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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Model-based PSF and MTF estimation and validation from skeletal clinical CT images

Purpose: A method was developed to correct for systematic errors in estimating the thickness of thin bones due to image blurring in CT images using bone interfaces to estimate the point-spread-function (PSF). This study validates the accuracy of the PSFs estimated using said method from various clinical CT images featuring cortical bones. Methods: Gaussian PSFs, characterized by a different extent in the z (scan) direction than in the x and y directions were obtained using our method from 11 clinical CT scans of a cadaveric craniofacial skeleton. These PSFs were estimated for multiple combinations of scanning parameters and reconstruction methods. The actual PSF for each scan setting was measured using the slanted-slit technique within the image slice plane and the longitudinal axis. The Gaussian PSF and the corresponding modulation transfer function (MTF) are compared against the actual PSF and MTF for validation. Results: The differences (errors) between the actual and estimated full-width half-max (FWHM) of the PSFs were 0.09 ± 0.05 and 0.14 ± 0.11 mm for the xy and z axes, respectively. The overall errors in the predicted frequencies measured at 75%, 50%, 25%, 10%, and 5% MTF levels were 0.06 ± 0.07 and 0.06 ± 0.04 cycles/mm for the xy and z axes, respectively. The accuracy of the estimates was dependent on whether they were reconstructed with a standard kernel (Toshiba's FC68, mean error of 0.06 ± 0.05 mm, MTF mean error 0.02 ± 0.02 cycles/mm) or a high resolution bone kernel (Toshiba's FC81, PSF FWHM error 0.12 ± 0.03 mm, MTF mean error 0.09 ± 0.08 cycles/mm). Conclusions: The method is accurate in 3D for an image reconstructed using a standard reconstruction kernel, which conforms to the Gaussian PSF assumption but less accurate when using a high resolution bone kernel. The method is a practical and self-contained means of estimating the PSF in clinical CT images featuring cortical bones, without the need phantoms or any prior knowledge about the scanner-specific parameters.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Optimization of the design of thick, segmented scintillators for megavoltage cone-beam CT using a novel, hybrid modeling technique

Purpose: Active matrix flat-panel imagers (AMFPIs) incorporating thick, segmented scintillators have demonstrated order-of-magnitude improvements in detective quantum efficiency (DQE) at radiotherapy energies compared to systems based on conventional phosphor screens. Such improved DQE values facilitate megavoltage cone-beam CT (MV CBCT) imaging at clinically practical doses. However, the MV CBCT performance of such AMFPIs is highly dependent on the design parameters of the scintillators. In this paper, optimization of the design of segmented scintillators was explored using a hybrid modeling technique which encompasses both radiation and optical effects. Methods: Imaging performance in terms of the contrast-to-noise ratio (CNR) and spatial resolution of various hypothetical scintillator designs was examined through a hybrid technique involving Monte Carlo simulation of radiation transport in combination with simulation of optical gain distributions and optical point spread functions. The optical simulations employed optical parameters extracted from a best fit to measurement results reported in a previous investigation of a 1.13 cm thick, 1016μm pitch prototype BGO segmented scintillator. All hypothetical designs employed BGO material with a thickness and element-to-element pitch ranging from 0.5 to 6 cm and from 0.508 to 1.524 mm, respectively. In the CNR study, for each design, full tomographic scans of a contrast phantom incorporating various soft-tissue inserts were simulated at a total dose of 4 cGy. Results: Theoretical values for contrast, noise, and CNR were found to be in close agreement with empirical results from the BGO prototype, strongly supporting the validity of the modeling technique. CNR and spatial resolution for the various scintillator designs demonstrate complex behavior as scintillator thickness and element pitch are varied—with a clear trade-off between these two imaging metrics up to a thickness of ∼3 cm. Based on these results, an optimization map indicating the regions of design that provide a balance between these metrics was obtained. The map shows that, for a given set of optical parameters, scintillator thickness and pixel pitch can be judiciously chosen to maximize performance without resorting to thicker, more costly scintillators. Conclusions: Modeling radiation and optical effects in thick, segmented scintillators through use of a hybrid technique can provide a practical way to gain insight as to how to optimize the performance of such devices in radiotherapy imaging. Assisted by such modeling, the development of practical designs should greatly facilitate low-dose, soft tissue visualization employing MV CBCT imaging in external beam radiotherapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

Purpose: Statistical model based iterative reconstruction (MBIR) methods have been introduced to clinical CT systems and are being used in some clinical diagnostic applications. The purpose of this paper is to experimentally assess the unique spatial resolution characteristics of this nonlinear reconstruction method and identify its potential impact on the detectabilities and the associated radiation dose levels for specific imaging tasks. Methods: The thoracic section of a pediatric phantom was repeatedly scanned 50 or 100 times using a 64-slice clinical CT scanner at four different dose levels [CTDI{sub vol} =4, 8, 12, 16 (mGy)]. Both filtered backprojection (FBP) and MBIR (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for image reconstruction and results were compared with one another. Eight test objects in the phantom with contrast levels ranging from 13 to 1710 HU were used to assess spatial resolution. The axial spatial resolution was quantified with the point spread function (PSF), while the z resolution was quantified with the slice sensitivity profile. Both were measured locally on the test objects and in the image domain. The dependence of spatial resolution on contrast and dose levels was studied. The study also features a systematic investigation of the potential trade-off between spatial resolution and locally defined noise and their joint impact on the overall image quality, which was quantified by the image domain-based channelized Hotelling observer (CHO) detectability index d′. Results: (1) The axial spatial resolution of MBIR depends on both radiation dose level and image contrast level, whereas it is supposedly independent of these two factors in FBP. The axial spatial resolution of MBIR always improved with an increasing radiation dose level and/or contrast level. (2) The axial spatial resolution of MBIR became equivalent to that of FBP at some transitional contrast level, above which MBIR demonstrated superior spatial resolution than FBP (and vice versa); the value of this transitional contrast highly depended on the dose level. (3) The PSFs of MBIR could be approximated as Gaussian functions with reasonably good accuracy. (4) Thez resolution of MBIR showed similar contrast and dose dependence. (5) Noise standard deviation assessed on the edges of objects demonstrated a trade-off with spatial resolution in MBIR. (5) When both spatial resolution and image noise were considered using the CHO analysis, MBIR led to significant improvement in the overall CT image quality for both high and low contrast detection tasks at both standard and low dose levels. Conclusions: Due to the intrinsic nonlinearity of the MBIR method, many well-known CT spatial resolution and noise properties have been modified. In particular, dose dependence and contrast dependence have been introduced to the spatial resolution of CT images by MBIR. The method has also introduced some novel noise-resolution trade-off not seen in traditional CT images. While the benefits of MBIR regarding the overall image quality, as demonstrated in this work, are significant, the optimal use of this method in clinical practice demands a thorough understanding of its unique physical characteristics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-I-82: Improving CT Image Quality for Radiation Therapy Using Iterative Reconstruction Algorithms and Slightly Increasing Imaging Doses

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. For CT in radiation therapy (RT), slightly increasing imaging dose to improve IQ may be justified if it can substantially enhance structure delineation. The purpose of this study is to investigate and to quantify the IQ enhancement as a result of increasing imaging doses and using IR algorithms. Methods: CT images were acquired for phantoms, built to evaluate IQ metrics including spatial resolution, contrast and noise, with a variety of imaging protocols using a CT scanner (Definition AS Open, Siemens) installed inside a Linac room. Representative patients were scanned once the protocols were optimized. Both phantom and patient scans were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and the Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared. Results: IR techniques are demonstrated to preserve spatial resolution as measured by the point spread function and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is doubled by adopting the highest SAFIRE strength. As expected, increasing imaging dose reduces noise for both SAFIRE and FBP reconstructions. The contrast to noise increases from 3 to 5 by increasing the dose by a factor of 4. Similar IQ improvement was observed on the CTs for selected patients with pancreas and prostrate cancers. Conclusion: The IR techniques produce a measurable enhancement to CT IQ by reducing the noise. Increasing imaging dose further reduces noise independent of the IR techniques. The improved CT enables more accurate delineation of tumors and/or organs at risk during RT planning and delivery guidance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-F-18C-07: Hardware Advances for MTF Improvement in Dedicated Breast CT

Purpose: In this study, we have designed and implemented a prototype dedicated breast CT system (bCT) to improve the spatial resolution characteristics, in order to improve detection of micro-calcifications. Methods: A 10.8 kW water-cooled, tungsten anode x-ray tube, running up to 240 mA at 60 kV, coupled with an x-ray generator specifically designed for this application, and 0.3 mm of added copper filter was used to generate x-ray pulses. A CsI CMOS flat panel detector with a pixel pitch of 0.075 mm in native binning mode was used. The system geometry was designed in a way to achieve an FOV on par with similar bCT prototypes, resulting in a magnification factor of 1.39. A 0.013 mm tungsten wire was used to generate point spread functions. Multiple scans were performed with different numbers of projections, different reconstruction kernel sizes and different reconstruction filters to study the effects of each parameter on MTF. The resulting MTFs were then evaluated quantitatively using the generated PFSs. Duplicate scans with the same parameters were performed on two other dedicated breast CT systems to compare the performance of the new prototype. Results: The results of the MTF experiments demonstrate a significant improvement in the spatial resolution characteristics. In the new prototype, using the pulsed x-ray source results in a restoration of the azimuthal MTF degradation, due to motion blurring previously seen in other bCT systems. Moreover, employing the higher resolution x-ray detector considerably improves the MTF. The MTF at 10% of the new system is at 3.5 1/mm, a factor of 4.36 greater than an earlier bCT scanner. Conclusion: The MTF analysis of the new prototype bCT shows that using the new hardware and control results in a significant improvement in visualization of finer detail. This suggests that the visualization of micro-calcifications will be significantly improved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

Sampling strategies for subsampled segmented EPI PRF thermometry in MR guided high intensity focused ultrasound

Purpose: To investigate k-space subsampling strategies to achieve fast, large field-of-view (FOV) temperature monitoring using segmented echo planar imaging (EPI) proton resonance frequency shift thermometry for MR guided high intensity focused ultrasound (MRgHIFU) applications. Methods: Five different k-space sampling approaches were investigated, varying sample spacing (equally vs nonequally spaced within the echo train), sampling density (variable sampling density in zero, one, and two dimensions), and utilizing sequential or centric sampling. Three of the schemes utilized sequential sampling with the sampling density varied in zero, one, and two dimensions, to investigate sampling the k-space center more frequently. Two of the schemes utilized centric sampling to acquire the k-space center with a longer echo time for improved phase measurements, and vary the sampling density in zero and two dimensions, respectively. Phantom experiments and a theoretical point spread function analysis were performed to investigate their performance. Variable density sampling in zero and two dimensions was also implemented in a non-EPI GRE pulse sequence for comparison. All subsampled data were reconstructed with a previously described temporally constrained reconstruction (TCR) algorithm. Results: The accuracy of each sampling strategy in measuring the temperature rise in the HIFU focal spot was measured in terms of the root-mean-square-error (RMSE) compared to fully sampled “truth.” For the schemes utilizing sequential sampling, the accuracy was found to improve with the dimensionality of the variable density sampling, giving values of 0.65 °C, 0.49 °C, and 0.35 °C for density variation in zero, one, and two dimensions, respectively. The schemes utilizing centric sampling were found to underestimate the temperature rise, with RMSE values of 1.05 °C and 1.31 °C, for variable density sampling in zero and two dimensions, respectively. Similar subsampling schemes with variable density sampling implemented in zero and two dimensions in a non-EPI GRE pulse sequence both resulted in accurate temperature measurements (RMSE of 0.70 °C and 0.63 °C, respectively). With sequential sampling in the described EPI implementation, temperature monitoring over a 192 × 144 × 135 mm{sup 3} FOV with a temporal resolution of 3.6 s was achieved, while keeping the RMSE compared to fully sampled “truth” below 0.35 °C. Conclusions: When segmented EPI readouts are used in conjunction with k-space subsampling for MR thermometry applications, sampling schemes with sequential sampling, with or without variable density sampling, obtain accurate phase and temperature measurements when using a TCR reconstruction algorithm. Improved temperature measurement accuracy can be achieved with variable density sampling. Centric sampling leads to phase bias, resulting in temperature underestimations.

42 ENGINEERING↗
DOE OSTI2015

A novel partial volume effects correction technique integrating deconvolution associated with denoising within an iterative PET image reconstruction

Purpose: Partial volume effect (PVE) plays an important role in both qualitative and quantitative PET image accuracy, especially for small structures. A previously proposed voxelwise PVE correction method applied on PET reconstructed images involves the use of Lucy–Richardson deconvolution incorporating wavelet-based denoising to limit the associated propagation of noise. The aim of this study is to incorporate the deconvolution, coupled with the denoising step, directly inside the iterative reconstruction process to further improve PVE correction. Methods: The list-mode ordered subset expectation maximization (OSEM) algorithm has been modified accordingly with the application of the Lucy–Richardson deconvolution algorithm to the current estimation of the image, at each reconstruction iteration. Acquisitions of the NEMA NU2-2001 IQ phantom were performed on a GE DRX PET/CT system to study the impact of incorporating the deconvolution inside the reconstruction [with and without the point spread function (PSF) model] in comparison to its application postreconstruction and to standard iterative reconstruction incorporating the PSF model. The impact of the denoising step was also evaluated. Images were semiquantitatively assessed by studying the trade-off between the intensity recovery and the noise level in the background estimated as relative standard deviation. Qualitative assessments of the developed methods were additionally performed on clinical cases. Results: Incorporating the deconvolution without denoising within the reconstruction achieved superior intensity recovery in comparison to both standard OSEM reconstruction integrating a PSF model and application of the deconvolution algorithm in a postreconstruction process. The addition of the denoising step permitted to limit the SNR degradation while preserving the intensity recovery. Conclusions: This study demonstrates the feasibility of incorporating the Lucy–Richardson deconvolution associated with a wavelet-based denoising in the reconstruction process to better correct for PVE. Future work includes further evaluations of the proposed method on clinical datasets and the use of improved PSF models.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Sparse-view proton computed tomography using modulated proton beams

Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method–projection onto convex sets (SM-POCS), superiorization method–expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Investigating the limits of PET/CT imaging at very low true count rates and high random fractions in ion-beam therapy monitoring

Purpose: External beam radiotherapy with protons and heavier ions enables a tighter conformation of the applied dose to arbitrarily shaped tumor volumes with respect to photons, but is more sensitive to uncertainties in the radiotherapeutic treatment chain. Consequently, an independent verification of the applied treatment is highly desirable. For this purpose, the irradiation-induced β{sup +}-emitter distribution within the patient is detected shortly after irradiation by a commercial full-ring positron emission tomography/x-ray computed tomography (PET/CT) scanner installed next to the treatment rooms at the Heidelberg Ion-Beam Therapy Center (HIT). A major challenge to this approach is posed by the small number of detected coincidences. This contribution aims at characterizing the performance of the used PET/CT device and identifying the best-performing reconstruction algorithm under the particular statistical conditions of PET-based treatment monitoring. Moreover, this study addresses the impact of radiation background from the intrinsically radioactive lutetium-oxyorthosilicate (LSO)-based detectors at low counts. Methods: The authors have acquired 30 subsequent PET scans of a cylindrical phantom emulating a patientlike activity pattern and spanning the entire patient counting regime in terms of true coincidences and random fractions (RFs). Accuracy and precision of activity quantification, image noise, and geometrical fidelity of the scanner have been investigated for various reconstruction algorithms and settings in order to identify a practical, well-suited reconstruction scheme for PET-based treatment verification. Truncated listmode data have been utilized for separating the effects of small true count numbers and high RFs on the reconstructed images. A corresponding simulation study enabled extending the results to an even wider range of counting statistics and to additionally investigate the impact of scatter coincidences. Eventually, the recommended reconstruction scheme has been applied to exemplary postirradiation patient data-sets. Results: Among the investigated reconstruction options, the overall best results in terms of image noise, activity quantification, and accurate geometrical recovery were achieved using the ordered subset expectation maximization reconstruction algorithm with time-of-flight (TOF) and point-spread function (PSF) information. For this algorithm, reasonably accurate (better than 5%) and precise (uncertainty of the mean activity below 10%) imaging can be provided down to 80 000 true coincidences at 96% RF. Image noise and geometrical fidelity are generally improved for fewer iterations. The main limitation for PET-based treatment monitoring has been identified in the small number of true coincidences, rather than the high intrinsic random background. Application of the optimized reconstruction scheme to patient data-sets results in a 25% − 50% reduced image noise at a comparable activity quantification accuracy and an improved geometrical performance with respect to the formerly used reconstruction scheme at HIT, adopted from nuclear medicine applications. Conclusions: Under the poor statistical conditions in PET-based treatment monitoring, improved results can be achieved by considering PSF and TOF information during image reconstruction and by applying less iterations than in conventional nuclear medicine imaging. Geometrical fidelity and image noise are mainly limited by the low number of true coincidences, not the high LSO-related random background. The retrieved results might also impact other emerging PET applications at low counting statistics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

{sup 90}Y -PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

Purpose: {sup 90}Y -positron emission tomography (PET) imaging is becoming a recognized modality for postinfusion quantitative assessment following radioembolization therapy. However, the extremely low counts and high random fraction associated with {sup 90}Y -PET may significantly impair both qualitative and quantitative results. The aim of this work was to study image quality and noise level in relation to the quantification and bias performance of two types of Siemens PET scanners when imaging {sup 90}Y and to compare experimental results with clinical data from two types of commercially available {sup 90}Y microspheres. Methods: Data were acquired on both Siemens Biograph TruePoint [non-time-of-flight (TOF)] and Biograph microcomputed tomography (mCT) (TOF) PET/CT scanners. The study was conducted in three phases. The first aimed to assess quantification and bias for different reconstruction methods according to random fraction and number of true counts in the scan. The NEMA 1994 PET phantom was filled with water with one cylindrical insert left empty (air) and the other filled with a solution of {sup 90}Y . The phantom was scanned for 60 min in the PET/CT scanner every one or two days. The second phase used the NEMA 2001 PET phantom to derive noise and image quality metrics. The spheres and the background were filled with a {sup 90}Y solution in an 8:1 contrast ratio and four 30 min acquisitions were performed over a one week period. Finally, 32 patient data (8 treated with Therasphere{sup ®} and 24 with SIR-Spheres{sup ®}) were retrospectively reconstructed and activity in the whole field of view and the liver was compared to theoretical injected activity. Results: The contribution of both bremsstrahlung and LSO trues was found to be negligible, allowing data to be decay corrected to obtain correct quantification. In general, the recovered activity for all reconstruction methods was stable over the range studied, with a small bias appearing at extremely high random fraction and low counts for iterative algorithms. Point spread function (PSF) correction and TOF reconstruction in general reduce background variability and noise and increase recovered concentration. Results for patient data indicated a good correlation between the expected and PET reconstructed activities. A linear relationship between the expected and the measured activities in the organ of interest was observed for all reconstruction method used: a linearity coefficient of 0.89 ± 0.05 for the Biograph mCT and 0.81 ± 0.05 for the Biograph TruePoint. Conclusions: Due to the low counts and high random fraction, accurate image quantification of {sup 90}Y during selective internal radionuclide therapy is affected by random coincidence estimation, scatter correction, and any positivity constraint of the algorithm. Nevertheless, phantom and patient studies showed that the impact of number of true and random coincidences on quantitative results was found to be limited as long as ordinary Poisson ordered subsets expectation maximization reconstruction algorithms with random smoothing are used. Adding PSF correction and TOF information to the reconstruction greatly improves the image quality in terms of bias, variability, noise reduction, and detectability. On the patient studies, the total activity in the field of view is in general accurately measured by Biograph mCT and slightly overestimated by the Biograph TruePoint.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-I-08: Investigation of Deconvolution Methods for Blocker-Based CBCT Scatter Estimation

Purpose: To investigate whether deconvolution methods can improve the scatter estimation under different blurring and noise conditions for blocker-based scatter correction methods for cone-beam X-ray computed tomography (CBCT). Methods: An “ideal” projection image with scatter was first simulated for blocker-based CBCT data acquisition by assuming no blurring effect and no noise. The ideal image was then convolved with long-tail point spread functions (PSF) with different widths to mimic the blurring effect from the finite focal spot and detector response. Different levels of noise were also added. Three deconvolution Methods: 1) inverse filtering; 2) Wiener; and 3) Richardson-Lucy, were used to recover the scatter signal in the blocked region. The root mean square error (RMSE) of estimated scatter serves as a quantitative measure for the performance of different methods under different blurring and noise conditions. Results: Due to the blurring effect, the scatter signal in the blocked region is contaminated by the primary signal in the unblocked region. The direct use of the signal in the blocked region to estimate scatter (“direct method”) leads to large RMSE values, which increase with the increased width of PSF and increased noise. The inverse filtering is very sensitive to noise and practically useless. The Wiener and Richardson-Lucy deconvolution methods significantly improve scatter estimation compared to the direct method. For a typical medium PSF and medium noise condition, both methods (∼20 RMSE) can achieve 4-fold improvement over the direct method (∼80 RMSE). The Wiener method deals better with large noise and Richardson-Lucy works better on wide PSF. Conclusion: We investigated several deconvolution methods to recover the scatter signal in the blocked region for blocker-based scatter correction for CBCT. Our simulation results demonstrate that Wiener and Richardson-Lucy deconvolution can significantly improve the scatter estimation compared to the direct method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

WE-D-204-06: An Open Source ImageJ CatPhan Analysis Tool

Purpose: The CatPhan is a popular QA device for assessing CT image quality. There are a number of software options which perform analysis of the CatPhan. However, there is often little ability for the user to adjust the analysis if it isn’t running properly, and these are all expensive options. An open source tool is an effective solution. Methods: To use the software, the user imports the CT as an image sequence in ImageJ. The user then scrolls to the slice with the lateral dots. The user then runs the plugin. If tolerance constraints are not already created, the user is prompted to enter them or to use generic tolerances. Upon completion of the analysis, the plugin calls pdfLaTex to compile the pdf report. There is a csv version of the report as well. A log of the results from all CatPhan scans is kept as a csv file. The user can use this to baseline the machine. Results: The tool is capable of detecting the orientation of the phantom. If the CatPhan was scanned backwards, one can simply flip the stack of images horizontally and proceed with the analysis. The analysis includes Sensitometry (estimating the effective beam energy), HU values and linearity, Low Contrast Visibility (using LDPE & Polystyrene), Contrast Scale, Geometric Accuracy, Slice Thickness Accuracy, Spatial resolution (giving the MTF using the line pairs as well as the point spread function), CNR, Low Contrast Detectability (including the raw data), Uniformity (including the Cupping Effect). Conclusion: This is a robust tool that analyzes more components of the CatPhan than other software options (with the exception of ImageOwl). It produces an elegant pdf and keeps a log of analyses for long-term tracking of the system. Because it is open source, users are able to customize any component of it.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Optimization of oncological {sup 18}F-FDG PET/CT imaging based on a multiparameter analysis

Purpose: This paper describes a method to achieve consistent clinical image quality in {sup 18}F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60–90 kg, >90 kg) allows improved image quality with both point spread function and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

MO-DE-207B-07: Assessment of Reproducibility Of FDG-PET-Based Radiomics Features Across Scanners Using Phantom Imaging

Purpose: Use a NEMA-IEC PET phantom to assess the robustness of FDG-PET-based radiomics features to changes in reconstruction parameters across different scanners. Methods: We scanned a NEMA-IEC PET phantom on 3 different scanners (GE Discovery VCT, GE Discovery 710, and Siemens mCT) using a FDG source-to-background ratio of 10:1. Images were retrospectively reconstructed using different iterations (2–3), subsets (21–24), Gaussian filter widths (2, 4, 6mm), and matrix sizes (128,192,256). The 710 and mCT used time-of-flight and point-spread-functions in reconstruction. The axial-image through the center of the 6 active spheres was used for analysis. A region-of-interest containing all spheres was able to simulate a heterogeneous lesion due to partial volume effects. Maximum voxel deviations from all retrospectively reconstructed images (18 per scanner) was compared to our standard clinical protocol. PET Images from 195 non-small cell lung cancer patients were used to compare feature variation. The ratio of a feature’s standard deviation from the patient cohort versus the phantom images was calculated to assess for feature robustness. Results: Across all images, the percentage of voxels differing by <1SUV and <2SUV ranged from 61–92% and 88–99%, respectively. Voxel-voxel similarity decreased when using higher resolution image matrices (192/256 versus 128) and was comparable across scanners. Taking the ratio of patient and phantom feature standard deviation was able to identify features that were not robust to changes in reconstruction parameters (e.g. co-occurrence correlation). Metrics found to be reasonably robust (standard deviation ratios > 3) were observed for routinely used SUV metrics (e.g. SUVmean and SUVmax) as well as some radiomics features (e.g. co-occurrence contrast, co-occurrence energy, standard deviation, and uniformity). Similar standard deviation ratios were observed across scanners. Conclusions: Our method enabled a comparison of feature variability across scanners and was able to identify features that were not robust to changes in reconstruction parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-IeP1-01: Alternative K-Edge Filters for Low-Energy Image Acquisition in Contrast Enhanced Spectral Mammography

Purpose: In Contrast Enhanced Spectral Mammography (CESM), Rh filter is often used during low-energy image acquisition. The potential for using Ag, In and Sn filters, which exhibit K-edge closer to, and just below that of Iodine, instead of the Rh filter, was investigated for the low-energy image acquisition. Methods: Analytical computations of the half-value thickness (HVT) and the photon fluence per mAs (photons/mm2/mAs) for 50µm Rh were compared with other potential K-edge filters (Ag, In and Sn), all with K-absorption edge below that of Iodine. Two strategies were investigated: fixed kVp and filter thickness (50µm for all filters) resulting in HVT variation, and fixed kVp and HVT resulting in variation in Ag, In and Sn thickness. Monte Carlo simulations (GEANT4) were conducted to determine if the scatter-to-primary ratio (SPR) and the point spread function of scatter (scatter PSF) differed between Rh and other K-edge filters. Results: Ag, In and Sn filters (50µm thick) increased photon fluence/mAs by 1.3–1.4, 1.8–2, and 1.7–2 at 28-32 kVp compared to 50µm Rh, which could decrease exposure time. Additionally, the fraction of spectra closer to and just below Iodine’s K-edge increased with these filters, which could improve post-subtraction image contrast. For HVT matched to 50µm Rh filtered spectra, the thickness range for Ag, In, and Sn were (41,44)µm, (49,55)µm and (45,53)µm, and increased photon fluence/mAs by 1.5–1.7, 1.6–2, and 1.6–2.2, respectively. Monte Carlo simulations showed that neither the SPR nor the scatter PSF of Ag, In and Sn differed from Rh, indicating no additional detriment due to x-ray scatter. Conclusion: The use of Ag, In and Sn filters for low-energy image acquisition in CESM is potentially feasible and could decrease exposure time and may improve post-subtraction image contrast. Effect of these filters on radiation dose, contrast, noise and associated metrics are being investigated. Funding Support: Supported in part by NIH R01CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or NCI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-207B-08: Towards Standardization of X-Ray Filters in Digital Mammography-Enabled Breast Tomosynthesis Systems

Purpose: In digital breast tomosynthesis (DBT) systems capable of digital mammography (DM), Al filters are used during DBT and K-edge filters during DM. The potential for standardizing the x-ray filters with Al, instead of K-edge filters, was investigated with intent to reduce exposure duration and to promote a simpler system design. Methods: Analytical computations of the half-value thickness (HVT) and the photon fluence per mAs (photons/mm2/mAs) for K-edge filters (50µm Rh; 50µm Ag) were compared with Al filters of varying thickness. Two strategies for matching the HVT from K-edge and Al filtered spectra were investigated: varying the kVp for fixed Al thickness, or varying the Al thickness at matched kVp. For both strategies, Al filters were an order of magnitude thicker than K-edge filters. Hence, Monte Carlo simulations were conducted with the GEANT4 toolkit to determine if the scatter-to-primary ratio (SPR) and the point spread function of scatter (scatter PSF) differed between Al and K-edge filters. Results: Results show the potential for replacing currently used Kedge filters with Al. For fixed Al thickness (700µm), ±1 kVp and +(1–3) kVp change, matched HVT of Rh and Ag filtered spectra. At matched kVp, Al thickness range (650,750)µm and (750,860)µm matched the HVT from Rh and Ag filtered spectra. Photon fluence/mAs with Al filters were 1.5–2.5 times higher, depending on kVp and Al thickness, compared to K-edge filters. Although Al thickness was an order higher than K-edge filters, neither the SPR nor the scatter PSF differed from K-edge filters. Conclusion: The use of Al filters for digital mammography is potentially feasible. The increased fluence/mAs with Al could decrease exposure duration for the combined DBT+DM exam and simplify system design. Effect of x-ray spectrum change due to Al filtration on radiation dose, signal, noise, contrast and related metrics are being investigated. Funding support: Supported in part by NIH R21CA176470 and R01CA195512. The contents are solely the responsibility of the authors and do not reflect the official views of the NIH or NCI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-207A-01: Computational Evaluation of High-Resolution 18F Positron Imaging Using Radioluminescence Microscopy with Lu2O3: Eu Thin-Film Scintillator

Purpose: Radioluminescence microscopy, an emerging and powerful tool for high resolution beta imaging, has been applied to molecular imaging of cellular metabolism to understand tumor biology. A novel thin-film (10 µm thickness) scintillator made of Lu{sub 2}O{sub 3}: Eu has been developed to enhance the system performance. However the advances of radioluminescence imaging with Lu{sub 2}O{sub 3}scintillator compared with that using conventional scintillator have not been explored theoretically to date. To validate the advantages of the thin-film scintillator, this study uses a novel computational simulation framework to evaluate the performance of radioluminescence microscopy using both conventional and thin-film scintillators. Methods: Numerical models for different stages of positron imaging are established. Positron from {sup 18}F passing through the scintillator and its neighbor structures are modeled by Monte-Carlo simulation using Geant4. The propagation and focus of photons by the microscope are modeled by convolution with a depth-varying point spread function generated by the Gibson-Lanni model. Photons focused on the detector plane are then captured and converted into electronic signals by an electron multiplication (EM) CCD camera, which is described by a photosensor model considering various noises and charge amplification. Results: The performance metrics of radioluminescence imaging with a thin-film Lu{sub 2}O{sub 3} and conventional CdWO{sub 4} scintillator are compared, including spatial resolution, sensitivity, positron track area and intensity. The spatial resolution of Lu{sub 2}O{sub 3} system can achieve 10 µm maximally, a 12 µm enhancement from that obtained from CdWO{sub 4} system. Meanwhile, the system with Lu{sub 2}O{sub 3} scintillator can provide a higher mean sensitivity: 40% compared with that (21.5%) obtained from CdWO{sub 4} system. Moreover, the simulation results are in good agreement with previous experimental measurements. Conclusion: This study provides a new theoretical understanding of our imaging system and has the potential to promote the development of radioluminescence microscopy for more reliable and robust application on the functional imaging of delicate biological structures. The authors acknowledge funding from NIH grant R01CA186275 and SBIR grant 1R43GM110888-01.

60 APPLIED LIFE SCIENCES↗