The grid-dose-spreading algorithm for dose distribution calculation in heavy charged particle radiotherapy

A new variant of the pencil-beam (PB) algorithm for dose distribution calculation for radiotherapy with protons and heavier ions, the grid-dose spreading (GDS) algorithm, is proposed. The GDS algorithm is intrinsically faster than conventional PB algorithms due to approximations in convolution integral, where physical calculations are decoupled from simple grid-to-grid energy transfer. It was effortlessly implemented to a carbon-ion radiotherapy treatment planning system to enable realistic beam blurring in the field, which was absent with the broad-beam (BB) algorithm. For a typical prostate treatment, the slowing factor of the GDS algorithm relative to the BB algorithm was 1.4, which is a great improvement over the conventional PB algorithms with a typical slowing factor of several tens. The GDS algorithm is mathematically equivalent to the PB algorithm for horizontal and vertical coplanar beams commonly used in carbon-ion radiotherapy while dose deformation within the size of the pristine spread occurs for angled beams, which was within 3 mm for a single proton pencil beam of $30^\circ$ incidence, and needs to be assessed against the clinical requirements and tolerances in practical situations.Comment: 7 pages, 3 figure

Respiratory motion modelling for MR-guided lung cancer radiotherapy: model development and geometric accuracy evaluation.

Objective.Respiratory motion of lung tumours and adjacent structures is challenging for radiotherapy. Online MR-imaging cannot currently provide real-time volumetric information of the moving patient anatomy, therefore limiting precise dose delivery, delivered dose reconstruction, and downstream adaptation methods.Approach.We tailor a respiratory motion modelling framework towards an MR-Linac workflow to estimate the time-resolved 4D motion from real-time data. We develop a multi-slice acquisition scheme which acquires thick, overlapping 2D motion-slices in different locations and orientations, interleaved with 2D surrogate-slices from a fixed location. The framework fits a motion model directly to the input data without the need for sorting or binning to account for inter- and intra-cycle variation of the breathing motion. The framework alternates between model fitting and motion-compensated super-resolution image reconstruction to recover a high-quality motion-free image and a motion model. The fitted model can then estimate the 4D motion from 2D surrogate-slices. The framework is applied to four simulated anthropomorphic datasets and evaluated against known ground truth anatomy and motion. Clinical applicability is demonstrated by applying our framework to eight datasets acquired on an MR-Linac from four lung cancer patients.Main results.The framework accurately reconstructs high-quality motion-compensated 3D images with 2 mm3isotropic voxels. For the simulated case with the largest target motion, the motion model achieved a mean deformation field error of 1.13 mm. For the patient cases residual error registrations estimate the model error to be 1.07 mm (1.64 mm), 0.91 mm (1.32 mm), and 0.88 mm (1.33 mm) in superior-inferior, anterior-posterior, and left-right directions respectively for the building (application) data.Significance.The motion modelling framework estimates the patient motion with high accuracy and accurately reconstructs the anatomy. The image acquisition scheme can be flexibly integrated into an MR-Linac workflow whilst maintaining the capability of online motion-management strategies based on cine imaging such as target tracking and/or gating

Towards real-time MRI-guided 3D localization of deforming targets for non-invasive cardiac radiosurgery.

Radiosurgery to the pulmonary vein antrum in the left atrium (LA) has recently been proposed for non-invasive treatment of atrial fibrillation (AF). Precise real-time target localization during treatment is necessary due to complex respiratory and cardiac motion and high radiation doses. To determine the 3D position of the LA for motion compensation during radiosurgery, a tracking method based on orthogonal real-time MRI planes was developed for AF treatments with an MRI-guided radiotherapy system. Four healthy volunteers underwent cardiac MRI of the LA. Contractile motion was quantified on 3D LA models derived from 4D scans with 10 phases acquired in end-exhalation. Three localization strategies were developed and tested retrospectively on 2D real-time scans (sagittal, temporal resolution 100 ms, free breathing). The best-performing method was then used to measure 3D target positions in 2D-2D orthogonal planes (sagittal-coronal, temporal resolution 200-252 ms, free breathing) in 20 configurations of a digital phantom and in the volunteer data. The 3D target localization accuracy was quantified in the phantom and qualitatively assessed in the real data. Mean cardiac contraction was  ⩽  3.9 mm between maximum dilation and contraction but anisotropic. A template matching approach with two distinct template phases and ECG-based selection yielded the highest 2D accuracy of 1.2 mm. 3D target localization showed a mean error of 3.2 mm in the customized digital phantoms. Our algorithms were successfully applied to the 2D-2D volunteer data in which we measured a mean 3D LA motion extent of 16.5 mm (SI), 5.8 mm (AP) and 3.1 mm (LR). Real-time target localization on orthogonal MRI planes was successfully implemented for highly deformable targets treated in cardiac radiosurgery. The developed method measures target shifts caused by respiration and cardiac contraction. If the detected motion can be compensated accordingly, an MRI-guided radiotherapy system could potentially enable completely non-invasive treatment of AF

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking

PURPOSE: With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom. METHODS: A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2%/2 mm γ-tests. RESULTS: The overall tracking system latency was 172 ms. The mean 2D root-mean-square tracking error was 1.03 mm (0.80 mm prostate, 1.31 mm lung). MLC tracking improved the dose delivery in all cases with an overall reduction in the γ-failure rate of 91.2% (3%/3 mm) and 89.9% (2%/2 mm) compared to no motion compensation. Low modulation VMAT plans had no (3%/3 mm) or minimal (2%/2 mm) residual γ-failures while tracking reduced the γ-failure rate from 17.4% to 2.8% (3%/3 mm) and from 33.9% to 6.5% (2%/2 mm) for plans with high modulation. CONCLUSIONS: Real-time 4D ultrasound tracking was successfully integrated with online MLC tracking for the first time. The developed framework showed an accuracy and latency comparable with other MLC tracking methods while holding the potential to measure and adapt to target motion, including rotation and deformation, noninvasively

Innovations in Radiotherapy Technology.

Many low- and middle-income countries, together with remote and low socioeconomic populations within high-income countries, lack the resources and services to deal with cancer. The challenges in upgrading or introducing the necessary services are enormous, from screening and diagnosis to radiotherapy planning/treatment and quality assurance. There are severe shortages not only in equipment, but also in the capacity to train, recruit and retain staff as well as in their ongoing professional development via effective international peer-review and collaboration. Here we describe some examples of emerging technology innovations based on real-time software and cloud-based capabilities that have the potential to redress some of these areas. These include: (i) automatic treatment planning to reduce physics staffing shortages, (ii) real-time image-guided adaptive radiotherapy technologies, (iii) fixed-beam radiotherapy treatment units that use patient (rather than gantry) rotation to reduce infrastructure costs and staff-to-patient ratios, (iv) cloud-based infrastructure programmes to facilitate international collaboration and quality assurance and (v) high dose rate mobile cobalt brachytherapy techniques for intraoperative radiotherapy

On voxel-by-voxel accumulated dose for prostate radiation therapy using deformable image registration.

Since delivered dose is rarely the same with planned, we calculated the delivered total dose to ten prostate radiotherapy patients treated with rectal balloons using deformable dose accumulation (DDA) and compared it with the planned dose. The patients were treated with TomoTherapy using two rectal balloon designs: five patients had the Radiadyne balloon (balloon A), and five patients had the EZ-EM balloon (balloon B). Prostate and rectal wall contours were outlined on each pre-treatment MVCT for all patients. Delivered fractional doses were calculated using the MVCT taken immediately prior to delivery. Dose grids were accumulated to the last MVCT using DDA tools in Pinnacle3 TM (v9.100, Philips Radiation Oncology Systems, Fitchburg, USA). Delivered total doses were compared with planned doses using prostate and rectal wall DVHs. The rectal NTCP was calculated based on total delivered and planned doses for all patients using the Lyman model. For 8/10 patients, the rectal wall NTCP calculated using the delivered total dose was less than planned, with seven patients showing a decrease of more than 5% in NTCP. For 2/10 patients studied, the rectal wall NTCP calculated using total delivered dose was 2% higher than planned. This study indicates that for patients receiving hypofractionated radiotherapy for prostate cancer with a rectal balloon, total delivered doses to prostate is similar with planned while delivered dose to rectal walls may be significantly different from planned doses. 8/10 patients show significant correlation between rectal balloon anterior-posterior positions and some VD values

Integration of Spatial Distortion Effects in a 4D Computational Phantom for Simulation Studies in Extra-Cranial MRI-guided Radiation Therapy: Initial Results.

PurposeSpatial distortions in magnetic resonance imaging (MRI) are mainly caused by inhomogeneities of the static magnetic field, nonlinearities in the applied gradients, and tissue‐specific magnetic susceptibility variations. These factors may significantly alter the geometrical accuracy of the reconstructed MR image, thus questioning the reliability of MRI for guidance in image‐guided radiation therapy. In this work, we quantified MRI spatial distortions and created a quantitative model where different sources of distortions can be separated. The generated model was then integrated into a four‐dimensional (4D) computational phantom for simulation studies in MRI‐guided radiation therapy at extra‐cranial sites.MethodsA geometrical spatial distortion phantom was designed in four modules embedding laser‐cut PMMA grids, providing 3520 landmarks in a field of view of (345 × 260 × 480) mm3. The construction accuracy of the phantom was verified experimentally. Two fast MRI sequences for extra‐cranial imaging at 1.5 T were investigated, considering axial slices acquired with online distortion correction, in order to mimic practical use in MRI‐guided radiotherapy. Distortions were separated into their sources by acquisition of images with gradient polarity reversal and dedicated susceptibility calculations. Such a separation yielded a quantitative spatial distortion model to be used for MR imaging simulations. Finally, the obtained spatial distortion model was embedded into an anthropomorphic 4D computational phantom, providing registered virtual CT/MR images where spatial distortions in MRI acquisition can be simulated.ResultsThe manufacturing accuracy of the geometrical distortion phantom was quantified to be within 0.2 mm in the grid planes and 0.5 mm in depth, including thickness variations and bending effects of individual grids. Residual spatial distortions after MRI distortion correction were strongly influenced by the applied correction mode, with larger effects in the trans‐axial direction. In the axial plane, gradient nonlinearities caused the main distortions, with values up to 3 mm in a 1.5 T magnet, whereas static field and susceptibility effects were below 1 mm. The integration in the 4D anthropomorphic computational phantom highlighted that deformations can be severe in the region of the thoracic diaphragm, especially when using axial imaging with 2D distortion correction. Adaptation of the phantom based on patient‐specific measurements was also verified, aiming at increased realism in the simulation.ConclusionsThe implemented framework provides an integrated approach for MRI spatial distortion modeling, where different sources of distortion can be quantified in time‐dependent geometries. The computational phantom represents a valuable platform to study motion management strategies in extra‐cranial MRI‐guided radiotherapy, where the effects of spatial distortions can be modeled on synthetic images in a virtual environment

Improving Radiotherapy Targeting for Cancer Treatment Through Space and Time

Radiotherapy is a common medical treatment in which lethal doses of ionizing radiation are preferentially delivered to cancerous tumors. In external beam radiotherapy, radiation is delivered by a remote source which sits several feet from the patient\u27s surface. Although great effort is taken in properly aligning the target to the path of the radiation beam, positional uncertainties and other errors can compromise targeting accuracy. Such errors can lead to a failure in treating the target, and inflict significant toxicity to healthy tissues which are inadvertently exposed high radiation doses. Tracking the movement of targeted anatomy between and during treatment fractions provides valuable localization information that allows for the reduction of these positional uncertainties. Inter- and intra-fraction anatomical localization data not only allows for more accurate treatment setup, but also potentially allows for 1) retrospective treatment evaluation, 2) margin reduction and modification of the dose distribution to accommodate daily anatomical changes (called `adaptive radiotherapy\u27), and 3) targeting interventions during treatment (for example, suspending radiation delivery while the target it outside the path of the beam). The research presented here investigates the use of inter- and intra-fraction localization technologies to improve radiotherapy to targets through enhanced spatial and temporal accuracy. These technologies provide significant advancements in cancer treatment compared to standard clinical technologies. Furthermore, work is presented for the use of localization data acquired from these technologies in adaptive treatment planning, an investigational technique in which the distribution of planned dose is modified during the course of treatment based on biological and/or geometrical changes of the patient\u27s anatomy. The focus of this research is directed at abdominal sites, which has historically been central to the problem of motion management in radiation therapy

4D-MRI in Radiotherapy

Four-dimensional (4D) imaging provides a useful estimation of tissue motion pattern and range for radiation therapy of moving targets. 4D-CT imaging has been a standard care of practice for stereotactic body radiation therapy of moving targets. Recently, 4D-MRI has become an emerging developmental area in radiotherapy. In comparison with 4D-CT imaging, 4D-MRI provides better spatial rendering of radiotherapy targets in abdominal and pelvis regions with improved visualization of soft tissue motion. Successful implementation of 4D-MRI requires an integration of optimized acquisition protocols, advanced image reconstruction techniques, and sufficient hardware capabilities. The proposed chapter intends to introduce basic theories, current research, development, and applications of 4D-MRI in radiotherapy

A biomechanical approach for real-time tracking of lung tumors during External Beam Radiation Therapy (EBRT)

Lung cancer is the most common cause of cancer related death in both men and women. Radiation therapy is widely used for lung cancer treatment. However, this method can be challenging due to respiratory motion. Motion modeling is a popular method for respiratory motion compensation, while biomechanics-based motion models are believed to be more robust and accurate as they are based on the physics of motion. In this study, we aim to develop a biomechanics-based lung tumor tracking algorithm which can be used during External Beam Radiation Therapy (EBRT). An accelerated lung biomechanical model can be used during EBRT only if its boundary conditions (BCs) are defined in a way that they can be updated in real-time. As such, we have developed a lung finite element (FE) model in conjunction with a Neural Networks (NNs) based method for predicting the BCs of the lung model from chest surface motion data. To develop the lung FE model for tumor motion prediction, thoracic 4D CT images of lung cancer patients were processed to capture the lung and diaphragm geometry, trans-pulmonary pressure, and diaphragm motion. Next, the chest surface motion was obtained through tracking the motion of the ribcage in 4D CT images. This was performed to simulate surface motion data that can be acquired using optical tracking systems. Finally, two feedforward NNs were developed, one for estimating the trans-pulmonary pressure and another for estimating the diaphragm motion from chest surface motion data. The algorithm development consists of four steps of: 1) Automatic segmentation of the lungs and diaphragm, 2) diaphragm motion modelling using Principal Component Analysis (PCA), 3) Developing the lung FE model, and 4) Using two NNs to estimate the trans-pulmonary pressure values and diaphragm motion from chest surface motion data. The results indicate that the Dice similarity coefficient between actual and simulated tumor volumes ranges from 0.76±0.04 to 0.91±0.01, which is favorable. As such, real-time lung tumor tracking during EBRT using the proposed algorithm is feasible. Hence, further clinical studies involving lung cancer patients to assess the algorithm performance are justified