Dual resolution cone beam breast CT: a feasibility study

Low-dose spectral CT reconstruction based on image-gradient L0-norm and adaptive spectral PICCS

The photon-counting detector based spectral computed tomography (CT) is promising for lesion detection, tissue characterization, and material decomposition. However, the lower signal-to-noise ratio within multi-energy projection dataset can result in poorly reconstructed image quality. Recently, as prior information, a high-quality spectral mean image was introduced into the prior image constrained compressed sensing (PICCS) framework to suppress noise, leading to spectral PICCS (SPICCS). In the original SPICCS model, the image gradient L₁-norm is employed, and it can cause blurred edge structures in the reconstructed images. Encouraged by the advantages in edge preservation and finer structure recovering, the image gradient L₀-norm was incorporated into the PICCS model. Furthermore, due to the difference of energy spectrum in different channels, a weighting factor is introduced and adaptively adjusted for different channel-wise images, leading to an L₀-norm based adaptive SPICCS (L₀-ASPICCS) algorithm for low-dose spectral CT reconstruction. The split-Bregman method is employed to minimize the objective function. Extensive numerical simulations and physical phantom experiments are performed to evaluate the proposed method. By comparing with the state-of-the-art algorithms, such as the simultaneous algebraic reconstruction technique, total variation minimization, and SPICCS, the advantages of our proposed method are demonstrated in terms of both qualitative and quantitative evaluation results.

Clinical Micro-CT Empowered by Interior Tomography, Robotic Scanning, and Deep Learning

While micro-CT systems are instrumental in preclinical research, clinical micro-CT imaging has long been desired with cochlear implantation as a primary application. The structural details of the cochlear implant and the temporal bone require a significantly higher image resolution than that (about 0.2 mm) provided by current medical CT scanners. In this paper, we propose a clinical micro-CT (CMCT) system design integrating conventional spiral cone-beam CT, contemporary interior tomography, deep learning techniques, and the technologies of a micro-focus X-ray source, a photon-counting detector (PCD), and robotic arms for ultrahigh-resolution localized tomography of a freely-selected volume of interest (VOI) at a minimized radiation dose level. The whole system consists of a standard CT scanner for a clinical CT exam and VOI specification, and a robotic micro-CT scanner for a local scan of high spatial and spectral resolution at minimized radiation dose. The prior information from the global scan is also fully utilized for background compensation of the local scan data for accurate and stable VOI reconstruction. Our results and analysis show that the proposed hybrid reconstruction algorithm delivers accurate high-resolution local reconstruction, and is insensitive to the misalignment of the isocenter position, initial view angle and scale mismatch in the data/image registration. These findings demonstrate the feasibility of our system design. We envision that deep learning techniques can be leveraged for optimized imaging performance. With high-resolution imaging, high dose efficiency and low system cost synergistically, our proposed CMCT system has great promise in temporal bone imaging as well as various other clinical applications.

Quantitative contrast-enhanced spectral mammography based on photon-counting detectors: A feasibility study

PURPOSE

To investigate the feasibility of accurate quantification of iodine mass thickness in contrast-enhanced spectral mammography.

MATERIALS AND METHODS

A computer simulation model was developed to evaluate the performance of a photon-counting spectral mammography system in the application of contrast-enhanced spectral mammography. A figure-of-merit (FOM), which was defined as the decomposed iodine signal-to-noise ratio (SNR) with respect to the square root of the mean glandular dose (MGD), was chosen to optimize the imaging parameters, in terms of beam energy, splitting energy, and prefiltrations for breasts of various thicknesses and densities. Experimental phantom studies were also performed using a beam energy of 40 kVp and a splitting energy of 34 keV with 3 mm Al prefiltration. A two-step calibration method was investigated to quantify the iodine mass thickness, and was validated using phantoms composed of a mixture of glandular and adipose materials, for various breast thicknesses and densities. Finally, the traditional dual-energy log-weighted subtraction method was also studied as a comparison. The measured iodine signal from both methods was compared to the known value to characterize the quantification accuracy and precision.

RESULTS

The optimal imaging parameters, which lead to the highest FOM, were found at a beam energy between 42 and 46 kVp with a splitting energy at 34 keV. The optimal tube voltage decreased as the breast thickness or the Al prefiltration increased. The proposed quantification method was able to measure iodine mass thickness on phantoms of various thicknesses and densities with high accuracy. The root-mean-square (RMS) error for cm-scale lesion phantoms was estimated to be 0.20 mg/cm² . The precision of the technique, characterized by the standard deviation of the measurements, was estimated to be 0.18 mg/cm² . The traditional weighted subtraction method also predicted a linear correlation between the measured signal and the known iodine mass thickness. However, the correlation slope and offset values were strongly dependent on the total breast thickness and density.

CONCLUSION

The results of this study suggest that iodine mass thickness for cm-scale lesions can be accurately quantified with contrast-enhanced spectral mammography. The quantitative information can potentially improve the differential power for malignancy.

Augmented laminography, a correlative 3D imaging method for revealing the inner structure of compressed fossils

Non-destructive imaging techniques can be extremely useful tools for the investigation and the assessment of palaeontological objects, as mechanical preparation of rare and valuable fossils is precluded in most cases. However, palaeontologists are often faced with the problem of choosing a method among a wide range of available techniques. In this case study, we employ x-ray computed tomography (CT) and computed laminography (CL) to study the first fossil xiphosuran from the Muschelkalk (Middle Triassic) of the Netherlands. The fossil is embedded in micritic limestone, with the taxonomically important dorsal shield invisible, and only the outline of its ventral part traceable. We demonstrate the complementarity of CT and CL which offers an excellent option to visualize characteristic diagnostic features. We introduce augmented laminography to correlate complementary information of the two methods in Fourier space, allowing to combine their advantages and finally providing increased anatomical information about the fossil. This method of augmented laminography enabled us to identify the xiphosuran as a representative of the genus Limulitella.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling. Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm  ×  25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise. Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8  ×  higher CNR (at matched spatial resolution) compared to the constant penalty. The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

Radiation doses in volume-of-interest breast computed tomography--A Monte Carlo simulation study

PURPOSE

Cone beam breast computed tomography (breast CT) with true three-dimensional, nearly isotropic spatial resolution has been developed and investigated over the past decade to overcome the problem of lesions overlapping with breast anatomical structures on two-dimensional mammographic images. However, the ability of breast CT to detect small objects, such as tissue structure edges and small calcifications, is limited. To resolve this problem, the authors proposed and developed a volume-of-interest (VOI) breast CT technique to image a small VOI using a higher radiation dose to improve that region's visibility. In this study, the authors performed Monte Carlo simulations to estimate average breast dose and average glandular dose (AGD) for the VOI breast CT technique.

METHODS

Electron-Gamma-Shower system code-based Monte Carlo codes were used to simulate breast CT. The Monte Carlo codes estimated were validated using physical measurements of air kerma ratios and point doses in phantoms with an ion chamber and optically stimulated luminescence dosimeters. The validated full cone x-ray source was then collimated to simulate half cone beam x-rays to image digital pendant-geometry, hemi-ellipsoidal, homogeneous breast phantoms and to estimate breast doses with full field scans. 13-cm in diameter, 10-cm long hemi-ellipsoidal homogeneous phantoms were used to simulate median breasts. Breast compositions of 25% and 50% volumetric glandular fractions (VGFs) were used to investigate the influence on breast dose. The simulated half cone beam x-rays were then collimated to a narrow x-ray beam with an area of 2.5 × 2.5 cm(2) field of view at the isocenter plane and to perform VOI field scans. The Monte Carlo results for the full field scans and the VOI field scans were then used to estimate the AGD for the VOI breast CT technique.

RESULTS

The ratios of air kerma ratios and dose measurement results from the Monte Carlo simulation to those from the physical measurements were 0.97 ± 0.03 and 1.10 ± 0.13, respectively, indicating that the accuracy of the Monte Carlo simulation was adequate. The normalized AGD with VOI field scans was substantially reduced by a factor of about 2 over the VOI region and by a factor of 18 over the entire breast for both 25% and 50% VGF simulated breasts compared with the normalized AGD with full field scans. The normalized AGD for the VOI breast CT technique can be kept the same as or lower than that for a full field scan with the exposure level for the VOI field scan increased by a factor of as much as 12.

CONCLUSIONS

The authors' Monte Carlo estimates of normalized AGDs for the VOI breast CT technique show that this technique can be used to markedly increase the dose to the breast and thus the visibility of the VOI region without increasing the dose to the breast. The results of this investigation should be helpful for those interested in using VOI breast CT technique to image small calcifications with dose concern.

Breast tissue decomposition with spectral distortion correction: a postmortem study

PURPOSE

To investigate the feasibility of an accurate measurement of water, lipid, and protein composition of breast tissue using a photon-counting spectral computed tomography (CT) with spectral distortion corrections.

METHODS

Thirty-eight postmortem breasts were imaged with a cadmium-zinc-telluride-based photon-counting spectral CT system at 100 kV. The energy-resolving capability of the photon-counting detector was used to separate photons into low and high energy bins with a splitting energy of 42 keV. The estimated mean glandular dose for each breast ranged from 1.8 to 2.2 mGy. Two spectral distortion correction techniques were implemented, respectively, on the raw images to correct the nonlinear detector response due to pulse pileup and charge-sharing artifacts. Dual energy decomposition was then used to characterize each breast in terms of water, lipid, and protein content. In the meantime, the breasts were chemically decomposed into their respective water, lipid, and protein components to provide a gold standard for comparison with dual energy decomposition results.

RESULTS

The accuracy of the tissue compositional measurement with spectral CT was determined by comparing to the reference standard from chemical analysis. The averaged root-mean-square error in percentage composition was reduced from 15.5% to 2.8% after spectral distortion corrections.

CONCLUSIONS

The results indicate that spectral CT can be used to quantify the water, lipid, and protein content in breast tissue. The accuracy of the compositional analysis depends on the applied spectral distortion correction technique.

Sparse-view spectral CT reconstruction using spectral patch-based low-rank penalty

Spectral computed tomography (CT) is a promising technique with the potential for improving lesion detection, tissue characterization, and material decomposition. In this paper, we are interested in kVp switching-based spectral CT that alternates distinct kVp X-ray transmissions during gantry rotation. This system can acquire multiple X-ray energy transmissions without additional radiation dose. However, only sparse views are generated for each spectral measurement; and the spectra themselves are limited in number. To address these limitations, we propose a penalized maximum likelihood method using spectral patch-based low-rank penalty, which exploits the self-similarity of patches that are collected at the same position in spectral images. The main advantage is that the relatively small number of materials within each patch allows us to employ the low-rank penalty that is less sensitive to intensity changes while preserving edge directions. In our optimization formulation, the cost function consists of the Poisson log-likelihood for X-ray transmission and the nonconvex patch-based low-rank penalty. Since the original cost function is difficult to minimize directly, we propose an optimization method using separable quadratic surrogate and concave convex procedure algorithms for the log-likelihood and penalty terms, which results in an alternating minimization that provides a computational advantage because each subproblem can be solved independently. We performed computer simulations and a real experiment using a kVp switching-based spectral CT with sparse-view measurements, and compared the proposed method with conventional algorithms. We confirmed that the proposed method improves spectral images both qualitatively and quantitatively. Furthermore, our GPU implementation significantly reduces the computational cost.

Compensator models for fluence field modulated computed tomography

PURPOSE

Fluence field modulated computed tomography (FFMCT) presents a novel approach for acquiring CT images, whereby a patient model guides dynamically changing fluence patterns in an attempt to achieve task-based, user-prescribed, regional variations in image quality, while also controlling dose to the patient. This work aims to compare the relative effectiveness of FFMCT applied to different thoracic imaging tasks (routine diagnostic CT, lung cancer screening, and cardiac CT) when the modulator is subject to limiting constraints, such as might be present in realistic implementations.

METHODS

An image quality plan was defined for a simulated anthropomorphic chest slice, including regions of high and low image quality, for each of the thoracic imaging tasks. Modulated fluence patterns were generated using a simulated annealing optimization script, which attempts to achieve the image quality plan under a global dosimetric constraint. Optimization was repeated under different types of modulation constraints (e.g., fixed or gantry angle dependent patterns, continuous or comprised of discrete apertures) with the most limiting case being a fixed conventional bowtie filter. For each thoracic imaging task, an image quality map (IQMsd) representing the regionally varying standard deviation is predicted for each modulation method and compared to the prescribed image quality plan as well as against results from uniform fluence fields. Relative integral dose measures were also compared.

RESULTS

Each IQMsd resulting from FFMCT showed improved agreement with planned objectives compared to those from uniform fluence fields for all cases. Dynamically changing modulation patterns yielded better uniformity, improved image quality, and lower dose compared to fixed filter patterns with optimized tube current. For the latter fixed filter cases, the optimal choice of tube current modulation was found to depend heavily on the task. Average integral dose reduction compared to a uniform fluence field ranged from 10% using a bowtie filter to 40% or greater using an idealized modulator.

CONCLUSIONS

The results support that FFMCT may achieve regionally varying image quality distributions in good agreement with user-prescribed values, while limiting dose. The imposition of constraints inhibits dose reduction capacity and agreement with image quality plans but still yields significant improvement over what is afforded by conventional dose minimization techniques. These results suggest that FFMCT can be implemented effectively even when the modulator has limited modulation capabilities.

Volume-of-interest imaging of the inner ear in a human temporal bone specimen using a robot- driven C-arm flat panel detector CT system

VOI imaging can provide higher image quality at a reduced dose for a subregion. In this study with a robot-driven C-arm FDCT system, the goals were proof of feasibility for inner ear imaging, higher flexibility during data acquisition, and easier processing during reconstruction. First a low-dose OV scan was acquired allowing an orientation and enabling the selection of the VOI. The C-arm was then moved by the robotic system without a need for patient movement and the VOI was scanned with adapted parameters. Uncompromised artifact-free image quality was achieved by the 2-scan approach and the dose was reduced by 80%-90% in comparison with conventional MSCT and FPCT scans.

Abnormal pixel detection using sum-of-projections symmetry in cone beam computed tomography

A novel abnormal pixels (APs) detection approach is proposed to remove artefacts from reconstructed images in cone beam computed tomography (CBCT). This approach is based on the symmetry detection of sum-of-projections (SOP). Because some factors affect the SOP symmetry, we combine dyadic wavelet transform-based singularity detection to extract the APs. Next, the Laplacian solution (LS) method is employed to restore the APs in each projection image. Experimental results demonstrate the efficiency of our approach for different imaging tasks.

High resolution dual detector volume-of-interest cone beam breast CT--Demonstration with a bench top system

PURPOSE

In this study, we used a small field high resolution detector in conjunction with a full field flat panel detector to implement and investigate the dual detector volume-of-interest (VOI) cone beam breast computed tomography (CBCT) technique on a bench-top system. The potential of using this technique to image small calcifications without increasing the overall dose to the breast was demonstrated. Significant reduction of scatter components in the high resolution projection image data of the VOI was also shown.

METHODS

With the regular flat panel based CBCT technique, exposures were made at 80 kVp to generate an air kerma of 6 mGys at the isocenter. With the dual detector VOI CBCT technique, a high resolution small field CMOS detector was used to scan a cylindrical VOI (2.5 cm in diameter and height, 4.5 cm off-center) with collimated x-rays at four times of regular exposure level. A flat panel detector was used for full field scan with low x-ray exposures at half of the regular exposure level. The low exposure full field image data were used to fill in the truncated space in the VOI scan data and generate a complete projection image set. The Feldkamp-Davis-Kress (FDK) filtered backprojection algorithm was used to reconstruct high resolution images for the VOI. Two scanning techniques, one breast centered and the other VOI centered, were implemented and investigated. Paraffin cylinders with embedded thin aluminum (Al) wires were imaged and used in conjunction with optically stimulated luminescence (OSL) dose measurements to demonstrate the ability of this technique to image small calcifications without increasing the mean glandular dose (MGD).

RESULTS

Using exposures that produce an air kerma of 6 mGys at the isocenter, the regular CBCT technique was able to resolve the cross-sections of Al wires as thin as 254 μm in diameter in the phantom. For the specific VOI studied, by increasing the exposure level by a factor of 4 for the VOI scan and reducing the exposure level by a factor of 2 for the full filed scan, the dual-detector CBCT technique was able to resolve the cross-sections of Al wires as thin as 152 μm in diameter. The CNR evaluated for the entire Al wire cross-section was found to be improved from 5.5 in regular CBCT to 14.4 and 16.8 with the breast centered and VOI centered scanning techniques, respectively. Even inside VOI center, the VOI scan resulted in significant dose saving with the dose reduced by a factor of 1.6 at the VOI center. Dose saving outside the VOI was substantial with the dose reduced by a factor of 7.3 and 7.8 at the breast center for the breast centered and VOI centered scans, respectively, when compared to full field scan at the same exposure level. The differences between the two dual detector techniques in terms of dose saving and scatter reduction were small with VOI scan at 4× exposure level and full field scan at 0.5 × exposure level. The MGDs were only 94% of that from the regular CBCT scan.

CONCLUSIONS

For the specific VOI studied, the dual detector VOI CBCT technique has the potential to provide high quality images inside the VOI with MGD similar to or even lower than that of full field breast CBCT. It was also found that our results were compromised by the use of inadequate detectors for the VOI scan. An appropriately selected detector would better optimize the image quality improvement that can be achieved with the VOI CBCT technique.

Region-of-interest material decomposition from truncated energy-resolved CT

PURPOSE

Energy-resolved CT using photon-counting detectors has the potential to provide improved material decomposition compared to dual-kVp approaches. However, available photon-counting detectors are susceptible to pulse-pileup artifacts, especially at the periphery of the field of view (FOV) where the object attenuation is low compared to the center of the FOV. Pulse pileup may be avoided by imaging a region-of-interest (ROI) where the dynamic range is expected to be limited. This work investigated performing material decomposition and reconstructing ROI basis images from truncated energy-resolved data.

METHODS

A method is proposed to reconstruct images of basis functions primarily contained within the ROI, such as targeted or localized K-edge contrast agents. Material decomposition is performed independently for each ray in the sinogram, followed by filtered backprojection from the truncated data encompassing the ROI. A second method is proposed that uses a prior conventional energy-integrating image to estimate energy-resolved data outside the ROI. The measured and estimated energy-resolved data are decomposed into basis projections and merged into basis sinograms of the full FOV. Basis images of the ROI are then reconstructed through filtered backprojection. This method is most easily applied to objects that do not contain K-edge contrast agents outside the ROI. Simulations of a voxelized thorax phantom with iodine in the blood pool and a detector with five energy bins were performed. Full FOV, truncated, and truncated data merged with data estimated from the prior energy-integrating image were decomposed into Compton, photoelectric, and iodine basis functions. An empirical weighting factor was determined to blend the merged sinogram at the boundary of the truncated data. The effects of noise and misalignment in the prior image were also quantified. Basis images of the central 15 cm × 15 cm ROI containing the heart were reconstructed via filtered backprojection. Basis image accuracy was quantified relative to gold-standard basis images reconstructed from full FOV energy-resolved data.

RESULTS

The error in the iodine basis image reconstructed from truncated energy-resolved data without prior information was less than 1% for the central 7 cm of the 7.5-cm-radius ROI and 3% at the edge of the ROI. When the truncated and estimated basis sinograms were blended, the error was below 1% throughout the ROI for photoelectric basis images and ranged from 1% at the center of the ROI to 4% at the edge for the Compton basis image.

CONCLUSIONS

The density of localized K-edge contrast agents can be estimated to within 1% error using filtered back projection without prior information. For noncontrast and localized-contrast scans, ROI images of general basis functions can be reconstructed to within a few percent error using a prior energy-integrating image. The ability to perform material decomposition for a limited ROI may facilitate energy-resolved CT with available photon-counting detectors.

Volume-of-interest (VOI) imaging in C-arm flat-detector CT for high image quality at reduced dose

PURPOSE

A novel method for flat-detector computed tomography was developed to enable volume-of-interest (VOI) imaging at high resolution, low noise, and reduced dose. For this, a full low-dose overview (OV) scan and a local high-dose scan of a VOI are combined.

METHODS

The first scan yields an overview of the whole object and enables the selection of an arbitrary VOI. The second scan of that VOI assures high image quality within the interesting volume. The combination of the two consecutive scans is based on a forward projection of the reconstructed OV volume that was registered to the VOI. The artificial projection data of the OV scan are combined with the measured VOI data in the raw data domain. Different projection values are matched by an appropriate transformation and weighting. The reconstruction is performed with a standard Feldkamp-type algorithm. In simulations, the combination of OV scan and VOI scan was investigated on a mathematically described phantom. In measurements, spatial resolution and noise were evaluated with image quality phantoms. Modulation transfer functions and noise values were calculated. Measurements of an anthropomorphic head phantom were used to validate the proposed method for realistic applications, e.g., imaging stents. In Monte Carlo simulations, 3D dose distributions were calculated and dose values were assessed quantitatively.

RESULTS

By the proposed combination method, an image is generated which covers the whole object and provides the VOI at high image quality. In the OV image, a resolution of 0.7 lp/mm (line pairs per millimeter) and noise of 63.5 HU were determined. Inside the VOI, resolution was increased to 2.4 lp/mm and noise was decreased to 18.7 HU. For the performed measurements, the cumulative dose was significantly reduced in comparison to conventional scans by up to 93%. The dose of a high-quality scan, for example, was reduced from 97 to less than 7 mGy, while keeping image quality constant within the VOI.

CONCLUSIONS

The proposed VOI application with two scans is an effective way to ensure high image quality within the VOI while simultaneously reducing the cumulative patient dose.