Consistent and invertible deformation vector fields for a breathing anthropomorphic phantom: a post-processing framework for the XCAT phantom

Breathing motion is challenging for radiotherapy planning and delivery. This requires advanced four-dimensional (4D) imaging and motion mitigation strategies and associated validation tools with known deformations. Numerical phantoms such as the XCAT provide reproducible and realistic data for simulation-based validation. However, the XCAT generates partially inconsistent and non-invertible deformations where tumours remain rigid and structures can move through each other. We address these limitations by post-processing the XCAT deformation vector fields (DVF) to generate a breathing phantom with realistic motion and quantifiable deformation. An open-source post-processing framework was developed that corrects and inverts the XCAT-DVFs while preserving sliding motion between organs. Those post-processed DVFs are used to warp the first XCAT-generated image to consecutive time points providing a 4D phantom with a tumour that moves consistently with the anatomy, the ability to scale lung density as well as consistent and invertible DVFs. For a regularly breathing case, the inverse consistency of the DVFs was verified and the tumour motion was compared to the original XCAT. The generated phantom and DVFs were used to validate a motion-including dose reconstruction (MIDR) method using isocenter shifts to emulate rigid motion. Differences between the reconstructed doses with and without lung density scaling were evaluated. The post-processing framework produced DVFs with a maximum [Formula: see text]-percentile inverse-consistency error of 0.02 mm. The generated phantom preserved the dominant sliding motion between the chest wall and inner organs. The tumour of the original XCAT phantom preserved its trajectory while deforming consistently with the underlying tissue. The MIDR was compared to the ground truth dose reconstruction illustrating its limitations. MIDR with and without lung density scaling resulted in small dose differences up to 1 Gy (prescription 54 Gy). The proposed open-source post-processing framework overcomes important limitations of the original XCAT phantom and makes it applicable to a wider range of validation applications within radiotherapy.

Continuous generation of volumetric images during stereotactic body radiation therapy using periodic kV imaging and an external respiratory surrogate

We present a technique for continuous generation of volumetric images during SBRT using periodic kV imaging and an external respiratory surrogate signal to drive a patient-specific PCA motion model. Using the on-board imager, kV radiographs are acquired every 3 s and used to fit the parameters of a motion model so that it matches observed changes in internal patient anatomy. A multi-dimensional correlation model is established between the motion model parameters and the external surrogate position and velocity, enabling volumetric image reconstruction between kV imaging time points. Performance of the algorithm was evaluated using 10 realistic eXtended CArdiac-Torso (XCAT) digital phantoms including 3D anatomical respiratory deformation programmed with 3D tumor positions measured with orthogonal kV imaging of implanted fiducial gold markers. The clinically measured ground truth 3D tumor positions provided a dataset with realistic breathing irregularities, and the combination of periodic on-board kV imaging with recorded external respiratory surrogate signal was used for correlation modeling to account for any changes in internal-external correlation. The three-dimensional tumor positions are reconstructed with an average root mean square error (RMSE) of 1.47 mm, and an average 95th percentile 3D positional error of 2.80 mm compared with the clinically measured ground truth 3D tumor positions. This technique enables continuous 3D anatomical image generation based on periodic kV imaging of internal anatomy without the additional dose of continuous kV imaging. The 3D anatomical images produced using this method can be used for treatment verification and delivered dose computation in the presence of irregular respiratory motion.

Optical computed tomography for spatially isotropic four-dimensional imaging of live single cells

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.

Evidence-based recommendations for musculoskeletal kinematic 4D-CT studies using wide area-detector scanners: a phantom study with cadaveric correlation

PROPOSE

To establish evidence-based recommendations for musculoskeletal kinematic 4D-CT on wide area-detector CT.

MATERIALS AND METHODS

In order to assess factors influencing image quality in kinematic CT studies, a phantom consisting of a polymethylmethacrylate rotating disk with round wells of different sizes was imaged with various acquisition protocols. Cadaveric acquisitions were performed on the ankle joint during motion in two different axes and at different speeds to allow validation of phantom data. Images were acquired with a 320 detector-row CT scanner and were evaluated by two readers.

RESULTS

Motion artefacts were significantly correlated with various parameters (movement axis, distance to centre, rotation speed and volume acquisition speed) (p < 0.0001). The relation between motion artefacts and distance to motion fulcrum was exponential (R² 0.99). Half reconstruction led to a 23 % increase in image noise and a 40 % decrease in motion artefacts. Cadaveric acquisitions confirmed phantom data. Based on these findings, high tube rotation speed and half reconstruction are recommended for kinematic CT. The axis of motion significantly influences image artefacts and should be considered in patient training and evaluation of acquisition protocol suitability.

CONCLUSION

This study provides evidence-based recommendations for musculoskeletal kinematic 4D-CT.

KEY POINTS

• Motion artefacts can hamper the quality and interpretation of dynamic joint studies • The recommendations presented here help increase image quality • Patient training and preparation can be improved • The artefact-free distance concept helps protocol adaptation and comparison.

3D printer generated thorax phantom with mobile tumor for radiation dosimetry

This article describes the design, construction, and properties of an anthropomorphic thorax phantom with a moving surrogate tumor. This novel phantom permits detection of dose both inside and outside a moving tumor and within the substitute lung tissue material. A 3D printer generated the thorax shell composed of a chest wall, spinal column, and posterior regions of the phantom. Images of a computed tomography scan of the thorax from a patient with lung cancer provided the template for the 3D printing. The plastic phantom is segmented into two materials representing the muscle and bones, and its geometry closely matches a patient. A surrogate spherical plastic tumor controlled by a 3D linear stage simulates a lung tumor's trajectory during normal breathing. Sawdust emulates the lung tissue in terms of average and distribution in Hounsfield numbers. The sawdust also provides a forgiving medium that permits tumor motion and sandwiching of radiochromic film inside the mobile surrogate plastic tumor for dosimetry. A custom cork casing shields the film and tumor and eliminates film bending during extended scans. The phantom, lung tissue surrogate, and radiochromic film are exposed to a seven field plan based on an ECLIPSE plan for 6 MV photons from a Trilogy machine delivering 230 cGy to the isocenter. The dose collected in a sagittal plane is compared to the calculated plan. Gamma analysis finds 8.8% and 5.5% gamma failure rates for measurements of large amplitude trajectory and static measurements relative to the large amplitude plan, respectively. These particular gamma analysis results were achieved using parameters of 3% dose and 3 mm, for regions receiving doses >150 cGy. The plan assumes a stationary detection grid unlike the moving radiochromic film and tissues. This difference was experimentally observed and motivated calculated dose distributions that incorporated the phase of the tumor periodic motion. These calculations modestly improve agreement between the measured and intended doses.

A method for volumetric imaging in radiotherapy using single x-ray projection

PURPOSE

It is an intriguing problem to generate an instantaneous volumetric image based on the corresponding x-ray projection. The purpose of this study is to develop a new method to achieve this goal via a sparse learning approach.

METHODS

To extract motion information hidden in projection images, the authors partitioned a projection image into small rectangular patches. The authors utilized a sparse learning method to automatically select patches that have a high correlation with principal component analysis (PCA) coefficients of a lung motion model. A model that maps the patch intensity to the PCA coefficients was built along with the patch selection process. Based on this model, a measured projection can be used to predict the PCA coefficients, which are then further used to generate a motion vector field and hence a volumetric image. The authors have also proposed an intensity baseline correction method based on the partitioned projection, in which the first and the second moments of pixel intensities at a patch in a simulated projection image are matched with those in a measured one via a linear transformation. The proposed method has been validated in both simulated data and real phantom data.

RESULTS

The algorithm is able to identify patches that contain relevant motion information such as the diaphragm region. It is found that an intensity baseline correction step is important to remove the systematic error in the motion prediction. For the simulation case, the sparse learning model reduced the prediction error for the first PCA coefficient to 5%, compared to the 10% error when sparse learning was not used, and the 95th percentile error for the predicted motion vector was reduced from 2.40 to 0.92 mm. In the phantom case with a regular tumor motion, the predicted tumor trajectory was successfully reconstructed with a 0.82 mm error for tumor center localization compared to a 1.66 mm error without using the sparse learning method. When the tumor motion was driven by a real patient breathing signal with irregular periods and amplitudes, the average tumor center error was 0.6 mm. The algorithm robustness with respect to sparsity level, patch size, and presence or absence of diaphragm, as well as computation time, has also been studied.

CONCLUSIONS

The authors have developed a new method that automatically identifies motion information from an x-ray projection, based on which a volumetric image is generated.

Deformation vector fields (DVF)-driven image reconstruction for 4D-CBCT

BACKGROUND

High quality 4D-CBCT can be obtained by deforming a planning CT (pCT), where the deformation vector fields (DVF) are estimated by matching the forward projections of pCT and 4D-CBCT projections. The matching metric used in the previous study is the sum of squared intensity differences (SSID). The scatter signal level in CBCT projections is much higher than pCT, the SSID metric may not lead to optimal DVF.

OBJECTIVE

To improve the DVF estimation accuracy, we develop a new matching metric that is less sensitive to the intensity level difference caused by the scatter signal.

METHODS

The negative logarithm of correlation coefficient (NLCC) is used as the matching metric. A non-linear conjugate gradient optimization algorithm is used to estimate the DVF. A 4D NCAT phantom and an anthropomorphic thoracic phantom were used to evaluate the NLCC-based algorithm.

RESULTS

In the NCAT phantom study, the relative reconstruction error is reduced from 18.0% in SSID to 14.13% in NLCC. In the thoracic phantom study, the root mean square error of the tumor motion is reduced from 1.16 mm in SSID to 0.43 mm in NLCC.

CONCLUSION

NLCC metric can improve the image reconstruction and motion estimation accuracy of DVF-driven image reconstruction for 4D-CBCT.

Registration-based reconstruction of four-dimensional cone beam computed tomography

We present a new method for reconstruction of 4-D cone beam computed tomography from an undersampled set of X-ray projections. The novelty of the proposed method lies in utilizing optical flow based registration to facilitate that each temporal phase is reconstructed from the full set of acquired projections. The reconstruction of each phase thus exhibits limited aliasing despite significant intra-phase undersampling. The method is fully self-contained. Initially an approximate 4-D volume is reconstructed and an inter-phase registration based hereon. A subsequent reconstruction pass integrates the optical flow estimation in a cost function formulation in which the X-ray projections from all temporal phases are considered for the reconstruction of each individual phase. Quantitative and qualitative evaluations were performed through reconstruction of both a numerical phantom and a clinical dataset. The obtained reconstructions are compared to the state-of-the-art alternatives of total variation regularization and prior image constrained compressed sensing. Our studies show that the proposed method is the better overall "compromise" in the depiction of both moving and stationary anatomical structures.

4D digital subtraction angiography: implementation and demonstration of feasibility

BACKGROUND AND PURPOSE

Conventional 3D-DSA volumes are reconstructed from a series of projections containing temporal information. It was our purpose to develop a technique which would generate fully time-resolved 3D-DSA vascular volumes having better spatial and temporal resolution than that which is available with CT or MR angiography.

MATERIALS AND METHODS

After a single contrast injection, projections from the mask and fill rotation are subtracted to create a series of vascular projections. With the use of these projections, a conventional conebeam CT reconstruction is generated (conventional 3D-DSA). This is used to constrain the reconstruction of individual 3D temporal volumes, which incorporate temporal information from the acquired projections (4D-DSA).

RESULTS

Typically, 30 temporal volumes per second are generated with the use of currently available flat detector systems, a factor of ∼200 increase over that achievable with the use of multiple gantry rotations. Dynamic displays of the reconstructed volumes are viewable from any angle. Good results have been obtained by using both intra-arterial and intravenous injections.

CONCLUSIONS

It is feasible to generate time-resolved 3D-DSA vascular volumes with the use of commercially available flat detector angiographic systems and clinically practical injection protocols. The spatial resolution and signal-to-noise ratio of the time frames are largely determined by that of the conventional 3D-DSA constraining image and not by that of the projections used to generate the 3D reconstruction. The spatial resolution and temporal resolution exceed that of CTA and MRA, and the small vessel contrast is increased relative to that of conventional 2D-DSA due to the use of maximum intensity projections.

Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization

PURPOSE

The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms.

METHODS

The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models.

RESULTS

Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve as a jumping point from which to create an unlimited number of 3D and 4D variations for imaging research.

CONCLUSIONS

A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. The series of anatomically variable phantoms developed in this work provide a valuable resource for investigating 3D and 4D imaging devices and the effects of anatomy and motion in imaging. Combined with Monte Carlo simulation programs, the phantoms also provide a valuable tool to investigate patient-specific dose and image quality, and optimization for adults undergoing imaging procedures.

Stereotactic body radiotherapy for pulmonary metastases. Prognostic factors and adverse respiratory events

PURPOSE

The aim of this retrospective study was to evaluate the feasibility, safety, and effectiveness of stereotactic body radiotherapy (SBRT) for pulmonary metastases.

PATIENTS AND METHODS

Between April 2007 and March 2011, 87 patients underwent SBRT for pulmonary metastases using the in-house Air-Bag System(TM) to obtain the four-dimensional image for treatment planning and to reduce intrafractional intrathoracic organ motion with abdominal compression to reduce the risk of radiation pneumonitis. Survival and respiratory adverse events were analyzed.

RESULTS

The 2- and 3-year overall survival (OS) rates were 47 and 32 %, and the corresponding cause-specific survivals were 52 and 36 %. The 2- and 3-year OS rates were 57 and 49 % for patients in group 1, respectively, while the corresponding OS rates were 48 and 21 %, and 40 and 32 % for patients in groups 2 and 3, respectively. The 2- and 3-year local control (LC) rates were 80 and 80 %, respectively. The corresponding intrathoracic progression-free survival rates were 40 and 32 %, respectively. Concerning adverse respiratory events after SBRT for pulmonary metastases, 14 % were grade 0 (G0), 66 % G1, 13 % G2, 6 % G3, and 1 % G4. Concerning the adverse respiratory events (NCI-CTC) by grade scale, 1- and 2-year cumulative probabilities of radiation pneumonitis were 12 and 20 % for G2 and 4 and 10 % for G3/4, respectively. The mean values for cumulative V20 were 11.6 ± 8.5 %, 29.8 ± 18.6 %, and 25.7 ± 12.8 % in G0/1, G2, and G3/4, respectively. The number of pulmonary metastases that could be safely treated with SBRT was 6 PTVs (or seven gross tumor volumes) within a cumulative V20 of 30 % under the restricted intrafractional respiratory tumor motion using the Air-Bag System(TM).

CONCLUSION

We propose that the number of pulmonary metastases that can be safely treated with SBRT is 6 PTVs with a cumulative V20 of 30 % under the restricted respiratory tumor motion using the Air-Bag System(TM). SBRT for pulmonary metastases offers locally effective treatment for recurrent or residual lesions after first line chemotherapy.

Proton radiography and fluoroscopy of lung tumors: a Monte Carlo study using patient-specific 4DCT phantoms

PURPOSE

Monte Carlo methods are used to simulate and optimize a time-resolved proton range telescope (TRRT) in localization of intrafractional and interfractional motions of lung tumor and in quantification of proton range variations.

METHODS

The Monte Carlo N-Particle eXtended (MCNPX) code with a particle tracking feature was employed to evaluate the TRRT performance, especially in visualizing and quantifying proton range variations during respiration. Protons of 230 MeV were tracked one by one as they pass through position detectors, patient 4DCT phantom, and finally scintillator detectors that measured residual ranges. The energy response of the scintillator telescope was investigated. Mass density and elemental composition of tissues were defined for 4DCT data.

RESULTS

Proton water equivalent length (WEL) was deduced by a reconstruction algorithm that incorporates linear proton track and lateral spatial discrimination to improve the image quality. 4DCT data for three patients were used to visualize and measure tumor motion and WEL variations. The tumor trajectories extracted from the WEL map were found to be within 1 mm agreement with direct 4DCT measurement. Quantitative WEL variation studies showed that the proton radiograph is a good representation of WEL changes from entrance to distal of the target.

CONCLUSIONS

MCNPX simulation results showed that TRRT can accurately track the motion of the tumor and detect the WEL variations. Image quality was optimized by choosing proton energy, testing parameters of image reconstruction algorithm, and comparing to ground truth 4DCT. The future study will demonstrate the feasibility of using the time resolved proton radiography as an imaging tool for proton treatments of lung tumors.