Comparison of target registration errors for multiple image-guided techniques in accelerated partial breast irradiation.

PURPOSE: External beam accelerated partial breast irradiation requires accurate localization of the target volume for each treatment fraction. Using the concept of target registration error (TRE), the performance of several methods of target localization was compared. METHODS AND MATERIALS: Twelve patients who underwent external beam accelerated partial breast irradiation were included in this study. TRE was quantified for four methods of image guidance: standard laser-based setup, kilovoltage imaging of the chest wall, kilovoltage imaging of surgically implanted clips, and three-dimensional surface imaging of the breast. The use of a reference surface created from a free-breathing computed tomography scan and a reference surface directly captured with three-dimensional video imaging were compared. The effects of respiratory motion were also considered, and gating was used for 8 of 12 patients. RESULTS: The median value of the TRE for the laser, chest wall, and clip alignment was 7.1 mm (n=94), 5.4 mm (n=81), and 2.4 mm (n=93), respectively. The median TRE for gated surface imaging based on the first fraction reference surface was 3.2 mm (n=49), and the TRE for gated surface imaging using the computed tomography-based reference surface was 4.9 mm (n=56). The TRE for nongated surface imaging using the first fraction reference surface was 6.2 mm (n=25). CONCLUSIONS: The TRE of surface imaging using a reference surface directly captured with three-dimensional video and the TRE for clip-based setup were within 1 mm. Gated capture is important for surface imaging to reduce the effects of respiratory motion in accelerated partial breast irradiation.

Dosimetric impact of motion in free-breathing and gated lung radiotherapy: a 4D Monte Carlo study of intrafraction and interfraction effects.

The purpose of this study was to investigate if interfraction and intrafraction motion in free-breathing and gated lung IMRT can lead to systematic dose differences between 3DCT and 4DCT. Dosimetric effects were studied considering the breathing pattern of three patients monitored during the course of their treatment and an in-house developed 4D Monte Carlo framework. Imaging data were taken in free-breathing and in cine mode for both 3D and 4D acquisition. Treatment planning for IMRT delivery was done based on the free-breathing data with the CORVUS (North American Scientific, Chatsworth, CA) planning system. The dose distributions as a function of phase in the breathing cycle were combined using deformable image registration. The study focused on (a) assessing the accuracy of the CORVUS pencil beam algorithm with Monte Carlo dose calculation in the lung, (b) evaluating the dosimetric effect of motion on the individual breathing phases of the respiratory cycle, and (c) assessing intrafraction and interfraction motion effects during free-breathing or gated radiotherapy. The comparison between (a) the planning system and the Monte Carlo system shows that the pencil beam algorithm underestimates the dose in low-density regions, such as lung tissue, and overestimates the dose in high-density regions, such as bone, by 5% or more of the prescribed dose (corresponding to approximately 3-5 Gy for the cases considered). For the patients studied this could have a significant impact on the dose volume histograms for the target structures depending on the margin added to the clinical target volume (CTV) to produce either the planning target (PTV) or internal target volume (ITV). The dose differences between (b) phases in the breathing cycle and the free-breathing case were shown to be negligible for all phases except for the inhale phase, where an underdosage of the tumor by as much as 9.3 Gy relative to the free-breathing was observed. The large difference was due to breathing-induced motion/deformation affecting the soft/lung tissue density and motion of the bone structures (such as the rib cage) in and out of the beam. Intrafraction and interfraction dosimetric differences between (c) free-breathing and gated delivery were found to be small. However, more significant dosimetric differences, of the order of 3%-5%, were observed between the dose calculations based on static CT (3DCT) and the ones based on time-resolved CT (4DCT). These differences are a consequence of the larger contribution of the inhale phase in the 3DCT data than in the 4DCT.

Fluoroscopic tracking of multiple implanted fiducial markers using multiple object tracking.

When treating mobile tumors using techniques such as beam gating or beam tracking, precise localization of tumor position is required, which is often realized by fluoroscopically tracking implanted fiducial markers. Multiple markers placed inside or near a tumor are often preferred to a single marker for the sake of accuracy. In this work, we propose a marker tracking system that can track multiple markers simultaneously, without confusing them, and that is also robust enough to continue tracking even when the markers are moving behind bony anatomy. The integrated radiotherapy imaging system (IRIS), developed at the Massachusetts General Hospital (MGH), was used to take fluoroscopy videos for marker tracking. The tracking system integrates marker detection with a multiple object tracking process, inspired by the multiple hypothesis marker tracking (MHT) process. It also utilizes breathing pattern information to help tracking. Four criteria are used to identify tracking failure, and when tracking failure occurs, the system can immediately inform the user. (In the clinical environment, the system would immediately disable the treatment beam.) In this paper, two liver patients with implanted fiducial markers were studied, and the studies were performed retrospectively to assess the effectiveness of the new tracking system. For both patients, LAT and AP fluoroscopic videos were studied. In order to better test the proposed tracking system, artificial markers were added around the real markers to disturb the tracking of the real markers. The performance of the proposed system was compared to that of a conventional tracking system (one that did not use multiple object tracking). The performance of the new system was also investigated with and without consideration of the breathing pattern information. We found that the conventional tracking system can easily miss tracking markers in the presence of artificial markers, and it cannot detect the tracking failures. On the other hand, our proposed system can track markers well and can also successfully detect tracking failures. Failure rate was calculated on a per-frame-per-marker basis for the proposed tracking system. When the system considered breathing pattern information, it had a 0% failure rate 75% of the time and 0.4% failure rate 25% of the time. However, when the system did not consider breathing patterns, it had a much higher failure rate, in the range of 1.2%-12%. Both examples of the proposed system yielded low e(95) (the maximum marker tracking error at 95% confidence level)-less than 1.5 mm.

Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers.

For gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. We have previously investigated and demonstrated the feasibility of generating gating signals using the correlation scores between the reference template image and the fluoroscopic images acquired during the treatment. In this paper, we present an in-depth study, aiming at the improvement of robustness of the algorithm and its validation using multiple sets of patient data. Three different template generating and matching methods have been developed and evaluated: (1) single template method, (2) multiple template method, and (3) template clustering method. Using the fluoroscopic data acquired during patient setup before each fraction of treatment, reference templates are built that represent the tumour position and shape in the gating window, which is assumed to be at the end-of-exhale phase. For the single template method, all the setup images within the gating window are averaged to generate a composite template. For the multiple template method, each setup image in the gating window is considered as a reference template and used to generate an ensemble of correlation scores. All the scores are then combined to generate the gating signal. For the template clustering method, clustering (grouping of similar objects together) is performed to reduce the large number of reference templates into a few representative ones. Each of these methods has been evaluated against the reference gating signal as manually determined by a radiation oncologist. Five patient datasets were used for evaluation. In each case, gated treatments were simulated at both 35% and 50% duty cycles. False positive, negative and total error rates were computed. Experiments show that the single template method is sensitive to noise; the multiple template and clustering methods are more robust to noise due to the smoothing effect of aggregation of correlation scores; and the clustering method results in the best performance in terms of computational efficiency and accuracy.

Efficient Descriptor-Based Segmentation of Parotid Glands With Nonlocal Means.

OBJECTIVE: We introduce descriptor-based segmentation that extends existing patch-based methods by combining intensities, features, and location information. Since it is unclear which image features are best suited for patch selection, we perform a broad empirical study on a multitude of different features. METHODS: We extend nonlocal means segmentation by including image features and location information. We search larger windows with an efficient nearest neighbor search based on kd-trees. We compare a large number of image features. RESULTS: The best results were obtained for entropy image features, which have not yet been used for patch-based segmentation. We further show that searching larger image regions with an approximate nearest neighbor search and location information yields a significant improvement over the bounded nearest neighbor search traditionally employed in patch-based segmentation methods. CONCLUSION: Features and location information significantly increase the segmentation accuracy. The best features highlight boundaries in the image. SIGNIFICANCE: Our detailed analysis of several aspects of nonlocal means-based segmentation yields new insights about patch and neighborhood sizes together with the inclusion of location information. The presented approach advances the state-of-the-art in the segmentation of parotid glands for radiation therapy planning.

Determination of the initial beam parameters in Monte Carlo linac simulation.

For Monte Carlo linac simulations and patient dose calculations, it is important to accurately determine the phase space parameters of the initial electron beam incident on the target. These parameters, such as mean energy and radial intensity distribution, have traditionally been determined by matching the calculated dose distributions with the measured dose distributions through a trial and error process. This process is very time consuming and requires a lot of Monte Carlo simulation experience and computational resources. In this paper, we propose an easy, efficient, and accurate method for the determination of the initial beam parameters. We hypothesize that (1) for one type of linacs, the geometry and material of major components of the treatment head are the same; the only difference is the phase space parameters of the initial electron beam incident on the target, and (2) most linacs belong to a limited number of linac types. For each type of linacs, Monte Carlo treatment planning system (MC-TPS) vendors simulate the treatment head and calculate the three-dimensional (3D) dose distribution in water phantom for a grid of initial beam energies and radii. The simulation results (phase space files and dose distribution files) are then stored in a data library. When a MC-TPS user tries to model their linac which belongs to the same type, a standard set of measured dose data is submitted and compared with the calculated dose distributions to determine the optimal combination of initial beam energy and radius. We have applied this method to the 6 MV beam of a Varian 21EX linac. The linac was simulated using EGSNRC/BEAM code and the dose in water phantom was calculated using EGSNRC/DOSXYZ. We have also studied issues related to the proposed method. Several common cost functions were tested for comparing measured and calculated dose distributions, including chi2, mean absolute error, dose difference at the penumbra edge point, slope of the dose difference of the lateral profile, and the newly proposed Kappaalpha factor (defined as the fraction of the voxels with absolute dose difference less than alpha%). It was found that the use of the slope of the lateral profile difference or the difference of the penumbra edge points may lead to inaccurate determination of the initial beam parameters. We also found that in general the cost function value is very sensitive to the simulation statistical uncertainty, and there is a tradeoff between uncertainty and specificity. Due to the existence of statistical uncertainty in simulated dose distributions, it is practically impossible to determine the best energy/radius combination; we have to accept a group of energy/radius combinations. We have also investigated the minimum required data set for accurate determination of the initial beam parameters. We found that the percent depth dose curves along or only a lateral profile at certain depth for a large field size is not sufficient and the minimum data set should include several lateral profiles at various depths as well as the central axis percent depth dose curve for a large field size.

On dose distribution comparison.

In radiotherapy practice, one often needs to compare two dose distributions. Especially with the wide clinical implementation of intensity-modulated radiation therapy, software tools for quantitative dose (or fluence) distribution comparison are required for patient-specific quality assurance. Dose distribution comparison is not a trivial task since it has to be performed in both dose and spatial domains in order to be clinically relevant. Each of the existing comparison methods has its own strengths and weaknesses and there is room for improvement. In this work, we developed a general framework for comparing dose distributions. Using a new concept called maximum allowed dose difference (MADD), the comparison in both dose and spatial domains can be performed entirely in the dose domain. Formulae for calculating MADD values for various comparison methods, such as composite analysis and gamma index, have been derived. For convenience in clinical practice, a new measure called normalized dose difference (NDD) has also been proposed, which is the dose difference at a point scaled by the ratio of MADD to the predetermined dose acceptance tolerance. Unlike the simple dose difference test, NDD works in both low and high dose gradient regions because it considers both dose and spatial acceptance tolerances through MADD. The new method has been applied to a test case and a clinical example. It was found that the new method combines the merits of the existing methods (accurate, simple, clinically intuitive and insensitive to dose grid size) and can easily be implemented into any dose/intensity comparison tool.

Estimation of the delivered patient dose in lung IMRT treatment based on deformable registration of 4D-CT data and Monte Carlo simulations.

The purpose of this study is to accurately estimate the difference between the planned and the delivered dose due to respiratory motion and free breathing helical CT artefacts for lung IMRT treatments, and to estimate the impact of this difference on clinical outcome. Six patients with representative tumour motion, size and position were selected for this retrospective study. For each patient, we had acquired both a free breathing helical CT and a ten-phase 4D-CT scan. A commercial treatment planning system was used to create four IMRT plans for each patient. The first two plans were based on the GTV as contoured on the free breathing helical CT set, with a GTV to PTV expansion of 1.5 cm and 2.0 cm, respectively. The third plan was based on the ITV, a composite volume formed by the union of the CTV volumes contoured on free breathing helical CT, end-of-inhale (EOI) and end-of-exhale (EOE) 4D-CT. The fourth plan was based on GTV contoured on the EOE 4D-CT. The prescribed dose was 60 Gy for all four plans. Fluence maps and beam setup parameters of the IMRT plans were used by the Monte Carlo dose calculation engine MCSIM for absolute dose calculation on both the free breathing CT and 4D-CT data. CT deformable registration between the breathing phases was performed to estimate the motion trajectory for both the tumour and healthy tissue. Then, a composite dose distribution over the whole breathing cycle was calculated as a final estimate of the delivered dose. EUD values were computed on the basis of the composite dose for all four plans. For the patient with the largest motion effect, the difference in the EUD of CTV between the planed and the delivered doses was 33, 11, 1 and 0 Gy for the first, second, third and fourth plan, respectively. The number of breathing phases required for accurate dose prediction was also investigated. With the advent of 4D-CT, deformable registration and Monte Carlo simulations, it is feasible to perform an accurate calculation of the delivered dose, and compare our delivered dose with doses estimated using prior techniques.