Purpose-To investigate the feasibility and value of positron emission tomography and computed tomography (PET/CT) for treatment verification after proton radiotherapy.Methods and Materials-This study included 9 patients with tumors in the cranial base, spine, orbit, and eye. Total doses of 1.8-3 GyE and 10 GyE (for an ocular melanoma) per fraction were delivered in 1 or 2 fields. Imaging was performed with a commercial PET/CT scanner for 30 min, starting within 20 min after treatment. The same treatment immobilization device was used during imaging for all but 2 patients. Measured PET/CT images were coregistered to the planning CT and compared with the corresponding PET expectation, obtained from CT-based Monte Carlo calculations complemented by functional information. For the ocular case, treatment position was approximately replicated, and spatial correlation was deduced from reference clips visible in both the planning radiographs and imaging CT. Here, the expected PET image was obtained from an analytical model.Results-Good spatial correlation and quantitative agreement within 30% were found between the measured and expected activity. For head-and-neck patients, the beam range could be verified with an accuracy of 1-2 mm in well-coregistered bony structures. Low spine and eye sites indicated the need for better fixation and coregistration methods. An analysis of activity decay revealed as tissueeffective half-lives of 800-1,150 s.Conclusions-This study demonstrates the feasibility of postradiation PET/CT for in vivo treatment verification. It also indicates some technological and methodological improvements needed for optimal clinical application.

Protons are an interesting modality for radiotherapy because of their well defined range and favourable depth dose characteristics. On the other hand, these same characteristics lead to added uncertainties in their delivery. This is particularly the case at the distal end of proton dose distributions, where the dose gradient can be extremely steep. In practice however, this gradient is rarely used to spare critical normal tissues due to such worries about its exact position in the patient. Reasons for this uncertainty are inaccuracies and non-uniqueness of the calibration from CT Hounsfield units to proton stopping powers, imaging artefacts (e.g. due to metal implants) and anatomical changes of the patient during treatment. In order to improve the precision of proton therapy therefore, it would be extremely desirable to verify proton range in vivo, either prior to, during, or after therapy. In this review, we describe and compare state-of-the art in vivo proton range verification methods currently being proposed, developed or clinically implemented.

Pencil-beam scanning (PBS) proton therapy (PT), particularly intensity modulated PT, represents the latest advanced PT technology for treating cancers, including thoracic malignancies. On the basis of virtual clinical studies, PBS-PT appears to have great potential in its ability to tightly tailor the dose to the target while sparing critical structures, thereby reducing treatment-related toxicities, particularly for tumors in areas with complicated anatomy. However, implementing PBS-PT for moving targets has several additional technical challenges compared with intensity modulated photon radiation therapy or passive scattering PT. Four-dimensional computed tomography-based motion management and robust optimization and evaluation are crucial for minimizing uncertainties associated with beam range and organ motion. Rigorous quality assurance is required to validate dose delivery both before and during the course of treatment. Active motion management (eg, breath hold), beam gating, rescanning, tracking, or adaptive planning may be needed for cases involving significant motion or changes in motion or anatomy over the course of treatment.

The most advanced delivery technique for proton radiotherapy is active spot scanning. So far, predominantly static targets have been treated with active spot scanning, since mobile targets in combination with dynamic treatment delivery can lead to interplay effects, causing inhomogeneous dose distributions. One way to mitigate motion effects is re-scanning. In this study we investigate the effectiveness of re-scanning in relation to different plan parameters (number of fields, field directions, number of re-scans) as well as in respect to different motion parameters (motion amplitude, motion starting phase). A systematic study was performed for three liver patients, for which ten different plans have been calculated, respectively. The treatment plans were evaluated for three different scenarios (static, motion/single-scan-delivery, motion/re-scanned-delivery). The choice of motion parameters was based on an evaluation of the 4D CT data sets of the three patients. It is shown that the effect of motion/re-scanning per fraction is largest the fewer fields per plan are used and the more the field direction differs from the main motion direction. For amplitudes up to 6 mm, re-scanning may not be required if multiple fields are used, since only dose blurring effects appear that cannot be compensated by re-scanning. For larger motion amplitudes two planning strategies are proposed.

Radiotherapy (RT) aims to deliver a spatially conformal dose of radiation to tumours while maximizing the dose sparing to healthy tissues. However, the internal patient anatomy is constantly moving due to respiratory, cardiac, gastrointestinal and urinary activity. The long term goal of the RT community to ‘see what we treat, as we treat’ and to act on this information instantaneously has resulted in rapid technological innovation. Specialized treatment machines, such as robotic or gimbal-steered linear accelerators (linac) with in-room imaging suites, have been developed specifically for real-time treatment adaptation. Additional equipment, such as stereoscopic kilovoltage (kV) imaging, ultrasound transducers and electromagnetic transponders, has been developed for intrafraction motion monitoring on conventional linacs. Magnetic resonance imaging (MRI) has been integrated with cobalt treatment units and more recently with linacs. In addition to hardware innovation, software development has played a substantial role in the development of motion monitoring methods based on respiratory motion surrogates and planar kV or Megavoltage (MV) imaging that is available on standard equipped linacs. In this paper, we review and compare the different intrafraction motion monitoring methods proposed in the literature and demonstrated in real-time on clinical data as well as their possible future developments. We then discuss general considerations on validation and quality assurance for clinical implementation. Besides photon RT, particle therapy is increasingly used to treat moving targets. However, transferring motion monitoring technologies from linacs to particle beam lines presents substantial challenges. Lessons learned from the implementation of real-time intrafraction monitoring for photon RT will be used as a basis to discuss the implementation of these methods for particle RT.

No abstract

The authors have demonstrated that motion information from 4D-MRI can be used to generate realistic 4D-CT data sets on the basis of a single static 3D-CT data set. 4D-CT(MRI) presents a novel approach to test the robustness of treatment plans in the circumstance of patient motion.

In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation decisions. Image quality deficiencies though, hamper dose calculation accuracy and make corrections of CBCTs a necessity. This study compared three methods to correct CBCTs and create synthetic CTs that are suitable for proton dose calculations. CBCTs, planning CTs and repeated CTs (rCT) from 33 H&N cancer patients were used to compare a deep convolutional neural network (DCNN), deformable image registration (DIR) and an analytical image-based correction method (AIC) for synthetic CT (sCT) generation. Image quality of sCTs was evaluated by comparison with a same-day rCT, using mean absolute error (MAE), mean error (ME), Dice similarity coefficient (DSC), structural non-uniformity (SNU) and signal/contrast-to-noise ratios (SNR/CNR) as metrics. Dosimetric accuracy was investigated in an intracranial setting by performing gamma analysis and calculating range shifts. Neural network-based sCTs resulted in the lowest MAE and ME (37/2 HU) and the highest DSC (0.96). While DIR and AIC generated images with a MAE of 44/77 HU, a ME of −8/1 HU and a DSC of 0.94/0.90. Gamma and range shift analysis showed almost no dosimetric difference between DCNN and DIR based sCTs. The lower image quality of AIC based sCTs affected dosimetric accuracy and resulted in lower pass ratios and higher range shifts. Patient-specific differences highlighted the advantages and disadvantages of each method. For the set of patients, the DCNN created synthetic CTs with the highest image quality. Accurate proton dose calculations were achieved by both DCNN and DIR based sCTs. The AIC method resulted in lower image quality and dose calculation accuracy was reduced compared to the other methods.