Paul Segars

Evaluation of quantitative planar (90)Y bremsstrahlung whole-body imaging.

With high-dose administration of (90)Y labeled antibodies, it is possible to image (90)Y without an admixture of (111)In. We have earlier shown that it is possible to perform quantitative (90)Y bremsstrahlung SPECT for dosimetry purposes with reasonable accuracy. However, whole-body (WB) activity quantification with the conjugate view method is not as time consuming as SPECT and has been the method of choice for dosimetry. We have investigated the possibility of using a conjugate view method where scatter-, backscatter- and septal-penetration compensations are performed by inverse filtering and attenuation correction is performed with a WB x-ray image, for total-body and organ activity quantification of (90)Y. The method was evaluated using both Monte Carlo simulated scintillation camera images using realistic source distributions, and by an experimental phantom study. The method was evaluated in terms of image quality and accuracy of the activity quantification. The experimental phantom study was performed using the RSD torso phantom with (90)Y activity uniformly distributed in the liver insert. A GE Discovery VH/Hawkeye system was used to acquire the image. The simulation study was performed for a realistic activity distribution in the NCAT anthropomorphic phantom where (90)Y bremsstrahlung images were generated using the SIMIND MC program. Two different phantom configurations and two activity distributions were simulated. To mimic the RSD phantom experiment one simulation study was also made with (90)Y activity located only in the liver. The SIMIND program was configured to resemble a GE Discovery VH/Hawkeye system. An x-ray projector program was used to generate whole-body x-ray images from the NCAT phantom for attenuation correction in the conjugate view method. Organ activities were calculated from ROIs that exactly covered the organs. Corrections for background activity, overlapping activity and source extension in the depth direction were applied on the ROI data. The total-body activities for the simulated images were generally overestimated by around 10%, which is reasonable since the correction for source extension was not applied on the total-body values. The accuracy of the organ activities was mostly within 15% for both the simulation study and the experimental study. The results suggest that it is possible to quantify (90)Y activity in ROIs with reasonable accuracy using this method.

Extension of the NCAT phantom for the investigation of intra-fraction respiratory motion in IMRT using 4D Monte Carlo

The purpose of this work was to create a computational platform for studying motion in intensity modulated radiotherapy (IMRT). Specifically, the non-uniform rational B-spline (NURB) cardiac and torso (NCAT) phantom was modified for use in a four-dimensional Monte Carlo (4D-MC) simulation system to investigate the effect of respiratory-induced intra-fraction organ motion on IMRT dose distributions as a function of diaphragm motion, lesion size and lung density. Treatment plans for four clinical scenarios were designed: diaphragm peak-to-peak amplitude of 1 cm and 3 cm, and two lesion sizes--2 cm and 4 cm diameter placed in the lower lobe of the right lung. Lung density was changed for each phase using a conservation of mass calculation. Further, a new heterogeneous lung model was implemented and tested. Each lesion had an internal target volume (ITV) subsequently expanded by 15 mm isotropically to give the planning target volume (PTV). The PTV was prescribed to receive 72 Gy in 40 fractions. The MLC leaf sequence defined by the planning system for each patient was exported and used as input into the MC system. MC simulations using the dose planning method (DPM) code together with deformable image registration based on the NCAT deformation field were used to find a composite dose distribution for each phantom. These composite distributions were subsequently analyzed using information from the dose volume histograms (DVH). Lesion motion amplitude has the largest effect on the dose distribution. Tumor size was found to have a smaller effect and can be mitigated by ensuring the planning constraints are optimized for the tumor size. The use of a dynamic or heterogeneous lung density model over a respiratory cycle does not appear to be an important factor with a <or=0.6% change in the mean dose received by the ITV, PTV and right lung. The heterogeneous model increases the realism of the NCAT phantom and may provide more accurate simulations in radiation therapy investigations that use the phantom. This work further evaluates the NCAT phantom for use as a tool in radiation therapy research in addition to its extensive use in diagnostic imaging and nuclear medicine research. Our results indicate that the NCAT phantom, combined with 4D-MC simulations, is a useful tool in radiation therapy investigations and may allow the study of relative effects in many clinically relevant situations.

Improved dose?volume histogram estimates for radiopharmaceutical therapy by optimizing quantitative SPECT reconstruction parameters

In radiopharmaceutical therapy, an understanding of the dose distribution in normal and target tissues is important for optimizing treatment. Three-dimensional (3D) dosimetry takes into account patient anatomy and the nonuniform uptake of radiopharmaceuticals in tissues. Dose-volume histograms (DVHs) provide a useful summary representation of the 3D dose distribution and have been widely used for external beam treatment planning. Reliable 3D dosimetry requires an accurate 3D radioactivity distribution as the input. However, activity distribution estimates from SPECT are corrupted by noise and partial volume effects (PVEs). In this work, we systematically investigated OS-EM based quantitative SPECT (QSPECT) image reconstruction in terms of its effect on DVHs estimates. A modified 3D NURBS-based Cardiac-Torso (NCAT) phantom that incorporated a non-uniform kidney model and clinically realistic organ activities and biokinetics was used. Projections were generated using a Monte Carlo (MC) simulation; noise effects were studied using 50 noise realizations with clinical count levels. Activity images were reconstructed using QSPECT with compensation for attenuation, scatter and collimator-detector response (CDR). Dose rate distributions were estimated by convolution of the activity image with a voxel S kernel. Cumulative DVHs were calculated from the phantom and QSPECT images and compared both qualitatively and quantitatively. We found that noise, PVEs, and ringing artifacts due to CDR compensation all degraded histogram estimates. Low-pass filtering and early termination of the iterative process were needed to reduce the effects of noise and ringing artifacts on DVHs, but resulted in increased degradations due to PVEs. Large objects with few features, such as the liver, had more accurate histogram estimates and required fewer iterations and more smoothing for optimal results. Smaller objects with fine details, such as the kidneys, required more iterations and less smoothing at early time points post-radiopharmaceutical administration but more smoothing and fewer iterations at later time points when the total organ activity was lower. The results of this study demonstrate the importance of using optimal reconstruction and regularization parameters. Optimal results were obtained with different parameters at each time point, but using a single set of parameters for all time points produced near-optimal dose-volume histograms.

Establishing a framework to implement 4D XCAT Phantom for 4D radiotherapy research

AIMS To establish a framework to implement the 4D integrated extended cardiac torso (XCAT) digital phantom for 4D radiotherapy (RT) research. MATERIALS AND METHODS A computer program was developed to facilitate the characterization and implementation of the 4D XCAT phantom. The program can (1) generate 4D XCAT images with customized parameter files; (2) review 4D XCAT images; (3) generate composite images from 4D XCAT images; (4) track motion of selected region-of-interested (ROI); (5) convert XCAT raw binary images into DICOM format; (6) analyse clinically acquired 4DCT images and real-time position management (RPM) respiratory signal. Motion tracking algorithm was validated by comparing with manual method. Major characteristics of the 4D XCAT phantom were studied. RESULTS The comparison between motion tracking and manual measurements of lesion motion trajectory showed a small difference between them (mean difference in motion amplitude: 1.2 mm). The maximum lesion motion decreased nearly linearly (R 2 = 0.97) as its distance to the diaphragm (DD) increased. At any given DD, lesion motion amplitude increased nearly linearly (R 2 range: 0.89 to 0.95) as the inputted diaphragm motion increased. For a given diaphragm motion, the lesion motion is independent of the lesion size at any given DD. The 4D XCAT phantom can closely reproduce irregular breathing profile. The end-to-end test showed that clinically comparable treatment plans can be generated successfully based on 4D XCAT images. CONCLUSIONS An integrated computer program has been developed to generate, review, analyse, process, and export the 4D XCAT images. A framework has been established to implement the 4D XCAT phantom for 4D RT research.

Digital anthropomorphic phantoms of non-rigid human respiratory and voluntary body motion for investigating motion correction in emission imaging

The development of methods for correcting patient motion in emission tomography has been receiving increased attention. Often the performance of these methods is evaluated through simulations using digital anthropomorphic phantoms, such as the commonly used extended cardiac torso (XCAT) phantom, which models both respiratory and cardiac motion based on human studies. However, non-rigid body motion, which is frequently seen in clinical studies, is not present in the standard XCAT phantom. In addition, respiratory motion in the standard phantom is limited to a single generic trend. In this work, to obtain a more realistic representation of motion, we developed a series of individual-specific XCAT phantoms, modeling non-rigid respiratory and non-rigid body motions derived from the magnetic resonance imaging (MRI) acquisitions of volunteers. Acquisitions were performed in the sagittal orientation using the Navigator methodology. Baseline (no motion) acquisitions at end-expiration were obtained at the beginning of each imaging session for each volunteer. For the body motion studies, MRI was again acquired only at end-expiration for five body motion poses (shoulder stretch, shoulder twist, lateral bend, side roll, and axial slide). For the respiratory motion studies, an MRI was acquired during free/regular breathing. The magnetic resonance slices were then retrospectively sorted into 14 amplitude-binned respiratory states, end-expiration, end-inspiration, six intermediary states during inspiration, and six during expiration using the recorded Navigator signal. XCAT phantoms were then generated based on these MRI data by interactive alignment of the organ contours of the XCAT with the MRI slices using a graphical user interface. Thus far we have created five body motion and five respiratory motion XCAT phantoms from the MRI acquisitions of six healthy volunteers (three males and three females). Non-rigid motion exhibited by the volunteers was reflected in both respiratory and body motion phantoms with a varying extent and character for each individual. In addition to these phantoms, we recorded the position of markers placed on the chest of the volunteers for the body motion studies, which could be used as external motion measurement. Using these phantoms and external motion data, investigators will be able to test their motion correction approaches for realistic motion obtained from different individuals. The non-uniform rational B-spline data and the parameter files for these phantoms are freely available for downloading and can be used with the XCAT license.

Creation of 3D Digital Anthropomorphic Phantoms which Model Actual Patient Non-rigid Body Motion as Determined from MRI and Position Tracking Studies of Volunteers

Patient motion can cause artifacts, which can lead to difficulty in interpretation. The purpose of this study is to create 3D digital anthropomorphic phantoms which model the location of the structures of the chest and upper abdomen of human volunteers undergoing a series of clinically relevant motions. The 3D anatomy is modeled using the XCAT phantom and based on MRI studies. The NURBS surfaces of the XCAT are interactively adapted to fit the MRI studies. A detailed XCAT phantom is first developed from an EKG triggered Navigator acquisition composed of sagittal slices with a 3 x 3 x 3 mm voxel dimension. Rigid body motion states are then acquired at breath-hold as sagittal slices partially covering the thorax, centered on the heart, with 9 mm gaps between them. For non-rigid body motion requiring greater sampling, modified Navigator sequences covering the entire thorax with 3 mm gaps between slices are obtained. The structures of the initial XCAT are then adapted to fit these different motion states. Simultaneous to MRI imaging the positions of multiple reflective markers on stretchy bands about the volunteers chest and abdomen are optically tracked in 3D via stereo imaging. These phantoms with combined position tracking will be used to investigate both imaging-data-driven and motion-tracking strategies to estimate and correct for patient motion. Our initial application will be to cardiacperfusion SPECT imaging where the XCAT phantoms will be used to create patient activity and attenuation distributions for each volunteer with corresponding motion tracking data from the markers on the body-surface. Monte Carlo methods will then be used to simulate SPECT acquisitions, which will be used to evaluate various motion estimation and correction strategies.

Improved scatter correction with factor analysis for planar and SPECT imaging

Quantitative nuclear medicine imaging is an increasingly important frontier. In order to achieve quantitative imaging, various interactions of photons with matter have to be modeled and compensated. Although correction for photon attenuation has been addressed by including x-ray CT scans (accurate), correction for Compton scatter remains an open issue. The inclusion of scattered photons within the energy window used for planar or SPECT data acquisition decreases the contrast of the image. While a number of methods for scatter correction have been proposed in the past, in this work, we propose and assess a novel, user-independent framework applying factor analysis (FA). Extensive Monte Carlo simulations for planar and tomographic imaging were performed using the SIMIND software. Furthermore, planar acquisition of two Petri dishes filled with 99mTc solutions and a Jaszczak phantom study (Data Spectrum Corporation, Durham, NC, USA) using a dual head gamma camera were performed. In order to use FA for scatter correction, we subdivided the applied energy window into a number of sub-windows, serving as input data. FA results in two factor images (photo-peak, scatter) and two corresponding factor curves (energy spectra). Planar and tomographic Jaszczak phantom gamma camera measurements were recorded. The tomographic data (simulations and measurements) were processed for each angular position resulting in a photo-peak and a scatter data set. The reconstructed transaxial slices of the Jaszczak phantom were quantified using an ImageJ plugin. The data obtained by FA showed good agreement with the energy spectra, photo-peak, and scatter images obtained in all Monte Carlo simulated data sets. For comparison, the standard dual-energy window (DEW) approach was additionally applied for scatter correction. FA in comparison with the DEW method results in significant improvements in image accuracy for both planar and tomographic data sets. FA can be used as a user-independent approach for scatter correction in nuclear medicine.

TH-EF-BRA-10: High Spatiotemporal Resolution Self-Sorted 4D MRI

PURPOSE To describe a novel method for self-sorted 4D-MRI and to characterize the output image quality as measured by signal-to-noise ratio (SNR), spatiotemporal resolution, and level of artifact. METHODS A three-dimensional radial sampling function with a quasi-random distribution of polar/azimuthal k-space angles was implemented in a standard pulse sequence. Acquisition time was approximately 2 minutes. The DC component of the k-space signal was used to estimate and sort the breathing cycle into ten respiratory phases. For a given respiratory phase, the k-space data were combined with the periphery of the k-space data from all phases and reconstructed with the re-gridding algorithm onto a 1283 matrix. The extent of data sharing was controlled by the average breathing curve. The sampling and reconstruction technique were tested and validated in simulation, dynamic phantom, animal, and human studies with varying breathing periods/amplitudes. RESULTS The signal at the k-space center accurately measures respiratory motion over a large range of breathing periods (0.5-7.0 seconds) and amplitudes (5-30% of FOV). Sharing of high frequency k-space data driven by the average breathing curve improves spatial resolution and artifact level at a cost of an increase in noise floor. Although equal sharing of k-space data improves resolution and SNR, phases with large temporal changes accumulate considerable distortion artifacts. In the absence of view-sharing, no distortion artifacts are observed while spatial resolution is degraded. CONCLUSION The use of a quasi-random sampling function and view-sharing driven by the average breathing curve provide a feasible method for self-sorted 4D MRI at reduced acquisition times. This approach allows for the extent of data sharing to be inversely-proportional to the average breathing motion hence improving resolution and decreasing artifact levels. NIH-1R21CA165384.

A method for generating large datasets of organ geometries for radiotherapy treatment planning studies

Abstract Background. With the rapidly increasing application of adaptive radiotherapy, large datasets of organ geometries based on the patient’s anatomy are desired to support clinical application or research work, such as image segmentation, re-planning, and organ deformation analysis. Sometimes only limited datasets are available in clinical practice. In this study, we propose a new method to generate large datasets of organ geometries to be utilized in adaptive radiotherapy. Methods. Given a training dataset of organ shapes derived from daily cone-beam CT, we align them into a common coordinate frame and select one of the training surfaces as reference surface. A statistical shape model of organs was constructed, based on the establishment of point correspondence between surfaces and non-uniform rational B-spline (NURBS) representation. A principal component analysis is performed on the sampled surface points to capture the major variation modes of each organ. Results. A set of principal components and their respective coefficients, which represent organ surface deformation, were obtained, and a statistical analysis of the coefficients was performed. New sets of statistically equivalent coefficients can be constructed and assigned to the principal components, resulting in a larger geometry dataset for the patient’s organs. Conclusions. These generated organ geometries are realistic and statistically representative

Workflow For Creating a Simulation Ready Virtual Population For Finite Element Modeling

A proof of concept workflow is demonstrated to easily translate 3D medical image data into finite element (FE) simulation ready phantom models. First, novel methods are used to drastically reduce manual segmentation time for a virtual population. Next, using Simpleware software, the segmented voxel datasets are extracted into faceted 3D CAD objects for tissues, while simultaneously maintaining conformal multi-tissue interfaces. Finally, the 3D CAD geometries are demonstrated to be readily compatible in a commercial 3D electromagnetic simulator, ANSYS HFSS.© 2013 ASME