Digital Phantom Research Articles

Improved reconstruction stability for chemical shift encoded hyperpolarized 13 C magnetic resonance spectroscopic imaging using k-t spiral acquisitions.

A multiecho, field of view (FOV)-oversampled k-t spiral acquisition and direct iterative decomposition of water and fat with echo asymmetry and least-squares estimation reconstruction is demonstrated to improve the stability of hyperpolarized 13 C magnetic resonance spectroscopic imaging (MRSI) in the presence of signal ambiguities attributed to low-SNR (signal-to-noise-ratio) species, local uncertainties in metabolite peaks, and echo-to-echo signal inconsistencies. k-t spiral acquisitions redistribute readout points to be more densely spaced radially in k-space by acquiring an FOV and matrix that are oversampled by η. These more densely spaced spiral turns constitute effective intraspiral echoes and can supplement conventional interspiral echoes to improve spectral separation and reduce spectral cross-talk to better resolve 13 C-labeled species for spectroscopic imaging. Digital simulations and imaging phantom experiments were performed for a range of interspiral echo spacings and η using multiecho, k-t spiral acquisitions. Image spectral cross-talk artifacts were evaluated both qualitatively and quantitatively as the percent error in measured metabolite ratios. In vivo murine experiments evaluated the feasibility of multiecho, k-t spiral [1-13 C]pyruvate MRSI to reduce spectral cross-talk for 3 scenarios of different expected reconstruction stability. Digital simulations and imaging phantom experiments both demonstrated reduced or comparable image spectral cross-talk and percent errors in measured metabolite ratios with increasing η and better choices of echo spacings. In vivo images displayed markedly reduced spectral cross-talk in lactate images acquired with η = 7 versus η = 1. The precision of hyperpolarized 13 C metabolic imaging and quantification in the presence of low-SNR species, local uncertainties in metabolite resonances, and echo-to-echo signal inconsistencies can be improved with the use of FOV-oversampled k-t spiral acquisitions.

Accurate Multi-Material Decomposition in Dual-Energy CT: A Phantom Study

DUAL-energy computed tomography (DECT) differentiates materials by exploiting the varying material linear attenuation coefficients (LACs) for different x-ray energy spectra. Multi-material decomposition (MMD) is a particularly attractive DECT clinical application to distinguish the complicated material components within the human body. One prior material assisted (PMA) image domain MMD method was implemented, but has suffered from inaccurate decomposition, magnified noise, and expensive computation. To suppress the noise, we implemented a statistical MMD (SMMD) algorithm, which applied the statistical weight to account for the noise variance in the DECT images. Its decomposition accuracy heavily relies on the initial value. In this paper, we propose a novel method to overcome these challenges. Based on the piecewise constant property of CT images with energy-dependent LAC, we assume that the pixels with high similarity have the same material composition. We cluster pixel patches into groups using the block-matching technique. The material composition in each group is preselected according to the shortest Euclidean distance in the energy map between the center of mass of the similar patch groups and the LAC of the object with known material composition pre-assigned by the clinician. MMD is performed on the central pixel of each patch using the preselected material composition. In a preliminary study, the proposed method is evaluated using the digital and water phantoms. The proposed method increases the volume fraction by 25.2% and decreases the standard deviation by 66.2% compared with the PMA method and increases the volume fraction by 19.6% compared with the SMMD method. The proposed method achieves an overall improvement of the normalized cross-correlation matrix diagonality by 34.8% and 69.4% compared with the PMA and SMMD methods. The phantom results indicate that the proposed method has the potential to be applied to clinical practice due to its increased decomposition accuracy, and suppressed noise and cross contamination.

Comparison of acquisition protocols for ventilation/perfusion SPECT—a Monte Carlo study

One of the most commonly used imaging techniques for diagnosing pulmonary embolism (PE) is ventilation/perfusion (V/P) scintigraphy. The aim of this study was to evaluate the performance of the currently used imaging protocols for V/P single photon emission computed tomography (V/P SPECT) at two nuclear medicine department sites and to investigate the effect of altering important protocol parameters.The Monte Carlo technique was used to simulate 4D digital phantoms with perfusion defects. Six imaging protocols were included in the study and a total of 72 digital patients were simulated. Six dually trained radiologists/nuclear medicine physicians reviewed the images and reported all perfusion mismatch findings. The radiologists also visually graded the image quality.No statistically significant differences in diagnostic performance were found between the studied protocols, but visual grading analysis pointed out one protocol as significantly superior to four of the other protocols. Considering the study results, we have decided to harmonize our clinical protocols for imaging patients with suspected PE. The administered Technegas and macro aggregated albumin activities have been altered, a low energy all purpose collimator is used instead of a low energy high resolution collimator and the acquisition times have been lowered.

Fast and accurate quantitative determination of the lung shunt fraction in hepatic radioembolization

Radioembolization treatment is preceded by a 99mTc-MAA safety procedure, which is used to estimate the lung shunt fraction (LSF). Normally, the LSF is estimated by using the geometric mean of planar scintigraphy (PS-GM). However, concern has been raised about the potential overestimation of the LSF by PS-GM.Alternatively, SPECT/CT may be used for LSF estimation, but requires lengthy acquisitions, 3D segmentation, and has a limited field of view, which calls for extrapolation of the reconstructed lung counts, which introduces another source of error.We have developed a simplified SPECT/CT protocol for LSF estimation, called the quantitative orthogonal planar (QOP) method that requires only four projections to quantitatively reconstruct liver and lung activity. This mitigates the problems associated with LSF estimations from SPECT/CT.The purpose of this study was to introduce and evaluate QOP by comparing its performance to PS-GM and SPECT/CT in a retrospective patient study, and by supporting simulation experiments.Patients who received at least one 99mTc-MAA safety procedure in our center were included in this study. QOP and PS-GM were compared to SPECT/CT in Bland–Altman analyses.Supporting digital phantom experiments with a known ground-truth were performed to evaluate the performance of this method.Analysis of PS-GM versus SPECT/CT LSF estimates revealed both a larger imprecision and significant bias by PS-GM (limits of agreement: 8.1 percentage points (pp); bias: 2.7 pp). The QOP method agreed better with the SPECT/CT-based estimation (limits of agreement: 2.07 pp; bias: 0.52 pp). This observation was consistent with the digital phantom experiments.We have proposed and evaluated a novel method called QOP for LSF estimation that performs almost as accurate as SPECT/CT, but without the need for lung mass extrapolation, long scan duration, or extensive manual segmentation, making it as fast as current PS-GM.

Effect of ME Collimator Characteristic, Energy Window Width, and Reconstruction Algorithm Selection on Imaging Performance of Yttrium-90: Simulation Study.

The treatment efficiency of 90Y and providing reliable estimates of activity are evaluated by SPECT imaging of bremsstrahlung radiation released during beta therapy. In this technique, the resulting spectrum from 90Y is very complex and continuous, which creates difficulties on the imaging protocol. Moreover, collimator geometry has an impressive effect on the spatial resolution, system sensitivity, image contrast, and the signal-to-noise ratio (SNR), which should be optimized. We evaluated the effect of energy window width, reconstruction algorithms, and different geometries of a medium-energy (ME) parallel-hole collimator on the image contrast and SNR of 90Y SPECT images. The Siemens E.Cam gamma camera equipped with a ME collimator and a digital Jaszczak phantom were simulated by SIMIND Monte Carlo program to generate the 90Y bremsstrahlung SPECT images. Our results showed that optimal image quality can be acquired by the reconstruction algorithm of OS-EM in the energy window width of 60 to 400 keV for 90Y bremsstrahlung SPECT imaging. Furthermore, the optimal values of the hole diameter and hole length of a ME collimator were obtained 0.235 and 4.4 cm, respectively. The acquired optimal ME collimator and energy window along with using a suitable reconstruction algorithm lead to improved contrast and SNR of 90Y bremsstrahlung images of hot spheres of the digital Jaszczak phantom. This can improve the accuracy and precision of the 90Y activity distribution estimation after radioembolization in targeted radionuclide therapy.

SLICR super-voxel algorithm for fast, robust quantification of myocardial blood flow by dynamic computed tomography myocardial perfusion imaging.

We created and evaluated a processing method for dynamic computed tomography myocardial perfusion imaging (CT-MPI) of myocardial blood flow (MBF), which combines a modified simple linear iterative clustering algorithm (SLIC) with robust perfusion quantification, hence the name SLICR. SLICR adaptively segments the myocardium into nonuniform super-voxels with similar perfusion time attenuation curves (TACs). Within each super-voxel, an α-trimmed-median TAC was computed to robustly represent the super-voxel and a robust physiological model (RPM) was implemented to semi-analytically estimate MBF. SLICR processing was compared with another voxel-wise MBF preprocessing approach, which included a spatiotemporal bilateral filter (STBF) for noise reduction prior to perfusion quantification. Image data from a digital CT-MPI phantom and a porcine ischemia model were evaluated. SLICR was -fold faster than voxel-wise RPM and other model-based methods while retaining sufficient resolution to show clinically relevant features, such as a transmural perfusion gradient. SLICR showed markedly improved accuracy and precision, as compared with other methods. At a simulated MBF of 100mL/min-100g and a tube current-time product of 100mAs (50% of nominal), the MBF estimates were , , and for SLICR, the voxel-wise Johnson-Wilson model, and a singular value decomposition-model independent method with STBF, respectively. SLICR estimated MBF precisely and accurately ( ) at 25% nominal dose, while other methods resulted in larger errors. With the porcine model, the SLICR results were consistent with the induced ischemia. SLICR simultaneously accelerated and improved the quality of quantitative perfusion processing without compromising clinically relevant distributions of perfusion characteristics.

Partial-ring PET image restoration using a deep learning based method

PET scanners with partial-ring geometry have been proposed for various imaging purposes. The incomplete projection data obtained from this design cause undesirable artifacts in the reconstructed images. In this study, we investigated the performance of a deep learning (DL) based method for the recovery of partial-ring PET images. Twenty digital brain phantoms were used in the Monte Carlo simulation toolkit, SimSET, to simulate 15 min full-ring PET scans. Partial-ring PET data were generated from full-ring PET data by removing coincidence events that hit these specific detector blocks. A convolutional neural network based on the residual U-Net architecture was trained to predict full-ring data from partial-ring data in either the projection or image domain. The performance of the proposed DL-based method was evaluated by comparing with the PET images reconstructed using the full-ring projection data in terms of the mean squared error (MSE), structural similarity (SSIM) index and recovery coefficient (RC). The MSE results showed the superiority of the image-domain approach in reduction of 91.7% in contrast to 14.3% for the projection-domain approach. Therefore, the image-domain approach was used to study the influence of the number of detector block removal. The SSIM results were 0.998, 0.996 and 0.993 for 3, 5 and 7 detector block removals, respectively. The activity of gray and white matters could be fully recovered even with 7 detector block removal, while the RCs of two artificially inserted small lesions (3 pixels in diameter) in the testing data were 94%, 89% and 79% for 3, 5, and 7 detector block removals, respectively. Our simulation results suggest that DL has the potential to recover partial-ring PET images.

Algorithms and Analyses for Joint Spectral Image Reconstruction in Y-90 Bremsstrahlung SPECT

Quantitative yttrium-90 (Y-90) SPECT imaging is challenging due to the nature of Y-90, an almost pure beta emitter that is associated with a continuous spectrum of bremsstrahlung photons that have a relatively low yield. This paper proposes joint spectral reconstruction (JSR), a novel bremsstrahlung SPECT reconstruction method that uses multiple narrow acquisition windows with accurate multi-band forward modeling to cover a wide range of the energy spectrum. Theoretical analyses using Fisher information and Monte-Carlo (MC) simulation with a digital phantom show that the proposed JSR model with multiple acquisition windows has better performance in terms of covariance (precision) than previous methods using multi-band forward modeling with a single acquisition window, or using a single-band forward modeling with a single acquisition window. We also propose an energy-window subset (ES) algorithm for JSR to achieve fast empirical convergence and maximum-likelihood based initialization for all reconstruction methods to improve quantification accuracy in early iterations. For both MC simulation with a digital phantom and experimental study with a physical multi-sphere phantom, our proposed JSR-ES, a fast algorithm for JSR with ES, yielded higher recovery coefficients (RCs) on hot spheres over all iterations and sphere sizes than all the other evaluated methods, due to fast empirical convergence. In experimental study, for the smallest hot sphere (diameter 1.6cm), at the 20th iteration the increase in RCs with JSR-ES was 66 and 31% compared with single wide and narrow band forward models, respectively. JSR-ES also yielded lower residual count error (RCE) on a cold sphere over all iterations than other methods for MC simulation with known scatter, but led to greater RCE compared with single narrow band forward model at higher iterations for experimental study when using estimated scatter.

Effect of source blur on digital breast tomosynthesis reconstruction.

Most digital breast tomosynthesis (DBT) reconstruction methods neglect the blurring of the projection views caused by the finite size or motion of the x-ray focal spot. This paper studies the effect of source blur on the spatial resolution of reconstructed DBT using analytical calculation and simulation, and compares the influence of source blur over a range of blurred source sizes. Mathematically derived formulas describe the point spread function (PSF) of source blur on the detector plane as a function of the spatial locations of the finite-sized source and the object. By using the available technical parameters of some clinical DBT systems, we estimated the effective source sizes over a range of exposure time and DBT scan geometries. We used the CatSim simulation tool (GE Global Research, NY) to generate digital phantoms containing line pairs and beads at different locations and imaged with sources of four different sizes covering the range of potential source blur. By analyzing the relative contrasts of the test objects in the reconstructed images, we studied the effect of the source blur on the spatial resolution of DBT. Furthermore, we simulated a detector that rotated in synchrony with the source about the rotation center and calculated the spatial distribution of the blurring distance in the imaged volume to estimate its influence on source blur. Calculations demonstrate that the PSF is highly shift-variant, making it challenging to accurately implement during reconstruction. The results of the simulated phantoms demonstrated that a typical finite-sized focal spot (~0.3mm) will not affect the reconstructed image resolution if the x-ray tube is stationary during data acquisition. If the x-ray tube moves during exposure, the extra blur due to the source motion may degrade image resolution, depending on the effective size of the source along the direction of the motion. A detector that rotates in synchrony with the source does not reduce the influence of source blur substantially. This study demonstrates that the extra source blur due to the motion of the x-ray tube during image acquisition substantially degrades the reconstructed image resolution. This effect cannot be alleviated by rotating the detector in synchrony with the source. The simulation results suggest that there are potential benefits of modeling the source blur in image reconstruction for DBT systems using continuous-motion acquisition mode.

Image-domain multimaterial decomposition for dual-energy computed tomography with nonconvex sparsity regularization.

Dual-energy computed tomography (CT) has the potential to decompose tissues into different materials. However, the classic direct inversion (DI) method for multimaterial decomposition (MMD) cannot accurately separate more than two basis materials due to the ill-posed problem and amplified image noise. We propose an integrated MMD method that addresses the piecewise smoothness and intrinsic sparsity property of the decomposition image. The proposed MMD was formulated as an optimization problem including a quadratic data fidelity term, an isotropic total variation term that encourages image smoothness, and a nonconvex penalty function that promotes decomposition image sparseness. The mass and volume conservation rule was formulated as the probability simplex constraint. An accelerated primal-dual splitting approach with line search was applied to solve the optimization problem. The proposed method with different penalty functions was compared against DI on a digital phantom, a Catphan® 600 phantom, a quantitative imaging phantom, and a pelvis patient. The proposed framework distinctly separated the CT image up to 12 basis materials plus air with high decomposition accuracy. The cross talks between two different materials are substantially reduced, as shown by the decreased nondiagonal elements of the normalized cross correlation (NCC) matrix. The mean square error of the measured electron densities was reduced by 72.6%. Across all datasets, the proposed method improved the average volume fraction accuracy from 61.2% to 99.9% and increased the diagonality of the NCC matrix from 0.73 to 0.96. Compared with DI, the proposed MMD framework improved decomposition accuracy and material separation.

Two-Point Frequency Shift Method for Shear Wave Attenuation Measurement.

Ultrasound shear wave elastography (SWE) is an increasingly used noninvasive modality for quantitative evaluation of tissue mechanical properties. SWE typically uses an acoustic radiation force to produce laterally propagating shear waves that are tracked in the spatial and temporal domains, in order to obtain the wave velocity. One of the ways to study the viscoelasticity is through studying the shear wave phase velocity dispersion curves. Shear wave attenuation can be also characterized in viscoelastic tissues with methods that use multiple lateral data samples. In this article, we present an alternative method for measuring the shear wave attenuation without using a rheological model two-point frequency shift (2P-FS). The technique uses information related to the amplitude spectra FS of shear waves measured at only two lateral locations. The theoretical basis for the 2P-FS is derived and validated. We examined how the first signal position and the distance between the two locations affect the shear wave attenuation estimation in the 2P-FS method. We tested this new method on digital phantom data created using the local interaction simulation approach (LISA) in viscoelastic media. Moreover, we tested data acquired from custom-made tissue-mimicking viscoelastic phantom experiments and ex vivo porcine liver measurements. We compared results from the 2P-FS method with the other two techniques used for assessing a shear wave attenuation: the FS-based method and the attenuation-measuring ultrasound shear wave elastography (AMUSE) technique. In addition, we evaluated the 2P-FS algorithm with different levels of added white Gaussian noise to the shear wave particle velocity using numerical phantoms. Tests conducted showed that the 2P-FS method gives robust results based on only two measurements and can be used to measure attenuation of viscoelastic soft tissues.

Improving the modelling of susceptibility-induced spatial distortions in MRI-guided extra-cranial radiotherapy

Magnetic-resonance linear-accelerator (MR-LINAC) systems integrating in-room magnetic-resonance-imaging (MRI) guidance are a currently emerging technology. Such systems address the need to provide frequent imaging at optimal soft-tissue contrast for treatment guidance. However, the use of MRI-guidance in radiotherapy should address imaging-related spatial distortions, which may hinder accurate geometrical characterization of the treatment site. Since spatial encoding relies on well-defined magnetic fields, accurate modeling of the magnetic field alterations due to -inhomogeneities, gradient nonlinearities, and susceptibilities is needed. In this work, the modeling of susceptibility induced distortions is considered. Dedicated susceptibility measurements are reported, aiming at extending the characterization of different tissues for MRI-guided extra-cranial radiotherapy applications. A digital 4D anthropomorphic phantom, providing time-resolved anatomical changes due to breathing, is exploited as reference anatomy to quantify spatial distortions due to variations in tissue susceptibility. Sub-millimeter values can be attributed to susceptibility-induced distortions, with maximum values up to 2.3 mm at a gradient strength of 5 mT m−1. Improvements in susceptibility simulation for extra-cranial sites are shown when including specifically the contributions from lung, liver and muscular tissues.

Shear wave attenuation measurement of tissue-mimicking materials using a two-point frequency shift method

Shear wave elastography (SWE) is a method used in several clinical applications for assessment of soft tissue viscoelastic properties. SWE uses an acoustic radiation force (ARF) to produce laterally propagating shear waves to obtain the wave velocity. Here, we present a two-point shear wave attenuation coefficient measurement method without using a rheological model. The technique uses information related to the magnitude spectrum frequency shift of shear waves measured at only two lateral locations. We examined how the distance from the start of the ARF push and the distance between the two locations affected the attenuation coefficient estimates. We tested this method on digital phantom data created using local interaction simulation approach in viscoelastic media and on data acquired from phantom and ex vivo liver experiments. We compared the results from the two-point method with other two techniques used for assessing shear wave attenuation: the frequency-shift-based (FS) method and attenuation measuring ultrasound shearwave elastography. In comparison with the FS method, our technique does not assume that the shape parameter of the Gamma function is constant over a lateral distance. Tests conducted showed that the proposed method is feasible to provide robust attenuation estimates based on two measurement points in tissue-mimicking materials and ex vivo liver tissue.Shear wave elastography (SWE) is a method used in several clinical applications for assessment of soft tissue viscoelastic properties. SWE uses an acoustic radiation force (ARF) to produce laterally propagating shear waves to obtain the wave velocity. Here, we present a two-point shear wave attenuation coefficient measurement method without using a rheological model. The technique uses information related to the magnitude spectrum frequency shift of shear waves measured at only two lateral locations. We examined how the distance from the start of the ARF push and the distance between the two locations affected the attenuation coefficient estimates. We tested this method on digital phantom data created using local interaction simulation approach in viscoelastic media and on data acquired from phantom and ex vivo liver experiments. We compared the results from the two-point method with other two techniques used for assessing shear wave attenuation: the frequency-shift-based (FS) method and attenuation measu...

EFFECTS OF IMAGE PROCESSING UPON RADIOGRAPHIC IMAGE QUALITY

<h3>Background</h3> There is evidence that capture and processing of the digital radiographic images may contain artifacts that could reduce the diagnostic value of dental radiographs. This phenomenon has been reported through various case reports. However, its effect on radiographic image quality has not been studied. <h3>Objective(s)</h3> The purpose of this study was to evaluate the effect of image processing on the quality of dental digital radiographs using the most common type of filter—sharpening. <h3>Study Design</h3> Three imaging modalities (2 complementary metal-oxide-semiconductor [CMOS], 1 photostimulable phosphor [PSP]) were used to image a DDQA imaging phantom (Digital Dental Quality Assurance phantom) and to create a flatfield radiograph. Contrast resolution, spatial resolution, dynamic range, and radiographic noise were assessed for image quality. Overshoot artifact was also assessed. Each image was sharpened and then highly sharpened. Images were compared using Friedman's 2-way nonparametric analysis of variance (ANOVA). <h3>Results</h3> Image sharpening significantly affected spatial resolution and noise. Conversely, dynamic range and contrast resolution were not significantly affected by image sharpening. Overshoot artifact increased with image sharpening. <h3>Discussion/Conclusions</h3> Image sharpening can create artifacts that could be misinterpreted. Although image sharpening significantly affects spatial resolution, no significant effect was seen on dynamic range or contrast resolution.

Statistical properties of cerebral CT perfusion imaging systems. Part II. Deconvolution-based systems.

The purpose of this work was to develop a theoretical framework to pinpoint the quantitative relationship between input parameters of deconvolution-based cerebral computed tomography perfusion (CTP) imaging systems and statistical properties of the output perfusion maps. Deconvolution-based CTP systems assume that the arterial input function, tissue enhancement curve, and flow-scaled residue function k(t) are related to each other through a convolution model, and thus by reversing the convolution operation, k(t) and the associated perfusion parameters can be estimated. The theoretical analysis started by deriving analytical formulas for the expected value and autocovariance of the residue function estimated using the singular value decomposition-based deconvolution method. Next, it analyzed statistical properties of the "max" and "arg max" operators, based on which the signal and noise properties of cerebral blood flow (CBF) and time-to-max ( ) are quantitatively related to the statistical model of the estimated residue function [ ] and system parameters. To validate the theory, CTP images of a digital head phantom were simulated, from which signal and noise of each perfusion parameter were measured and compared with values calculated using the theoretical model. In addition, an in vivo canine experiment was performed to validate the noise model of cerebral blood volume (CBV). For the numerical study, the relative root mean squared error between the measured and theoretically calculated value is ≤0.21% for the autocovariance matrix of , and is ≤0.13% for the expected form of . A Bland-Altman analysis demonstrated no significant difference between measured and theoretical values for the mean or noise of each perfusion parameter. For the animal study, the theoretical CBV noise fell within the 25th and 75th percentiles of the experimental values. To provide an example of the theory's utility, an expansion of the CBV noise formula was performed to unveil the dominant role of the baseline image noise in deconvolution-based CBV. Correspondingly, data of the three canine subjects used in the Part I paper were retrospectively processed to confirm that preferentially partitioning dose to the baseline frames benefits both nondeconvolution- and deconvolution-based CBV maps. Quantitative relationships between the statistical properties of deconvolution-based CTP maps, source image acquisition and reconstruction parameters, contrast injection protocol, and deconvolution parameters are established.

Compton imaging with 99mTc for human imaging

We have been developing a medical imaging system using a Compton camera and demonstrated the imaging ability of Compton camera for 99mTc-DMSA accumulated in rat kidneys. In this study, we performed imaging experiments using a human body phantom to confirm its applicability to human imaging. Preliminary simulations were conducted using a digital phantom with varying activity ratios between the kidney and body trunk regions. Gamma rays (141 keV) were generated and detected by a Compton camera based on a silicon and cadmium telluride (Si/CdTe) detector. Compton images were reconstructed with the list mode median root prior expectation maximization method. The appropriate number of iterations of the condition was confirmed through simulations. The reconstructed Compton images revealed two bright points in the kidney regions. Furthermore, the numerical value calculated by integrating pixel values inside the region of interest correlated well with the activity of the kidney regions. Finally, experimental studies were conducted to ascertain whether the results of the simulation studies could be reproduced. The kidneys could be successfully visualised. In conclusion, considering that the conditions in this study agree with those of typical human bodies and imaginable experimental setup, the Si/CdTe Compton camera has a high probability of success in human imaging. In addition, our results indicate the capability of (semi-) quantitative analysis using Compton images.

Development of a 4D Digital Phantom for Cone-Beam CT (CBCT) Imaging on the Varian On-Board Imager (OBI)

Mitigating effects of respiratory motion during image guided radiotherapy (IGRT) is important especially during thoracic and abdomen scanning protocols such as cone-beam CT (CBCT) imaging. However, the lack of ‘ground-truth’ in validating new algorithms has always been a challenge. The objective of this study is to outline the development of a novel 4D digital phantom for simulation of respiratory motion effects during CBCT image reconstruction based on Varian On-Board Imager (OBI): Half-Fan (HF) operating mode geometry. A set of actual 4D Magnetic Resonance (MR) data was used to develop the digital phantom. Firstly, the MR data sequencewasextendedto mimic a standard CBCT imaging acquisition protocol. Then, the images were segmented into several organs of interest and assigned with respective CT attenuation values. Subsequently, 2D projections of the developed digital phantom were simulated using the Varian OBI geometry. A Poisson noise model was also incorporated to the projection data to realistically simulate quantum noise that is present in an actual clinical environment. Three types of projections were then reconstructed using the standard 3D Feldkamp-Davis-Kress (FDK) algorithm, projections: without noise, with noise, and with noise and reconstructed with an additional Hann filter. As validation, the reconstructed images were compared against a single-frame of the developed phantom; quantitatively, using normalized root mean squared error (NRMSE) and qualitatively, using difference images. The results indicated that the phantom managed to display a consistent trend in modeling the effects of respiratory motion on the reconstructed images. On average, the NRMSE values for all three reconstructed images within the entire field-of-view (FOV) were evaluated to be approximately 29.07±0.22%. Nonetheless, the difference images indicated a large error in areas largely affected by respiratory motion. The NRMSE of a region-of-interest (ROI) near the affected area was evaluated as 51.26% that constitute to a significant +22.19% difference.

Time-resolved volumetric MRI in MRI-guided radiotherapy: an in silico comparative analysis

MRI-treatment units enable 2D cine-MRI centred in the tumour for motion detection in radiotherapy, but they lack 3D information due to spatio-temporal limits. To derive time-resolved 3D information, different approaches have been proposed in the literature, but a rigorous comparison among these strategies has not yet been performed. The goal of this study is to quantitatively investigate five published strategies that derive time-resolved volumetric MRI in MRI-guided radiotherapy: Propagation, out-of-plane motion compensation, Fayad model, ROI-based model and Stemkens model. Comparisons were performed using an MRI digital phantom generated with six different patient-derived motion signals and tumour-shapes. An average 4D cycle was generated as well as 2D cine-MRI data with corresponding 3D in-room ground truth. Quantitative analysis was performed by comparing the estimated 3D volume to the ground truth available for each 2D cine-MRI sample. A grouped patient statistical analysis was performed to evaluate the performance of the selected methods, in case of tumour tracking or motion estimation of the whole anatomy. Analyses were also performed based on patient characteristics. Quantitative ranking of the investigated methods highlighted that Propagation and ROI-based model strategies achieved an overall median tumour centre of mass 3D distance from the ground truth of 1.1 mm and 1.3 mm, respectively, and a diaphragm distance below 1.6 mm. Higher errors and variabilities were instead obtained for other methods, which lack the ability to compensate for in-room variations and to account for regional changes. These results were especially evident when further analysing patient characteristics, where errors above 2 mm/5 mm in tumour/diaphragm were found for more irregular breathing patterns in case of out-of-plane motion compensation, Fayad and Stemkens models. These findings suggest the potential of the proposed in silico framework to develop and compare strategies to estimate time-resolved 3DMRI in MRI-guided radiotherapy.

Motion robust respiratory-resolved 3D radial flow MRI and its application in neonatal congenital heart disease.

To test and implement a motion-robust and respiratory-resolved 3D Radial Flow framework that addresses the need for rapid, high resolution imaging in neonatal patients with congenital heart disease. A 4-point velocity encoding and 3D radial trajectory with double-golden angle ordering was combined with bulk motion correction (from projection center of mass) and respiration phase detection (from principal component analysis of heartbeat-averaged data) to create motion-robust 3D velocity cardiac time-averaged data. This framework was tested in a whole-chest digital phantom with simulated bulk and realistic physiological motion. In vivo imaging was performed in 20 congenital heart disease infants under feed-and-sleep with submillimeter isotropic resolution in ~3 min. Flows were validated against clinical 2D PCMRI and whole-heart visualizations of blood flow were performed. The proposed framework resolved all simulated digital phantom motion states (mean ± standard error: rotation - azimuthal = 0.29 ± 0.02°; translation - Ty = 1.29 ± 0.12 mm, Tz = -0.27 ± 0.13 mm; rotation+translation - polar = 0.49 ± 0.16°, Tx = -2.47 ± 0.51 mm, Tz = 5.78 ± 1.33 mm). Measured timing errors of peak expiration across all signal-to-noise ratio values were 22% of the true respiratory period (range = [404-489 ± 298-334] ms). For in vivo imaging, motion correction improved 3D Radial Flow measurements (no correction: R2 = 0.62, root mean square error = 0.80 L/min/m2 , Bland-Altman bias [limits of agreement] = -0.21 [-1.40, 0.94] L/min/m2 ; motion corrected, expiration: R2 = 0.90, root mean square error = 0.46 L/min/m2 , bias [limits of agreement] = 0.06 [-0.49, 0.62] L/min/m2 ). Respiratory-resolved 3D velocity visualizations were achieved in various neonatal pathologies pre- and postsurgical correction. 3D cardiac flow may be visualized and accurately quantified in neonatal subjects using the proposed framework. This technique may enable more comprehensive hemodynamic studies in small infants.

Jitter correction for transmission X-ray microscopy via measurement of geometric moments

Transmission X-ray microscopes (TXMs) have become one of the most powerful tools for imaging 3D structures of nano-scale samples using the computed tomography (CT) principle. As a major error source, sample jitter caused by mechanical instability of the rotation stage produces shifted 2D projections, from which reconstructed images contain severe motion artifacts. In this paper, a jitter correction algorithm is proposed, that has high accuracy and computational efficiency for TXM experiments with or without nano-particle markers. Geometric moments (GMs) are measured on segmented projections for each angle and fitted to sinusoidal curves in the angular direction. Sample jitter is estimated from the difference between the measured and the fitted GMs for image correction. On a digital phantom, the proposed method removes jitter errors at different noise levels. Physical experiments on chlorella cells show that the proposed GM method achieves better spatial resolution and higher computational efficiency than the re-projection method, a state-of-the-art algorithm using iterative correction. It even outperforms the approach of manual alignment, the current gold standard, on faithfully maintaining fine structures on the CT images. Our method is practically attractive in that it is computationally efficient and lowers experimental costs in current TXM studies without using expensive nano-particles markers.