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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

OPEN leaf : an open‐source cloud‐based phenotyping system for tracking dynamic changes at leaf‐specific resolution in Arabidopsis

SUMMARY The first draft of the Arabidopsis genome was released more than 20 years ago and despite intensive molecular research, more than 30% of Arabidopsis genes remained uncharacterized or without an assigned function. This is in part due to gene redundancy within gene families or the essential nature of genes, where their deletion results in lethality (i.e., thedark genome). High‐throughput plant phenotyping (HTPP) offers an automated and unbiased approach to characterize subtle or transient phenotypes resulting from gene redundancy or inducible gene silencing; however, access to commercial HTPP platforms remains limited. Here we describe the design and implementation ofOPEN leaf, an open‐source phenotyping system with cloud connectivity and remote bilateral communication to facilitate data collection, sharing and processing.OPEN leaf, coupled with our SMART imaging processing pipeline was able to consistently document and quantify dynamic changes at the whole rosette level and leaf‐specific resolution when plants experienced changes in nutrient availability. Our data also demonstrate that VIS sensors remain underutilized and can be used in high‐throughput screens to identify and characterize previously unidentified phenotypes in a leaf‐specific time‐dependent manner. Moreover, the modular and open‐source design ofOPEN leafallows seamless integration of additional sensors based on users and experimental needs.

Plant Sciences↗
DOE OSTI2017

PT -symmetry in kagome photonic lattices

Photonic lattices composed of balanced gain and loss waveguides have attracted considerable attention due of their potential applications in optical beam engineering and image processing. These photonic lattices belong to a larger class of intriguing active metamaterials that exhibit the parity-time ( PT ) symmetry. Kagome lattice is a two-dimensional network of corner-sharing triangles and is often associated with geometrical frustration. In particular, the frustrated coupling between waveguide modes in a kagome array leads to a dispersionless flat band consisting of spatially localized modes. Recently, a PT -symmetric photonics lattice based on the kagome structure has been proposed by placing PT -symmetric dimers at the kagome lattice points. Each dimer corresponds to a pair of strongly coupled waveguides. With balanced arrangement of gain and loss on individual dimers, the system exhibits a PT -symmetric phase for finite gain/loss parameter up to a critical value. Here we discuss the linear and nonlinear optical beam propagations in this novel PT -symmetric kagome system. The linear beam evolution in this complex kagome waveguide array exhibits a novel oscillatory rotation of optical power along the propagation distance. Long-lived local chiral structures originating from the nearly flat bands of the kagome structure are observed when the lattice is subject to a narrow beam excitation. We further show that inclusion of Kerr-type nonlinearity leads to novel optical solitons.

42 ENGINEERING↗
DOE OSTI2018

Snapshot 3D tracking of insulin granules in live cells

Rapid and accurate volumetric imaging remains a challenge, yet has the potential to enhance understanding of cell function. We developed and used a multifocal microscope (MFM) for 3D snapshot imaging to allow 3D tracking of insulin granules labeled with mCherry in MIN6 cells. MFM employs a special diffractive optical element (DOE) to simultaneously image multiple focal planes. This simultaneous acquisition of information deteunines the 3D location of single objects at a speed only limited by the array detector's frame rate. We validated the accuracy of MFM imaging/tracking with fluorescence beads; the 3D positions and trajectories of single fluorescence beads can be detelinined accurately over a wide range of spatial and temporal scales. The 3D positions and trajectories of single insulin granules in a 3.2um deep volume were deteunined with imaging processing that combines 3D decovolution, shift correction, and finally tracking using the Imaris software package. We find that the motion of the granules is super diffusive, but less so in 3D than 2D for cells grown on coverslip surfaces, suggesting an anisotropy in the cytoskeleton (e.g. microtubules and action).

3D tracking↗
DOE OSTI2024

Terahertz time-domain spectroscopy imaging of pancreatic ductal adenocarcinoma tissues

Pancreatic ductal adenocarcinoma (PDAC) ranks among the malignancies with the highest fatality and morbidity rates. This is predominantly attributable to an absence of understanding the intricate and diverse microenvironment of the tumor. We use terahertz time-domain spectroscopy (THz-TDS) imaging in transmission geometry to probe ex-vivo the heterogenous microenvironment of the genetically modified murine PDAC tissue that closely resembles the PDAC heterogeneity in human malignancy. We introduced a maximum a-posteriori probability estimation algorithm to objectively the tumor’s heterogenous microenvironment using the average values of refractive index and absorption coefficient within the useable terahertz bandwidth as imaging markers. Furthermore, direct comparison of stained histopathologic images and the refractive index and the absorption coefficient high-resolution, two dimensional maps of the same PDAC samples confirms the high potential of the THz-TDS method for tumor tissue characterization.

absorption↗
DOE OSTI2013

Low dose tomographic fluoroscopy: 4D intervention guidance with running prior

Purpose: Today's standard imaging technique in interventional radiology is the single- or biplane x-ray fluoroscopy which delivers 2D projection images as a function of time (2D+T). This state-of-the-art technology, however, suffers from its projective nature and is limited by the superposition of the patient's anatomy. Temporally resolved tomographic volumes (3D+T) would significantly improve the visualization of complex structures. A continuous tomographic data acquisition, if carried out with today's technology, would yield an excessive patient dose. Recently the authors proposed a method that enables tomographic fluoroscopy at the same dose level as projective fluoroscopy which means that if scanning time of an intervention guided by projective fluoroscopy is the same as that of an intervention guided by tomographic fluoroscopy, almost the same dose is administered to the patient. The purpose of this work is to extend authors' previous work and allow for patient motion during the intervention.Methods: The authors propose the running prior technique for adaptation of a prior image. This adaptation is realized by a combination of registration and projection replacement. In a first step the prior is deformed to the current position via affine and deformable registration. Then the information from outdated projections is replaced by newly acquired projections using forward and backprojection steps. The thus adapted volume is the running prior. The proposed method is validated by simulated as well as measured data. To investigate motion during intervention a moving head phantom was simulated. Real in vivo data of a pig are acquired by a prototype CT system consisting of a flat detector and a continuously rotating clinical gantry.Results: With the running prior technique it is possible to correct for motion without additional dose. For an application in intervention guidance both steps of the running prior technique, registration and replacement, are necessary. Reconstructed volumes based on the running prior show high image quality without introducing new artifacts and the interventional materials are displayed at the correct position.Conclusions: The running prior improves the robustness of low dose 3D+T intervention guidance toward intended or unintended patient motion.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Template-based CTA to x-ray angio rigid registration of coronary arteries in frequency domain with automatic x-ray segmentation

Purpose: A key challenge for image guided coronary interventions is accurate and absolutely robust image registration bringing together preinterventional information extracted from a three-dimensional (3D) patient scan and live interventional image information. In this paper, the authors present a novel scheme for 3D to two-dimensional (2D) rigid registration of coronary arteries extracted from preoperative image scan (3D) and a single segmented intraoperative x-ray angio frame in frequency and spatial domains for real-time angiography interventions by C-arm fluoroscopy.Methods: Most existing rigid registration approaches require a close initialization due to the abundance of local minima and high complexity of search algorithms. The authors' method eliminates this requirement by transforming the projections into translation-invariant Fourier domain for estimating the 3D pose. For 3D rotation recovery, template Digitally Reconstructed Radiographs (DRR) as candidate poses of 3D vessels of segmented computed tomography angiography are produced by rotating the camera (image intensifier) around the DICOM angle values with a specific range as in C-arm setup. The authors have compared the 3D poses of template DRRs with the segmented x-ray after equalizing the scales in three domains, namely, Fourier magnitude, Fourier phase, and Fourier polar. The best rotation pose candidate was chosen by one of the highest similarity measures returned by the methods in these domains. It has been noted in literature that frequency domain methods are robust against noise and occlusion which was also validated by the authors' results. 3D translation of the volume was then recovered by distance-map based BFGS optimization well suited to convex structure of the authors' objective function without local minima due to distance maps. A novel automatic x-ray vessel segmentation was also performed in this study.Results: Final results were evaluated in 2D projection space for patient data; and with ground truth values and landmark distances for the images acquired with a solid phantom vessel. Results validate that rotation recovery in frequency domain is robust against differences in segmentations in two modalities. Distance-map translation is successful in aligning coronary trees with highest possible overlap.Conclusions: Numerical and qualitative results show that single view rigid alignment in projection space is successful. This work can be extended with multiple views to resolve depth ambiguity and with deformable registration to account for nonrigid motion in patient data.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Characterization of a constrained paired-view technique in iterative reconstruction for breast tomosynthesis

Purpose: The order in which the projection views are employed in the reconstruction of tomosynthesis by iterative algorithms, such as simultaneous algebraic reconstruction technique and maximum likelihood, has a strong effect on the rate of convergence, accuracy, and the edge-blurring artifacts in the reconstructed image. The purpose of this investigation was to characterize and evaluate the effects of ordering schemes on image quality for breast tomosynthesis reconstruction and to explore a new constrained paired-view technique that could provide reduction of reconstruction artifacts. In this work, the authors compared several different ordering schemes and characterized the image quality and the formation of out-of-plane artifacts. Furthermore, a new normalization method is presented. It produces more accurate reconstructions with reduced artifacts comparing to the standard method of sequential ordering.Methods: In addition to visual assessment of image quality, several indices such as the signal-difference-to-noise ratio, the artifact-spread function, and the lesion detectability (d{sup ′}) were computed to quantitatively evaluate the effect of ordering scheme. The sets of breast tomosynthesis projection images were simulated for reconstruction; one set had uniform background (white noise only) and the other two contained both anatomic background and quantum noise. Clinical breast images were also studied for comparison.Results: The authors have quantified the image quality in reconstructed slices for a range of tumor sizes. The authors’ proposed method provides better performance for all of the metrics tested (contrast, d{sup ′}, and the level of artifacts) both for the uniform phantom case and in the presence of anatomical structure.Conclusions: The paired projection normalization provides better performance in the image quality of the reconstructed slices, and results in a lower level of artifacts in the Z direction. This implies that even a relatively simple method like the “side-to-side” sequence, which pairs two symmetrical projections with equal angular distance from the central projection, would achieve better reconstructed image quality than the conventional “step-by-step” method, which uses sequential projections one after another.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Performance of 12 DIR algorithms in low-contrast regions for mass and density conserving deformation

Purpose: Deformable image registration (DIR) has become a key tool for adaptive radiotherapy to account for inter- and intrafraction organ deformation. Of contemporary interest, the application to deformable dose accumulation requires accurate deformation even in low contrast regions where dose gradients may exist within near-uniform tissues. One expects high-contrast features to generally be deformed more accurately by DIR algorithms. The authors systematically assess the accuracy of 12 DIR algorithms and quantitatively examine, in particular, low-contrast regions, where accuracy has not previously been established.Methods: This work investigates DIR algorithms in three dimensions using deformable gel (DEFGEL) [U. J. Yeo, M. L. Taylor, L. Dunn, R. L. Smith, T. Kron, and R. D. Franich, “A novel methodology for 3D deformable dosimetry,” Med. Phys. 39, 2203–2213 (2012)], for application to mass- and density-conserving deformations. CT images of DEFGEL phantoms with 16 fiducial markers (FMs) implanted were acquired in deformed and undeformed states for three different representative deformation geometries. Nonrigid image registration was performed using 12 common algorithms in the public domain. The optimum parameter setup was identified for each algorithm and each was tested for deformation accuracy in three scenarios: (I) original images of the DEFGEL with 16 FMs; (II) images with eight of the FMs mathematically erased; and (III) images with all FMs mathematically erased. The deformation vector fields obtained for scenarios II and III were then applied to the original images containing all 16 FMs. The locations of the FMs estimated by the algorithms were compared to actual locations determined by CT imaging. The accuracy of the algorithms was assessed by evaluation of three-dimensional vectors between true marker locations and predicted marker locations.Results: The mean magnitude of 16 error vectors per sample ranged from 0.3 to 3.7, 1.0 to 6.3, and 1.3 to 7.5 mm across algorithms for scenarios I to III, respectively. The greatest accuracy was exhibited by the original Horn and Schunck optical flow algorithm. In this case, for scenario III (erased FMs not contributing to driving the DIR calculation), the mean error was half that of the modified demons algorithm (which exhibited the greatest error), across all deformations. Some algorithms failed to reproduce the geometry at all, while others accurately deformed high contrast features but not low-contrast regions—indicating poor interpolation between landmarks.Conclusions: The accuracy of DIR algorithms was quantitatively evaluated using a tissue equivalent, mass, and density conserving DEFGEL phantom. For the model studied, optical flow algorithms performed better than demons algorithms, with the original Horn and Schunck performing best. The degree of error is influenced more by the magnitude of displacement than the geometric complexity of the deformation. As might be expected, deformation is estimated less accurately for low-contrast regions than for high-contrast features, and the method presented here allows quantitative analysis of the differences. The evaluation of registration accuracy through observation of the same high contrast features that drive the DIR calculation is shown to be circular and hence misleading.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

A further investigation of the centroid-to-centroid method for stereotactic lung radiotherapy: A phantom study

Purpose: Our previous study [B. Lu et al., “A patient alignment solution for lung SBRT setups based on a deformable registration technique,” Med. Phys. 39(12), 7379–7389 (2012)] proposed a deformable-registration-based patient setup strategy called the centroid-to-centroid (CTC) method, which can perform an accurate alignment of internal-target-volume (ITV) centroids between averaged four-dimensional computed tomography and cone-beam computed tomography (CBCT) images. Scenarios with variations between CBCT and simulation CT caused by irregular breathing and/or tumor change were not specifically considered in the patient study [B. Lu et al., “A patient alignment solution for lung SBRT setups based on a deformable registration technique,” Med. Phys. 39(12), 7379–7389 (2012)] due to the lack of both a sufficiently large patient data sample and a method of tumor tracking. The aim of this study is to thoroughly investigate and compare the impacts of breathing pattern and tumor change on both the CTC and the translation-only (T-only) gray-value mode strategies by employing a four-dimensional (4D) lung phantom.Methods: A sophisticated anthropomorphic 4D phantom (CIRS Dynamic Thorax Phantom model 008) was employed to simulate all desired respiratory variations. The variation scenarios were classified into four groups: inspiration to expiration ratio (IE ratio) change, tumor trajectory change, tumor position change, tumor size change, and the combination of these changes. For each category the authors designed several scenarios to demonstrate the effects of different levels of breathing variation on both of the T-only and the CTC methods. Each scenario utilized 4DCT and CBCT scans. The ITV centroid alignment discrepancies for CTC and T-only were evaluated. The dose-volume-histograms (DVHs) of ITVs for two extreme cases were analyzed.Results: Except for some extreme cases in the combined group, the accuracy of the CTC registration was about 2 mm for all cases for both the single and the combined scenarios. The performance of the CTC method was insensitive to region-of-registration (ROR) size selections, as suggested by the comparable accuracy between 1 and 2 cm expansions of the ROR selections for the method. The T-only method was suitable for some single scenarios, such as trajectory variation, position variation, and size variation. However, for combined scenarios and/or a large variation in the IE ratio, the T-only method failed to produce reasonable registration results (within 3 mm). The discrepancy was close to, or even greater than, 1 cm. In addition, unlike the CTC method, the T-only method was sensitive to the ROR size selection. The DVH analysis suggested that a large ITV to PTV margin should be considered if a breathing pattern variation is observed.Conclusions: The phantom study demonstrated that the CTC method was reliable for scenarios in which breathing pattern variation was involved. The T-only gray value method worked for some scenarios, but not for scenarios that involved an IE ratio variation. For scenarios involving position variation, the T-only method worked only with a careful selection of the ROR, whereas the CTC method was independent of ROR size as long as the ITVs were included in the ROR. One indication of the dose consequence analysis was that a large ITV to PTV margin should be considered if a breathing pattern variation is observed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography

Purpose: Dual-energy computed tomography (DECT) makes it possible to get two fractions of basis materials without segmentation. One is the soft-tissue equivalent water fraction and the other is the hard-matter equivalent bone fraction. Practical DECT measurements are usually obtained with polychromatic x-ray beams. Existing reconstruction approaches based on linear forward models without counting the beam polychromaticity fail to estimate the correct decomposition fractions and result in beam-hardening artifacts (BHA). The existing BHA correction approaches either need to refer to calibration measurements or suffer from the noise amplification caused by the negative-log preprocessing and the ill-conditioned water and bone separation problem. To overcome these problems, statistical DECT reconstruction approaches based on nonlinear forward models counting the beam polychromaticity show great potential for giving accurate fraction images.Methods: This work proposes a full-spectral Bayesian reconstruction approach which allows the reconstruction of high quality fraction images from ordinary polychromatic measurements. This approach is based on a Gaussian noise model with unknown variance assigned directly to the projections without taking negative-log. Referring to Bayesian inferences, the decomposition fractions and observation variance are estimated by using the joint maximum a posteriori (MAP) estimation method. Subject to an adaptive prior model assigned to the variance, the joint estimation problem is then simplified into a single estimation problem. It transforms the joint MAP estimation problem into a minimization problem with a nonquadratic cost function. To solve it, the use of a monotone conjugate gradient algorithm with suboptimal descent steps is proposed.Results: The performance of the proposed approach is analyzed with both simulated and experimental data. The results show that the proposed Bayesian approach is robust to noise and materials. It is also necessary to have the accurate spectrum information about the source-detector system. When dealing with experimental data, the spectrum can be predicted by a Monte Carlo simulator. For the materials between water and bone, less than 5% separation errors are observed on the estimated decomposition fractions.Conclusions: The proposed approach is a statistical reconstruction approach based on a nonlinear forward model counting the full beam polychromaticity and applied directly to the projections without taking negative-log. Compared to the approaches based on linear forward models and the BHA correction approaches, it has advantages in noise robustness and reconstruction accuracy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Evaluation of the robustness of the preprocessing technique improving reversible compressibility of CT images: Tested on various CT examinations

Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations.Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique was developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CR{sub I}) was measured.Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CR{sub I} were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively.Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone-beam CT

Purpose: Image reconstruction and motion model estimation in four-dimensional cone-beam CT (4D-CBCT) are conventionally handled as two sequential steps. Due to the limited number of projections at each phase, the image quality of 4D-CBCT is degraded by view aliasing artifacts, and the accuracy of subsequent motion modeling is decreased by the inferior 4D-CBCT. The objective of this work is to enhance both the image quality of 4D-CBCT and the accuracy of motion model estimation with a novel strategy enabling simultaneous motion estimation and image reconstruction (SMEIR).Methods: The proposed SMEIR algorithm consists of two alternating steps: (1) model-based iterative image reconstruction to obtain a motion-compensated primary CBCT (m-pCBCT) and (2) motion model estimation to obtain an optimal set of deformation vector fields (DVFs) between the m-pCBCT and other 4D-CBCT phases. The motion-compensated image reconstruction is based on the simultaneous algebraic reconstruction technique (SART) coupled with total variation minimization. During the forward- and backprojection of SART, measured projections from an entire set of 4D-CBCT are used for reconstruction of the m-pCBCT by utilizing the updated DVF. The DVF is estimated by matching the forward projection of the deformed m-pCBCT and measured projections of other phases of 4D-CBCT. The performance of the SMEIR algorithm is quantitatively evaluated on a 4D NCAT phantom. The quality of reconstructed 4D images and the accuracy of tumor motion trajectory are assessed by comparing with those resulting from conventional sequential 4D-CBCT reconstructions (FDK and total variation minimization) and motion estimation (demons algorithm). The performance of the SMEIR algorithm is further evaluated by reconstructing a lung cancer patient 4D-CBCT.Results: Image quality of 4D-CBCT is greatly improved by the SMEIR algorithm in both phantom and patient studies. When all projections are used to reconstruct a 3D-CBCT by FDK, motion-blurring artifacts are present, leading to a 24.4% relative reconstruction error in the NACT phantom. View aliasing artifacts are present in 4D-CBCT reconstructed by FDK from 20 projections, with a relative error of 32.1%. When total variation minimization is used to reconstruct 4D-CBCT, the relative error is 18.9%. Image quality of 4D-CBCT is substantially improved by using the SMEIR algorithm and relative error is reduced to 7.6%. The maximum error (MaxE) of tumor motion determined from the DVF obtained by demons registration on a FDK-reconstructed 4D-CBCT is 3.0, 2.3, and 7.1 mm along left–right (L-R), anterior–posterior (A-P), and superior–inferior (S-I) directions, respectively. From the DVF obtained by demons registration on 4D-CBCT reconstructed by total variation minimization, the MaxE of tumor motion is reduced to 1.5, 0.5, and 5.5 mm along L-R, A-P, and S-I directions. From the DVF estimated by SMEIR algorithm, the MaxE of tumor motion is further reduced to 0.8, 0.4, and 1.5 mm along L-R, A-P, and S-I directions, respectively.Conclusions: The proposed SMEIR algorithm is able to estimate a motion model and reconstruct motion-compensated 4D-CBCT. The SMEIR algorithm improves image reconstruction accuracy of 4D-CBCT and tumor motion trajectory estimation accuracy as compared to conventional sequential 4D-CBCT reconstruction and motion estimation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Quantification of organ motion based on an adaptive image-based scale invariant feature method

Purpose: The availability of corresponding landmarks in IGRT image series allows quantifying the inter and intrafractional motion of internal organs. In this study, an approach for the automatic localization of anatomical landmarks is presented, with the aim of describing the nonrigid motion of anatomo-pathological structures in radiotherapy treatments according to local image contrast.Methods: An adaptive scale invariant feature transform (SIFT) was developed from the integration of a standard 3D SIFT approach with a local image-based contrast definition. The robustness and invariance of the proposed method to shape-preserving and deformable transforms were analyzed in a CT phantom study. The application of contrast transforms to the phantom images was also tested, in order to verify the variation of the local adaptive measure in relation to the modification of image contrast. The method was also applied to a lung 4D CT dataset, relying on manual feature identification by an expert user as ground truth. The 3D residual distance between matches obtained in adaptive-SIFT was then computed to verify the internal motion quantification with respect to the expert user. Extracted corresponding features in the lungs were used as regularization landmarks in a multistage deformable image registration (DIR) mapping the inhale vs exhale phase. The residual distances between the warped manual landmarks and their reference position in the inhale phase were evaluated, in order to provide a quantitative indication of the registration performed with the three different point sets.Results: The phantom study confirmed the method invariance and robustness properties to shape-preserving and deformable transforms, showing residual matching errors below the voxel dimension. The adapted SIFT algorithm on the 4D CT dataset provided automated and accurate motion detection of peak to peak breathing motion. The proposed method resulted in reduced residual errors with respect to standard SIFT, providing a motion description comparable to expert manual identification, as confirmed by DIR.Conclusions: The application of the method to a 4D lung CT patient dataset demonstrated adaptive-SIFT potential as an automatic tool to detect landmarks for DIR regularization and internal motion quantification. Future works should include the optimization of the computational cost and the application of the method to other anatomical sites and image modalities.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

The use of computed radiography plates to determine light and radiation field coincidence

Purpose: Photo-stimulable phosphor computed radiography (CR) has characteristics that allow the output to be manipulated by both radiation and optical light. The authors have developed a method that uses these characteristics to carry out radiation field and light field coincidence quality assurance on linear accelerators.Methods: CR detectors from Kodak were used outside their cassettes to measure both radiation and light field edges from a Varian linear accelerator. The CR detector was first exposed to a radiation field and then to a slightly smaller light field. The light impinged on the detector's latent image, removing to an extent the portion exposed to the light field. The detector was then digitally scanned. A MATLAB-based algorithm was developed to automatically analyze the images and determine the edges of the light and radiation fields, the vector between the field centers, and the crosshair center. Radiographic film was also used as a control to confirm the radiation field size.Results: Analysis showed a high degree of repeatability with the proposed method. Results between the proposed method and radiographic film showed excellent agreement of the radiation field. The effect of varying monitor units and light exposure time was tested and found to be very small. Radiation and light field sizes were determined with an uncertainty of less than 1 mm, and light and crosshair centers were determined within 0.1 mm.Conclusions: A new method was developed to digitally determine the radiation and light field size using CR photo-stimulable phosphor plates. The method is quick and reproducible, allowing for the streamlined and robust assessment of light and radiation field coincidence, with no observer interpretation needed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Evaluation of the cone beam CT for internal target volume localization in lung stereotactic radiotherapy in comparison with 4D MIP images

Purpose: To investigate whether the three-dimensional cone-beam CT (CBCT) is clinically equivalent to the four-dimensional computed tomography (4DCT) maximum intensity projection (MIP) reconstructed images for internal target volume (ITV) localization in image-guided lung stereotactic radiotherapy.Methods: A ball-shaped polystyrene phantom with built-in cube, sphere, and cone of known volumes was attached to a motor-driven platform, which simulates a sinusoidal movement with changeable motion amplitude and frequency. Target motion was simulated in the patient in a superior-inferior (S-I) direction with three motion periods and 2 cm peak-to-peak amplitudes. The Varian onboard Exact-Arms kV CBCT system and the GE LightSpeed four-slice CT integrated with the respiratory-position-management 4DCT scanner were used to scan the moving phantom. MIP images were generated from the 4DCT images. The clinical equivalence of the two sets of images was evaluated by comparing the extreme locations of the moving objects along the motion direction, the centroid position of the ITV, and the ITV volumes that were contoured automatically by Velocity or calculated with an imaging gradient method. The authors compared the ITV volumes determined by the above methods with those theoretically predicted by taking into account the physical object dimensions and the motion amplitudes. The extreme locations were determined by the gradient method along the S-I axis through the center of the object. The centroid positions were determined by autocenter functions. The effect of motion period on the volume sizes was also studied.Results: It was found that the extreme locations of the objects determined from the two image modalities agreed with each other satisfactorily. They were not affected by the motion period. The average difference between the two modalities in the extreme locations was 0.68% for the cube, 1.35% for the sphere, and 0.5% for the cone, respectively. The maximum difference in the centroid position of the cylinder, sphere, and cone was less than 1.4 mm between the two modalities for all motion periods studied. For the ITV volume evaluation, the authors found that both MIP-based and CBCT-based ITVs increased with increases of motion period. Furthermore, the MIP-based ITV volumes were generally larger than those determined from the CBCT images, with the difference in autocontoured volumes being 2.57%, 1.66%, and 1.82% for the sphere, cylinder, and cone, respectively, while these differences increased to 9.57%, 3.52%, 8.71% for the above objects when the gradient method was used. The authors found that the autocontour method was accurate enough to predict the actual ITV values with the absolute differences less than 2.4% comparing to the theoretically predicted values.Conclusions: The extreme location and the centroid position of the objects agree with each other between the two image modalities when the breathing motion is sinusoidal. Although the ITV volumes delineated from both image modalities changed with the motion period, the differences in ITV between the two modalities were minimal when an optimized window level was used. The authors’ results suggest that CBCT and MIP images are equivalent in determining an ITV's position in the conditions studied. The CBCT is adequate in providing imaging-guidance for lung cancer treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Quantitative Monte Carlo-based holmium-166 SPECT reconstruction

Purpose: Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ({sup 166}Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative {sup 166}Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum.Methods: A fast Monte Carlo (MC) simulator was developed for simulation of {sup 166}Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full {sup 166}Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A{sup est}) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six {sup 166}Ho RE patients.Results: At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96–106.21 ml were improved from 32%–63% (SPECT-DSW) and 50%–80% (SPECT-ppMC+DSW) to 76%–103% (SPECT-fMC). Furthermore, SPECT-fMC recovered whole-body activities were most accurate (A{sup est}= 1.06 × A − 5.90 MBq, R{sup 2}= 0.97) and SPECT-fMC tumor absorbed doses were significantly higher than with SPECT-DSW (p = 0.031) and SPECT-ppMC+DSW (p = 0.031).Conclusions: The quantitative accuracy of {sup 166}Ho SPECT is improved by Monte Carlo-based modeling of the image degrading factors. Consequently, the proposed reconstruction method enables accurate estimation of the radiation absorbed dose in clinical practice.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2013

An automated voxelized dosimetry tool for radionuclide therapy based on serial quantitative SPECT/CT imaging

Purpose: To create an accurate map of the distribution of radiation dose deposition in healthy and target tissues during radionuclide therapy.Methods: Serial quantitative SPECT/CT images were acquired at 4, 24, and 72 h for 28 {sup 177}Lu-octreotate peptide receptor radionuclide therapy (PRRT) administrations in 17 patients with advanced neuroendocrine tumors. Deformable image registration was combined with an in-house programming algorithm to interpolate pharmacokinetic uptake and clearance at a voxel level. The resultant cumulated activity image series are comprised of values representing the total number of decays within each voxel's volume. For PRRT, cumulated activity was translated to absorbed dose based on Monte Carlo-determined voxel S-values at a combination of long and short ranges. These dosimetric image sets were compared for mean radiation absorbed dose to at-risk organs using a conventional MIRD protocol (OLINDA 1.1).Results: Absorbed dose values to solid organs (liver, kidneys, and spleen) were within 10% using both techniques. Dose estimates to marrow were greater using the voxelized protocol, attributed to the software incorporating crossfire effect from nearby tumor volumes.Conclusions: The technique presented offers an efficient, automated tool for PRRT dosimetry based on serial post-therapy imaging. Following retrospective analysis, this method of high-resolution dosimetry may allow physicians to prescribe activity based on required dose to tumor volume or radiation limits to healthy tissue in individual patients.

61 RADIATION PROTECTION AND DOSIMETRY↗

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