Current status and future prospects of multi-dimensional image-guided particle therapy

Optimizing 3DCT image registration for interfractional changes in carbon-ion prostate radiotherapy

To perform setup procedures including both positional and dosimetric information, we developed a CT-CT rigid image registration algorithm utilizing water equivalent pathlength (WEPL)-based image registration and compared the resulting dose distribution with those of two other algorithms, intensity-based image registration and target-based image registration, in prostate cancer radiotherapy using the carbon-ion pencil beam scanning technique. We used the data of the carbon ion therapy planning CT and the four-weekly treatment CTs of 19 prostate cancer cases. Three CT-CT registration algorithms were used to register the treatment CTs to the planning CT. Intensity-based image registration uses CT voxel intensity information. Target-based image registration uses target position on the treatment CTs to register it to that on the planning CT. WEPL-based image registration registers the treatment CTs to the planning CT using WEPL values. Initial dose distributions were calculated using the planning CT with the lateral beam angles. The treatment plan parameters were optimized to administer the prescribed dose to the PTV on the planning CT. Weekly dose distributions using the three different algorithms were calculated by applying the treatment plan parameters to the weekly CT data. Dosimetry, including the dose received by 95% of the clinical target volume (CTV-D95), rectal volumes receiving > 20 Gy (RBE) (V20), > 30 Gy (RBE) (V30), and > 40 Gy (RBE) (V40), were calculated. Statistical significance was assessed using the Wilcoxon signed-rank test. Interfractional CTV displacement over all patients was 6.0 ± 2.7 mm (19.3 mm maximum standard amount). WEPL differences between the planning CT and the treatment CT were 1.2 ± 0.6 mm-H₂O (< 3.9 mm-H₂O), 1.7 ± 0.9 mm-H₂O (< 5.7 mm-H₂O) and 1.5 ± 0.7 mm-H₂O (< 3.6 mm-H₂O maxima) with the intensity-based image registration, target-based image registration, and WEPL-based image registration, respectively. For CTV coverage, the D95 values on the planning CT were > 95% of the prescribed dose in all cases. The mean CTV-D95 values were 95.8 ± 11.5% and 98.8 ± 1.7% with the intensity-based image registration and target-based image registration, respectively. The WEPL-based image registration was CTV-D95 to 99.0 ± 0.4% and rectal Dmax to 51.9 ± 1.9 Gy (RBE) compared to 49.4 ± 9.1 Gy (RBE) with intensity-based image registration and 52.2 ± 1.8 Gy (RBE) with target-based image registration. The WEPL-based image registration algorithm improved the target coverage from the other algorithms and reduced rectal dose from the target-based image registration, even though the magnitude of the interfractional variation was increased.

Streamlining the image-guided radiotherapy process for proton beam therapy

OBJECTIVES

This work evaluated the on-treatment imaging workflow in the UK's first proton beam therapy (PBT) centre, with a view to reducing times and unnecessary imaging doses to patients.

METHODS

Imaging dose and timing data from the first 20 patients (70% paediatrics, 30% TYA/adult) treated with PBT using the initial image-guided PBT (IGPBT) workflow of a 2-dimensional kilo-voltage (2DkV), followed by cone-beam computed-tomography (CBCT) and repeat 2DkV was included. Pearson correlations and Bland-Altman analysis were used to describe correlations between 2DkV and CBCT images to determine if any images were superfluous.

RESULTS

229 treatment sessions were evaluated. Patient repositioning following the initial 2DkV (i2DkV) was required on 19 (8.3%) fractions. This three-step process resulted in an additional mean imaging dose of 3.4 mGy per patient, and 5.1 minutes on the treatment bed for the patient, over a whole course of PBT, compared to a two-step workflow (removing the i2DkV image). Correspondence between the mean displacements from i2DkV and CBCT was high, with R = 0.94, 0.94 and 0.80 in the anteroposterior, superiorinferior and right-left directions, respectively. Bland-Altman analysis showed very little bias and narrow limits of agreement.

CONCLUSIONS

Removing the i2DkV, streamlining to a two-step workflow, would reduce treatment times and imaging dose, and has been implemented as standard verification protocol. For challenging cases (e.g. paediatric patients under GA), further investigations are required before the three-step workflow can be modified.

ADVANCES IN KNOWLEDGE

This is the first report assessing a preliminary imaging protocol in PBT in the UK and determining a way to reduce dose and time, which ultimately benefits the patient.

Simulated four-dimensional CT for markerless tumor tracking using a deep learning network with multi-task learning

INTRODUCTION

Our markerless tumor tracking algorithm requires 4DCT data to train models. 4DCT cannot be used for markerless tracking for respiratory-gated treatment due to inaccuracies and a high radiation dose. We developed a deep neural network (DNN) to generate 4DCT from 3DCT data.

METHODS

We used 2420 thoracic 4DCT datasets from 436 patients to train a DNN, designed to export 9 deformation vector fields (each field representing one-ninth of the respiratory cycle) from each CT dataset based on a 3D convolutional autoencoder with shortcut connections using deformable image registration. Then 3DCT data at exhale were transformed using the predicted deformation vector fields to obtain simulated 4DCT data. We compared markerless tracking accuracy between original and simulated 4DCT datasets for 20 patients. Our tracking algorithm used a machine learning approach with patient-specific model parameters. For the training stage, a pair of digitally reconstructed radiography images was generated using 4DCT for each patient. For the prediction stage, the tracking algorithm calculated tumor position using incoming fluoroscopic image data.

RESULTS

Diaphragmatic displacement averaged over 40 cases for the original 4DCT were slightly higher (<1.3 mm) than those for the simulated 4DCT. Tracking positional errors (95th percentile of the absolute value of displacement, "simulated 4DCT" minus "original 4DCT") averaged over the 20 cases were 0.56 mm, 0.65 mm, and 0.96 mm in the X, Y and Z directions, respectively.

CONCLUSIONS

We developed a DNN to generate simulated 4DCT data that are useful for markerless tumor tracking when original 4DCT is not available. Using this DNN would accelerate markerless tumor tracking and increase treatment accuracy in thoracoabdominal treatment.

Use of Gaussian-type functions for flux-based dose calculations in carbon ion therapy

In radiation therapy, it is very important to ensure that the radiation dose is correctly delivered to the patient. This is achieved by obtaining quantitative dose measurements for beam calibration in the treatment planning system. Dose calculations should be performed with the required accuracy to a degree of uncertainty of less than 1%. The measurement of the absorbed dose in and around body tissues irradiated with carbon ions requires careful use of materials selected from established phantom and radiation detectors. The main advantage of such materials is that when information on the energy and nature of charged particles at the desired point is incomplete or inaccurate, they can allow determination of the absorbed dose. In general, radiation interactions in a tissue representation caused by carbon ions can be characterized by calculating the linear stopping power. Carbon ions have a limited penetration depth within human tissues that depends on the energy and stopping power of these ions as they penetrate into the body. The purpose of the present study was to calculate the stopping power, range and dose to intestinal and prostate tissues of carbon ions. The stopping power values of these tissues were specified by the effective charge approach method. The 5ZaPa-NR-CV, pcemd-4 and pcSseg-4 sets of Gaussian-type functions were employed for the calculation of electronic charge density. Range calculations were made by means of the Gaussian quadrature method, making use of the continuous slowing down approximation. Flux-based dose calculations were also carried out in accordance with the Bragg-Gray theorem using the Geant4 and FLUKA simulation toolkits. The results were compared with each other and with the SRIM and CasP datasets. Then, depth-dose distributions and range values were verified by positron emission activity using the GATE toolkit. Among the different types of Gaussian functions used here, the best semi-analytical result was found for the 5ZaPa-NR-CV set. The results obtained in the present study can be used for dose verification and dose reconstruction in charged particle radiotherapy and for radiation research on the interaction of radiation with matter. The results calculated here will be useful for quantifying uncertainties associated with stopping power, range, and reconstruction of dose in charged particle therapy.

Automatic measurement of air gap for proton therapy using orthogonal x-ray imaging with radiopaque wires

Purpose

The main objective of this study was to develop a technique to accurately determine the air gap between the end of the proton beam compensator and the body of the patient in proton radiotherapy.

Methods

Orthogonal x‐ray image‐based automatic coordinate reconstruction was used to determine the air gap between the patient body surface contour and the end of beam nozzle in proton radiotherapy. To be able to clearly identify the patient body surface contour on the orthogonal images, a radiopaque wire was placed on the skin surface of the patient as a surrogate. In order to validate this method, a Rando^® head phantom was scanned and five proton plans were generated on a Mevion S250 Proton machine with various air gaps in Varian Eclipse Treatment Planning Systems (TPS). When setting up the phantom in a treatment room, a solder wire was placed on the surface of the phantom closest to the beam nozzle with the knowledge of the beam geometry in the plan. After the phantom positioning was verified using orthogonal kV imaging, the last pair of setup kV images was used to segment the solder wire and the in‐room coordinates of the wire were reconstructed using a back‐projection algorithm. Using the wire as a surrogate of the body surface, we calculated the air gaps by finding the minimum distance between the reconstructed wire and the end of the compensator. The methodology was also verified and validated on clinical cases.

Results

On the phantom study, the air gap values derived with the automatic reconstruction method were found to be within 1.1 mm difference from the planned values for proton beams with air gaps of 85.0, 100.0, 150.0, 180.0, and 200.0 mm. The reconstruction technique determined air gaps for a patient in two clinical treatment sessions were 38.4 and 41.8 mm, respectively, for a 40 mm planned air gap, and confirmed by manual measurements. There was strong agreement between the calculated values and the automatically measured values, and between the automatically and manually measured values.

Conclusions

An image‐based automatic method has been developed to conveniently determine the air gap of a proton beam, directly using the orthogonal images for patient positioning without adding additional imaging dose to the patient. The method provides an objective, accurate, and efficient way to confirm the target depth at treatment to ensure desired target coverage and normal tissue sparing.

A robotic C-arm cone beam CT system for image-guided proton therapy: design and performance

OBJECTIVE

A ceiling-mounted robotic C-arm cone beam CT (CBCT) system was developed for use with a 190° proton gantry system and a 6-degree-of-freedom robotic patient positioner. We report on the mechanical design, system accuracy, image quality, image guidance accuracy, imaging dose, workflow, safety and collision-avoidance.

METHODS

The robotic CBCT system couples a rotating C-ring to the C-arm concentrically with a kV X-ray tube and a flat-panel imager mounted to the C-ring. CBCT images are acquired with flex correction and maximally 360° rotation for a 53 cm field of view. The system was designed for clinical use with three imaging locations. Anthropomorphic phantoms were imaged to evaluate the image guidance accuracy.

RESULTS

The position accuracy and repeatability of the robotic C-arm was high (<0.5 mm), as measured with a high-accuracy laser tracker. The isocentric accuracy of the C-ring rotation was within 0.7 mm. The coincidence of CBCT imaging and radiation isocentre was better than 1 mm. The average image guidance accuracy was within 1 mm and 1° for the anthropomorphic phantoms tested. Daily volumetric imaging for proton patient positioning was specified for routine clinical practice.

CONCLUSION

Our novel gantry-independent robotic CBCT system provides high-accuracy volumetric image guidance for proton therapy. Advances in knowledge: Ceiling-mounted robotic CBCT provides a viable option than CT on-rails for partial gantry and fixed-beam proton systems with the added advantage of acquiring images at the treatment isocentre.

Quantification of Pediatric Abdominal Organ Motion With a 4-Dimensional Magnetic Resonance Imaging Method

PURPOSE

To characterize respiration-induced abdominal organ motion in children receiving radiation treatment with a 4-dimensional (4D) magnetic resonance imaging (MRI) method.

METHODS AND MATERIALS

We analyzed free-breathing coronal 4D MRI datasets acquired from 35 patients (aged 1-20 years) with abdominal tumors. A deformable image registration of the 4D MRI datasets was performed to derive motion trajectories of selected anatomic landmarks, from which organ motions were quantified. The association between organ motion and patient characteristics was investigated and compared with previous studies. The relation between patient height and organ motion was further investigated to predict organ motion in prospective patients.

RESULTS

Organ motion and its individual variation were reduced in younger patients (eg, kidney peak-to-peak motion <5 mm for all but 1 patient aged ≤8 years), although special motion management may be warranted in some adolescents. The liver and spleen exhibited greater motion than did the kidneys, while intraorgan variation was present. The motions in the liver and kidneys agreed with those reported by the previous 4D computed tomography studies. Individual variations of organ motion in younger patients were due, in part, to changes in respiration rate, which ostensibly reflected the effect of anesthesia. The prediction of organ motion was limited by large individual variations, particularly for older patients.

CONCLUSIONS

The 4D MRI acquisition method and motion analysis described in this study provide a nonionizing approach to understand age-associated organ motion, which aids in the planning of abdominal radiation therapy for pediatric patients. Use of 4D MRI facilitates monitoring of changes in target motion patterns during treatment courses and in various studies of the effect of organ motion on radiation treatment.

An Analysis of Plan Robustness for Esophageal Tumors: Comparing Volumetric Modulated Arc Therapy Plans and Spot Scanning Proton Planning

PURPOSE

Planning studies to compare x-ray and proton techniques and to select the most suitable technique for each patient have been hampered by the nonequivalence of several aspects of treatment planning and delivery. A fair comparison should compare similarly advanced delivery techniques from current clinical practice and also assess the robustness of each technique. The present study therefore compared volumetric modulated arc therapy (VMAT) and single-field optimization (SFO) spot scanning proton therapy plans created using a simultaneous integrated boost (SIB) for dose escalation in midesophageal cancer and analyzed the effect of setup and range uncertainties on these plans.

METHODS AND MATERIALS

For 21 patients, SIB plans with a physical dose prescription of 2 Gy or 2.5 Gy/fraction in 25 fractions to planning target volume (PTV)50Gy or PTV62.5Gy (primary tumor with 0.5 cm margins) were created and evaluated for robustness to random setup errors and proton range errors. Dose-volume metrics were compared for the optimal and uncertainty plans, with P<.05 (Wilcoxon) considered significant.

RESULTS

SFO reduced the mean lung dose by 51.4% (range 35.1%-76.1%) and the mean heart dose by 40.9% (range 15.0%-57.4%) compared with VMAT. Proton plan robustness to a 3.5% range error was acceptable. For all patients, the clinical target volume D98 was 95.0% to 100.4% of the prescribed dose and gross tumor volume (GTV) D98 was 98.8% to 101%. Setup error robustness was patient anatomy dependent, and the potential minimum dose per fraction was always lower with SFO than with VMAT. The clinical target volume D98 was lower by 0.6% to 7.8% of the prescribed dose, and the GTV D98 was lower by 0.3% to 2.2% of the prescribed GTV dose.

CONCLUSIONS

The SFO plans achieved significant sparing of normal tissue compared with the VMAT plans for midesophageal cancer. The target dose coverage in the SIB proton plans was less robust to random setup errors and might be unacceptable for certain patients. Robust optimization to ensure adequate target coverage of SIB proton plans might be beneficial.

Digital reconstructed radiography with multiple color image overlay for image-guided radiotherapy

Registration of patient anatomical structures to the reference position is a basic part of the patient set-up procedure. Registration of anatomical structures between the site of beam entrance on the patient surface and the distal target position is particularly important. Here, to improve patient positional accuracy during set-up for particle beam treatment, we propose a new visualization methodology using digitally reconstructed radiographs (DRRs), overlaid DRRs, and evaluation of overlaid DRR images in clinical cases. The overlaid method overlays two DRR images in different colors by dividing the CT image into two CT sections at the distal edge of the target along the treatment beam direction. Since our hospital uses fixed beam ports, the treatment beam angles for this study were set at 0 and 90 degrees. The DRR calculation direction was from the X-ray tube to the imaging device, and set to 180/270 degrees and 135/225 degrees, based on the installation of our X-ray imaging system. Original and overlaid DRRs were calculated using CT data for two patients, one with a parotid gland tumor and the other with prostate cancer. The original and overlaid DRR images were compared. Since the overlaid DRR image was completely separated into two regions when the DRR calculation angle was the same as the treatment beam angle, the overlaid DRR visualization technique was able to provide rich information for aiding recognition of the relationship between anatomical structures and the target position. This method will also be useful in patient set-up procedures for fixed irradiation ports.

Advances in 4D treatment planning for scanned particle beam therapy - report of dedicated workshops

We report on recent progress in the field of mobile tumor treatment with scanned particle beams, as discussed in the latest editions of the 4D treatment planning workshop. The workshop series started in 2009, with about 20 people from 4 research institutes involved, all actively working on particle therapy delivery and development. The first workshop resulted in a summary of recommendations for the treatment of mobile targets, along with a list of requirements to apply these guidelines clinically. The increased interest in the treatment of mobile tumors led to a continuously growing number of attendees: the 2012 edition counted more than 60 participants from 20 institutions and commercial vendors. The focus of research discussions among workshop participants progressively moved from 4D treatment planning to complete 4D treatments, aiming at effective and safe treatment delivery. Current research perspectives on 4D treatments include all critical aspects of time resolved delivery, such as in-room imaging, motion detection, beam application, and quality assurance techniques. This was motivated by the start of first clinical treatments of hepato cellular tumors with a scanned particle beam, relying on gating or abdominal compression for motion mitigation. Up to date research activities emphasize significant efforts in investigating advanced motion mitigation techniques, with a specific interest in the development of dedicated tools for experimental validation. Potential improvements will be made possible in the near future through 4D optimized treatment plans that require upgrades of the currently established therapy control systems for time resolved delivery. But since also these novel optimization techniques rely on the validity of the 4DCT, research focusing on alternative 4D imaging technique, such as MRI based 4DCT generation will continue.

Implementation of a target volume design function for intrafractional range variation in a particle beam treatment planning system

OBJECTIVE

Treatment planning for charged particle therapy in the thoracic and abdominal regions should take account of range uncertainty due to intrafractional motion. Here, we developed a design tool (4Dtool) for the target volume [field-specific target volume (FTV)], which accounts for this uncertainty using four-dimensional CT (4DCT).

METHODS

Target and normal tissue contours were input manually into a treatment planning system (TPS). These data were transferred to the 4Dtool via the picture archiving and communication system (PACS). Contours at the reference phase were propagated to other phases by deformable image registration. FTV was calculated using 4DCT on the 4Dtool. The TPS displays FTV contours using digital imaging and communications in medicine files imported from the PACS. These treatment parameters on the CT image at the reference phase were then used for dose calculation on the TPS. The tool was tested in single clinical case randomly selected from patients treated at our centre for lung cancer.

RESULTS

In this clinical case, calculation of dose distribution with the 4Dtool resulted in the successful delivery of carbon-ion beam at the reference phase of 95% of the prescribed dose to the clinical target volume (CTV). Application to the other phases also provided sufficient dose to the CTV.

CONCLUSION

The 4Dtool software allows the design of the target volume with consideration to intrafractional range variation and is now in routine clinical use at our institution.

ADVANCES IN KNOWLEDGE

Our alternative technique represents a practical approach to four-dimensional treatment planning within the current state of charged particle therapy.

Real-time image-processing algorithm for markerless tumour tracking using X-ray fluoroscopic imaging

OBJECTIVE

To ensure accuracy in respiratory-gating treatment, X-ray fluoroscopic imaging is used to detect tumour position in real time. Detection accuracy is strongly dependent on image quality, particularly positional differences between the patient and treatment couch. We developed a new algorithm to improve the quality of images obtained in X-ray fluoroscopic imaging and report the preliminary results.

METHODS

Two oblique X-ray fluoroscopic images were acquired using a dynamic flat panel detector (DFPD) for two patients with lung cancer. The weighting factor was applied to the DFPD image in respective columns, because most anatomical structures, as well as the treatment couch and port cover edge, were aligned in the superior-inferior direction when the patient lay on the treatment couch. The weighting factors for the respective columns were varied until the standard deviation of the pixel values within the image region was minimized. Once the weighting factors were calculated, the quality of the DFPD image was improved by applying the factors to multiframe images.

RESULTS

Applying the image-processing algorithm produced substantial improvement in the quality of images, and the image contrast was increased. The treatment couch and irradiation port edge, which were not related to a patient's position, were removed. The average image-processing time was 1.1 ms, showing that this fast image processing can be applied to real-time tumour-tracking systems.

CONCLUSION

These findings indicate that this image-processing algorithm improves the image quality in patients with lung cancer and successfully removes objects not related to the patient.

ADVANCES IN KNOWLEDGE

Our image-processing algorithm might be useful in improving gated-treatment accuracy.