Dual-source multienergy CT with triple or quadruple x-ray beams

A prototype spatial-spectral CT system for material decomposition with energy-integrating detectors

PURPOSE

Spectral CT has great potential for a variety of clinical applications due to improved tissue and material discrimination over conventional single-energy CT. Many clinical and preclinical spectral CT systems have two spectral channels enabling dual-energy CT. Strategies include split filtration, dual-layer detectors, photon-counting detectors, and kVp switching. The motivation for this work is the development of an x-ray source spectral modulation device with three or more spectral channels to enable high-sensitivity multi-material decomposition with energy-integrating detectors.

MATERIALS AND METHODS

We present spatial-spectral filters which are a new x-ray source modulation technology with the potential for additional channel diversity. The filtering device consists of an array of K-edge materials which divide the x-ray beam into spectrally varied beamlets. This design allows for an arbitrary number of spectral channels-trading off spatial and spectral information. We use a one-step model-based material decomposition (MBMD) algorithm to iteratively estimate material density images directly from the spatial-spectral CT data. In this work, we present a prototype spatial-spectral filter integrated with an x-ray CT test bench. The filter is composed of an array of tin, erbium, tantalum, and lead filter tiles which spatially modulate the system spectral sensitivity pattern. In a simulation study, we investigate the particular problem of mis-calibration between the data acquisition and the reconstruction model. With an understanding of the required model accuracy, we present a spectral calibration method to estimate the critical model parameters. To demonstrate feasibility of the spatial-spectral filter with a calibrated beamlet model, we collected a spatial-spectral CT scan of a multicontrast-enhanced phantom containing water, iodine, and gadolinium solutions.

RESULTS

With simulations, we show that material decomposition is possible with spatial-spectral-filtered CT data, and we demonstrate the importance of a well-calibrated physical model. We find a 50% increase in error for focal spot model mismatch of 0.27mm and gap width model mismatch of 16 mμ. With physical results, we demonstrate that the calibrated system model is in close agreement with the measured data, and that the reconstructed material density images match the ground truth concentrations for the multicontrast phantom. Empirical results indicate gadolinium density estimation had an error of 17-58% mostly due to a systematic constant bias of 0.30-0.60 mg/ml. Water density estimates are within 1% and iodine estimates are within 10% of ground truth.

CONCLUSION

These preliminary results demonstrate the potential of spatial-spectral filters to enable multicontrast imaging. Moreover, this device is compatible with energy-integrating detectors and so provides a feasible modification to enable spectral CT imaging with existing single-energy systems.

Dual Energy Differential Phase Contrast CT (DE-DPC-CT) Imaging

When more than two elemental materials are present in a given object, material quantification may not be robust and accurate when the routine two-material decomposition scheme in current dual energy CT imaging is employed. In this work, we present an innovative scheme to accomplish accurate three-material decomposition with measurements from a dual energy differential phase contrast CT (DE-DPC-CT) acquisition. A DE-DPC-CT system was constructed using a grating interferometer and a photon counting CT imaging system with two energy bins. The DE-DPC-CT system can simultaneously measure both the imaginary and the real part of the complex refractive index to enable a three-material decomposition. Physical phantom with 21 material inserts were constructed and measured using DE-DPC-CT system. Results demonstrated excellent accuracy in elemental material quantification. For example, relative root-mean-square errors of 4.5% for calcium and 5.2% for iodine were achieved using the proposed three-material decomposition scheme. Biological tissues with iodine inserts were used to demonstrate the potential utility of the proposed spectral CT imaging method. Experimental results showed that the proposed method correctly differentiates the bony structure, iodine, and the soft tissue in the biological specimen samples. A triple spectra CT scan was also performed to benchmark the performance of the DE-DPC-CT scan. Results demonstrated that the material decomposition from the DE-DPC-CT has a much lower quantification noise than that from the triple spectra CT scan.

Multi-energy CT imaging for large patients using dual-source photon-counting detector CT

Multi-energy CT imaging of large patients with conventional dual-energy (DE)-CT using an energy-integrating-detector (EID) is challenging due to photon starvation-induced image artifacts, especially in lower tube potential (80-100 kV) images. Here, we performed phantom experiments to investigate the performance of DECT for morbidly obese patients, using an iodine and water material decomposition task as an example, on an emulated dual-source (DS)-photon-counting-detector (PCD)-CT, and compared its performance with a clinical DS-EID-CT. An abdominal CT phantom with iodine inserts of different concentrations was wrapped with tissue-equivalent gel layers to emulate a large patient (50 cm lateral size). The phantom was scanned on a research whole-body single-source (SS)-PCD-CT (140 kV tube potential), a DS-PCD-CT (100/Sn140 kV; Sn140 indicates 140 kV with Sn filter), and a clinical DS-EID-CT (100/Sn140 kV) with the same radiation dose. Phantom scans were repeated five times on each system. The DS-PCD-CT acquisition was emulated by scanning twice on the SS-PCD-CT using different tube potentials. The multi-energy CT images acquired on each system were then reconstructed, and iodine- and water-specific images were generated using material decomposition. The root-mean-square-error (RMSE) between true and measured iodine concentrations were calculated for each system and compared. The images acquired on the DS-EID-CT showed severe artifacts, including ringing, reduced uniformity, and photon starvation artifacts, especially for low-energy images. These were largely reduced in DS-PCD-CT images. The CT number difference that was measured using regions-of-interest across field-of-view were reduced from 20.3 ± 0.9 (DS-EID-CT) to 2.5 ± 0.4 HU on DS-PCD-CT, showing improved image uniformity using DS-PCD-CT. Iodine RMSE was reduced from 3.42 ± 0.03 mg ml^-1 (SS-PCD-CT) and 2.90 ± 0.03 mg ml^-1 (DS-EID-CT) to 2.39 ± 0.05 mg ml^-1 using DS-PCD-CT. DS-PCD-CT out-performed a clinical DS-EID-CT for iodine and water-based material decomposition on phantom emulating obese patients by reducing image artifacts and improving iodine quantification (RMSE reduced by 20%). With DS-PCD-CT, multi-energy CT can be performed on large patients that cannot be accommodated with current DECT.

Multi-energy CT with Triple X-ray Beams: A Feasibility Animal Study

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.

Radiation dose efficiency of multi-energy photon-counting-detector CT for dual-contrast imaging

Compared to traditional multi-scan single-energy CT (SECT), one potential advantage of single-scan multi-energy CT (MECT) proposed for simultaneous imaging of multiple contrast agents is the radiation dose reduction. This phantom study aims to rigorously evaluate whether the radiation dose can truly be reduced in a single-scan MECT protocol (MECT_1s) in biphasic liver imaging with iodine and gadolinium, and small bowel imaging with iodine and bismuth, compared to traditional two-scan SECT protocols (SECT_2s). For MECT_1s, mixed iodine/gadolinium samples were prepared corresponding to late arterial/portal-venous phase for biphasic liver imaging. Mixed iodine/bismuth samples were prepared representing the arterial/enteric enhancement for small bowel imaging. For SECT_2s, separate contrast samples were prepared to mimic separate scans in arterial/venous phase and arterial/enteric enhancement. Samples were placed in a 35 cm wide water phantom and scanned by a research whole-body photon-counting-detector-CT (PCD-CT) system ('chess' mode). MECT images were acquired with optimized kV/threshold settings for each imaging task, and SECT images were acquired at 120 kV. Total CTDIvol was matched for the two protocols. Image-based three-material decomposition was employed in MECT_1s to determine the basis material concentration values, which were converted to CT numbers at 120 kV (i.e. virtual SECT images) to compare with the SECT images directly acquired with SECT_2s. The noise difference between the SECT and the virtual SECT images was compared to evaluate the dose efficiency of MECT_1s. Compared to SECT_2s, MECT_1s was not dose efficient for both imaging tasks. The amount of noise increase is highly task dependent, with noise increased by 203%/278% and 110%/82% in virtual SECT images for iodine/gadolinium and iodine/bismuth quantifications, respectively, corresponding to dose increase by 819%/1328% and 340%/230% in MECT_1s to achieve the same image noise level. MECT with the current PCD-CT technique requires higher radiation dose than SECT to achieve the same image quality.

Quantitative accuracy and dose efficiency of dual-contrast imaging using dual-energy CT: a phantom study

PURPOSE

To evaluate the quantitative accuracy and dose efficiency of simultaneous imaging of two contrast agents using dual-energy computed tomography (DECT), two imaging tasks each representing one potential clinical application were investigated in a phantom study: biphasic liver imaging with iodine and gadolinium, and small bowel imaging with iodine and bismuth.

METHODS

To separate and quantify mixtures of two contrast agents using a single DECT scan, mixed iodine and gadolinium samples were prepared with the contrast enhancement values corresponding to the late arterial (iodine) and the portal-venous (gadolinium) phase for biphasic liver imaging. Mixed iodine and bismuth samples were prepared mimicking the arterial (iodine) and the enteric (bismuth) enhancement for small bowel imaging. For comparison to the reference condition of performing two single-energy CT (SECT) scans, contrast samples were prepared separately to mimic separate scans in the arterial/venous phase and arterial/enteric enhancement. Samples were placed in a 35 cm wide water tank and scanned using a third-generation dual-source DECT scanner with three tube potential pairs: 80/Sn150, 90/Sn150, and 100/Sn150 kV, all with default dose partitioning between two x-ray beams to acquire DECT data. The same scanner operated in a single-energy mode acquired SECT data (120 kV). Total radiation dose (CTDIvol) was matched for the single-scan DECT and the two-scan SECT protocols. The DECT protocol was followed by a generic image-based three-material decomposition method to determine the material-specific images, based on which concentrations of each basis material were quantified and noise levels were measured. To compare with the SECT images directly acquired with the SECT protocol, the concentration values in each contrast-specific image were converted to CT numbers at 120 kV (i.e., virtual SECT (vSECT) images). The noise level and noise power spectra differences between the SECT and vSECT images were compared to evaluate the dose efficiency of the single-scan DECT protocol. The impact of dose partitioning in the DECT protocol on quantitative dual-contrast imaging performance was also studied.

RESULTS

For each imaging task, contrast materials were accurately quantified against the nominal concentrations using the DECT data with strong correlation (R²  ≥ 0.98 for both imaging tasks). Compared to the SECT protocol, the DECT protocol was not dose efficient. With the optimal x-ray tube potential pair 80/Sn150 kV, the noise level in vSECT images increased by 401%/488% (arterial/portal-venous) for the biphasic liver imaging task and by 10%/41% (arterial/enteric) for the small bowel imaging task compared to that in SECT images. The corresponding radiation dose increase is 2410%/3357% for the biphasic liver imaging task and 21%/99% for the small bowel imaging task, respectively, to achieve the same noise as that in SECT images. This could be improved by adjusting the dose partitioning in DECT.

CONCLUSIONS

DECT can be used to simultaneously separate and quantify two contrast materials. However, compared to a two-scan SECT protocol, much higher radiation dose is needed in a single-scan DECT protocol to achieve the same image noise, especially for tasks involving the dual contrast of iodine and gadolinium.

Feasibility of multi-contrast imaging on dual-source photon counting detector (PCD) CT: An initial phantom study

PURPOSE

Photon-counting-detector-computed tomography (PCD-CT) allows separation of multiple, simultaneously imaged contrast agents, such as iodine (I), gadolinium (Gd), and bismuth (Bi). However, PCDs suffer from several technical limitations such as charge sharing, K-edge escape, and pulse pile-up, which compromise spectral separation of multi-energy data and degrade multi-contrast imaging performance. The purpose of this work was to determine the performance of a dual-source (DS) PCD-CT relative to a single-source (SS) PCD-CT for the separation of simultaneously imaged I, Gd, and Bi contrast agents.

METHODS

Phantom experiments were performed using a research whole-body PCD-CT and head/abdomen-sized phantoms containing vials of different I, Gd, Bi concentrations. To emulate a DS-PCD-CT, the phantoms were scanned twice on the SS-PCD-CT using different tube potentials for each scan. A tube potential of 80 kV (energy thresholds = 25/50 keV) was used for low-energy tube, while the high-energy tube used Sn140 kV (Sn indicates tin filter) and thresholds of 25/90 keV. The same phantoms were scanned also on the SS-PCD-CT using the chess acquisition mode. In chess mode, the 4 × 4 subpixels within a macro detector pixel are split into two sets based on a chess-board pattern. With each subpixel set having two energy thresholds, chess mode allows four energy-bin data sets, which permits simultaneous multi-contrast imaging. Because of this design, only 50% area of each detector pixel is configured to receive photons of a pre-defined threshold, leading to 50% dose utilization efficiency. To compensate for this dose inefficiency, the radiation dose for this scan was doubled compared to DS-PCD-CT. A 140 kV tube potential and thresholds = 25/50/75/90 keV were used. These settings were determined based on the K-edges of Gd, and Bi, and were found to yield good differentiation of I/Gd/Bi based on phantom experiments and other literature. The energy-bin images obtained from each scan (scan pair) were used to generate I-, Gd-, Bi-specific image via material decomposition. Root-mean-square-error (RMSE) between the known and measured concentrations was calculated for each scenario. A 20-cm water cylinder phantom was scanned on both systems, which was used for evaluating the magnitude of noise, and noise power spectra (NPS) of I/Gd/Bi-specific images.

RESULTS

Phantom results showed that DS-PCD-CT reduced noise in material-specific images for both head and body phantoms compared to SS-PCD-CT. The noise level of SS-PCD was reduced from 2.55 to 0.90 mg/mL (I), 1.97 to 0.78 mg/mL (Gd), and 0.85 to 0.74 mg/mL (Bi) using DS-PCD. NPS analysis showed that the noise texture of images acquired on both systems is similar. For the body phantom, the RMSE for SS-PCD-CT was reduced relative to DS-PCD-CT from 10.52 to 2.76 mg/mL (I), 7.90 to 2.01 mg/mL (Gd), and 1.91 to 1.16 mg/mL (Bi). A similar trend was observed for the head phantom: RMSE reduced from 2.59 (SS-PCD) to 0.72 (DS-PCD) mg/mL (I), 2.02 to 0.58 mg/mL (Gd), and 0.85 to 0.57 mg/mL (Bi).

CONCLUSION

We demonstrate the feasibility of performing simultaneous imaging of I, Gd, and Bi materials on DS-PCD-CT. Under the condition without cross scattering, DS-PCD reduced the RMSE for quantification of material concentration in relative to a SS-PCD-CT system using chess mode.

Impact of prior information on material decomposition in dual- and multienergy computed tomography

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.

Quantification of multiple mixed contrast and tissue compositions using photon-counting spectral computed tomography

Quantitative material decomposition of multiple mixed, or spatially coincident, contrast agent (gadolinium and iodine) and tissue (calcium and water) compositions is demonstrated using photon-counting spectral computed tomography (CT). Material decomposition is performed using constrained maximum likelihood estimation (MLE) in the image domain. MLE is calibrated by multiple linear regression of all pure material compositions, which exhibits a strong correlation ( R 2 > 0.91 ) between the measured x-ray attenuation in each photon energy bin and known concentrations in the calibration phantom. Material decomposition of mixed compositions in the sample phantom provides color material concentration maps that clearly identify and differentiate each material. The measured area under the receiver operating characteristic curve is > 0.95 , indicating highly accurate material identification. Material decomposition also provides accurate quantitative estimates of material concentrations in mixed compositions with a root-mean-squared error < 12 % of the maximum concentration for each material. Thus, photon-counting spectral CT enables quantitative molecular imaging of multiple spatially coincident contrast agent (gadolinium and iodine) and tissue (calcium and water) compositions, which is not possible with current clinical molecular imaging modalities, such as nuclear imaging and magnetic resonance imaging.