Jessie Q. Xia

Introduction to neutron stimulated emission computed tomography

Neutron stimulated emission computed tomography (NSECT) is presented as a new technique for in vivo tomographic spectroscopic imaging. A full implementation of NSECT is intended to provide an elemental spectrum of the body or part of the body being interrogated at each voxel of a three-dimensional computed tomographic image. An external neutron beam illuminates the sample and some of these neutrons scatter inelastically, producing characteristic gamma emission from the scattering nuclei. These characteristic gamma rays are acquired by a gamma spectrometer and the emitting nucleus is identified by the emitted gamma energy. The neutron beam is scanned over the body in a geometry that allows for tomographic reconstruction. Tomographic images of each element in the spectrum can be reconstructed to represent the spatial distribution of elements within the sample. Here we offer proof of concept for the NSECT method, present the first single projection spectra acquired from multi-element phantoms, and discuss potential biomedical applications.

Dedicated breast computed tomography: volume image denoising via a partial-diffusion equation based technique.

Dedicated breast computed tomography (CT) imaging possesses the potential for improved lesion detection over conventional mammograms, especially for women with dense breasts. The breast CT images are acquired with a glandular dose comparable to that of standard two-view mammography for a single breast. Due to dose constraints, the reconstructed volume has a non-negligible quantum noise when thin section CT slices are visualized. It is thus desirable to reduce noise in the reconstructed breast volume without loss of spatial resolution. In this study, partial diffusion equation (PDE) based denoising techniques specifically for breast CT were applied at different steps along the reconstruction process and it was found that denoising performed better when applied to the projection data rather than reconstructed data. Simulation results from the contrast detail phantom show that the PDE technique outperforms Wiener denoising as well as adaptive trimmed mean filter. The PDE technique increases its performance advantage relative to Wiener techniques when the photon fluence is reduced. With the PDE technique, the sensitivity for lesion detection using the contrast detail phantom drops by less than 7% when the dose is cut down to 40% of the two-view mammography. For subjective evaluation, the PDE technique was applied to two human subject breast data sets acquired on a prototype breast CT system. The denoised images had appealing visual characteristics with much lower noise levels and improved tissue textures while maintaining sharpness of the original reconstructed volume.

Neutron Stimulated Emission Computed Tomography of Stable Isotopes

Here we report on the development of a new molecular imaging technique using inelastic scattering of fast neutrons. Earlier studies demonstrated a significant difference in trace element concentrations between benign and malignant tissue for several cancers including breast, lung, and colon. Unfortunately, the measurement techniques were not compatible with living organisms and this discovery did not translate into diagnostic techniques. Recently we have developed a tomographic approach to measuring the trace element concentrations using neutrons to stimulate characteristic gamma emission from atomic nuclei in the body. Spatial projections of the emitted energy spectra allow tomographic image reconstruction of the elemental concentrations. In preliminary experiments, spectra have been acquired using a 7.5MeV neutron beam incident on several multi-element phantoms. These experiments demonstrate our ability to determine the presence of Oxygen, Carbon, Copper, Iron, and Calcium. We describe the experimental technique and present acquired spectra.

Neutron-stimulated emission computed tomography of a multi-element phantom

This paper describes the implementation of neutron-stimulated emission computed tomography (NSECT) for non-invasive imaging and reconstruction of a multi-element phantom. The experimental apparatus and process for acquisition of multi-spectral projection data are described along with the reconstruction algorithm and images of the two elements in the phantom. Independent tomographic reconstruction of each element of the multi-element phantom was performed successfully. This reconstruction result is the first of its kind and provides encouraging proof of concept for proposed subsequent spectroscopic tomography of biological samples using NSECT.

Variance Component Analysis of a Multi-Site Study for the Reproducibility of Multiple Reaction Monitoring Measurements of Peptides in Human Plasma

BACKGROUND In the Addona et al. paper (Nature Biotechnology 2009), a large-scale multi-site study was performed to quantify Multiple Reaction Monitoring (MRM) measurements of proteins spiked in human plasma. The unlabeled signature peptides derived from the seven target proteins were measured at nine different concentration levels, and their isotopic counterparts were served as the internal standards. METHODOLOGY/PRINCIPAL FINDINGS In this paper, the sources of variation are analyzed by decomposing the variance into parts attributable to specific experimental factors: technical replicates, sites, peptides, transitions within each peptide, and higher-order interaction terms based on carefully built mixed effects models. The factors of peptides and transitions are shown to be major contributors to the variance of the measurements considering heavy (isotopic) peptides alone. For the light ((12)C) peptides alone, in addition to these factors, the factor of study*peptide also contributes significantly to the variance of the measurements. Heterogeneous peptide component models as well as influence analysis identify the outlier peptides in the study, which are then excluded from the analysis. Using a log-log scale transformation and subtracting the heavy/isotopic peptide [internal standard] measurement from the peptide measurements (i.e., taking the logarithm of the peak area ratio in the original scale establishes that), the MRM measurements are overall consistent across laboratories following the same standard operating procedures, and the variance components related to sites, transitions and higher-order interaction terms involving sites have greatly reduced impact. Thus the heavy peptides have been effective in reducing apparent inter-site variability. In addition, the estimates of intercepts and slopes of the calibration curves are calculated for the sub-studies. CONCLUSIONS/SIGNIFICANCE The MRM measurements are overall consistent across laboratories following the same standard operating procedures, and heavy peptides can be used as an effective internal standard for reducing apparent inter-site variability. Mixed effects modeling is a valuable tool in mass spectrometry-based proteomics research.

Development of a High-Energy Gamma Camera for use with NSECT Imaging of the Breast

A new imaging technique, neutron stimulated emission computed tomography (NSECT), is being developed that has potential for utilization in breast cancer imaging. NSECT is a spectroscopic imaging technique that is able to produce elemental concentration images and previous studies have identified differences in trace element concentrations between malignant and benign tissues. NSECT illuminates the body via a beam of neutrons causing elemental nuclei to become excited and emit characteristic gamma radiation. By imaging the gamma rays in a tomographic manner it is possible to reconstruct elemental composition images. This method requires high-resolution spectroscopy, thereby eliminating the use conventional scintillation gamma cameras; in this case, spectral information is obtained from high-purity germanium (HPGe) semiconductor detectors, providing only 1D spatial information. To obtain 2D elemental concentration images, we are adapting high-energy solar spectroscopy technology. A rotating modulation collimator (RMC) consisting of two parallel-slat collimators is placed in front of the detector and modulates the incoming signal in a manner predicted by its geometry. Reconstruction of 2D images is possible by counting the number incident gammas at each rotation angle. A significant challenge is presented when attempting to modify the RMC for use in the near field and a prototype camera has been constructed to verify the geometric validity of a RMC for this use. Herein we present the progress to date in the design and development of a high-energy spectroscopic gamma camera for use with NSECT imaging of the breast.

Detector evaluation of a prototype amorphous selenium-based full field digital mammography system

This study evaluated the physical performance of a selenium-based direct full-field digital mammography prototype detector (Siemens Mammomat NovationDR), including the pixel value vs. exposure linearity, the modulation transfer function (MTF), the normalized noise power spectrum (NNPS), and the detective quantum efficiency (DQE). The current detector is the same model which received an approvable letter from FDA for release to the US market. The results of the current prototype are compared to those of an earlier prototype. Two IEC standard beam qualities (RQA-M2: Mo/Mo, 28 kVp, 2 mm Al; RQA-M4: Mo/Mo, 35 kVp, 2 mm Al) and two additional beam qualities (MW2: W/Rh, 28 kVp, 2 mm Al; MW4: W/Rh, 35 kVp, 2 mm Al) were investigated. To calculate the modulation transfer function (MTF), a 0.1 mm Pt-Ir edge was imaged at each beam quality. Detector pixel values responded linearly against exposure values (R2 0.999). As before, above 6 cycles/mm Mo/Mo MTF was slightly higher along the chest-nipple axis compared to the left-right axis. MTF was comparable to the previously reported prototype, with slightly reduced resolution. The DQE peaks ranged from 0.71 for 3.31 μC/kg (12.83 mR) to 0.4 for 0.48 μC/kg (1.86 mR) at 1.75 cycles/mm for Mo/Mo at 28 kVp. The DQE range for W/Rh at 28 kVP was 0.81 at 2.03 μC/kg (7.87 mR) to 0.50 at 0.50 μC/kg (1.94 mR) at 1 cycle/mm. NNPS tended to increase with greater exposures, while all exposures had a significant low-frequency component. Bloom and detector edge artifacts observed previously were no longer present in this prototype. The new detector shows marked noise improvement, with slightly reduced resolution. There remain artifacts due to imperfect gain calibration, but at a reduced magnitude compared to a prototype detector.

Calibration using constrained smoothing with applications to mass spectrometry data.

Linear regressions are commonly used to calibrate the signal measurements in proteomic analysis by mass spectrometry. However, with or without a monotone (e.g., log) transformation, data from such functional proteomic experiments are not necessarily linear or even monotone functions of protein (or peptide) concentration except over a very restricted range. A computationally efficient spline procedure improves upon linear regression. However, mass spectrometry data are not necessarily homoscedastic; more often the variation of measured concentrations increases disproportionately near the boundaries of the instruments measurement capability (dynamic range), that is, the upper and lower limits of quantitation. These calibration difficulties exist with other applications of mass spectrometry as well as with other broad-scale calibrations. Therefore the method proposed here uses a functional data approach to define the calibration curve and also the limits of quantitation under the two assumptions: (i) that the variance is a bounded, convex function of concentration; and (ii) that the calibration curve itself is monotone at least between the limits of quantitation, but not necessarily outside these limits. Within this paradigm, the limit of detection, where the signal is definitely present but not measurable with any accuracy, is also defined. An iterative approach draws on existing smoothing methods to account simultaneously for both restrictions and is shown to achieve the global optimal convergence rate under weak conditions. This approach can also be implemented when convexity is replaced by other (bounded) restrictions. Examples from Addona et al. (2009, Nature Biotechnology 27, 663-641) both motivate and illustrate the effectiveness of this functional data methodology when compared with the simpler linear regressions and spline techniques.

Mass detectability in dedicated breast CT: A simulation study with the application of volume noise removal

Dedicated breast Computed Tomography (CT) is an emerging new technique for breast cancer imaging. Breast CT data can be acquired at a dose level as low as the conventional two-view mammography. Since the dose is equally split into hundreds of projection views, each projection image contains non-ignorable quantum noise. This study is aimed at investigating how volume noise removal affects the mass detectability in breast CT. A Partial Diffusion Equation (PDE) based denoising technique was applied before the reconstruction of either a simulated breast volume embedded with a contrast-detail mass phantom or a real human subject breast CT volume embedded with a simulated spherical mass. By applying a mathematical observer, it is found that the PDE volume noise removal technique improves the mass detectability in breast CT in a statistically significant sense.

On the development of a gaussian noise model for scatter compensation

The underlying mechanism in projection radiography as well as in computed tomography (CT) is the accumulative attenuation of a pencil x-ray beam along a straight line. However, when a portion of photons is deviated from their original path by scattering, it is not valid to assume that these photons are the survival photons along the lines connecting the x-ray source and the individual locations where they are detected. Since these photons do not carry the correct spatial information, the final image is contaminated. Researchers are seeking techniques to reduce scattering, and hence, improve image quality, by scatter compensation. Previously, we presented a post-acquisition scatter compensation technique based on an underlying statistical model. We used the Poisson noise model, which assumed that the signals in the detector individually followed the Poisson process. Since most x-ray detectors are energy integrating rather than photon counting, the Poisson noise model can be improved by taking this property into account. In this study, we developed a Gaussian noise model by the matching-of-the-first-two-moments method. The Maximum Likelihood Estimator of the scatter-free image was derived via the expectation maximization (EM) technique. The maximum a posteriori estimate was also calculated. The Gaussian noise model was preliminarily evaluated on a full-field digital mammography system.