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Artificial Intelligence in Adaptive Radiation Therapy
CBCT shows anatomic change but can also be determined from computed tomography (CT), positron emission tomography (PET), or MRI. Online adaptive therapy is generally based on CBCT or MRI, with PET being a recent addition. In principle, the use of MRI or PET can provide important functional information about changes in the tumor, in addition to anatomic changes. However, adaptation that shrinks the target volume based on either anatomic or functional imaging risks undertreatment of the disease.

4.2 Imaging for treatment planning

Tumor delineation stands as a pivotal process in radiotherapy, inuencing treatment accuracy and patient outcomes. Medical imaging plays a crucial role in this regard by facilitating the precise localization of tumor targets for radiation delivery. Historically, planar x-ray imaging served as the primary modality for this purpose. However, the advent of CT revolutionized the eld by enabling three-dimensional visualization of both the tumor and surrounding normal tissues within the patient anatomy. CT integration into radiotherapy treatment planning ushered in a new era of three-dimensional dose optimization and enhanced patient positioning accuracy. Despite these advancements, CT exhibits limitations in tissue contrast and lacks functional insights.
The emergence of linear accelerators (linacs) and advanced dose delivery techniques underscores the importance of achieving higher precision in radio­therapy. The accuracy of manual tumor delineation on CT now dictates the level of treatment precision attainable. Consequently, there is a growing demand for more rened tumor denition techniques to optimize patient outcomes. Integrating complementary imaging modalities such as MRI and PET offers a promising avenue for enhancing tumor delineation. MRI excels in providing superior soft tissue contrast, thereby facilitating more accurate tumor delineation compared to CT. PET imaging, on the other hand, offers valuable metabolic and functional information critical for tumor grading and delineation. By combining the strengths of CT with these modalities, clinicians can access a comprehensive dataset that improves tumor denition and, ultimately, treatment efcacy in radiotherapy.
4.2.1 CT simulation
CT provides volumetric imaging for both diagnostic imaging and radiation oncology. CT uses a gantry-mounted x-ray source and detectors to record x-ray transmission of an object. The x-ray source consists of a cathode and an anode. Electrons are produced by the cathode and then accelerated towards a rotating tungsten anode to create x-ray via Bremsstrahlung. The detectors are usually made of a scintillating material, converting x-ray to visible light, which is then collected by a photodiode. During image acquisition, the x-ray and detectors rotate simulta­neously. The raw x-ray projection data form a sinogram. The CT image is reconstructed from the sinogram using ltered-back-projection (FBP) techniques. The output of FBP is the linear attenuation coefcient (μ) for each voxel. CT images are displayed with Hounseld units (HU):
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U 1000 .
mm
material water
m
water
CT is commonly used in radiation oncology for patient simulation. It provides planning CT volumes for patient positioning and dose calculation. The CT simulator has a at couch to mimic the treatment couch of a linac so that the patient pose is similar during treatment. They also have lasers to help reproduce the patient position when aligning for treatment. Unlike CTs in diagnostic imaging, HU accuracy is crucial for CT simulators. The HU is converted to electron density and serves as the basis for dose calculation. The electron density derived from the CT simulator is the gold standard for dose calculation. Therefore, an accurate calibration curve is required during the commissioning of the scanner to ensure accurate dose calculation.
Technological advances in CT have been applied to radiation oncology. Coolens et al implemented a 320-slice volumetric scanner for CT simulation [7]. By using volume scanning instead of helical scanning, the scanner can capture the entire treatment site within a single gantry rotation. The scan time is thus reduced, and motion artifacts are minimized. Most centers, however, still use the larger bore helical scanners. Dual-energy CT (DECT) was investigated as a candidate for simulation in proton therapy. By capturing CT images under two energies, DECT can differentiate x-ray attenuation change in density or chemical composition [8]. It can then calculate stopping power ratio and improve proton radiotherapy planning by reducing range uncertainties. Currently, the high level of noise still hinders the wider adoption of DECT in proton therapy simulation [9]. More recently, clinical deployment of photon counting CT (PCCT) also provides opportunities in the improvement of radiation simulation. The photon counting detector can resolve energy by counting photons in selected energy bins. It has the potential to directly calculate the stopping power ratio using the Bethe–Bloch equation. The scanner achieved stopping power ratio estimates that are comparable to DECT scanners [10]. PCCT is also capable of generating quantitative contrast enhanced CT scans. It can leverage the photon counting detectors energy resolution to provide increased tissue and contrast agent discrimination. This capability helps PCCT generate virtual non-contrast electron density and stopping power [11]. Patients can poten­tially avoid a non-contrast scan as well as its dose during simulation.
4.2.2 4D-CT
Four-dimensional CT (4D-CT) is often used for motion management during patient simulation. Patient breathing motion can often introduce uncertainty and blurring in simulation CT scans. 4D-CT captures multiple CT volumes at different phases of a patients breathing motion. This acquisition protocol oversamples at every position of interest in the superior–inferior direction by using the axial cine mode. Multiple CT images are reconstructed per slice and each of them represents a different anatomical state during a respiratory cycle. These CT images are sorted based on the phase of breathing measured by a breathing monitoring device such as respiratory gating system or abdominal belt [12]. The entire 4D-CT volume captures the patient
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motion throughout the entire breathing cycle. Maximum intensity projection and average CT are often compiled from the 4D-CT volume to account for patient motion. Clinicians can then dene the treatment target based on the tumor and organs-at-risk (OARs) motion throughout the treatment.
4.2.3 PET/CT
PET serves as a valuable tool for investigating the biodistribution of radio-labeled tracers, thereby enabling crucial metabolic and functional insights based on the biochemical pathways of these tracers. Among the commonly utilized tracers, uorine-18 udeoxyglucose (
18
F-FDG) stands out as a glucose analog that under­goes cellular uptake and subsequent intracellular entrapment. Through this mech­anism, FDG-PET identies metabolically active tissue within the body. PET/CT imaging combines anatomical and metabolic information, with CT images provid­ing anatomical reference points and aiding in attenuation correction for PET data. The integration of PET and CT functionalities within a hybrid device mitigates the risk of misalignment associated with patient repositioning [13]. PET/CT plays a pivotal role in identifying primary tumors and associated regional lymph nodes based on the increased uptake of
18
F-FDG [14]. Its utility becomes particularly evident in scenarios where tumor volumes are poorly dened or when dose escalation is warranted, necessitating precise delineation of tumor volumes and distinct boundaries from surrounding tissues.
Studies have underscored the efcacy of PET/CT in tumor delineation for various cancers, including lung, head and neck, esophageal, and cervical malignancies [15]. In lung cancer, PET/CT facilitates more accurate lymph node staging [16], reduces inter-observer variability during tumor delineation [17], and renes the delineation of tumor borders in conjunction with atelectasis [18]. Notably, PET/CT-derived gross tumor volumes (GTVs) have demonstrated superior accuracy when comparing with surgical specimens in a head and neck cancer study [19]. Prospective investigations in esophageal and cervical cancers have corroborated the positive impact of PET/CT on tumor delineation and the signicant reduction in late radiation toxicity [2022]. The evolution of PET/CT-guided radiotherapy has gained interest in dose painting strategies targeting specic tumor sub-volumes based on biological imaging [23]. Escalated doses can be prescribed to radio-resistant tumor regions to enhance local tumor control [24].
Despite the widespread use of
18
F-FDG, other PET tracers such as uorine-18 uoromisonidazole (FMISO) and uorine-18 uoroazomycin arabinoside (FAZA) provide non-invasive and quantitative assessments of tumor hypoxiaacritical determinant of radiation treatment resistance. Hypoxia volumes measured via FMISO-PET serve as predictive factors for patient survival in head and neck cancer [25]. Targeting hypoxic tumor volumes with escalated doses represents a promising strategy to improve tumor control. Additionally, the active cellular proliferation characteristic of tumors can be assessed using uorine-18 uorothymidine ( a thymidine analogue that monitors thymidine kinase activitya surrogate marker for cell proliferation [26]. Given its low uptake in inammatory tissues,
18
F-FLT),
18
F-FLT is
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preferred in highly inammatory cancers such as head and neck cancer, where false­positive results from FDG-PET could lead to the enlargement of GTVs [27].
While PET imaging aids in avoiding tumor misses and minimizing unnecessary radiation exposure to healthy tissues, its spatial resolution remains a limitation compared to modern CT scanners [28]. The spatial resolution of current PET scanners typically ranges from 5 to 8 mm, which may result in the oversight of small lesions, particularly in cases of signicant patient motion [29]. Furthermore, there is a risk of including non-malignant FDG-avid tissue within the target volume, potentially increasing the likelihood of long-term complications. The delineation method employed signicantly impacts the quality assessment of GTVs. While thresholding based on a percentage of the maximum tumor standardized uptake value (SUV
) is a common approach [30], alternative methods such as contrast-
max
based [31], gradient-based [32], and statistically stochastic algorithms [33] are also utilized, with their efcacy dependent on imaging parameters and tumor character­istics [30].
4.2.4 MRI
Despite its established role in diagnostic imaging, MRI has emerged as a valuable complement to CT imaging in radiotherapy treatment planning. MRI offers several advantages over CT, notably superior soft tissue contrast and its intrinsic three­dimensional imaging capability. However, limitations include the absence of electron density information, geometric distortion, and a restricted eld-of-view (FOV). Nonetheless, advancements in MRI technology have facilitated its integra­tion into the radiotherapy workow. Initially, disparities in patient positioning between diagnostic MR scans and radiotherapy simulation CT scans posed challenges due to the differences between curved cushion-lined MR systems with at-bed couches in CT scanners. Subsequent availability of commercial MRI­simulators featuring at-bed couches has mitigated this issue. Nevertheless, image co-registration remains essential to align the two modalities within the same coordinate system. Image registration introduces systematic geometrical uncertain­ties of 2–3 mm throughout the treatment process, potentially compromising tumor control [34 ]. The integration of MRI into treatment planning has yielded signicant improvements in target delineation quality and reduced inter-observer variability, particularly in tumors of the brain, head and neck, and pelvis [35].
As a multi-parametric modality, MR systems offer both anatomical and func­tional information through diverse techniques and sequences. The concept of MR­only treatment planning has recently gained traction [34]. While MRI inherently lacks direct electron density information, various methods have been proposed to generate synthetic CT images based on MRI data [36, 37]. However, challenges such as image distortion and artifacts have hindered the widespread adoption of MRI as a primary imaging modality in radiotherapy planning. Despite these challenges, ongoing research aims to address these limitations and further optimize the integration of MRI into radiotherapy planning workows [3841].
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4.2.4.1 Anatomical MRI
MRI relies on the detection of nuclear magnetic moments, primarily originating from hydrogen nuclei (protons) that are predominantly found in water and lipids within the body. These protons undergo precession at the Larmor frequency (ω
= γB0) when subjected to a strong main magnetic eld (B0), where γ represents
0
the gyromagnetic ratio. MR images can be acquired to visualize the distribution of protons in the body, commonly referred to as proton density images. However, proton density images typically exhibit limited tissue contrast, although they prove valuable in diagnosing conditions such as edema and inammatory diseases [42]. The most frequently employed anatomical MRI sequences include T1-weighted (T1w) and T2-weighted (T2w) scans, which rely on the manipulation of longitudinal (T1) and transverse (T2) relaxation times. These relaxation times are inuenced by molecular motion and interactions within tissues, resulting in varying signal characteristics across different tissue types. Contrast in MRI is achieved by weighting signals based on T1 and T2 relaxation times. T1w images are generated using short echo time (TE) and relaxation time (TR), whereas T2w images are produced using relatively longer TE and TR parameters. Various techniques, such as fat saturation, inversion-recovery imaging, and opposed-phase imaging, can be employed to suppress fat signal, enhancing tissue contrast [43]. T1w and T2w images nd extensive utility in MR-guided adaptive radiotherapy, facilitating improved visualization and delineation of target volumes [44].
4.2.4.2 Post-contrasted MRI
Paramagnetic or superparamagnetic agents capable of signicantly altering the relaxation times (T1 and/or T2) of nearby protons serve as crucial MRI contrast agents. Among the most employed agents is gadolinium-based contrast agent, which effectively shortens T1 relaxation times. Tissues enhanced with gadolinium-based agents exhibit increased signals in T1w images. Studies indicate that gadolinium­contrasted MRI yields better concordance with biopsy ndings compared to T2w MRI [45]. Another prevalent contrast agent is superparamagnetic iron oxide (SPIO) particles, which attenuate T2 signals in tissues where they accumulate, and are commonly employed in imaging of kidneys and spleens [46]. Additionally, man­ganese-based and iron platinum-based agents are currently under investigation [47].
Dynamic contrast enhanced MRI (DCE-MRI) involves the acquisition of T1w images before and after the administration of contrast agents. DCE-MRI enables the measurement of multiple parameters related to tissue perfusion and micro­vascular status. Integration of DCE-MRI into tumor delineation protocols has been shown to reduce inter-observer variability [48]. Dynamic susceptibility contrast MRI (DSC-MRI) captures local magnetic inhomogeneities between extra- and intra­vascular volumes, generating attenuated T2 signals due to the presence of contrast agents within the vasculature [49]. Moreover, blood oxygen level-dependent (BOLD) imaging exploits differences in magnetic susceptibility between oxyhemo­globin and deoxyhemoglobin, while diffusion-weighted imaging (DWI) quanties molecular diffusion properties within tissues. These modalities have demonstrated
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efcacy in delineating tumor boundaries [5054]. However, considerable variation exists in the consistency of target volumes delineated using these protocols [55, 56].

4.3 Imaging for treatment guidance

4.3.1 Portal imaging
Modern image-guided radiation therapy (IGRT) systems are typically equipped with two imaging panels, the electric portal imaging device (EPID) and kV imaging panel. The EPID is used to capture 2D-MV planar images. It is typically an amorphous­silicon (a-Si) flat-panel imaging device mounted on a robotic arm directly under the linac head. The Varian Truebeam equipped with the latest aS1200 panel has a 40 × 40
2
active imaging area and a pixel size of 0.0336 cm. The robotic arm allows a source
cm to EPID distance from 95 to 180 cm. Improvements have been made on the panel so that it can handle a attening lter free (FFF) dose rate without saturation at any source to detector distance [57]. Elekta linacs are equipped with iViewGT EPID. The active imaging area is 41 × 41 cm × 1024 diodes with a pitch of 400 μm[58]. Both the Varian and Elekta IGRT systems are also capable of capturing kV planar images. The Varian On-Board Imager (OBI) has two robotic arms that are mounted perpendicular to the radiation beam. One holds the x-ray source and the other holds the a-Si at-panel detector. The active imaging area is 40 × 30 cm imager distance from 100 to 182.5 cm depending on the imaging protocol. The Elekta X-ray Volume Imaging (XVI) system has a similar layout with two robotic arms. The active imaging is 42.5 × 42.5 cm systems are comparable [58, 59]. Both kV and MV planar imaging techniques are quick to acquire and deliver less dose to the patient. While soft tissue might be difcult to visualize on planar images, bony structures or ducials are visible. This makes planar x-ray imaging ideal for treatment set-up verication.
2
. The image matrix is created from an array of 1024
2
for the OBI system. The user can adjust the source to
2
. The high contrast spatial resolutions of the two
4.3.2 CBCT
4.3.2.1 kV-CBCT
For modern IGRT systems, gantry-mounted kV imaging is an important compo­nent. Elektas XVI and Varians OBI provide imaging at the same isocenter of the linear accelerator. With kV-CBCT, volumetric imaging is available for therapists to align patient to the reference CT simulation image before each fraction. This allows the localization of patient anatomy at each treatment fraction and improves the accuracy of treatment delivery.
The developments in at-panel detectors made gantry-mounted kV-CBCT possible. The a-Si at-panel detector used in gantry-mounted kV imaging systems is made up of a CsI plastic scintillator which converts the x-ray photons into visible light which is then detected by a-Si thin lm transistor (TFT) and read out as an electrical signal [60]. This indirect detector is ideal for the orthogonal conguration proposed by Jaffray et al [61] due to its compact size and potential for high resolution imaging. Cone beam reconstruction was applied to reconstruct a volumetric image from the at panel. Compared to multi-slice detectors in fan
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beam CTs, the a-Si at panel has a lower x-ray cross section, higher noise, longer readout, and longer time to reset. These properties are important factors to consider when it is used as image guidance for adaptive radiation therapy. In addition, the on-board CBCTs FOV is limited by the size of the at-panel detector. Cone beam reconstruction only requires a 180° rotation under full-fan mode to acquire a sonogram for a volumetric image. A half fan technique was proposed to increase the FOV to up to 50 cm. The detector and the kV source are offset in this conguration. A 360° rotation is required to acquire two separate sonograms that are stitched together for a full view of the patient.
Accurate characterization of the HU is crucial for CBCT used in adaptive therapy settings. Calibration of the at panel is thus essential for an adaptive program. The pixel array of the at-panel detector is made of groups of a-Si units. Each pixel has different calibration curve. Dark eld calibration is used to characterize the dark signal of the pixel. Flood eld calibration is used to characterize the slope of the calibration curve. Individual calibration curves are applied to each pixel so that the response of the at panel remains uniform despite variances within readout electronics. However, cone beam geometry introduces non-uniformity in HU char­acterization for CBCT. The x-ray scatter is more pronounced at the center of the CBCT image for large FOV scans. This leads to cupping artifacts and introduces non­uniformity into the volumetric image. CBCT is also susceptible to motion artifacts. Since the on-board imager takes around 60s to complete the acquisition, CBCT is more susceptible to motion artifacts compared to fan beam CT. Metal artifacts in CBCT are also more pronounced due to the lack of metal artifact reduction common in diagnostic CT. These artifacts contribute to uncertainties in HU characterization and should be noted for CBCT-based adaptive therapy programs.
4.3.2.2 Hypersight kV-CBCT
The new Hypersight kV-CBCT system integrated in the Halcyon/Ethos ring style linac was introduced recently. The new system applied iterative CBCT image reconstruction (iCBCT) techniques to reconstruct the volumetric image. Compared to the lter back projection-based Feldkamp–Davis–Kress (FDK) algorithm, iCBCT exhibited increased accuracy in CT number accuracy and reduced noise. In addition, a larger kV imaging panel (86 × 43 cm
2
versus 43 × 43 cm2) made of cesium iodide scintillator (higher efciency) was added. With the larger panel, the imager operates in full-fan mode. The detector with a high frame rate also enabled a faster scan time down to 5.9 s. A new anti-scatter grid was introduced. A more robust scatter correction algorithm incorporating Acuros CTS based scatter model and Monte Carlo based hardware scatter was incorporated in the iCBCT software [62]. It also incorporated an extended FOV (eFOV) up to 70 cm and metal artifact reduction (MAR).
The new CBCT addressed many existing concerns with CBCT regarding scatter correction, metal artifacts, and motion artifacts for image quality. For adaptive therapy purposes, the CBCT system generated encouraging results. The new imaging system achieved more realistic CT numbers under the CBCT mode. In a recent study by Bogowicz et al [63], the CBCT-based planning dose distributions showed an
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agreement above 97% and 93% for gamma analysis with criteria of 3%/1 mm and 2%/ 1 mm, respectively, compared with the simulation CT dose distribution. All dose–volume histogram (DVH) differences between CT and CBCT were below 2%. The CBCT images provided by the Hypersight kV-CBCT system would be suitable for online adaptive radiotherapy workow.
4.3.3 CT-on-rail and CT-linac
In modern radiotherapy, the minimization of treatment margins holds signicant importance as these margins directly correlate with excessive tissue toxicity and impose constraints on the dose escalation necessary for improved tumor control. Enhancing the accuracy of daily patient set-up and tumor localization represents a pivotal approach to address this challenge. The integration of in-room CT scanners has signicantly contributed to the implementation of imaging-guided techniques [64]. Siemens introduced the PRIMATOM system, featuring a xed couch and diagnostic CT scanners mounted on rails, commonly referred to as CT-on-rail systems. In this set-up, the linac gantry and CT gantry can be positioned on opposite ends of the treatment couch. Pre-treatment 3D CT localization of the tumor is achieved by rotating the couch 180°. The reported positional accuracy of the couch in CT-on-rail systems is within 0.4 mm in all three directions [65]. Systematic investigations have been conducted to assess the mechanical uncertainties of CT-on­rail systems [66]. Given the superior image quality and the ability to visualize real­time anatomy while the patient is immobilized, CT-on-rail systems have found extensive application in clinical studies, particularly in prostate cancer treatment. Various institutions have reported the feasibility and dosimetric advantages of CT­on-rail for daily prostate alignment [6769]. Moreover, the system has demonstrated utility in other treatment sites characterized by signicant target position variability, such as the lungs and liver [70, 71].
Another innovative solution incorporating in-room CT scanning is the CT-linac system, which integrates a C-arm linear accelerator with a CT scanner coaxially attached behind the linear accelerator. Unlike the CT-on-rail approach, the CT­linac system eliminates the need for 180 ° couch rotation, thereby reducing the uncertainties associated with rotation. Investigations have demonstrated that the CT-linac system offers clinically acceptable plan quality and dose delivery efciency [7274].
4.3.4 MR-linac
The MR-linac represents one of the latest developments of image-guided adaptive radiotherapy. It utilizes real-time on-board MRI during treatment sessions to guide and adapt the delivery of radiation. A unique advantage of MR-guided radio­therapy (MRgRT) is the superior visualization of tumors and soft tissues provided by the real-time MRI [75]. The crispy target visualization and online adaptive platform offered by MR-linac enables precise targeting while minimizing radiation exposure to healthy tissues, leading to improved therapeutic outcomes. In addition, MRgRT has the advantage of real-time imaging while the treatment beam is on,
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enabling real-time target motion monitoring and tracking, further improving the precision of radiation treatment. The currently most popular MR-linac systems are summarized below. Details of the MRgRT can be found in chapter 16.
4.3.4.1 Low field MR-linac
The ViewRay MRIdian system is a representative of low eld MR-linac systems. The ViewRay system integrates a 0.35 tesla low eld MRI scanner with a linear accelerator for MRI-guided treatment. This system is the rst MR-linac device used for clinical MRgRT and received Food and Drug Administration (FDA) approval in 2017 [5]. The MRIdian system consists of a split-bore superconducting magnet with a bore diameter of 70 cm perpendicular to a 6 MV FFF linear accelerator system. The linear accelerator produces coplanar static intensity-modulated radia­tion therapy (IMRT) elds and delivers dose at 650 MU/min with a 0.5 revolutions per minute (rpm) gantry rotation. The MRI system uses a balanced steady state free precession pulse sequence for MR imaging that can be used for treatment planning and set-up verication. The MRIdian system also allows for real-time imaging during treatment beam-on, enabling intrafraction motion monitoring during treat­ment. This feature allows for real-time tumor tracking and automatic beam gating based on user dened gating boundaries on a sagittal cine image [76]. Another low eld MR-linac system is the MagnetTx Aurora-RT, which is a 0.5 tesla MR-linac utilizing an open bore in-line design to mitigate the electron return effect [77]. The Aurora-RT received FDA premarket clearance in 2022 and treated its rst patient in
2023.
4.3.4.2 High field MR-linac
The Elekta Unity system (Elekta AB, Stockholm, Sweden) is the rst high eld MR­linac that integrates a 7 MV FFF linac system and a 1.5 tesla Philips (Philips Healthcare, Best, the Netherlands) MRI system [78]. The Unity system is designed as a bore-type machine with a linac system rotating around the MRI system, which has an inner bore diameter of 70 cm [79]. The radiation beam is perpendicular to the magnetic eld orientation. The treatment couch moves in the longitudinal direction only; however, during treatment the couch is not designed to move to adjust treatment isocenter location. Instead, online adaptive planning is utilized to account for isocenter shifts. The system offers an integrated online adaptive planning workow and every fraction treated with Elekta Unity requires an online adaptive planning. The system also allows for simultaneous MR imagining and treatment delivery. In its rst version, the Unity system offered only tumor motion monitoring [80]. In late 2023, Elekta released the comprehensive motion management (CMM) system, allowing for different levels of motion management for better control of respiratory motion and other motion uncertainty during treatment delivery [81]. It is also worth noting that due to the high strength of the magnetic eld, the beam prole is inherently off-center and asymmetric, and the electron return effect can cause electrons to change trajectory to returnto a higher density material at the interface of exiting a higher density material into a lower density material [82].
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4.3.5 PET-linac
The advent of PET-linac systems, exemplied by the Reexion system, has introduced the concept of biology-guided radiotherapy (BgRT) [83]. Integrating both kV CT and PET scanners within a ring gantry linear accelerator, the Reexion system enables real-time beamlet conformation based on PET signals acquired from the tumor, with sub-second latency. This swift response capability allows the system to manage patient motion without the need for motion trackers or breath-holding techniques. Moreover, PET images generated by the Reexion system exhibit comparability to those obtained from traditional PET/CT scanners [84]. PET images hold signicant potential in the realm of biologically adaptive radiation therapy (BART), which integrates tumor or OAR function into adaptive planning strategies. Prior trials have demonstrated the advantages of intra-treatment FDG and hypoxia PET images in facilitating dose escalation and enhancing local tumor control [85, 86]. The evolution of PET-linac technology is expected to facilitate clinical trials aimed at investigating the efcacy of daily PET-guided plan adaptation.

4.4 Imaging for motion management

4.4.1 ExacTrac
Novalis ExacTrac system is an x-ray system designed for stereotactic radiosurgery (SRS) and stereotactic body radiotherapy (SBRT). The system consists of two components: a real-time infrared (IR) tracking system and a kV imaging system. The IR system detects motion in real time using the IR reecting markers. These markers can be placed on the reference frame mounted on the treatment couch, or on the patients skin. The camera combined with the IR system conrms patient position­ing and monitors patient movement. The x-ray system has two x-ray tubes installed in the oor and two at-panel detectors mounted on the ceiling. The system is mounted obliquely to the mid-sagittal plane of the accelerator. The x-ray system acquires projection images and localizes the patient by registering bony landmarks or implanted markers with the corresponding digitally reconstructed radiograph (DRR) from the planning CT.
4.4.2 Varian triggered imaging
Triggered imaging is a kV imaging technique included in the Varian advanced imaging package. Triggered imaging uses the OBI of the Varian Truebeam to monitor high contrast regions during treatment delivery. The high contrast regions are typically implanted ducial markers, endogenous patient anatomy (vertebral body and spinous process), or endogenous orthopedic hardware [87]. The kV images are typically taken with an intrafraction motion review application at specic gantry intervals to ensure accurate delivery. The system is capable of auto beam hold (ABH), pausing the beam delivery when the tracking region falls outside of tolerance. Varian triggered imaging enables intrafraction IGRT. There have been
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