Low pitch significantly reduces helical artifacts in abdominal CT.

PURPOSE: High helical pitch scanning minimizes scan times in CT imaging, and thus also minimizes motion artifact and mis-synchronization with contrast bolus. However, high pitch produces helical artifacts that may adversely affect diagnostic image quality. This study aims to determine the severity and incidence of helical artifacts in abdominal CT imaging and their relation to the helical pitch scan parameter. METHODS: To obtain a dataset with varying pitch values, we used CT exam data both internal and external to our center. A cohort of 59 consecutive adult patients receiving an abdomen CT examination at our center with an accompanying prior examination from an external center was selected for retrospective review. Two expert observers performed a blinded rating of helical artifact in each examination using a five-point Likert scale. The incidence of artifacts with respect to the helical pitch was assessed. A generalized linear mixed-effects regression (GLMER) model, with study arm (Internal or External to our center) and helical pitch as the fixed-effect predictor variables, was fit to the artifact ratings, and significance of the predictor variables was tested. RESULTS: For a pitch of <0.75, the proportion of exams with mild or worse helical artifacts (Likert scores of 1-3) was <1%. The proportion increased to 16% for exams with pitch between 0.75 and 1.2, and further increased to 78% for exams with a pitch greater than 1.2. Pitch was significantly associated with helical artifact in the GLMER model (p = 2.8 × 10-9), while study arm was not a significant factor (p = 0.76). CONCLUSION: The incidence and severity of helical artifact increased with helical pitch. This difference persisted even after accounting for the potential confounding factor of the center where the study was performed.

How Do Cancer-Specific Computed Tomography Protocols Compare With the American College of Radiology Dose Index Registry? An Analysis of Computed Tomography Dose at 2 Cancer Centers.

BACKGROUND: Little guidance exists on how to stratify radiation dose according to diagnostic task. Changing dose for different cancer types is currently not informed by the American College of Radiology Dose Index Registry dose survey. METHODS: A total of 9602 patient examinations were pulled from 2 National Cancer Institute designated cancer centers. Computed tomography dose (CTDI vol ) was extracted, and patient water equivalent diameter was calculated. N-way analysis of variance was used to compare the dose levels between 2 protocols used at site 1, and three protocols used at site 2. RESULTS: Sites 1 and 2 both independently stratified their doses according to cancer indications in similar ways. For example, both sites used lower doses ( P < 0.001) for follow-up of testicular cancer, leukemia, and lymphoma. Median dose at median patient size from lowest to highest dose level for site 1 were 17.9 (17.7-18.0) mGy (mean [95% confidence interval]) and 26.8 (26.2-27.4) mGy. For site 2, they were 12.1 (10.6-13.7) mGy, 25.5 (25.2-25.7) mGy, and 34.2 (33.8-34.5) mGy. Both sites had higher doses ( P < 0.001) between their routine and high-image-quality protocols, with an increase of 48% between these doses for site 1 and 25% for site 2. High-image-quality protocols were largely applied for detection of low-contrast liver lesions or subtle pelvic pathology. CONCLUSIONS: We demonstrated that 2 cancer centers independently choose to stratify their cancer doses in similar ways. Sites 1 and 2 dose data were higher than the American College of Radiology Dose Index Registry dose survey data. We thus propose including a cancer-specific subset for the dose registry.

Oncology-specific radiation dose and image noise reference levels in adult abdominal-pelvic CT.

OBJECTIVES: To provide our oncology-specific adult abdominal-pelvic CT reference levels for image noise and radiation dose from a high-volume, oncologic, tertiary referral center. METHODS: The portal venous phase abdomen-pelvis acquisition was assessed for image noise and radiation dose in 13,320 contrast-enhanced CT examinations. Patient size (effective diameter) and radiation dose (CTDIvol) were recorded using a commercial software system, and image noise (Global Noise metric) was quantified using a custom processing system. The reference level and range for dose and noise were calculated for the full dataset, and for examinations grouped by CT scanner model. Dose and noise reference levels were also calculated for exams grouped by five different patient size categories. RESULTS: The noise reference level was 11.25 HU with a reference range of 10.25-12.25 HU. The dose reference level at a median effective diameter of 30.7 cm was 26.7 mGy with a reference range of 19.6-37.0 mGy. Dose increased with patient size; however, image noise remained approximately constant within the noise reference range. The doses were 2.1-2.5 times than the doses in the ACR DIR registry for corresponding patient sizes. The image noise was 0.63-0.75 times the previously published reference level in abdominal-pelvic CT examinations. CONCLUSIONS: Our oncology-specific abdominal-pelvic CT dose reference levels are higher than in the ACR dose index registry and our oncology-specific image noise reference levels are lower than previously proposed image noise reference levels. ADVANCES IN KNOWLEDGE: This study reports reference image noise and radiation dose levels appropriate for the indication of abdomen-pelvis CT examination for cancer diagnosis and staging. The difference in these reference levels from non-oncology-specific CT examinations highlight a need for indication-specific, dose index and image quality reference registries.

Assessment of the global noise algorithm for automatic noise measurement in head CT examinations.

PURPOSE: The global noise (GN) algorithm has been previously introduced as a method for automatic noise measurement in clinical CT images. The accuracy of the GN algorithm has been assessed in abdomen CT examinations, but not in any other body part until now. This work assesses the GN algorithm accuracy in automatic noise measurement in head CT examinations. METHODS: A publicly available image dataset of 99 head CT examinations was used to evaluate the accuracy of the GN algorithm in comparison to reference noise values. Reference noise values were acquired using a manual noise measurement procedure. The procedure used a consistent instruction protocol and multiple observers to mitigate the influence of intra- and interobserver variation, resulting in precise reference values. Optimal GN algorithm parameter values were determined. The GN algorithm accuracy and the corresponding statistical confidence interval were determined. The GN measurements were compared across the six different scan protocols used in this dataset. The correlation of GN to patient head size was also assessed using a linear regression model, and the CT scanner's X-ray beam quality was inferred from the model fit parameters. RESULTS: Across all head CT examinations in the dataset, the range of reference noise was 2.9-10.2 HU. A precision of ±0.33 HU was achieved in the reference noise measurements. After optimization, the GN algorithm had a RMS error 0.34 HU corresponding to a percent RMS error of 6.6%. The GN algorithm had a bias of +3.9%. Statistically significant differences in GN were detected in 11 out of the 15 different pairs of scan protocols. The GN measurements were correlated with head size with a statistically significant regression slope parameter (p < 10-7 ). The CT scanner X-ray beam quality estimated from the slope parameter was 3.5 cm water HVL (2.8-4.8 cm 95% CI). CONCLUSION: The GN algorithm was validated for application in head CT examinations. The GN algorithm was accurate in comparison to reference manual measurement, with errors comparable to interobserver variation in manual measurement. The GN algorithm can detect noise differences in examinations performed on different scanner models or using different scan protocols. The trend in GN across patients of different head sizes closely follows that predicted by a physical model of X-ray attenuation.

A Benchmark for automatic noise measurement in clinical computed tomography.

PURPOSE: Assessment of image quality directly in clinical image data is an important quality control objective as phantom-based testing does not fully represent image quality across patient variation. Computer algorithms for automatically measuring noise in clinical computed tomography (CT) images have been introduced, but the accuracy of these algorithms is unclear. This work benchmarks the accuracy of the global noise (GN) algorithm for automatic noise measurement in contrast-enhanced abdomen CT exams in comparison to precise reference noise measurements. The GN algorithm was further optimized compared to the previous report in the literature. METHODS: Reference values of noise were established in a public image dataset of 82 contrast-enhanced abdomen CT exams. The reference noise values were obtained by manual regions-of-interest measurements of pixel standard deviation in the liver parenchyma according to an instruction protocol. Noise measurements taken by six observers were averaged together to improve reference noise statistical precision. The GN algorithm was used to automatically measure noise in each image set. The accuracy of the GN algorithm was determined in terms of RMS error compared to reference noise. The GN algorithm was optimized by conducting 1000 trials with random algorithm parameter values. The trial with the lowest RMS error was used to select optimum algorithm parameters. RESULTS: The range of noise across CT image sets was 8.8-28.8 HU. Reference noise measurements were made with a precision of ±0.78 HU (95% confidence interval). The RMS error of automatic noise measurement was 0.93 HU (0.77-1.19 HU 95% confidence interval). The automatic noise measurements were equally accurate across image sets of varying noise magnitude. Optimum GN algorithm parameter values were: a kernel size of 7 pixels, and soft tissue lower and upper thresholds of 0 and 170 HU, respectively. CONCLUSIONS: The performance of automatic noise measurement was benchmarked in a large clinical CT dataset. The study provides a framework for thorough validation of automatic clinical image quality measurement methods. The GN algorithm was optimized and validated for automatic measurement of soft-tissue noise in abdomen CT exams.

Reduced acquisition time for L-shell x-ray fluorescence computed tomography using polycapillary x-ray optics.

PURPOSE: X-ray fluorescence computed tomography (XFCT) is an emerging molecular imaging modality for preclinical and clinical applications with high atomic number contrast agents. XFCT allows detection of molecular biomarkers at tissue depths of 4-9 mm at L-shell energies and several centimeters for K-shell energies, while maintaining high spatial resolution. This is typically not possible for other molecular imaging modalities. The purpose of this study is to demonstrate XFCT imaging with reduced acquisition times. To accomplish this, x-ray focusing polycapillary optics are utilized to simultaneously increase x-ray fluence rate and spatial resolution in L-shell XFCT imaging. MATERIALS AND METHODS: A prototype imaging system using a polycapillary focusing optic was demonstrated. The optic, which was custom-designed for this prototype, provided a high fluence rate with a focal spot size of 2.6 mm at a source to isocenter distance of 3 cm with a ten times higher fluence rate compared to standard collimation. The study evaluates three different phantoms to explore different trade-offs and limitations of L-shell XFCT imaging. A low-contrast gold phantom and a high-contrast gold phantom, each with three target regions with gold concentrations of 60, 80, and 100 µg ml - 1 for low contrast and 200, 600, and 1000 µg ml - 1 for high contrast, and a mouse-sized water phantom with gold concentrations between 300 and 500 µg ml - 1 were imaged. X-ray fluorescence photons were measured using a silicon drift detector (SDD) with an energy resolution of 180 eV FWHM at an x-ray energy of 11 keV. Images were reconstructed with an iterative image reconstruction algorithm and analyzed for contrast to noise ratio (CNR) and signal to noise ratio (SNR). RESULTS: The XFCT data acquisition could be reduced from 17 h to under 1 h. The polycapillary x-ray optic increases the x-ray fluence rate and lowers the amount of background scatter which leads to reduced imaging time and improved sensitivity. The quantitative analysis of the reconstructed images validates that concentrations of 60 µg ml - 1 of gold can be visualized with L-shell XFCT imaging. For a mouse-sized phantom, a concentration of 300 µg ml - 1 gold was detected within a 66 min measurement. CONCLUSIONS: With a high fluence rate pencil beam from a polycapillary x-ray source, a reduction in signal integration time is achieved. It is presented that subtle amounts of contrast agents can be detected with L-shell XFCT within biologically relevant time frames. Our basic measurements show that the polycapillary x-ray source technology is appropriate to realize preclinical L-shell XFCT imaging. The integration of more SDDs into the system will lower the dose and increase the sensitivity.

Assessment of a photon-counting detector for a dual-energy C-arm angiographic system.

PURPOSE: This article presents the implementation and assessment of photon-counting dual-energy x-ray detector technology for angiographic C-arm systems in interventional radiology. METHODS: A photon-counting detector was successfully integrated into a clinical C-arm CT system. Detector performance was assessed using image uniformity metrics in both 2D projections and 3D cone-beam computed tomography (CBCT) images. Uniform exposure fields were acquired to analyze projection images and scans of a homogeneous cylinder phantom were taken to analyze 3D reconstructions. Image uniformity was assessed over a broad range of imaging parameters. RESULTS: Detector calibration greatly improved image uniformity, reducing image variation from 8.8% to 0.5% in an ideal scenario, but image uniformity degraded when imaging parameters varied strongly from values set at calibration: the tube voltage, low-high energy threshhold, and tube current had the greatest impact. Material discrimination and dynamic angiography capabilities were successfully demonstrated in separate phantom and in vivo experiments. CONCLUSION: The uniformity results identified major factors degrading image quality. The quantitative results will guide selection of calibration points to mitigate the loss of uniformity. The unique combination of dual-energy and fluoroscopy imaging capabilities with a flat-panel photon-counting detector may enable new applications in interventional radiology.

Iterative volume of interest based 4D cone-beam CT.

PURPOSE: 4D cone-beam CT (CBCT) has potential applications in soft tissue alignment and tumor motion verification at the time of radiation treatment. However, prominent streak artifacts with conventional image reconstructions have limited its clinical use and alternative reconstructions are generally too computationally expensive for the time available. We propose an iterative volume of interest based (I4D VOI) reconstruction technique, where 4D reconstruction is only performed within a VOI, to limit streak artifacts with limited added computation time. METHODS: The I4D VOI technique is compared to standard cone-beam filtered back projection (FDK), an FDK VOI technique, and unconstrained total variation (TV) minimization by comparing tumor motion quantification errors and image quality. 14 long CBCT scans (6.5 to 12 min) of patients receiving radiation treatment for lung cancer were used for the comparison. Rigid registration between phase images of FDK reconstructions using all projections were used to quantify the gold standard motion. Projections were removed to simulate 2 minute scans and these new projection sets were used for each of the test reconstructions. RESULTS: Excluding two patients where registration failed, the average root mean square (RMS) error for each method was as follows: 1.5 ± 0.2 mm for FDK, 1.4 ± 0.2 mm for FDK VOI, 1.3 ± 0.2 mm for I4D VOI, 1.7 ± 0.4 mm for low regularization TV minimization, and 1.1 ± 0.2 mm for high regularization TV minimization. No significant difference was observed between RMS error for I4D VOI and the other methods, except for unsmoothed FDK VOI (P = 0.02). An increase in RMS error difference between I4D VOI and smoothed FDK VOI was observed going from 2 min to 1 min scans (0.1 mm to 0.3 mm, P = 0.20 to P = 0.09). CONCLUSIONS: I4D VOI and FDK VOI reconstruction measured tumor trajectories with equivalent accuracy as TV minimization with improved bony anatomy image quality and computation time (I4D VOI was approximately 15 and 95 times faster than low and high regularization TV minimization, respectively). Within the VOI, streak artifact reduction compared to FDK VOI may be beneficial for tumor visualization and motion measurement, but requires further study.

The Role of Cone-Beam CT in Transcatheter Arterial Chemoembolization for Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

PURPOSE: To review available evidence for use of cone-beam CT during transcatheter arterial chemoembolization in hepatocellular carcinoma (HCC) for detection of tumor and feeding arteries. MATERIALS AND METHODS: Literature searches were conducted from inception to May 15, 2016, in PubMed (MEDLINE), Scopus, and Cochrane Central Register of Controlled Trials. Searches included "cone beam," "CBCT," "C-arm," "CACT," "cone-beam CT," "volumetric CT," "volume computed tomography," "volume CT," AND "liver," "hepatic*," "hepatoc*." Studies that involved adults with HCC specifically and treated with transcatheter arterial chemoembolization that used cone-beam CT were included. RESULTS: Inclusion criteria were met by 18 studies. Pooled sensitivity of cone-beam CT for detecting tumor was 90% (95% confidence interval [CI], 82%-95%), whereas pooled sensitivity of digital subtraction angiography (DSA) for tumor detection was 67% (95% CI, 51%-80%). Pooled sensitivity of cone-beam CT for detecting tumor feeding arteries was 93% (95% CI, 91%-95%), whereas pooled sensitivity of DSA was 55% (95% CI, 36%-74%). CONCLUSIONS: Cone-beam CT can significantly increase detection of tumors and tumor feeding arteries during transcatheter arterial chemoembolization. Cone-beam CT should be considered as an adjunct tool to DSA during transcatheter arterial chemoembolization treatments of HCC.

The Role of Dual-Phase Cone-Beam CT in Predicting Short-Term Response after Transarterial Chemoembolization for Hepatocellular Carcinoma.

PURPOSE: To identify computational and qualitative features derived from dual-phase cone-beam CT that predict short-term response in patients undergoing transarterial chemoembolization for hepatocellular carcinoma (HCC). MATERIALS AND METHODS: This retrospective study included 43 patients with 59 HCCs. Six features were extracted, including intensity of tumor enhancement on both phases and characteristics of the corona on the washout phase. Short-term response was evaluated by modified Response Evaluation Criteria in Solid Tumors on follow-up imaging, and extracted features were correlated to response using univariate and multivariate analyses. RESULTS: Univariate and multivariate analyses did not reveal a correlation between absolute and relative tumor enhancement characteristics on either phase with response (arterial P = .21; washout P = .40; ∆ P = .90). On multivariate analysis of qualitative characteristics, the presence of a diffuse corona was an independent predictor of incomplete response (P = .038) and decreased the odds ratio of objective response by half regardless of tumor size. CONCLUSIONS: Computational features extracted from contrast-enhanced dual-phase cone-beam CT are not prognostic of response to transarterial chemoembolization in patients with HCC. HCCs that demonstrate a diffuse, patchy corona have reduced odds of achieving complete response after transarterial chemoembolization and should be considered for additional treatment with an alternative modality.

Feasibility study of Compton cameras for x-ray fluorescence computed tomography with humans.

X-ray fluorescence imaging is a promising imaging technique able to depict the spatial distributions of low amounts of molecular agents in vivo. Currently, the translation of the technique to preclinical and clinical applications is hindered by long scanning times as objects are scanned with flux-limited narrow pencil beams. The study presents a novel imaging approach combining x-ray fluorescence imaging with Compton imaging. Compton cameras leverage the imaging performance of XFCT and abolish the need for pencil beam excitation. The study examines the potential of this new imaging approach on the base of Monte-Carlo simulations. In the work, it is first presented that the particular option of slice/fan-beam x-ray excitation has advantages in image reconstruction in regard of processing time and image quality compared to traditional volumetric Compton imaging. In a second experiment, the feasibility of the approach for clinical applications with tracer agents made from gold nano-particles is examined in a simulated lung scan scenario. The high energy of characteristic x-ray photons from gold is advantageous for deep tissue penetration and has lower angular blurring in the Compton camera. It is found that Doppler broadening in the first detector stage of the Compton camera adds the largest contribution on the angular blurring; physically limiting the spatial resolution. Following the analysis of the results from the spatial resolution test, resolutions in the order of one centimeter are achievable with the approach in the center of the lung. The concept of Compton imaging allows one to distinguish to some extent between scattered photons and x-ray fluorescent photons based on their difference in emission position. The results predict that molecular sensitivities down to 240 pM l-1 for 5 mm diameter lesions at 15 mGy for 50 nm diameter gold nano-particles are achievable. A 45-fold speed up time for data acquisition compared to traditional pencil beam XFCT could be achieved for lung imaging at the cost of a small sensitivity decrease.

High Resolution X-ray-Induced Acoustic Tomography.

Absorption based CT imaging has been an invaluable tool in medical diagnosis, biology, and materials science. However, CT requires a large set of projection data and high radiation dose to achieve superior image quality. In this letter, we report a new imaging modality, X-ray Induced Acoustic Tomography (XACT), which takes advantages of high sensitivity to X-ray absorption and high ultrasonic resolution in a single modality. A single projection X-ray exposure is sufficient to generate acoustic signals in 3D space because the X-ray generated acoustic waves are of a spherical nature and propagate in all directions from their point of generation. We demonstrate the successful reconstruction of gold fiducial markers with a spatial resolution of about 350 µm. XACT reveals a new imaging mechanism and provides uncharted opportunities for structural determination with X-ray.

Theoretical detection threshold of the proton-acoustic range verification technique.

PURPOSE: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. METHODS: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1-10 µs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. RESULTS: The calculated noise in the transducer was 12-28 mPa, depending on the transducer central frequency (70-380 kHz). The minimum number of protons detectable by the technique was on the order of 3-30 × 10(6) per pulse, with 30-800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 µs pulses producing signals with frequency less than 100 kHz. CONCLUSIONS: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10(6) protons/pulse and beam current.

Proton-induced x-ray fluorescence CT imaging.

PURPOSE: To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations. METHODS: First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%-5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm(2) CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%-5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data. RESULTS: A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R(2) > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images. CONCLUSIONS: Proton-induced x-ray fluorescence CT imaging of 3%-5% gold solutions in a small animal sized water phantom has been demonstrated for the first time by means of experiments and MC simulations.

Evaluation of intrinsic respiratory signal determination methods for 4D CBCT adapted for mice.

PURPOSE: 4D CT imaging in mice is important in a variety of areas including studies of lung function and tumor motion. A necessary step in 4D imaging is obtaining a respiratory signal, which can be done through an external system or intrinsically through the projection images. A number of methods have been developed that can successfully determine the respiratory signal from cone-beam projection images of humans, however only a few have been utilized in a preclinical setting and most of these rely on step-and-shoot style imaging. The purpose of this work is to assess and make adaptions of several successful methods developed for humans for an image-guided preclinical radiation therapy system. METHODS: Respiratory signals were determined from the projection images of free-breathing mice scanned on the X-RAD system using four methods: the so-called Amsterdam shroud method, a method based on the phase of the Fourier transform, a pixel intensity method, and a center of mass method. The Amsterdam shroud method was modified so the sharp inspiration peaks associated with anesthetized mouse breathing could be detected. Respiratory signals were used to sort projections into phase bins and 4D images were reconstructed. Error and standard deviation in the assignment of phase bins for the four methods compared to a manual method considered to be ground truth were calculated for a range of region of interest (ROI) sizes. Qualitative comparisons were additionally made between the 4D images obtained using each of the methods and the manual method. RESULTS: 4D images were successfully created for all mice with each of the respiratory signal extraction methods. Only minimal qualitative differences were noted between each of the methods and the manual method. The average error (and standard deviation) in phase bin assignment was 0.24 ± 0.08 (0.49 ± 0.11) phase bins for the Fourier transform method, 0.09 ± 0.03 (0.31 ± 0.08) phase bins for the modified Amsterdam shroud method, 0.09 ± 0.02 (0.33 ± 0.07) phase bins for the intensity method, and 0.37 ± 0.10 (0.57 ± 0.08) phase bins for the center of mass method. Little dependence on ROI size was noted for the modified Amsterdam shroud and intensity methods while the Fourier transform and center of mass methods showed a noticeable dependence on the ROI size. CONCLUSIONS: The modified Amsterdam shroud, Fourier transform, and intensity respiratory signal methods are sufficiently accurate to be used for 4D imaging on the X-RAD system and show improvement over the existing center of mass method. The intensity and modified Amsterdam shroud methods are recommended due to their high accuracy and low dependence on ROI size.

Experimental validation of L-shell x-ray fluorescence computed tomography imaging: phantom study.

Thanks to the current advances in nanoscience, molecular biochemistry, and x-ray detector technology, x-ray fluorescence computed tomography (XFCT) has been considered for molecular imaging of probes containing high atomic number elements, such as gold nanoparticles. The commonly used XFCT imaging performed with K-shell x rays appears to have insufficient imaging sensitivity to detect the low gold concentrations observed in small animal studies. Low energy fluorescence L-shell x rays have exhibited higher signal-to-background ratio and appeared as a promising XFCT mode with greatly enhanced sensitivity. The aim of this work was to experimentally demonstrate the feasibility of L-shell XFCT imaging and to assess its achievable sensitivity. We built an experimental L-shell XFCT imaging system consisting of a miniature x-ray tube and two spectrometers, a silicon drift detector (SDD), and a CdTe detector placed at [Formula: see text] with respect to the excitation beam. We imaged a 28-mm-diameter water phantom with 4-mm-diameter Eppendorf tubes containing gold solutions with concentrations of 0.06 to 0.1% Au. While all Au vials were detectable in the SDD L-shell XFCT image, none of the vials were visible in the CdTe L-shell XFCT image. The detectability limit of the presented L-shell XFCT SDD imaging setup was 0.007% Au, a concentration observed in small animal studies.

Optimized Detector Angular Configuration Increases the Sensitivity of X-ray Fluorescence Computed Tomography (XFCT).

In this work, we demonstrated that an optimized detector angular configuration based on the anisotropic energy distribution of background scattered X-rays improves X-ray fluorescence computed tomography (XFCT) detection sensitivity. We built an XFCT imaging system composed of a bench-top fluoroscopy X-ray source, a CdTe X-ray detector, and a phantom motion stage. We imaged a 6.4-cm-diameter phantom containing different concentrations of gold solution and investigated the effect of detector angular configuration on XFCT image quality. Based on our previous theoretical study, three detector angles were considered. The X-ray fluorescence detector was first placed at 145 (°) (approximating back-scatter) to minimize scatter X-rays. XFCT image quality was compared to images acquired with the detector at 60 (°) (forward-scatter) and 90 (°) (side-scatter). The datasets for the three different detector positions were also combined to approximate an isotropically arranged detector. The sensitivity was optimized with detector in the 145 (°) back-scatter configuration counting the 78-keV gold Kß1 X-rays. The improvement arose from the reduced energy of scattered X-ray at the 145 (°) position and the large energy separation from gold K ß1 X-rays. The lowest detected concentration in this configuration was 2.5 mgAu/mL (or 0.25% Au with SNR = 4.3). This concentration could not be detected with the 60 (°) , 90 (°) , or isotropic configurations (SNRs = 1.3, 0, 2.3, respectively). XFCT imaging dose of 14 mGy was in the range of typical clinical X-ray CT imaging doses. To our knowledge, the sensitivity achieved in this experiment is the highest in any XFCT experiment using an ordinary bench-top X-ray source in a phantom larger than a mouse ( > 3 cm).

Synergistic assembly of heavy metal clusters and luminescent organic bridging ligands in metal-organic frameworks for highly efficient X-ray scintillation.

We have designed two metal-organic frameworks (MOFs) to efficiently convert X-ray to visible-light luminescence. The MOFs are constructed from M6(µ3-O)4(µ3-OH)4(carboxylate)12 (M = Hf or Zr) secondary building units (SBUs) and anthracene-based dicarboxylate bridging ligands. The high atomic number of Zr and Hf in the SBUs serves as effective X-ray antenna by absorbing X-ray photons and converting them to fast electrons through the photoelectric effect. The generated electrons then excite multiple anthracene-based emitters in the MOF through inelastic scattering, leading to efficient generation of detectable photons in the visible spectrum. The MOF materials thus serve as efficient X-ray scintillators via synergistic X-ray absorption by the metal-cluster SBUs and optical emission by the bridging ligands.

Order of magnitude sensitivity increase in X-ray Fluorescence Computed Tomography (XFCT) imaging with an optimized spectro-spatial detector configuration: theory and simulation.

The purpose of this study was to increase the sensitivity of XFCT imaging by optimizing the data acquisition geometry for reduced scatter X-rays. The placement of detectors and detector energy window were chosen to minimize scatter X-rays. We performed both theoretical calculations and Monte Carlo simulations of this optimized detector configuration on a mouse-sized phantom containing various gold concentrations. The sensitivity limits were determined for three different X-ray spectra: a monoenergetic source, a Gaussian source, and a conventional X-ray tube source. Scatter X-rays were minimized using a backscatter detector orientation (scatter direction > 110(°) to the primary X-ray beam). The optimized configuration simultaneously reduced the number of detectors and improved the image signal-to-noise ratio. The sensitivity of the optimized configuration was 10 µg/mL (10 pM) at 2 mGy dose with the mono-energetic source, which is an order of magnitude improvement over the unoptimized configuration (102 pM without the optimization). Similar improvements were seen with the Gaussian spectrum source and conventional X-ray tube source. The optimization improvements were predicted in the theoretical model and also demonstrated in simulations. The sensitivity of XFCT imaging can be enhanced by an order of magnitude with the data acquisition optimization, greatly enhancing the potential of this modality for future use in clinical molecular imaging.

Hard X-ray-induced optical luminescence via biomolecule-directed metal clusters.

Here, we demonstrate that biomolecule-directed metal clusters are applicable in the study of hard X-ray excited optical luminescence, promising a new direction in the development of novel X-ray-activated imaging probes.