Can megavoltage computed tomography reduce proton range uncertainties in treatment plans for patients with large metal implants?

Treatment planning calculations for proton therapy require an accurate knowledge of radiological path length, or range, to the distal edge of the target volume. In most cases, the range may be calculated with sufficient accuracy using kilovoltage (kV) computed tomography (CT) images. However, metal implants such as hip prostheses can cause severe streak artifacts that lead to large uncertainties in proton range. The purposes of this study were to quantify streak-related range errors and to determine if they could be avoided by using artifact-free megavoltage (MV) CT images in treatment planning. Proton treatment plans were prepared for a rigid, heterogeneous phantom and for a prostate cancer patient with a metal hip prosthesis using corrected and uncorrected kVCT images alone, uncorrected MVCT images and a combination of registered MVCT and kVCT images (the hybrid approach). Streak-induced range errors of 5-12 mm were present in the uncorrected kVCT-based patient plan. Correcting the streaks by manually assigning estimated true Hounsfield units improved the range accuracy. In a rigid heterogeneous phantom, the implant-related range uncertainty was estimated at approach, the kVCT images provided good delineation of soft tissues due to high-contrast resolution, and the streak-free MVCT images provided smaller range uncertainties because they did not require artifact correction. © 2008 Institute of Physics and Engineering in Medicine

A margin-based analysis of the dosimetric impact of motion on step-and-shoot IMRT lung plans

PURPOSE: Intrafraction motion during step-and-shoot (SNS) IMRT is known to affect the target dosimetry by a combination of dose blurring and interplay effects. These effects are typically managed by adding a margin around the target. A quantitative analysis was performed, assessing the relationship between target motion, margin size, and target dosimetry with the goal of introducing new margin recipes. METHODS: A computational algorithm was used to calculate 1,174 motion-encoded dose distributions and DVHs within the patient’s CT dataset. Sinusoidal motion tracks were used simulating intrafraction motion for nine lung tumor patients, each with multiple margin sizes. RESULTS: D(95%) decreased by less than 3% when the maximum target displacement beyond the margin experienced motion less than 5 mm in the superior-inferior direction and 15 mm in the anterior-posterior direction. For target displacements greater than this, D(95%) decreased rapidly. CONCLUSIONS: Targets moving in excess of 5 mm outside the margin can cause significant changes to the target. D(95%) decreased by up to 20% with target motion 10 mm outside the margin, with underdosing primarily limited to the target periphery. Multi-fractionated treatments were found to exacerbate target under-coverage. Margins several millimeters smaller than the maximum target displacement provided acceptable motion protection, while also allowing for reduced normal tissue morbidity

Real-Time Simulation And Visualization Of Subject-Specific 3D Lung Dynamics

In this paper we discuss a framework for modeling the 3D lung dynamics of normal and diseased human subjects and visualizing them using an Augmented Reality (AR) based environment. The framework is based on the results obtained from pulmonary function tests and lung image-data of human subjects obtained from 4D High-Resolution Computed Tomography (HRCT). The components of the framework include a parameterized pressure-volume (PV) relation estimated from normal human subjects, and a physics and physiology-based 3D deformable lung model extracted from the 4D HRCT data of normal and tumor-influenced human subjects. The parameterized PV relation allows modeling different breathing conditions of a human subject. The 3D deformable lung model allows visualizing the 3D shape changes of the lung for the breathing condition simulated by the PV relation. Additionally, the 3D lung model is deformed using a graphics processing unit (GPU) and its vertex shaders, which satisfies the real-time frame-rate requirements of the AR environment. © 2006 IEEE

Visualization Of Tumor-Influenced 3D Lung Dynamics

A framework for real-time visualization of a tumor-influenced lung dynamics is presented in this paper. This framework potentially allows clinical technicians to visualize in 3D the morphological changes of lungs under different breathing conditions. Consequently, this technique may provide a sensitive and accurate assessment tool for preoperative and intra-operative clinical guidance. The proposed simulation method extends work previously developed for modeling and visualizing normal 3D lung dynamics. The model accounts for the changes in the regional lung functionality and the global motor response due to the presence of a tumor. For real-time deformation purposes, we use a Green\u27s function (GF), a physically based approach that allows real-time multi-resolution modeling of the lung deformations. This function also allows an analytical estimation of the GF\u27s deformation parameters from the 4D lung datasets at different level-of-details of the lung model. Once estimated, the subject-specific GF facilitates the simulation of tumor-influenced lung deformations subjected to any breathing condition modeled by a parametric Pressure-Volume (PV) relation

Feasibility of the utilization of BNCT in the fast neutron therapy beam at Fermilab

The Neutron Therapy Facility at Fermilab has treated cancer patients since 1976. Since then more than 2,300 patients have been treated and a wealth of clinical information accumulated. The therapeutic neutron beam at Fermilab is produced by bombarding a beryllium target with 66 MeV protons. The resulting continuous neutron spectrum ranges from thermal to 66 MeV in neutron energy. It is clear that this spectrum is not well suited for the treatment of tumors with boron neutron capture therapy (BNCT) only However, since this spectrum contains thermal and epithermal components the authors are investigating whether BNCT can be used in this beam to boost the tumor dose. There are clinical scenarios in which a selective tumor dose boost of 10 - 15% could be clinically significant. For these cases the principal treatment would still be fast neutron therapy but a tumor boost could be used either to deliver a higher dose to the tumor tissue or to reduce the dose to the normal healthy tissue while maintaining the absorbed dose level in the tumor tissue

Observations On Real-Time Prostate Gland Motion Using Electromagnetic Tracking

Purpose: To quantify and describe the real-time movement of the prostate gland in a large data set of patients treated with radiotherapy. Methods and Materials: The Calypso four-dimensional localization system was used for target localization in 17 patients, with electromagnetic markers implanted in the prostate of each patient. We analyzed a total of 550 continuous tracking sessions. The fraction of time that the prostate was displaced by \u3e3, \u3e5, \u3e7, and \u3e10 mm was calculated for each session and patient. The frequencies of displacements after initial patient positioning were analyzed over time. Results: Averaged over all patients, the prostate was displaced \u3e3 and \u3e5 mm for 13.6% and 3.3% of the total treatment time, respectively. For individual patients, the corresponding maximal values were 36.2% and 10.9%. For individual fractions, the corresponding maximal values were 98.7% and 98.6%. Displacements \u3e3 mm were observed at 5 min after initial alignment in about one-eighth of the observations, and increased to one-quarter by 10 min. For individual patients, the maximal value of the displacements \u3e3 mm at 5 and 10 min after initial positioning was 43% and 75%, respectively. Conclusion: On average, the prostate was displaced by \u3e3 mm and \u3e5 mm approximately 14% and 3% of the time, respectively. For individual patients, these values were up to three times greater. After the initial positioning, the likelihood of displacement of the prostate gland increased with elapsed time. This highlights the importance of initiating treatment shortly after initially positioning the patient. © 2008 Elsevier Inc. All rights reserved

Safety considerations for IGRT: Executive summary

AbstractRadiation therapy is an effective cancer treatment that is constantly being transformed by technological innovation. Dedicated devices for fraction-by-fraction imaging and guidance within the treatment room have enabled image guided radiation therapy (IGRT) allowing clinicians to pursue highly conformal dose distributions, higher dose prescriptions, and shorter fractionation schedules. Capitalizing on IGRT-enabled accuracy and precision requires a strong link between IGRT practices and planning target volume (PTV) design. This is clearly central to high quality, safe radiation therapy. Failure to properly apply IGRT methods or to coordinate their use with an appropriate PTV margin can result in a treatment that is ‘precisely wrong’. The white paper summarized in this executive summary recommends foundational elements and specific activities to maximize the safety and effectiveness of IGRT

Benchmarking of five commercial deformable image registration algorithms for head and neck patients

Benchmarking is a process in which standardized tests are used to assess system performance. The data produced in the process are important for comparative purposes, particularly when considering the implementation and quality assurance of DIR algorithms. In this work, five commercial DIR algorithms (MIM, Velocity, RayStation, Pinnacle, and Eclipse) were benchmarked using a set of 10 virtual phantoms. The phantoms were previously developed based on CT data collected from real head and neck patients. Each phantom includes a start of treatment CT dataset, an end of treatment CT dataset, and the ground‐truth deformation vector field (DVF) which links them together. These virtual phantoms were imported into the commercial systems and registered through a deformable process. The resulting DVFs were compared to the ground‐truth DVF to determine the target registration error (TRE) at every voxel within the image set. Real treatment plans were also recalculated on each end of treatment CT dataset and the dose transferred according to both the ground‐truth and test DVFs. Dosimetric changes were assessed, and TRE was correlated with changes in the DVH of individual structures. In the first part of the study, results show mean TRE on the order of 0.5 mm to 3 mm for all phantoms and ROIs. In certain instances, however, misregistrations were encountered which produced mean and max errors up to 6.8 mm and 22 mm, respectively. In the second part of the study, dosimetric error was found to be strongly correlated with TRE in the brainstem, but weakly correlated with TRE in the spinal cord. Several interesting cases were assessed which highlight the interplay between the direction and magnitude of TRE and the dose distribution, including the slope of dosimetric gradients and the distance to critical structures. This information can be used to help clinicians better implement and test their algorithms, and also understand the strengths and weaknesses of a dose adaptive approach. PACS number(s): 87.57.nj, 87.55.dk, 87.55.Q