off-line workflow is intended for a
current PT scenario with near room MR scanners, whereas the online workflow (highlighted in yellow) for inbeam integrated MRI-PT system.
7-9
Imaging in Particle Therapy
compared with pathology (Dirix et al 2014). Nevertheless, although consensus
guidelines and online available CT/MRI atlases have been created to support
tumours and OARs delineation on CT/MRI data on head-and-neck, prostate and
abdominal tumours (Heerkens et al 2017, Salembier et al 2018, Lukovic et al 2020,
Eekers et al 2021) and show that MRI contributes to improved contouring,
challenges in target volume definition with MRI are still present for some peculiar
tumours such as ocular melanoma, where increased resolution or fusion with
complementary ophthalmological imaging are required (Via et al 2021, Fleury
et al 2021).
Apart from contouring, MRI can be useful to support treatment planning
optimization. Several studies demonstrated the feasibility in deriving synthetic CT
from MRI data with bulk density override, atlas-based analysis and more recently
novel deep learning strategies (Johnstone et al 2018, Boulanger et al 2021), with
promising results in terms of dose metrics for proton therapy applications (<1% of
the prescribed dose in brain pediatric patients and <3% of the prescribed dose in
abdominal pediatric patients; see Florkow et al 2020, Maspero et al 2020). This
would allow optimizing the treatment plan directly on the MRI, thus (i) avoiding
non-therapeutic dose to the patients for CT acquisitions and (ii) pushing towards
MRI-only workflows, which perfectly match with the future availability of MRIintegrated proton therapy systems. Initial investigations on synthetic CT generation
from MRI for PT have started. Although different methods have shown promising
results in treatment planning studies (see table 10.1 in Hoffmann et al 2020), no
validation studies have been performed so far. A comprehensive review on artificial
intelligence strategies to derive synthetic CT is reported in chapter 8.
In the context of uveal melanoma, the feasibility and suitability of a 3D MRIbased treatment planning approach have been successfully tested, by implementing a
full 3D MRI-based treatment planning approach with a gaze-angle proton dose
optimization from 7 Tesla high-resolution MRI data (Fleury et al 2021).
MRI has also shown the potential to enhance the quantification of tissue
parameters that are relevant for PT planning, such as the stopping power ratio
(SPR; Scholey et al 2021). This brings the prospect of reducing systematic
uncertainties in estimating the particle range, when compared to conventional
stoichiometric calibration based on CT (Paganetti 2012).
The relevance of MRI in treatment planning has also been demonstrated in the
literature for moving organs, where the plan, which currently relies on a single
4DCT before treatment ignoring respiratory variability, must be robust enough to
account for inter- and intra-fraction variations. Specifi cally, respiratory-correlated
4DMRI was exploited to implement the so-called virtual 4DCT (v4DCT), which
was first introduced by Boye et al (2013) and subsequently extended by Meschini
et al (2020), and consisted of warping a planning static CT on respiratory phases
depicted in a respiratory-correlated 4DMRI, thus producing additional respiratory
phases with respect to those depicted in a planning 4DCT, which can be included in
plan optimization or used to evaluate the plan robustness against unseen conditions
(Bernatowicz et al 2016). Relying on this methodology, Krieger et al (2020)
optimized 4D proton treatment plans on internal target volumes (ITVs) based on
7-10
Imaging in Particle Therapy
different v4DCTs. Different probabilistic ITVs were created by incorporating the
voxels covered by the clinical target volume in at least 25%, 50%, or 75% (ITV25,
ITV50, ITV75) of the cycles, and compared with the conservative ITV encompassing
all possible target positions; results showed that probabilistic ITV50 provided an
adequate compromise between target coverage and lung dose for most scenarios,
with irregular respiration significantly affecting target coverage when ITVs were
only defined by single 4DCTs. In pancreatic cancer, the v4DCT methodology was
exploited to investigate the effectiveness of the gating procedure both in proton and
carbon ions treatments (Dolde et al 2019a, Meschini et al 2022b) and to evaluate the
interplay effect for pencil beam scanning proton therapy (Dolde et al 2019b). The
method was also validated relying on physical phantoms and tested for its
application in proton and carbon ions treatment of lung cancer (Annunziata et al
2023).
Cine-MRI data were also investigated to quantify off-line organ motion and
evaluate margins in carbon ion therapy of abdominal lesions against cycle-to-cycle
variations, showing that the gating procedure adopted in a clinical institution (i.e.
National Center for Oncological Hadrontherapy, Pavia, Italy) was effective
(Kalantzopoulos et al 2020, Meschini et al 2022a). Specifically, in Meschini et al
(2022a), time-resolved virtual 3DCTs were generated for each cine-MRI frame
(figure 7.6) allowing for dose recalculation, potential testing of RBE-weighted 4D
Figure 7.6. Treatment plan robustness evaluation. Planned dose on end-exhale CT (a and c) and recalculated
dose on the virtual CT (vCT) (b and d) for two representative patients with high and limited anatomical
variations, respectively. The contoured structures represent gross target volume (GTV; red), clinical target
volume (CTV; pink), duodenum (light blue), stomach (green), and colon (orange). Picture taken from
Meschini et al (
Periodicals LLC on behalf of American Association of Physicists in Medicine.
2022a). John Wiley & Sons. © 2022 The Authors. Medical Physics published by Wiley
7-11
Imaging in Particle Therapy
particle dose calculation for non-periodic motion (Steinsberger et al 2021) and
eventual dose accumulation.
7.4.2 Off-line adaptation
In current PT practice where no in-room/in-beam MRI systems are available, nearroom MRI can be then adopted offline to adapt the original treatment plan on the
basis of the daily patient-specific anatomo-pathological condition. This is most often
encountered when changes in patient contour are seen, as on the current workflow
based on CBCT, because of weight change or treatment response during conventionally fractioned courses. These changes trigger the creation of a new plan in an
attempt to improve dosimetry and achieve the planned prescription for the
remaining fractions (Hunt et al 2018). The current clinical approach adopted in
MRI-linacs mainly consists of registering via DIR the planning CT scan on the inroom MRI acquisition, thus obtaining a virtual CT scan on which the plan can be
recalculated and adapted on the anatomy of the day (Kurz et al 2020). This can be
potentially translated in an offline scenario, where virtual CT (or virtual 4DCT in
case of moving organs) can be exploited through repeated radiation-free MRI
acquisitions and combined with automated contour propagation and plan reoptimization engines for more frequent plan adjustments (Landry et al 2015,
Meschini et al 2022b). As previously mentioned, synthetic CT based on deep
learning could also play a role in treatment adaptation, by directly generating a CT
scan on the basis of the acquired MRI scan of the day, thus overcoming DIR
limitations when markedly different anatomy is present between the planning CT
and the MRI scan. In this context, any adaptation, even if implemented at a single
time point during a conventionally fractionated treatment course, delivers dosimetric improvement above a single planning scan.
Recently, the potential value of MRI-based adaptation during PT has been
investigated relying on MRI data acquired offline in the treatment position to detect
anatomo-pathological changes. Patients demonstrating changes on MRI showed
improved plan quality when reoptimized offline (Acharya et al 2021; figure 7.7).
The feasibility for an offline adaptive protocol with near-room MRI was
implemented relying on a shuttle-based MRI workflow in pelvic tumours in
conventional radiotherapy, but limitations, also transferrable to a PT scenario,
are still present in terms of (i) long treatment workflow, (ii) prolongated patient
immobilization and (iii) persistence of inter- and intra-fraction variations, especially
in case of organs affected by respiratory motion (Bostel et al 2018).
7.4.3 Online adaptation
In in-beam MRI proton therapy systems, the generation of accurate volumetric and
time-resolved or 4D MR images of the patient in the treatment position will
immediately raise important questions regarding the impending fraction of radiation
to be delivered pushing towards online adaptation (Hoffmann et al 2020). The
obvious question is whether or not the patient’s daily anatomy and positioning
matches that of the planning stage. A dose recalculation on the new MRI scan of the
7-12
Imaging in Particle Therapy
Figure 7.7. Gross tumour volume initial (yellow), clinical target volume initial (red), gross tumour volume
adapted (blue), clinical target volume adapted (brown), and 95% isodose line (green) of the initial plan, the
delivered plan on MRI
demonstrating tissue density change; (B) patient 3, demonstrating target volume shift as the medial border of the
resection cavity shifts laterally; (C) patient 8, demonstrating target volume reduction; and (D) patient 5,
demonstrating tissue density change and target volume reduction. Reprinted from Acharya et al (
Copyright (2021), with permission from Elsevier.
(i.e. MRI acquired during treatment), and the adapted plan for (A) patient 1,
tx
2021).
day acquired online of the patient anatomy will need to be performed and the dose
coverage and constraints be reassessed. All this needs to be completed in a timely
fashion as well, since the patient will be waiting on the treatment couch. Also, in this
case as for off-line adaptation, the generation of virtual/synthetic CT from MRI
data would support the online workflow.
Further to this, delivering a proton beam fraction with real-time MRI images (i.e.
cine-MRI) will open up the option to (i) treat with beam gating or even tumour
tracking while directly imaging the tumour, and (ii) accumulate the delivered dose
information for offline treatment replanning or re-optimization. Gated treatments
could be expected as the default treatment style, where real-time MRI information
provided by cine-MRI is used to confirm that the patient position has not changed
significantly and that beam-on can continue as normal. For tumours that move,
7-13
Imaging in Particle Therapy
real-time motion mitigation could be achieved through synchronizing the dynamic
MR images with the beam control system; simple lateral tumour motion (relative the
beam direction) could be in principle tracked dynamically by globally shifting
the PBS delivery pattern, but beam energy adaptation depending on the changes of
the traversed anatomy, and in the more realistic case of true 3D tumour motion,
could be challenging due to the degradation of the dose coverage (Mori et al 2018,
Hoffmann et al 2020). Alternatively, multiphase 4D dose delivery schemes could be
applied, as they require only lateral adaptation with online selection of a library of
plans corresponding to different breathing phases (Steinsberger et al 2022).
The unique offerings of in-beam integrated MRI-guided proton therapy will give
rise to an almost mandatory change in workflow. A similar workflow is observed in
MRI-linac radiotherapy systems where daily replanning is required if the anatomy of
the day is not consistent with the planning stages. It can be appreciated that proton
therapy planning is more sensitive to anatomy changes than x-ray radiotherapy, dose
calculation accuracy requirements are more demanding in proton therapy than in
x-ray therapy, and so the integrated MRI-guided proton therapy workflow will need to
be very robust to unlock the true potential of such hybrid systems.
7.4.4 Follow-up examinations
Finally, the treatment response is usually evaluated by acquiring follow-up MR
images and measuring the change in size of the tumour either in one dimension
(RECIST and RECIST 1.1—Response Evaluation Criteria in Solid Tumours) or in
two dimensions (WHO criteria—World Health Organization; Suzuki et al 2008).
The advantage of MRI to obtain functional imaging can be also exploited to
evaluate with quantitative parameters (e.g. from diffusion and perfusion MRI) the
structural characteristics of the tumour in response to therapy, along with potential
toxicities in nearby healthy organs (Gurney-Champion et al 2020, Kurz et al 2020,
Thorwarth et al 2020, Keall et al 2022). Refer to chapter 11 for more details on
quantitative MRI.
7.5 Conclusion and future perspectives
MRI offers exquisite soft-tissue contrast, unparalleled fast image acquisition
flexibility, ionizing dose-free imaging and functional imaging capabilities. Due to
these advantages, commercial MRI-linac systems have been recently introduced in
the clinic of conventional x-ray radiotherapy with potential improvements on
treatment outcome. The potential of MRI guidance can be also exploited in PT
to exploit the full benefit of its intrinsic geometrical selectivity and radiobiological
effectiveness.
Currently, the utility of MRI has been already demonstrated in the literature
relying on acquisitions with near-room MRI scanners. MRI can be used to support
treatment planning, including contouring, treatment evaluation and robust optimization. For this latter application, the availability of time-resolved and respiratory-correlated 4DMRI in anatomical site that move as a function of respiration
could provide more accurate information on respiratory motion variability than that
7-14