P Mishra

Quantifying ITV instabilities arising from 4DCT: a simulation study using patient data.

Treatment planning for patients undergoing radiation therapy is often performed based on four-dimensional computed tomography (4DCT) when respiratory motion is present, as in lung cancer patients. 4DCT is used to define the internal target volume (ITV) that, ideally, incorporates all potential locations of the tumour. In this work, we use the locations of gold fiducial markers implanted in lung tumours of eight patients to represent tumour motion. These fiducial locations are used in a simulation of a four-slice CT scanner to generate the ITV for 10, 20 and 30 mm diameter model tumours. To demonstrate instabilities in the ITV definition based on 4DCT, the ITV calculation was repeated for the same patients for consecutive scan start times, staggered by 1 s. The volumetric difference in the ITV and the per cent of time that the ITV contains in the tumour are both evaluated. The ITV from a single patient was found to vary by 46%-127% for a tumour diameter of 10 mm. The ITV did not cover the entirety of the tumour 11%-74% of the time for a 10 mm tumour diameter.

Adaptation and applications of a realistic digital phantom based on patient lung tumor trajectories.

Digital phantoms continue to play a significant role in modeling and characterizing medical imaging. The currently available XCAT phantom incorporates both the flexibility of mathematical phantoms and the realistic nature of voxelized phantoms. This phantom generates images based on a regular breathing pattern and can include arbitrary lung tumor trajectories. In this work, we present an algorithm that modifies the current XCAT phantom to generate 4D imaging data based on irregular breathing. First, a parameter is added to the existing XCAT phantom to include any arbitrary tumor motion. This modification introduces the desired tumor motion but, comes at the cost of decoupled diaphragm, chest wall and lung motion. To remedy this problem diaphragm and chest wall motion is first modified based on initial tumor location and then input to the XCAT phantom. This generates a phantom with synchronized respiratory motion. Mapping of tumor motion trajectories to diaphragm and chest wall motion is done by adaptively calculating a scale factor based on tumor to lung contour distance. The distance is calculated by projecting the initial tumor location to lung edge contours characterized by quadratic polynomials. Data from ten patients were used to evaluate the accuracy between actual independent tumor location and the location obtained from the modified XCAT phantom. The RMSE and standard deviations for ten patients in x, y, and z directions are: (0.29 ± 0.04, 0.54 ± 0.17, and0.39 ± 0.06) mm. To demonstrate the utility of the phantom, we use the new phantom to simulate a 4DCT acquisition as well as a recently published method for phase sorting. The modified XCAT phantom can be used to generate more realistic imaging data for enhanced testing of algorithms for CT reconstruction, tumor tracking, and dose reconstruction.

Registration of clinical volumes to beams-eye-view images for real-time tracking.

PURPOSE The authors combine the registration of 2D beams eye view (BEV) images and 3D planning computed tomography (CT) images, with relative, markerless tumor tracking to provide automatic absolute tracking of physician defined volumes such as the gross tumor volume (GTV). METHODS During treatment of lung SBRT cases, BEV images were continuously acquired with an electronic portal imaging device (EPID) operating in cine mode. For absolute registration of physician-defined volumes, an intensity based 2D/3D registration to the planning CT was performed using the end-of-exhale (EoE) phase of the four dimensional computed tomography (4DCT). The volume was converted from Hounsfield units into electron density by a calibration curve and digitally reconstructed radiographs (DRRs) were generated for each beam geometry. Using normalized cross correlation between the DRR and an EoE BEV image, the best in-plane rigid transformation was found. The transformation was applied to physician-defined contours in the planning CT, mapping them into the EPID image domain. A robust multiregion method of relative markerless lung tumor tracking quantified deviations from the EoE position. RESULTS The success of 2D/3D registration was demonstrated at the EoE breathing phase. By registering at this phase and then employing a separate technique for relative tracking, the authors are able to successfully track target volumes in the BEV images throughout the entire treatment delivery. CONCLUSIONS Through the combination of EPID/4DCT registration and relative tracking, a necessary step toward the clinical implementation of BEV tracking has been completed. The knowledge of tumor volumes relative to the treatment field is important for future applications like real-time motion management, adaptive radiotherapy, and delivered dose calculations.

An initial study on the estimation of time-varying volumetric treatment images and 3D tumor localization from single MV cine EPID images

PURPOSE In this work the authors develop and investigate the feasibility of a method to estimate time-varying volumetric images from individual MV cine electronic portal image device (EPID) images. METHODS The authors adopt a two-step approach to time-varying volumetric image estimation from a single cine EPID image. In the first step, a patient-specific motion model is constructed from 4DCT. In the second step, parameters in the motion model are tuned according to the information in the EPID image. The patient-specific motion model is based on a compact representation of lung motion represented in displacement vector fields (DVFs). DVFs are calculated through deformable image registration (DIR) of a reference 4DCT phase image (typically peak-exhale) to a set of 4DCT images corresponding to different phases of a breathing cycle. The salient characteristics in the DVFs are captured in a compact representation through principal component analysis (PCA). PCA decouples the spatial and temporal components of the DVFs. Spatial information is represented in eigenvectors and the temporal information is represented by eigen-coefficients. To generate a new volumetric image, the eigen-coefficients are updated via cost function optimization based on digitally reconstructed radiographs and projection images. The updated eigen-coefficients are then multiplied with the eigenvectors to obtain updated DVFs that, in turn, give the volumetric image corresponding to the cine EPID image. RESULTS The algorithm was tested on (1) Eight digital eXtended CArdiac-Torso phantom datasets based on different irregular patient breathing patterns and (2) patient cine EPID images acquired during SBRT treatments. The root-mean-squared tumor localization error is (0.73 ± 0.63 mm) for the XCAT data and (0.90 ± 0.65 mm) for the patient data. CONCLUSIONS The authors introduced a novel method of estimating volumetric time-varying images from single cine EPID images and a PCA-based lung motion model. This is the first method to estimate volumetric time-varying images from single MV cine EPID images, and has the potential to provide volumetric information with no additional imaging dose to the patient.

Low-Z linac targets for low-MV gold nanoparticle radiation therapy

PURPOSE To investigate the potential of low-Z/low-MV (low-Z) linac targets for gold nanoparticle radiotherapy (GNPT) and to determine the microscopic dose enhancement ratio (DER) due to GNP for the alternative beamlines. In addition, to evaluate the degradation of dose enhancement arising from the increased attenuation of x rays and larger skin dose in water for the low-MV beams compared to the standard linac. METHODS Monte Carlo simulations were used to compute dose and DER for various flattening-filter-free beams (2.5, 4, 6.5 MV). Target materials were beryllium, diamond, and tungsten-copper high-Z target. Target thicknesses were selected based on 20%, 60%, 70%, and 80% of the continuous slowing down approximation electron ranges for a given target material and energy. Evaluation of the microscopic DER was carried out for 100 nm GNP including the degradation factors due to beam attenuation. RESULTS The greatest increase in DER compared to the standard 6.5 MV linac was for a 2.5 MV Be-target (factor of ∼ 2). Skin dose ranged from ∼ 10% (Be, 6.5 MV-80%) to ∼ 85% (Be, 2.5 MV-20%) depending on the target case. Attenuation of 2.5 MV beams at 22 cm was higher by ∼ 75% compared with the standard beam. Taking into account the attenuation at 22 cm depth, the effective dose enhancement was up to ∼ 60% above the DER of the high-Z target. For these cases the effective DER ranged between ∼ 1.6 and 6 compared with the standard linac. CONCLUSIONS Low-Z (2.5 MV) GNPT is possible even after accounting for greater beam attenuation for deep-seated tumors (22 cm) and the increased skin dose. Further, it can lead to significant sparing of normal tissue while simultaneously escalating the dose in the tumor cells.

Cine EPID evaluation of two non-commercial techniques for DIBH

PURPOSE To evaluate the efficacy of two noncommercial techniques for deep inspiration breathhold (DIBH) treatment of left-sided breast cancer (LSBC) using cine electronic portal imaging device (EPID) images. METHODS 23,875 EPID images of 65 patients treated for LSBC at two different cancer treatment centers were retrieved. At the Milford Regional Cancer Center, DIBH stability was maintained by visual alignment of inroom lasers and patient skin tattoos (TAT). At the South Shore Hospital, a distance-measuring laser device (RTSSD) was implemented. For both centers,cine EPID images were acquired at least once per week during beam-on. Chest wall position relative to image boundary was measured and tracked over the course of treatment for every patient and treatment fraction for which data were acquired. RESULTS Median intrabeam chest motion was 0.31 mm for the TAT method and 0.37 mm for the RTSSD method. The maximum excursions exceeded our treatment protocol threshold of 3 mm in 0.3% of cases (TAT) and 1.2% of cases (RTSSD). The authors did not observe a clinically significant difference between the two datasets. CONCLUSIONS Both noncommercial techniques for monitoring the DIBH location provided DIBH stability within the predetermined treatment protocol parameters (<3 mm). The intreatment imaging offered by the EPID operating in cine mode facilitates retrospective analysis and validation of both techniques.

Simulations using patient data to evaluate systematic errors that may occur in 4D treatment planning: A proof of concept study

PURPOSE The purpose of this work is to present a framework to evaluate the accuracy of four-dimensional treatment planning in external beam radiation therapy using measured patient data and digital phantoms. METHODS To accomplish this, 4D digital phantoms of two model patients were created using measured patient lung tumor positions. These phantoms were used to simulate a four-dimensional computed tomography image set, which in turn was used to create a 4D Monte Carlo (4DMC) treatment plan. The 4DMC plan was evaluated by simulating the delivery of the treatment plan over approximately 5 min of tumor motion measured from the same patient on a different day. Unique phantoms accounting for the patient position (tumor position and thorax position) at 2 s intervals were used to represent the model patients on the day of treatment delivery and the delivered dose to the tumor was determined using Monte Carlo simulations. RESULTS For Patient 1, the tumor was adequately covered with 95.2% of the tumor receiving the prescribed dose. For Patient 2, the tumor was not adequately covered and only 74.3% of the tumor received the prescribed dose. CONCLUSIONS This study presents a framework to evaluate 4D treatment planning methods and demonstrates a potential limitation of 4D treatment planning methods. When systematic errors are present, including when the imaging study used for treatment planning does not represent all potential tumor locations during therapy, the treatment planning methods may not adequately predict the dose to the tumor. This is the first example of a simulation study based on patient tumor trajectories where systematic errors that occur due to an inaccurate estimate of tumor motion are evaluated.

A mass-conserving 4D XCAT phantom for dose calculation and accumulation

PURPOSE The XCAT phantom is a realistic 4D digital torso phantom that is widely used in imaging and therapy research. However, lung mass is not conserved between respiratory phases of the phantom, making detailed dosimetric simulations and dose accumulation unphysical. A framework is developed to correct this issue by enforcing local mass conservation in the XCAT lung. Dose calculations are performed to assess the implications of neglecting mass conservation, and to demonstrate an application of the phantom to calculate the accumulated delivered dose in an irregularly breathing patient. METHODS A displacement vector field (DVF) between each respiratory state and a reference image is generated from the XCAT motion model and its divergence is calculated and used to correct the lung density. A series of phantoms with regular and irregular breathing (based on patient data) are generated and modified to conserve mass. Monte Carlo methods are used to simulate conventional and SBRT treatment delivery. The calculated dose is deformed and accumulated using the DVF. Results from the mass-conserving and original XCAT are compared. A 4DCT is simulated for the irregularly breathing patient, and a 4DCT-based dose estimate is compared with the accumulated delivered dose. RESULTS The presented framework successfully conserves mass in the XCAT lung. The spatial distribution of the lung dose was qualitatively changed by the use of a mass conservation in the XCAT; however, the corresponding DVH did not change significantly. The comparison of the delivered dose with the 4DCT-based prediction shows similar lung metric results, however dose differences of 10% can be seen in some spatial regions. CONCLUSIONS The XCAT phantom has been successfully modified so that it conserves lung mass during respiration, enabling it to be used as a tool to perform dose accumulation studies in the lung without relying on deformable image registration. Neglecting mass conservation can result in erroneous spatial distributions of the dose in the lung. Using this tool to simulate patient treatments reveals differences between the planned dose and the calculated delivered dose for the full treatment. The software is freely available from the authors.

3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery.

TU‐CD‐304‐11: Veritas 2.0: A Cloud‐Based Tool to Facilitate Research and Innovation

Purpose: We introduce Veritas 2.0, a cloud-based, non-clinical research portal, to facilitate translation of radiotherapy research ideas to new delivery techniques. The ecosystem of research tools includes web apps for a research beam builder for TrueBeam Developer Mode, an image reader for compressed and uncompressed XIM files, and a trajectory log file based QA/beam delivery analyzer. Methods: The research beam builder can generate TrueBeam readable XML file either from scratch or from pre-existing DICOM-RT plans. DICOM-RT plan is first converted to XML format and then researcher can interactively modify or add control points to them. Delivered beam can be verified via reading generated images and analyzing trajectory log files. Image reader can read both uncompressed and HND-compressed XIM images. The trajectory log analyzer lets researchers plot expected vs. actual values and deviations among 30 mechanical axes. The analyzer gives an animated view of MLC patterns for the beam delivery. Veritas 2.0 is freely available and its advantages versus standalone software are i) No software installation or maintenance needed, ii) easy accessibility across all devices iii) seamless upgrades and iv) OS independence. Veritas is written using open-source tools like twitter bootstrap, jQuery, flask, and Python-based modules. Results: In the first experiment, an anonymized 7-beam DICOM-RT IMRT plan was converted to XML beam containing 1400 control points. kV and MV imaging points were inserted into this XML beam. In another experiment, a binary log file was analyzed to compare actual vs expected values and deviations among axes. Conclusions: Veritas 2.0 is a public cloud-based web app that hosts a pool of research tools for facilitating research from conceptualization to verification. It is aimed at providing a platform for facilitating research and collaboration. I am full time employee at Varian Medical systems, Palo Alto.