Bridging the gap between micro- and macro-scales in medical imaging with textural analysis - A biological basis for CT radiomics classifiers?

INTRODUCTION: Studies suggest there is utility in computed tomography (CT) radiomics for pancreatic disease; however, the precise biological interpretation of its features is unclear. In this manuscript, we present a novel approach towards this interpretation by investigating sub-micron tissue structure using digital pathology. METHODS: A classification-to attenuation (CAT) function was developed and applied to digital pathology images to create sub-micron linear attenuation maps. From these maps, grey level co-occurrence matrix (GLCM) features were extracted and compared to pathology features. To simulate the spatial frequency loss in a CT scanner, the attenuation maps were convolved with a point spread function (PSF) and subsequently down-sampled. GLCM features were extracted from these down-sampled maps to assess feature stability as a function of spatial frequency loss. RESULTS: Two GLCM features were shown to be strongly and positively correlated (r = 0.8) with underlying characteristics of the tumor microenvironment, namely percent pimonidazole staining in the tumor. All features underwent marked change as a function of spatial frequency loss; progressively larger spatial frequency losses resulted in progressively larger inter-tumor standard deviations; two GLCM features exhibited stability up to a 100 µm pixel size. CONCLUSION: This work represents a necessary step towards understanding the biological significance of radiomics. Our preliminary results suggest that cellular metrics of pimonidazole-detectable hypoxia correlate with sub-micron attenuation coefficient texture; however, the consistency of these textures in face of spatial frequency loss is detrimental for robust radiomics. Further study in larger data sets may elucidate additional, potentially more robust features of biologic and clinical relevance.

Monte Carlo kilovoltage X-ray tube simulation: A statistical analysis and compact simulation method.

INTRODUCTION: Monte Carlo (MC) simulations are a powerful tool for improving image quality in X-ray based imaging modalities. An accurate X-ray source model is essential to MC modeling for CBCT but can be difficult to implement on a GPU while maintaining efficiency and memory limitations. A statistical analysis of the photon distribution from a MC X-ray tube simulation is conducted in hopes of building a compact source model. MATERIALS & METHODS: MC simulations of an X-ray tube were carried out using BEAMnrc. The resulting photons were sorted into four categories: primary, scatter, off-focal radiation (OFR), and both (scatter and OFR). A statistical analysis of the photon components (energy, position, direction) was completed. A novel method for a compact (memory efficient) representation of the PHSP data was implemented and tested using different statistical based linear transformations (PCA, ZCA, ICA), as well as a geometrical transformation. RESULTS: The statistical analysis showed all photon groupings had strong correlations between position and direction, with the largest correlation in the primary data. The novel method was successful in compactly representing the primary (error < 2%) and scatter (error < 6%) photon groupings by reducing the component correlations. DISCUSSION & CONCLUSION: Statistical linear transforms provide a method of reducing the memory required to accurately simulate an X-ray source in a GPU MC system. If all photon types are required, the proposed method reduces the memory requirements by 3.8 times. When only primary and scatter data is needed, the memory requirement is reduced from gigabytes to kilobytes.

Intraoperative cone-beam CT spatial priors for diffuse optical fluorescence tomography.

A hybrid system for intraoperative cone-beam CT (CBCT) imaging and continuous-wave fluorescence tomography (FT) has been developed using an image-guidance framework. Intraoperative CBCT images with sub-millimeter spatial resolution are acquired with a flat-panel C-Arm. Tetrahedral meshes are generated from CBCT for finite element method implementation of diffuse optical tomography (NIRFAST). Structural data from CBCT is incorporated directly into the optical reconstruction process using Laplacian-type regularization ('soft spatial priors'). Experiments were performed using an in-house optical system designed for indocyanine green (ICG) fluorescence. A dynamic non-contact geometry was achieved using a stereoscopic optical tracker for real-time localization of a laser diode and CCD camera. Source and detector positions were projected onto the boundary elements of the tissue mesh using algorithms for ray-triangle intersection and camera lens calibration. Simulation studies showed the capabilities of a soft-prior approach, even in the presence of segmentation uncertainties. Experiments with ICG targets embedded in liquid phantoms determined the improvements in the quantification of the fluorophore yield, with errors of 85% and <20% for no priors and spatial priors, respectively. Similar results were observed with the ICG target embedded in ex vivo porcine loin, with errors of 52% and 12%, respectively. A proof-of-principal animal study was performed in a VX2-tumor in vivo rabbit model using liposomal nanoparticles co-encapsulating contrast for CT (iohexol) and fluorescence (ICG) imaging. Fusion of CBCT and FT reconstructions demonstrated concurrent anatomical and functional delineations of contrast enhancement around the periphery of the buccal tumor. These developments motivate future clinical translation of the FT system into an ongoing CBCT-guided head and neck surgery trial.

Navigated non-contact fluorescence tomography.

A non-contact approach for diffuse optical tomography (DOT) has been developed for on-demand image updates using surgical navigation technology. A stereoscopic optical tracker provides real-time localization of reflective spheres mounted to a laser diode and near-infrared camera. Standard camera calibration is combined with tracking data to determine the intrinsic camera parameters (focal length, principal point and non-linear lens distortion) and the tracker-to-camera transform. Tracker-to-laser calibration is performed using images of laser beam intersection with a tracked calibration surface. Source and detector positions for a finite-element DOT implementation are projected onto the boundary elements of the tissue mesh by finding ray-triangle intersections. A multi-stage model converts camera counts to surface flux by accounting for lens aperture settings, fluorescence filter transmittance, photodetector quantum efficiency, photon energy, exposure time, readout offset and camera gain. The image-guidance framework was applied to an in-house optical tomography system configured for indocyanine green (ICG) fluorescence. Mean target registration errors for camera and laser calibration were less than 1 mm. Surface flux measurements of total reflectance and fluorescence in Intralipid-based fluorescence phantoms (0-2 µg ml-1) had mean errors of 3.1% and 4.4%, respectively, relative to diffusion theory predictions. Spatially-resolved reflectance measurements in a calibrated optical phantom agreed with theory for radial distances up to 25 mm from the laser source. Inverse fluorescence reconstructions of a sub-surface fluorescence target confirmed the localization accuracy (average target centroid error of 0.44 mm). This translational research system is under investigation for clinical applications in head and neck surgery, including oral cavity tumor resection, lymph node mapping and free-flap perforator assessment.

Quantification accuracy for dynamic contrast enhanced (DCE) CT imaging: phantom and quality assurance framework.

PURPOSE: Standardization and protocol optimization is essential for quantification of Dynamic Contrast Enhanced CT as an imaging biomarker. Currently, no commercially available quality assurance (QA) phantoms can provide for testing a complete set of imaging parameters pertaining to routine quality control for contrast-enhanced (CE) CT, as well as spatiotemporal accuracy. The purpose of this work was, therefore: (a) developing a solid calibration phantom for routine CE CT quality assurance; (b) investigating the sensitivity of CECT to organ motion, and (c) characterizing a volumetric CT scanner for CECT. METHODS: CECT calibration phantom consisting of an acrylic uniform cylinder containing multiple capsules of varying diameters and orientations was designed and built. The capsules contain different solid density materials mimicking iodine contrast enhancement. Sensitivity and accuracy of CECT measurements on all capsules was performed using a 320-slice CT scanner for a range of scan parameters both with and without phantom motion along the transaxial axis of the scanner. RESULTS: Routine commissioning tests such as uniformity, spatial resolution and image noise were successfully determined using the CECT phantom. Partial volume effect and motion blurring both contribute to a general decrease in contrast enhancement and this was further dependent on capsule orientation (least pronounced for the transaxial orientation). Scanning with a rotation time of less than 0.5 s, the effect of blurring is less than 3% for all orientations and phantom speeds. CONCLUSION: A new robust contrast calibration phantom was developed and used to evaluate the performance of a 320-slice volumetric CT scanner for DCE-CT.

Technical Note: Harmonic analysis applied to MR image distortion fields specific to arbitrarily shaped volumes.

PURPOSE: Magnetic resonance imaging is expected to play a more important role in radiation therapy given the recent developments in MR-guided technologies. MR images need to consistently show high spatial accuracy to facilitate RT-specific tasks such as treatment planning and in-room guidance. The present study investigates a new harmonic analysis method for the characterization of complex three-dimensional (3D) fields derived from MR images affected by system-related distortions. METHODS: An interior Dirichlet problem based on solving the Laplace equation with boundary conditions (BCs) was formulated for the case of a 3D distortion field. The second-order boundary value problem (BVP) was solved using a finite elements method (FEM) for several quadratic geometries - that is, sphere, cylinder, cuboid, D-shaped, and ellipsoid. To stress-test the method and generalize it, the BVP was also solved for more complex surfaces such as a Reuleaux 9-gon and the MR imaging volume of a scanner featuring a high degree of surface irregularities. The BCs were formatted from reference experimental data collected with a linearity phantom featuring a volumetric grid structure. The method was validated by comparing the harmonic analysis results with the corresponding experimental reference fields. RESULTS: The harmonic fields were found to be in good agreement with the baseline experimental data for all geometries investigated. In the case of quadratic domains, the percentage of sampling points with residual values larger than 1 mm was 0.5% and 0.2% for the axial components and vector magnitude, respectively. For the general case of a domain defined by the available MR imaging field of view, the reference data showed a peak distortion of about 1 mm and 79% of the sampling points carried a distortion magnitude larger than 1 mm (tolerance intrinsic to the experimental data). The upper limits of the residual values after comparison with the harmonic fields showed max and mean of 1.4 and 0.25 mm, respectively, with only 1.5% of sampling points exceeding 1 mm. CONCLUSIONS: A novel harmonic analysis approach relying on finite element methods was introduced and validated for multiple volumes with surface shape functions ranging from simple to highly complex. Since a boundary value problem is solved the method requires input data from only the surface of the desired domain of interest. It is believed that the harmonic method will facilitate (a) the design of new phantoms dedicated for the quantitation of MR image distortions in large volumes and (b) an integrative approach of combining multiple imaging tests specific to radiotherapy into a single test object for routine imaging quality control.

Design and implementation of a 3D-MR/CT geometric image distortion phantom/analysis system for stereotactic radiosurgery.

The design, construction and application of a multimodality, 3D magnetic resonance/computed tomography (MR/CT) image distortion phantom and analysis system for stereotactic radiosurgery (SRS) is presented. The phantom is characterized by (1) a 1 × 1 × 1 (cm)3 MRI/CT-visible 3D-Cartesian grid; (2) 2002 grid vertices that are 3D-intersections of MR-/CT-visible 'lines' in all three orthogonal planes; (3) a 3D-grid that is MR-signal positive/CT-signal negative; (4) a vertex distribution sufficiently 'dense' to characterize geometrical parameters properly, and (5) a grid/vertex resolution consistent with SRS localization accuracy. When positioned correctly, successive 3D-vertex planes along any orthogonal axis of the phantom appear as 1 × 1 (cm)2-2D grids, whereas between vertex planes, images are defined by 1 × 1 (cm)2-2D arrays of signal points. Image distortion is evaluated using a centroid algorithm that automatically identifies the center of each 3D-intersection and then calculates the deviations dx, dy, dz and dr for each vertex point; the results are presented as a color-coded 2D or 3D distribution of deviations. The phantom components and 3D-grid are machined to sub-millimeter accuracy, making the device uniquely suited to SRS applications; as such, we present it here in a form adapted for use with a Leksell stereotactic frame. Imaging reproducibility was assessed via repeated phantom imaging across ten back-to-back scans; 80%-90% of the differences in vertex deviations dx, dy, dz and dr between successive 3 T MRI scans were found to be ⩽0.05 mm for both axial and coronal acquisitions, and over >95% of the differences were observed to be ⩽0.05 mm for repeated CT scans, clearly demonstrating excellent reproducibility. Applications of the 3D-phantom/analysis system are presented, using a 32-month time-course assessment of image distortion/gradient stability and statistical control chart for 1.5 T and 3 T GE TwinSpeed MRI systems.

Strategic planning in an academic radiation medicine program.

BACKGROUND: In this paper, we report on the process of strategic planning in the Radiation Medicine Program (rmp) at the Princess Margaret Cancer Centre. The rmp conducted a strategic planning exercise to ensure that program priorities reflect the current health care environment, enable nimble responses to the increasing burden of cancer, and guide program operations until 2020. METHODS: Data collection was guided by a project charter that outlined the project goal and the roles and responsibilities of all participants. The process was managed by a multidisciplinary steering committee under the guidance of an external consultant and consisted of reviewing strategic planning documents from close collaborators and institutional partners, conducting interviews with key stakeholders, deploying a program-wide survey, facilitating an anonymous and confidential e-mail feedback box, and collecting information from group deliberations. RESULTS: The process of strategic planning took place from December 2014 to December 2015. Mission and vision statements were developed, and core values were defined. A final document, Strategic Roadmap to 2020, was established to guide programmatic pursuits during the ensuing 5 years, and an implementation plan was developed to guide the first year of operations. CONCLUSIONS: The strategic planning process provided an opportunity to mobilize staff talents and identify environmental opportunities, and helped to enable more effective use of resources in a rapidly changing health care environment. The process was valuable in allowing staff to consider and discuss the future, and in identifying strategic issues of the greatest importance to the program. Academic programs with similar mandates might find our report useful in guiding similar processes in their own organizations.

Modeling Current Density Maps Using Aliev-Panfilov Electrophysiological Heart Model.

Most existing studies of cardiac arrhythmia rely on surface measurements through optical or electrical mapping techniques. Current density imaging (CDI) is a method which enables us to study current pathways inside the tissue. However, this method entails implementation complexities for beating ex vivo hearts. Hence, this work presents an approach to simulate and study the current distributions in different cardiac electrophysiological states. The results are corroborated by experimental data, and they indicate that different states were distinguishable. The CDI simulations can be used for studying cardiac arrhythmias under simulation conditions which are otherwise impossible or difficult to be implemented experimentally.

Investigation of the 4D composite MR image distortion field associated with tumor motion for MR-guided radiotherapy.

PURPOSE: Magnetic resonance (MR) images are affected by geometric distortions due to the specifics of the MR scanner and patient anatomy. Quantifying the distortions associated with mobile tumors is particularly challenging due to real anatomical changes in the tumor's volume, shape, and relative location within the MR imaging volume. In this study, the authors investigate the 4D composite distortion field, which combines the effects of the susceptibility-induced and system-related distortion fields, experienced by mobile lung tumors. METHODS: The susceptibility (χ) effects were numerically simulated for two specific scenarios: (a) a full motion cycle of a lung tumor due to breathing as depicted on ten phases of a 4D CBCT data set and (b) varying the tumor size and location in lung tissue via a synthetically generated sphere with variable diameter (4-80 mm). The χ simulation procedure relied on the segmentation and generation of 3D susceptibility (χ) masks and computation of the magnetic field by means of finite difference methods. A system-related distortion field, determined with a phantom and image processing algorithm, was used as a reference. The 4D composite distortion field was generated as the vector summation of the χ-induced and system-related fields. The analysis was performed for two orientations of the main magnetic field (B0), which correspond to several MRIgRT system configurations. Specifically, B0 was set along the z-axis as in the case of a cylindrical-bore scanner and in the (x,y)-plane as for a biplanar MR. Computations were also performed for a full revolution at 15° increments in the case of a rotating biplanar magnet. Histograms and metrics such as maximum, mean, and range were used to evaluate the characteristics of the 4D distortion field. RESULTS: The χ-induced field depends on the change in volume and shape of the moving tumor as well as the local surrounding anatomy. In the case of system-related distortions, the tumor experiences increased field perturbations as it moves further away from the MR isocenter. For a mobile lung tumor, the 4D composite field, corresponding to a 1.5 T field and a readout gradient of 5 mT/m, amounts to 3.0 and 2.8 mm for the MRIgRT system designs featuring B0 oriented along the z-axis (cylindrical-bore scanner) and in the (x,y)-plane (biplanar scanner), respectively. For a rotating biplanar scanner, the composite distortion field varied nonlinearly with the rotation angle. Overall, the dominant contribution to the composite field was from the system-related distortion field. The tumor centroid experienced a systematic shift of 2 mm and showed a negligible perturbation for different B0 values. The dependency on the tumor size was also investigated, namely the max values varied from 1.2 to 2.5 mm for spherical volumes with a diameter between 4 and 80 mm. CONCLUSIONS: The composite distortion field requires adequate quantification for lung radiation therapy applications such as treatment planning, pretreatment patient setup verification, and real-time treatment delivery guidance. For certain scenarios such as small tumor volumes, the spatial distortions may be corrected by applying systematic shifts derived from a single tumor motion phase. In the case of high readout gradients common to fast imaging applications, the χ distortions were found to be less than 1 mm irrespective of scanner configuration.

Early mobilisation of thoracolumbar burst fractures without neurology: a natural history observation.

AIMS: The authors present the results of a cohort study of 60 adult patients presenting sequentially over a period of 15 years from 1997 to 2012 to our hospital for treatment of thoracic and/or lumbar vertebral burst fractures, but without neurological deficit. METHOD: All patients were treated by early mobilisation within the limits of pain, early bracing for patient confidence and all progress in mobilisation was recorded on video. Initial hospital stay was one week. Subsequent reviews were made on an outpatient basis. RESULTS: The mean duration from admission to final follow-up was three months, and longer follow-up was undertaken telephonically. The mean kyphosis deformity on arrival was 17.4° (5° to 29°); mean kyphosis at final discharge three months later was 19.5° (1° to 28°). Spinal canal encroachment had no influence on successful functional recovery. DISCUSSION: Pain has not been a significant problem for any patient, irrespective of the degree of kyphosis and no patient has a self-perception of clinical deformity. In all, 11 patients took occasional analgesia. All patients returned to their original work level or better. Two patients died 2.5 years after treatment, from unrelated causes. TAKE HOME MESSAGE: The natural history of thoracolumbar burst fractures without neurology would appear to be benign.

Efficient scatter distribution estimation and correction in CBCT using concurrent Monte Carlo fitting.

PURPOSE: X-ray scatter is a significant impediment to image quality improvements in cone-beam CT (CBCT). The authors present and demonstrate a novel scatter correction algorithm using a scatter estimation method that simultaneously combines multiple Monte Carlo (MC) CBCT simulations through the use of a concurrently evaluated fitting function, referred to as concurrent MC fitting (CMCF). METHODS: The CMCF method uses concurrently run MC CBCT scatter projection simulations that are a subset of the projection angles used in the projection set, P, to be corrected. The scattered photons reaching the detector in each MC simulation are simultaneously aggregated by an algorithm which computes the scatter detector response, SMC. SMC is fit to a function, SF, and if the fit of SF is within a specified goodness of fit (GOF), the simulations are terminated. The fit, SF, is then used to interpolate the scatter distribution over all pixel locations for every projection angle in the set P. The CMCF algorithm was tested using a frequency limited sum of sines and cosines as the fitting function on both simulated and measured data. The simulated data consisted of an anthropomorphic head and a pelvis phantom created from CT data, simulated with and without the use of a compensator. The measured data were a pelvis scan of a phantom and patient taken on an Elekta Synergy platform. The simulated data were used to evaluate various GOF metrics as well as determine a suitable fitness value. The simulated data were also used to quantitatively evaluate the image quality improvements provided by the CMCF method. A qualitative analysis was performed on the measured data by comparing the CMCF scatter corrected reconstruction to the original uncorrected and corrected by a constant scatter correction reconstruction, as well as a reconstruction created using a set of projections taken with a small cone angle. RESULTS: Pearson's correlation, r, proved to be a suitable GOF metric with strong correlation with the actual error of the scatter fit, SF. Fitting the scatter distribution to a limited sum of sine and cosine functions using a low-pass filtered fast Fourier transform provided a computationally efficient and accurate fit. The CMCF algorithm reduces the number of photon histories required by over four orders of magnitude. The simulated experiments showed that using a compensator reduced the computational time by a factor between 1.5 and 1.75. The scatter estimates for the simulated and measured data were computed between 35-93 s and 114-122 s, respectively, using 16 Intel Xeon cores (3.0 GHz). The CMCF scatter correction improved the contrast-to-noise ratio by 10%-50% and reduced the reconstruction error to under 3% for the simulated phantoms. CONCLUSIONS: The novel CMCF algorithm significantly reduces the computation time required to estimate the scatter distribution by reducing the statistical noise in the MC scatter estimate and limiting the number of projection angles that must be simulated. Using the scatter estimate provided by the CMCF algorithm to correct both simulated and real projection data showed improved reconstruction image quality.

Iso-uncertainty control in an experimental fluoroscopy system.

PURPOSE: X-ray fluoroscopy remains an important imaging modality in a number of image-guided procedures due to its real-time nature and excellent spatial detail. However, the radiation dose delivered raises concerns about its use particularly in lengthy treatment procedures (>0.5 h). The authors have previously presented an algorithm that employs feedback of geometric uncertainty to control dose while maintaining a desired targeting uncertainty during fluoroscopic tracking of fiducials. The method was tested using simulations of motion against controlled noise fields. In this paper, the authors embody the previously reported method in a physical prototype and present changes to the controller required to function in a practical setting. METHODS: The metric for feedback used in this study is based on the trace of the covariance of the state of the system, tr(C). The state is defined here as the 2D location of a fiducial on a plane parallel to the detector. A relationship between this metric and the tube current is first developed empirically. This relationship is extended to create a manifold that incorporates a latent variable representing the estimated background attenuation. The manifold is then used within the controller to dynamically adjust the tube current and maintain a specified targeting uncertainty. To evaluate the performance of the proposed method, an acrylic sphere (1.6 mm in diameter) was tracked at tube currents ranging from 0.5 to 0.9 mA (0.033 s) at a fixed energy of 80 kVp. The images were acquired on a Varian Paxscan 4030A (2048 × 1536 pixels, ∼ 100 cm source-to-axis distance, ∼ 160 cm source-to-detector distance). The sphere was tracked using a particle filter under two background conditions: (1) uniform sheets of acrylic and (2) an acrylic wedge. The measured tr(C) was used in conjunction with a learned manifold to modulate the tube current in order to maintain a specified uncertainty as the sphere traversed regions of varying thickness corresponding to the acrylic sheets in the background. RESULTS: With feedback engaged, the tracking error was found to correlate well with the specified targeting uncertainty. Tracking of the fiducial was found to be robust to changes in the attenuation presented by the varying background conditions. For a desired uncertainty of 5.0 mm, comparison of the feedback framework with a comparable system employing fixed exposure demonstrated dose savings of 29%. CONCLUSIONS: This work presents a relation between a state descriptor, tr(C), the x-ray tube current used, and an estimate of the background attenuation. This relation is leveraged to modulate the tube current in order to maintain a desired geometric uncertainty during fluoroscopy. The authors' work demonstrates the use of the method in a real x-ray fluoroscopy system with physical motion against varying backgrounds. The method offers potential savings in imaging dose to patients and staff while maintaining tracking uncertainty during fluoroscopy-guided treatment procedures.

Multi-institutional dosimetric and geometric commissioning of image-guided small animal irradiators.

PURPOSE: To compare the dosimetric and geometric properties of a commercial x-ray based image-guided small animal irradiation system, installed at three institutions and to establish a complete and broadly accessible commissioning procedure. METHODS: The system consists of a 225 kVp x-ray tube with fixed field size collimators ranging from 1 to 44 mm equivalent diameter. The x-ray tube is mounted opposite a flat-panel imaging detector, on a C-arm gantry with 360° coplanar rotation. Each institution performed a full commissioning of their system, including half-value layer, absolute dosimetry, relative dosimetry (profiles, percent depth dose, and relative output factors), and characterization of the system geometry and mechanical flex of the x-ray tube and detector. Dosimetric measurements were made using Farmer-type ionization chambers, small volume air and liquid ionization chambers, and radiochromic film. The results between the three institutions were compared. RESULTS: At 225 kVp, with 0.3 mm Cu added filtration, the first half value layer ranged from 0.9 to 1.0 mm Cu. The dose-rate in-air for a 40 × 40 mm(2) field size, at a source-to-axis distance of 30 cm, ranged from 3.5 to 3.9 Gy/min between the three institutions. For field sizes between 2.5 mm diameter and 40 × 40 mm(2), the differences between percent depth dose curves up to depths of 3.5 cm were between 1% and 4% on average, with the maximum difference being 7%. The profiles agreed very well for fields >5 mm diameter. The relative output factors differed by up to 6% for fields larger than 10 mm diameter, but differed by up to 49% for fields ≤5 mm diameter. The mechanical characteristics of the system (source-to-axis and source-to-detector distances) were consistent between all three institutions. There were substantial differences in the flex of each system. CONCLUSIONS: With the exception of the half-value layer, and mechanical properties, there were significant differences between the dosimetric and geometric properties of the three systems. This underscores the need for careful commissioning of each individual system for use in radiobiological experiments.

A novel approach to quantification of real and artifactual components of current density imaging for phantom and live heart.

Spatial distribution of injected current in a subject could be calculated and visualized through current density imaging (CDI). Calculated CDI paths however have a limited degree of accuracy due to both avoidable methodological errors and inevitable limitations dictated by MR imaging constraints. The source and impact of these limitations are scrutinized in this paper. Quantification of such limitations is an essential step prior to passing any judgment about the results especially in biomedical applications. An innovative technique along with metrics for evaluation of range of errors using baseline and phase cycle MR images is proposed in this work. The presented approach is helpful in pinpointing the local artifacts (areas for which CDI results are suspect), evaluation of global noises and artifacts and assessment of the effect of approximation algorithms on real and artifactual components. We will demonstrate how this error/reliability evaluation is applicable to interpretation of CDI results and in this framework, report the CDI results for an artificial phantom and a live pig heart in Langendorff setup. It is contended here that using this method, the inevitable trade-off between details and approximations of CDI components could be monitored which provides a great opportunity for robust interpretation of results. The proposed approach could be extended, adapted and used for statistical analysis of similar methods which aim at mapping current and impedance based on magnetic flux images obtained through MRI.

Fusion of structural and functional cardiac magnetic resonance imaging data for studying ventricular fibrillation.

Magnetic Resonance Imaging (MRI) techniques such as Current Density Imaging (CDI) and Diffusion Tensor Imaging (DTI) provide a complementing set of imaging data that can describe both the functional and structural states of biological tissues. This paper presents a Joint Independent Component Analysis (jICA) based fusion approach which can be utilized to fuse CDI and DTI data to quantify the differences between two cardiac states: Ventricular Fibrillation (VF) and Asystolic/Normal (AS/NM). Such an approach could lead to a better insight on the mechanism of VF. Fusing CDI and DTI data from 8 data sets from 6 beating porcine hearts, in effect, detects the differences between two cardiac states, qualitatively and quantitatively. This initial study demonstrates the applicability of MRI-based imaging techniques and jICA-based fusion approach in studying cardiac arrhythmias.

Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections.

PURPOSE: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis. METHODS: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6 cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections. RESULTS: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm(-1) and 7/(2π) rad(-1) for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (~25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10(6) photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality. CONCLUSIONS: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.