Purpose: This work aims to develop a framework to accurately and efficiently simulate metallic objects used during interventional oncology (IO) procedures and their artifacts in computed tomography (CT) images of different body regions.
Approach: A metal insertion framework based on an existing lesion insertion tool was developed. Noise and beam hardening models were incorporated into the model and validated by comparing images of real and artificially inserted metallic rods of known material composition and dimensions. The framework was further validated by inserting ablation probes into a water phantom and comparing image appearance to scans of real probes at matching locations in the phantom. Finally, a comprehensive library of metallic probes used in our IO practice was generated and a graphical user interface was built to efficiently insert any number of probes at arbitrary positions in patient CT data, including projection and image domain insertions.
Results: Metallic rod experiments demonstrated that noise and beam hardening were properly modeled. Phantom and patient data with virtually inserted probes demonstrated similar artifact appearance and magnitude compared with real probes. The developed user interface resulted in accurately co-registered virtual probes both with and without accompanying artifacts from projection and image domain insertions, respectively.
Conclusions: The developed metal insertion framework successfully replicates metallic object and artifact appearance with projection domain insertions and provides corresponding artifact-free images with the metallic object in the identical location through image domain insertion. This framework has potential to generate robust training libraries for deep learning algorithms and facilitate image quality optimization in interventional CT.
Numerous advances in CT imaging have led to improved image guidance for interventional oncology procedures. However, image artifacts stemming from metal devices used during procedures have remained a persistent problem. Severe artifacts introduced by metallic treatment devices significantly degrade image quality in anatomical regions of interest and can substantially reduce the confidence of the interventional radiologist in accurate probe placement. The purpose of this work is to develop a framework to accurately simulate the presence of metal objects in CT images, which could be used for image quality assessment and development of artifact mitigation strategies. The projection domain insertion framework was developed based on an existing lesion insertion tool. New noise and beam hardening models were developed and incorporated into the insertion algorithm to better replicate the artifactual signal produced by the metal objects. These models were validated by comparing images of real and artificially inserted metallic rods with known material composition and dimensions in head and body CT phantoms. The validated model was applied to a single cryoablation probe, which was imaged with routine clinical acquisition parameters and reconstructed with three different sets of reconstruction settings to evaluate their effects on probe segmentation and eventual insertion performance. To determine the optimal digital probe model derived from CT images, the segmented probes were inserted into the projection data from a water phantom and compared to the corresponding water images with the real probe. Additional phantom studies were conducted with two probes positioned such that they were coplanar with the imaging plane, to fully evaluate the severity of the simulated metal artifacts. Finally, a comprehensive library of metallic probes used in our clinical practice during cryoablation and microwave ablation procedures was generated, and an intuitive graphical user interface was built to facilitate efficient insertion of any number of different probes at arbitrary positions in patient CT data. Results from the metallic rod experiments demonstrated that quantum noise, electronic noise, and beam hardening were properly modeled. Further, digital probe models derived from probe images from high resolution reconstructions with an extended HU scale yielded simulated image artifacts consistent with presentation of real artifacts; whereas, using probe models derived from segmentations of clinical reconstructions or high resolution reconstruction without the extended HU scale did not. Extension of the insertion model to two coplanar probes demonstrated production of realistic artifacts with similar magnitude and texture to real probes. Lastly, the model was successfully applied to patient data and generated convincing artifacts as compared to patient images with real probes.
Channelized Hotelling observer (CHO), which has been shown to be well correlated with human observer performance in many clinical CT tasks, has a great potential to become the method of choice for objective image quality assessment. However, the use of CHO in clinical CT is still quite limited, mainly due to its complexity in measurement and calculation in practice, and the lack of access to an efficient and validated software tool for most clinical users. In this work, a web-based software platform for CT image quality assessment and protocol optimization (CTPro) was introduced. A validated CHO tool, along with other common image quality assessment tools, was made readily accessible through this web platform for clinical users and researchers without the need of installing additional software. An example of its application to evaluation of convolutional-neural-network (CNN)-based denoising was demonstrated.
Energy-integrating-detector (EID)-based triple-beam multi-energy CT (TB-MECT) was recently implemented on a dual-source (DS) CT platform by mounting a z-axis split-filter (0.05 mm Au, 0.6 mm Sn) on one of the two tubes. The purpose of this work is to perform a feasibility animal study on this new MECT platform for a small bowel imaging task using two contrast agents, iodine and bismuth. Optimal triple-beam configurations, 70/Au140/Sn140 kV were determined in a phantom study for this task and applied in the animal study for best material decomposition imaging performance. The results demonstrated that the TB-MECT can successfully separate and quantify the two contrast agents from one single scan for the task of small bowel imaging.
A fast scan with a high helical pitch is desirable for many CT exams, such as pediatric, chest, and some of cardiovascular exams, to suppress patient motion artifacts. However, on a single-source scanner, the pitch typically cannot exceed ~1.5 without generating image distortion within the entire scanning field of view due to insufficient data acquired in a fast pitch mode. In this work, we developed a deep convolutional neural network-based approach to reducing artifacts on images reconstructed from insufficient data acquired in an ultra-fast-pitch mode (𝑝𝑝 ≥ 2.0). This custom-designed neural network, referred to as Ultra-fast-pitch image reconstruction neural network (UFP-net) consists of functional modules using both local and non-local operators, as well as the z-coordinate of each image, to effectively suppress the location- and structure-dependent artifacts induced by the fast-pitch mode. The UFP-net was trained using a customized loss function that involves image-gradient-correlation loss and feature reconstruction loss. Projection data at a regular pitch (𝑝𝑝 = 1.0) and a fast-pitch (𝑝𝑝 = 3.0) were simulated using 10 patient CT cases to generate training and validation datasets. Compared to filtered-back-projection (FBP), the UFP-net largely suppressed image artifacts and restored anatomical details. The structural similarity index (SSIM) was significantly improved (Mean SSIM: UFP-net 0.9, FBP 0.6), and the root-mean-square-error (RMSE) was largely reduced (Mean RMSE: UFP-net 57 HU, FBP 273 HU). The proposed method has the potential to enable ultra-fast-pitch data acquisition on single-source CT scanners to improve scanning speed while maintaining image quality.
Prior information is often included in the basis material decomposition to solve the quantification problem of three-material mixtures in dual-energy computed tomography (DECT). Multienergy computed tomography (MECT) with more than two energy bins can provide a sufficient solution to this problem without invoking additional prior information. However, a question remains as to whether the prior information should still be included in the material decomposition process using MECT to improve the quantification accuracy and control noise amplification. This study aims to evaluate the impact of the prior information on noise and quantification bias in both DECT and MECT. The material decomposition tasks we used in this study are to quantify water/iodine, water/iodine/gadolinium, and water/ iodine/calcium in two- and three-material decompositions, under the assumption that the object to be decomposed consists of the basis materials and their mixtures. We performed phantom simulation and experimental studies using a clinical DECT system and a research photon-counting-detector-based MECT system. Results in the current phantom studies show that the prior information can still improve the noise performance without substantially affecting the basis material quantitative accuracy during the material decomposition process, even when the number of x-ray energy beams/bins is equal or greater than the number of basis materials.
Multi-energy CT (MECT) enabled by energy-resolved photon-counting-detector CT (PCD-CT) is promising for materialspecific imaging with multiple contrast agents. However, non-idealities of the PCD such as pulse pileup, K-edge escape, and charge sharing may degrade the spectral performance. To perform MECT, an alternative approach was proposed by extending a “Twin Beam” design to a dual-source CT scanner with energy-integrating-detector (EID) by operating one or both sources in the “Twin Beam” mode to acquire three (triple-beam configuration) or four (quadruple-beam configuration) distinct X-ray beam measurements. Previous computer simulation studies demonstrated that the image quality and dose efficiency of the triple-beam configuration were comparable to that in PCD-CT for a three-material decomposition task involving iodine, bismuth, and water. The purpose of this work is to experimentally validate the proposed triple-beam MECT technique in comparison with PCD-CT. To mimic the dual-source triple-beam acquisition, two separate scans, one at 80 kV and the other at 120 kV operated in the “Twin Beam” mode, were performed on a single-source CT scanner. Two potential clinical applications of MECT for multiple contrast agents were investigated: iodine/gadolinium for biphasic liver imaging and iodine/bismuth for small bowel imaging. The results indicate that the imaging performance of the EID-based MECT may be comparable to that on the current PCD-CT platform for both the iodine/gadolinium and the iodine/bismuth material decomposition tasks.
Energy-resolved photon-counting-detector CT (PCD-CT) is promising for material-specific imaging of multiple contrast agents. In each PCD-CT scan, two groups of images can be reconstructed, namely threshold images and bin images, and both can be directly used for material decomposition. The performance may differ for different energy thresholds and imaging tasks and it remains unclear which group of images should be used. The purpose of this work is to evaluate the imaging performance of threshold images and bin images when they are used for a three-material decomposition task (iodine, gadolinium, and water) in PCD-CT. Material decomposition was performed in image-space by using both an ordinary least squares (OLS) method and a generalized least squares (GLS) method. Both numerical analysis and phantom experiments were conducted, which demonstrated that: 1) compared with OLS, GLS provided improved noise properties using either threshold or bin images; 2) for the GLS method, when the covariances among images are taken into account, threshold and bin images showed almost identical material-specific imaging performance. This work suggested that, when correlations among images are incorporated into material decomposition, threshold and bin images perform equivalently well.
Energy-resolved photon-counting-detector CT (PCD-CT) is promising for material decomposition with multiple contrast agents using two or more energy bins. However, corrections for nonidealities of PCDs are required, which are still active research topics. In addition, PCD-CT is also likely to have a very high cost due to the current lack of mass production capabilities. We proposed an alternative approach to perform multienergy CT (MECT), which is achieved by acquiring triple or quadruple x-ray beam measurements on a dual-source CT scanner. This strategy was based on a “twin-beam” design on a single-source scanner for dual-energy CT. Examples of beam filters and spectra for triple and quadruple x-ray beam were provided. Computer simulation studies were performed to evaluate the noise and accuracy of material decomposition for multiple contrast mixtures using both triple- and quadruple-beam configurations, compared with the performance on a PCD-CT platform. The results demonstrated that the image quality and dose efficiency of the triple-beam configuration in the proposed MECT technique were comparable to that in PCD-CT. The proposed technique can be readily implemented on a dual-source scanner, which may allow material decomposition of multiple contrast agents to be performed on clinical CT scanners with energy-integrating detectors.
In order to perform material decomposition for a three-material mixture, dual-energy CT (DECT) has to incorporate an additional condition, typically the prior information related to certain physical constraints such as volume or mass conservation. With the introduction of photon-counting CT and other multi-energy CT (MECT) platform, more than 2 energy bins can be simultaneously acquired, which in principle can solve a three-material problem without the need of additional prior information. The purpose of this work was to investigate the impact of prior information on noise and bias properties of three-material decomposition in both DECT and MECT, and to evaluate if the prior information is still needed in MECT. Computer simulation studies were performed to compare basis image noise and quantification accuracy among DECT with prior information, and MECT with/without prior information. For given spectral configurations, the simulation results showed that significant noise reductions can be achieved in all the basis material images when prior information was included in the material decomposition process. Compared to DECT with prior information, MECT (N=3) with prior information had slightly better noise performance due to additional beam measurement and well preserved spectral separation. In addition, when wrong prior information ([-2.0%, 2.0%]) was intentionally introduced, the quantification accuracy evaluated by root-mean-square-error (RMSR) using MECT with prior information was less than 1.5mg/cc for gadolinium quantification and 1.2mg/cc for iodine quantification.
Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task. The human observer study was performed on CT images from 7 abdominal CT exams. A noise insertion tool was employed to synthesize CT scans at two additional dose levels. A validated lesion insertion tool was used to numerically insert metastatic liver lesions of various sizes and contrasts into both phantom and patient images. We selected 12 conditions out of 72 possible experimental conditions to evaluate the correlation at various radiation doses, lesion sizes, lesion contrasts and reconstruction algorithms. CHO with both single and multi-slice viewing modes were strongly correlated with HO. The corresponding Pearson’s correlation coefficient was 0.982 (with 95% confidence interval (CI) [0.936, 0.995]) and 0.989 (with 95% CI of [0.960, 0.997]) in multi-slice and single-slice viewing modes, respectively. Therefore, this study demonstrated the potential to use the simplest single-slice CHO to assess image quality for more realistic clinically relevant CT detection tasks.
The characteristic performance of a photon counting detector for X-ray fluorescence (XRF) imaging of gold nanoparticles (GNPs) is investigated. The investigations are first performed in three aspects: X-ray photon energy (keV) to pulse height (mV) conversion, noise floor determination, and linear detection ranges. Then, theoretical models are applied to evaluate the detection efficiency of X-ray photons with respect to an increased incident photon rate. Last, through exciting 100% pure GNPs by a conventional X-ray tube operated at a voltage of 110kVp, we acquire XRF spectrum in the threshold mode, based on which multi-energy thresholds are selected for XRF imaging of GNPs with low concentrations. Preliminary XRF imaging results of GNPs obtained in the imaging mode are presented and analyzed. This investigation study is essential to the development of fast and accurate XRF imaging of GNPs as well as other high atomic (Z) imaging contrast agents absorbed in cancerous cells.
Excessive exposure to radiation increases the risk of cancer. We present the concept and design of a new imaging paradigm, X-ray induced acoustic computed tomography (XACT). Applying this innovative technology to breast imaging, one single X-ray exposure can generate a 3D acoustic image, which dramatically reduces the radiation dose to patients when compared to beast CT. A theoretical model is developed to analyze the sensitivity of XACT. A noise equivalent pressure model is used for calculating the minimal radiation dose in XACT imaging. Furthermore, K-Wave simulation is employed to study the acoustic wave propagation in breast tissue. Theoretical analysis shows that the X-ray induced acoustic signal has a 100% relative sensitivity to the X-ray absorption (given that the percentage change in the X-ray absorption coefficient yields the same percentage change in the acoustic signal amplitude), but not to X-ray scattering. The final detection sensitivity is primarily limited by the thermal noise. The radiation dose can be reduced by a factor of 100 compared with the newly FDA approved breast CT. Reconstruction result shows that breast calcification with diameter of 80 μm can be observed in XACT image by using ultrasound transducers with 5.5 MHz center frequency. Therefore, with the proposed innovative technology, one can potentially reduce radiation dose to patient in breast imaging as compared with current x-ray modalities.
This study compares the spatial resolution in step-and-shoot and continuous motion acquisition modes of digital tomosynthesis using a bench-top prototype designed for breast phantoms imaging. The prototype employs a flat panel detector with a 50 μm pixel pitch, a micro focus x-ray tube and a motorized stage. A sharp metal edge with a thickness of 0.2 mm was used to measure the modulation transfer function (MTF). The edge was rotated from −7.5° to +7.5° with 1.5° increments to acquire 11 angular projections using 40 kVp, 500 μA with 5.55 s per projection. In continuous motion mode, the motorized stage moved the test object for the whole exposure time at a speed of 0.377 mm/s. The impact of acquisition speed in continuous DBT was also investigated, and a high speed of 0.753 mm/s was used. In step-and-shoot mode, the cutoff frequencies (10% MTF) in projection view (0°) and reconstructed DBT slices were 5.55 lp/mm and 4.95 lp/mm. Spatial resolution dropped in the continuous motion mode of the DBT due to the blur caused by the rotation of the stage and the cutoff frequencies reduced to 3.6 lp/mm and 3.18 lp/mm in the projection view (0º) and reconstructed DBT slices. At high rotational speed in continuous motion mode, the cutoff frequencies in the DBT slices dropped by 17 % to 2.65 lp/mm. Rotational speed of the rotation stage and spatial resolution are interconnected. Hence, reducing the motion blur in the continuous acquisition mode is important to maintain high spatial resolution for diagnostic purposes.
X-ray fluorescence (XRF) is a promising spectroscopic technique to characterize imaging contrast agents with high atomic numbers (Z) such as gold nanoparticles (GNPs) inside small objects. Its utilization for biomedical applications, however, is greatly limited to experimental research due to longer data acquisition time. The objectives of this study are to apply a photon counting detector array for XRF imaging and to determine an optimized XRF data acquisition time, at which the acquired XRF image is of acceptable quality to allow the maximum level of radiation dose reduction. A prototype laboratory XRF imaging configuration consisting of a pencil-beam X-ray and a photon counting detector array (1 × 64 pixels) is employed to acquire the XRF image through exciting the prepared GNP/water solutions. In order to analyze the signal to noise ratio (SNR) improvement versus the increased exposure time, all the XRF photons within the energy range of 63 - 76KeV that include two Kα gold fluorescence peaks are collected for 1s, 2s, 3s, and so on all the way up to 200s. The optimized XRF data acquisition time for imaging different GNP solutions is determined as the moment when the acquired XRF image just reaches a quality with a SNR of 20dB which corresponds to an acceptable image quality.
The objective of this study was to characterize the operating parameters of an in-vivo micro CT system. In-plane spatial resolution, noise, geometric accuracy, CT number uniformity and linearity, and phase effects were evaluated using various phantoms. The system employs a flat panel detector with a 127 μm pixel pitch, and a micro focus x-ray tube with a focal spot size ranging from 5-30 μm. The system accommodates three magnification sets of 1.72, 2.54 and 5.10. The in-plane cutoff frequencies (10% MTF) ranged from 2.31 lp/mm (60 mm FOV, M=1.72, 2×2 binning) to 13 lp/mm (10 mm FOV, M=5.10, 1×1 binning). The results were qualitatively validated by a resolution bar pattern phantom and the smallest visible lines were in 30-40 μm range. Noise power spectrum (NPS) curves revealed that the noise peaks exponentially increased as the geometric magnification (M) increased. True in-plane pixel spacing and slice thickness were within 2% of the system’s specifications. The CT numbers in cone beam modality are greatly affected by scattering and thus they do not remain the same in the three magnifications. A high linear relationship (R2 > 0.999) was found between the measured CT numbers and Hydroxyapatite (HA) loadings of the rods of a water filled mouse phantom. Projection images of a laser cut acrylic edge acquired at a small focal spot size of 5 μm with 1.5 fps revealed that noticeable phase effects occur at M=5.10 in the form of overshooting at the boundary of air and acrylic. In order to make the CT numbers consistent across all the scan settings, scatter correction methods may be a valuable improvement for this system.
Accurate background estimation to isolate the fluorescence signals is an important issue for quantitative X-ray fluorescence (XRF) analysis of gold nanoparticles (GNPs). Though a good estimation can be obtained experimentally through acquiring the background spectrum of water solution, it inevitably leads to unnecessary second exposure in reality. Thus, several numerical methods such as trapezoidal shape estimation, interpolation by polynomial fitting and SNIP (Statistics sensitive Nonlinear Iterative Peak-Clipping) algorithm are proposed to achieve this goal. This paper aims to evaluate the estimation results calculated by these numerical methods through comparing with that acquired using the experimental way, in term of mean squared error (MSE). Four GNP/water solutions with various concentrations from 0.0% to 1.0% by weight are prepared. Then, ten spectra are acquired for each solution for further analysis, under the identical condition of using pencil beam x-ray and single spectrometer. Finally, the experimental and numerical methods are performed on these spectra within the optimally determined energy window and their statistical characteristics are analyzed and compared. These numerical background estimation methods as well as the evaluation methods can be easily extended to analyze the fluorescence signals of other nanoparticle biomarkers such as gadolinium, platinum and Barium in multiple biomedical applications.
Fluorescence in situ Hybridization technology is a commonly used tool to detect chromosome aberrations, which are often pathologically significant. Since manual FISH analysis is a tedious and time-consuming procedure, reliable and robust automated image acquisition and analysis are in demand. Under high magnification objective lenses such as 60x and 100x, the depth of field will often be too small and the FISH probes may not always lie in the same focal plane. A statistical variance based automated FISH analysis method is developed in order to address this problem. On a stack of slices at consecutive image planes with a step size d, the statistical variance alone the z-axis is calculated to form a 2-D matrix. Since pixels shift dramatically to high intensity at FISH probe location, the probes will manifest high peak values in the matrix. A computer-aided detection scheme based on top-hat transform is applied to the matrix to detect FISH probe signals. This study demonstrates a simple and robust method for FISH probe detection as well as a way of 2- D representation of 3-D data.
As one of the important components of optical microscopes, the condenser has a considerable impact on system
performance, especially on the depth of field (DOF). DOF is a critical technical feature in cytogenetic imaging that may
affect the efficiency and accuracy of clinical diagnosis. The purpose of this study is to investigate the influence of
microscopic condenser on DOF using a prototype of transmitted optical microscope, based on objective and subjective
evaluations. After the description of the relationship between condenser and objective lens and the theoretical analysis of
the condenser impact on system numerical aperture and DOF, a standard resolution pattern and several cytogenetic
samples are adopted to assess the condenser impact on DOF, respectively. The experimental results of these objective
and subjective evaluations are in agreement with the theoretical analysis and show that, under the specific intermediate
range of condenser numerical aperture ( NAcond ), the DOF value decreases with the increase of NAcond . Although the
above qualitative results are obtained under the experimental conditions with a specific prototype system, the methods
presented in this preliminary investigation could offer useful guidelines for optimizing operational parameters in
cytogenetic imaging.
The purpose of this study is to objectively investigate image sharpness of the metaphase chromosomes at different
scanning speeds. In cytogenetic imaging, high scanning speed is sometimes applied to optimize the efficiency. However,
at high scanning speed, the obtained image may be deteriorated, due to the scanning blur, under exposure and random
vibration of the scanning stage. In this study, the image sharpness of metaphase chromosomes is objectively evaluated.
A standard resolution target and several metaphase chromosomes are first imaged under different speeds, by a prototype
scanning microscope. Then the sharpness of the acquired images is objectively assessed using a sharpness function. For
this prototype system, the results demonstrate that the image sharpness of the metaphase chromosomes is optimized
when the scanning speed is 0.8mm/s, under the specified experimental conditions. The results of this study may be
useful for optimizing the efficiency and quality of clinical cytogenetic imaging procedures.
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