Daniel J. Tward

Cascaded systems analysis of the 3D noise transfer characteristics of flat-panel cone-beam CT

The physical factors that govern 2D and 3D imaging performance may be understood from quantitative analysis of the spatial-frequency-dependent signal and noise transfer characteristics [e.g., modulation transfer function (MTF), noise-power spectrum (NPS), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ)] along with a task-based assessment of performance (e.g., detectability index). This paper advances a theoretical framework based on cascaded systems analysis for calculation of such metrics in cone-beam CT (CBCT). The model considers the 2D projection NPS propagated through a series of reconstruction stages to yield the 3D NPS and allows quantitative investigation of tradeoffs in image quality associated with acquisition and reconstruction techniques. While the mathematical process of 3D image reconstruction is deterministic, it is shown that the process is irreversible, the associated reconstruction parameters significantly affect the 3D DQE and NEQ, and system optimization should consider the full 3D imaging chain. Factors considered in the cascade include: system geometry; number of projection views; logarithmic scaling; ramp, apodization, and interpolation filters; 3D back-projection; and 3D sampling (noise aliasing). The model is validated in comparison to experiment across a broad range of dose, reconstruction filters, and voxel sizes, and the effects of 3D noise correlation on detectability are explored. The work presents a model for the 3D NPS, DQE, and NEQ of CBCT that reduces to conventional descriptions of axial CT as a special case and provides a fairly general framework that can be applied to the design and optimization of CBCT systems for various applications.

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

PURPOSE The authors previously developed the 4D extended cardiac-torso (XCAT) phantom for multimodality imaging research. The XCAT consisted of highly detailed whole-body models for the standard male and female adult, including the cardiac and respiratory motions. In this work, the authors extend the XCAT beyond these reference anatomies by developing a series of anatomically variable 4D XCAT adult phantoms for imaging research, the first library of 4D computational phantoms. METHODS The initial anatomy of each phantom was based on chest-abdomen-pelvis computed tomography data from normal patients obtained from the Duke University database. The major organs and structures for each phantom were segmented from the corresponding data and defined using nonuniform rational B-spline surfaces. To complete the body, the authors manually added on the head, arms, and legs using the original XCAT adult male and female anatomies. The structures were scaled to best match the age and anatomy of the patient. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from the template XCAT phantom (male or female) to the target patient model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. Each new phantom was refined by checking for anatomical accuracy via inspection of the models. RESULTS Using these methods, the authors created a series of computerized phantoms with thousands of anatomical structures and modeling cardiac and respiratory motions. The database consists of 58 (35 male and 23 female) anatomically variable phantoms in total. Like the original XCAT, these phantoms can be combined with existing simulation packages to simulate realistic imaging data. Each new phantom contains parameterized models for the anatomy and the cardiac and respiratory motions and can, therefore, serve as a jumping point from which to create an unlimited number of 3D and 4D variations for imaging research. CONCLUSIONS A population of phantoms that includes a range of anatomical variations representative of the public at large is needed to more closely mimic a clinical study or trial. The series of anatomically variable phantoms developed in this work provide a valuable resource for investigating 3D and 4D imaging devices and the effects of anatomy and motion in imaging. Combined with Monte Carlo simulation programs, the phantoms also provide a valuable tool to investigate patient-specific dose and image quality, and optimization for adults undergoing imaging procedures.

Effects of protocol and obesity on dose conversion factors in adult body CT

PURPOSE In computed tomography (CT), organ dose, effective dose, and risk index can be estimated from volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) using conversion coefficients. Studies have investigated how these coefficients vary across scanner models, scan parameters, and patient size. However, their variability across CT protocols has not been systematically studied. Furthermore, earlier studies of the effect of patient size have not included obese individuals, which currently represent more than one-third of U.S. adults. The purpose of this study was to assess the effects of protocol and obesity on dose and risk conversion coefficients in adult body CT. METHODS Whole-body computational phantoms were created from clinical CT images of six adult patients (three males, three females), representing normal-weight patients and patients of three obesity classes. Body CT protocols at our institution were selected and categorized into ten examination categories based on anatomical region examined. A validated Monte Carlo program was used to estimate organ dose. Organ dose estimates were normalized by CTDI(vol) and size-specific dose estimate (SSDE) to obtain organ dose conversion coefficients (denoted as h and h(ss) factors, respectively). Assuming each phantom to be 20, 40, and 60 years old, effective dose and risk index were calculated and normalized by DLP to obtain effective dose and risk index conversion coefficients (denoted as k and q factors, respectively). Coefficient of variation was used to quantify the variability of each conversion coefficient across examination categories. The effect of obesity was assessed by comparing each obese phantom with the normal-weight phantom of the same gender. RESULTS For a given organ, the variability of h factor across examination categories that encompassed the entire organ volume was generally within 15%. However, k factor varied more across examination categories (15%-27%). For all three ages, the variability of q factor was small for male (<10%), but large for female phantoms (21%-43%). Relative to the normal-weight phantoms, the reduction in h factor (an average across fully encompassed organs) was 17%-42%, 17%-40%, and 51%-63% for obese-class-I, obese-class-II, and obese-class-III phantoms, respectively. h(ss) factor was not independent of patient diameter and generally decreased with increasing obesity. Relative to the normal-weight phantoms, the reduction in k factor was 12%-40%, 14%-46%, and 44%-59% for obese-class-I, obese-class-II, and obese-class-III phantoms, respectively. The respective reduction in q factor was 11%-36%, 17%-42%, and 48%-59% at 20 years of age and similar at other ages. CONCLUSIONS In adult body CT, dose to an organ fully encompassed by the primary radiation beam can be estimated from CTDI(vol) using a protocol-independent conversion coefficient. However, fully encompassed organs only account for 50% ± 19% of k factor and 46% ± 24% of q factor. Dose received by partially encompassed organs is also substantial. To estimate effective dose and risk index from DLP, it is necessary to use conversion coefficients specific to the anatomical region examined. Obesity has a significant effect on dose and risk conversion coefficients, which cannot be predicted using body diameter alone. SSDE-normalized organ dose is not independent of diameter. SSDE itself generally overestimates organ dose for obese patients.

Noise aliasing and the 3D NEQ of flat-panel cone-beam CT: effect of 2D/3D apertures and sampling.

The ability to tune an imaging system to be optimal for a specific task is an essential component of image quality. This article discusses the ability to tune the noise-equivalent quanta (NEQ) of cone-beam computed tomography (CBCT) by managing noise aliasing through binning of data at different points in the reconstruction cascade. The noise power spectrum, modulation transfer function, and NEQ for CBCT are calculated using cascaded systems analysis. Binning is treated as a modular process, insertable between any two stages (in both the 2D projection domain and in the 3D reconstruction domain), consisting of the application of an aperture, followed by the resampling of data (which introduces noise aliasing). Several conditions were examined to demonstrate the validity of the model and to describe the effect on the image quality of some common reconstruction and visualization techniques. It was found that when downsampling data for increased reconstruction speed, binning in 2D results in a superior low-frequency NEQ, while binning in 3D results in a superior high-frequency NEQ. Furthermore, visualization procedures such as slice averaging were found not to degrade the NEQ provided the sampling interval is unchanged. Finally methods for reducing noise aliasing by oversampling are examined, and a method to eliminate noise aliasing without increasing reconstruction time is proposed. These results demonstrate the ease with which the NEQ of CBCT can be modified and thus optimized for specific tasks and show how such analysis can be used to improve image quality.

Amygdalar atrophy in symptomatic Alzheimer's disease based on diffeomorphometry: the BIOCARD cohort.

This article examines the diffeomorphometry of magnetic resonance imaging-derived structural markers for the amygdala, in subjects with symptomatic Alzheimers disease (AD). Using linear mixed-effects models we show differences between those with symptomatic AD and controls. Based on template centered population analysis, the distribution of statistically significant change is seen in both the volume and shape of the amygdala in subjects with symptomatic AD compared with controls. We find that high-dimensional vertex based markers are statistically more significantly discriminating (p < 0.00001) than lower-dimensional markers and volumes, consistent with comparable findings in presymptomatic AD. Using a high-field 7T atlas, significant atrophy was found to be centered in the basomedial and basolateral subregions, with no evidence of centromedial involvement.

Beyond noise power in 3D computed tomography: the local NPS and off-diagonal elements of the Fourier domain covariance matrix.

PURPOSE To investigate the correlation and stationarity of noise in volumetric computed tomography (CT) using the local discrete noise-power spectrum (NPS) and off-diagonal elements of the covariance matrix of the discrete Fourier transform of noise-only images (denoted Σ(DFT)). Experimental conditions were varied to affect noise correlation and stationarity, the effects were quantified in terms of the NPS and Σ(DFT), and practical considerations in CT performance characterization were identified. METHODS Cone-beam CT (CBCT) images were acquired using a benchtop system comprising an x-ray tube and flat-panel detector for a range of acquisition techniques (e.g., dose and x-ray scatter) and three phantom configurations hypothesized to impart distinct effects on the NPS and Σ(DFT): (A) air, (B) a 20-cm-diameter water cylinder with a bowtie filter, and (C) the cylinder without a bowtie filter. The NPS and off-diagonal elements of the Σ(DFT) were analyzed as a function of position within the reconstructions. RESULTS The local NPS varied systematically throughout the axial plane in a manner consistent with changes in fluence transmitted to the detector and view sampling effects. Variability in fluence was manifest in the NPS magnitude-e.g., a factor of ~2 variation in NPS magnitude within the axial plane for case C (cylinder without bowtie), compared to nearly constant NPS magnitude for case B (bowtie filter matched to the cylinder). View sampling effects were most prominent in case A (air) where the variance increased at greater distance from the center of reconstruction and in case C (cylinder) where the NPS exhibited correlations in the radial direction. The effects of detector lag were observed as azimuthal correlation. The cylinder (without bowtie) had the strongest nonstationarity because of the larger variability in fluence transmitted to the detector. The diagonal elements of the Σ(DFT) were equivalent to the NPS estimated from the periodogram, and the average off-diagonal elements of the Σ(DFT) exhibited amplitude of ~1% of the NPS for the experimental conditions investigated. Furthermore, the off-diagonal elements demonstrated fairly long tails of nearly constant amplitude, with magnitude somewhat reduced for experimental conditions associated with greater stationarity (viz., lower Σ(DFT) tails for cases A and B in comparison to case C). CONCLUSIONS Volumetric CT exhibits nonstationarity in the NPS as hypothesized in relation to fluence uniformity and view sampling. Measurement of the NPS should seek to minimize such changes in noise correlations and include careful reporting of experimental conditions (e.g., phantom design and use of a bowtie filter) and spatial dependence (e.g., analysis at fixed radius within a phantom). Off-diagonal elements of the Σ(DFT) similarly depend on experimental conditions and can be readily computed from the same data as the NPS. This work begins to check assumptions in NPS analysis examine the extent to which NPS is an appropriate descriptor of noise correlations, and investigate the magnitude of off-diagonal elements of the Σ(DFT). While the magnitude of such off-diagonal elements appears to be low, their cumulative effect on space-variant detectability remains to be investigated-e.g., using task-specific figures of merit.

Soft‐tissue detectability in cone‐beam CT: Evaluation by 2AFC tests in relation to physical performance metrics

Soft-tissue detectability in cone-beam computed tomography (CBCT) was evaluated via two-alternative forced-choice (2AFC) tests. Investigations included the dependence of detectability on radiation dose, the influence of the asymmetric three-dimensional (3D) noise-power spectrum (NPS) in axial and sagittal or coronal planes, and the effect of prior knowledge on detectability. Custom-built phantoms (approximately 15 cm diameter cylinders) containing soft-tissue-simulating spheres of variable contrast and diameter were imaged on an experimental CBCT bench. The proportion of correct responses (Pcorr) in 2AFC tests was analyzed as a figure of merit, ideally equal to the area under the receiver operating characteristic curve. Pcorr was evaluated as a function of the sphere diameter (1.6-12.7 mm), contrast (20-165 HU), dose (1-7 mGy), plane of visualization (axial/sagittal), apodization filter (Hanning and Ram-Lak), and prior knowledge provided to the observer [ranging from stimulus known exactly (SKE) to stimulus unknown (SUK)]. Detectability limits were characterized in terms of the dose required to achieve a given level of Pcorr (e.g., 70%). For example, a 20 HU stimulus of diameter down to approximately 6 mm was detected with Pcorr 70% at dose > or =2 mGy. Detectability tended to be greater in axial than in sagittal planes, an effect amplified by sharper apodization filters in a manner consistent with 3D NPS asymmetry. Prior knowledge had a marked influence on detectability--e.g., Pcorr for a approximately 6 mm (20 HU) sphere was approximately 55%-65% under SUK conditions, compared to approximately 70%-85% for SKE conditions. Human observer tests suggest practical implications for implementation of CBCT: (i) Detectability limits help to define minimum-dose imaging techniques for specific imaging tasks; (ii) detectability of a given structure can vary between axial and sagittal/coronal planes, owing to the spatial-frequency content of the 3D NPS in relation to the imaging task; and (iii) performance under SKE conditions (e.g., image guidance tasks in which lesion characteristics are known) is maintained at a lower dose than in SUK conditions (e.g., diagnostic tasks in which lesion characteristics are unknown).

Network Neurodegeneration in Alzheimer's Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing.

This paper examines MRI analysis of neurodegeneration in Alzheimer’s Disease (AD) in a network of structures within the medial temporal lobe using diffeomorphometry methods coupled with high-field atlasing in which the entorhinal cortex is partitioned into eight subareas. The morphometry markers for three groups of subjects (controls, preclinical AD, and symptomatic AD) are indexed to template coordinates measured with respect to these eight subareas. The location and timing of changes are examined within the subareas as it pertains to the classic Braak and Braak staging by comparing the three groups. We demonstrate that the earliest preclinical changes in the population occur in the lateral most sulcal extent in the entorhinal cortex (alluded to as transentorhinal cortex by Braak and Braak), and then proceeds medially which is consistent with the Braak and Braak staging. We use high-field 11T atlasing to demonstrate that the network changes are occurring at the junctures of the substructures in this medial temporal lobe network. Temporal progression of the disease through the network is also examined via changepoint analysis, demonstrating earliest changes in entorhinal cortex. The differential expression of rate of atrophy with progression signaling the changepoint time across the network is demonstrated to be signaling in the intermediate caudal subarea of the entorhinal cortex, which has been noted to be proximal to the hippocampus. This coupled to the findings of the nearby basolateral involvement in amygdala demonstrates the selectivity of neurodegeneration in early AD.

A set of 4D pediatric XCAT reference phantoms for multimodality research.

PURPOSE The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols. METHODS Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection. RESULTS The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities. CONCLUSIONS The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.

Cascaded systems analysis of the 3D NEQ for cone-beam CT and tomosynthesis

Crucial to understanding the factors that govern imaging performance is a rigorous analysis of signal and noise transfer characteristics (e.g., MTF, NPS, and NEQ) applied to a task-based performance metric (e.g., detectability index). This paper advances a theoretical framework for calculation of the NPS, NEQ, and DQE of cone-beam CT (CBCT) and tomosynthesis based on cascaded systems analysis. The model considers the 2D projection NPS propagated through a series of reconstruction stages to yield the 3D NPS, revealing a continuum (from 2D projection radiography to limited-angle tomosynthesis and fully 3D CBCT) for which NEQ and detectability index may be investigated as a function of any system parameter. Factors considered in the cascade include: system geometry; angular extent of source-detector orbit; finite number of views; log-scaling; application of ramp, apodization, and interpolation filters; back-projection; and 3D noise aliasing - all of which have a direct impact on the 3D NEQ and DQE. Calculations of the 3D NPS were found to agree with experimental measurements across a broad range of imaging conditions. The model presents a theoretical framework that unifies 3D Fourier-based performance metrology in tomosynthesis and CBCT, providing a guide to optimization that rigorously considers the system configuration, reconstruction parameters, and imaging task.