Dual Layer CT. In: Johnson T, Fink C, Schönberg SO, Reiser MF, editors. Dual Energy CT in Clinical Practice. Berlin: Springer Berlin Heidelberg; 2011. pp. 21-34. [DOI: 10.1007/174_2010_56]

Systematic Review on Learning-based Spectral CT

Spectral computed tomography (CT) has recently emerged as an advanced version of medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two main forms: dual-energy computed tomography (DECT) and photon-counting computed tomography (PCCT), which offer image improvement, material decomposition, and feature quantification relative to conventional CT. However, the inherent challenges of spectral CT, evidenced by data and image artifacts, remain a bottleneck for clinical applications. To address these problems, machine learning techniques have been widely applied to spectral CT. In this review, we present the state-of-the-art data-driven techniques for spectral CT.

Photon-counting CT via interleaved/gapped spectral channels: Feasibility and imaging performance

PURPOSE

Compared to energy-integration, photon-counting x-ray detection facilitates the spectral channelization (energy binning) in spectral CT and thus offers the opportunity of implementing data acquisition via sophisticated schemes, e.g., gapping or interleaving in spectral channels. In this article, we report our investigation of the performance of material decomposition based spectral imaging in photon-counting CT implemented in such data acquisition schemes, and their comparison with the benchmark scheme and other schemes without spectral gapping or interleaving.

MATERIALS AND METHODS

Using a deliberately designed anthropomorphic head phantom that mimics the intracranial soft tissues and bony structures, a simulation study is carried out with the focus on two-material decomposition-based spectral imaging in photon-counting CT, under both ideal and realistic detector spectral responses. The projection data are acquired in four spectral channels, and then are sorted to implement the schemes of gapping ((ch₁ , ch₃ ); (ch₂ , ch₄ ); (ch₁ , ch₄ )) and interleaving ((ch₁ , ch₃ )+(ch₂ , ch₄ ); (ch₁ , ch₄ )+(ch₂ , ch₃ ); ((ch₁ +ch₃ ), (ch₂ +ch₄ )); ((ch₁ +ch₄ ), (ch₂ +ch₃ ))) in spectral channels, in addition to the benchmark scheme ((ch₁ +ch₂ ), (ch₃ +ch₄ )) and other conventional schemes (ch₁ , ch₂ ), (ch₂ , ch₃ ) and (ch₃ , ch₄ ), where 'ch' denotes channel, '+' denote addition, and (·,·) the operation of material decomposition and image reconstruction. Using the contrast-to-noise ratio between targeted regions of interest as the figure of merit, we study the performance of spectral imaging (material specific and virtual monochromatic) associated with these spectral channelization schemes.

RESULTS

Under ideal detector spectral response, the scheme (ch₁ , ch₄ ) outperforms the benchmark scheme ((ch₁ +ch₂ ), (ch₃ +ch₄ )) and others in gapped and/or interleaved spectral channelization in material specific imaging, while the interleaved scheme (ch₁ , ch₄ )+(ch₂ , ch₃ ) performs the best in virtual monochromatic imaging. Notably, only about half x-ray dose is utilized in the scheme (ch₁ , ch₄ ) for image formation. Under realistic detector spectral response, the difference in imaging performance over all spectral channelization schemes diminishes, along with degradation in each scheme's individual performance. The results suggest that (i) different strategy in spectral channelization may have to be exercised in material specific imaging and virtual monochromatic imaging, respectively, and (ii) the spectral distortion in realistic detector's response due to charge-sharing, Compton scattering and fluorescent escaping should be mitigated as much as possible.

CONCLUSION

The spectral channelization schemes and associated imaging performance reported herein are novel and thus informative to the community, which may further the understanding of physical fundamentals and design principles for material decomposition based spectral imaging in photon-counting CT and other x-ray related imaging modalities. This article is protected by copyright. All rights reserved.

ACCURACY OF CT NUMBERS OBTAINED BY DIRA AND MONOENERGETIC PLUS ALGORITHMS IN DUAL-ENERGY COMPUTED TOMOGRAPHY

Dual-energy computed tomography (CT) can be used in radiotherapy treatment planning for the calculation of absorbed dose distributions. The aim of this work is to evaluate whether there is room for improvement in the accuracy of the Monoenergetic Plus algorithm by Siemens Healthineers. A Siemens SOMATOM Force scanner was used to scan a cylindrical polymethyl methacrylate phantom with four rod-inserts made of different materials. Images were reconstructed using ADMIRE and processed with Monoenergetic Plus. The resulting CT numbers were compared with tabulated values and values simulated by the proof-of-a-concept algorithm DIRA developed by the authors. Both the Monoenergetic Plus and DIRA algorithms performed well; the accuracy of attenuation coefficients was better than about ±1% at the energy of 70 keV. Compared with DIRA, the worse performance of Monoenergetic Plus was caused by its (i) two-material decomposition to iodine and water and (ii) imperfect suppression of the beam hardening artifact in ADMIRE.

Fast and effective single-scan dual-energy cone-beam CT reconstruction and decomposition denoising based on dual-energy vectorization

PURPOSE

Flat-panel detector (FPD) based dual-energy cone-beam computed tomography (DE-CBCT) is a promising imaging technique for dedicated clinical applications. In this paper, we proposed a fully analytical method for fast and effective single-scan DE-CBCT image reconstruction and decomposition.

METHODS

A rotatable Mo filter was inserted between an x-ray source and imaged object to alternately produce low and high-energy x-ray spectra. First, filtered-backprojection (FBP) method was applied on down-sampled projections to reconstruct low and high-energy images. Then, the two images were converted into a vectorized form represented with an amplitude and an argument image. Using amplitude image as a guide, a joint bilateral filter was applied to denoise the argument image. Then, high-quality dual-energy images were recovered from the amplitude image and the denoised argument image. Finally, the recovered dual-energy images were further used for low-noise material decomposition and electron density synthesis. Imaging was conducted on a Catphan^® 600 phantom and an anthropomorphic head phantom. The proposed method was evaluated via comparison with the traditional two-scan method and a commonly used filtering method (HYPR-LR).

RESULTS

On the Catphan^® 600 phantom, the proposed method successfully reduced streaking artifacts and preserved spatial resolution and noise-power-spectrum (NPS) pattern. In the electron density image, the proposed method increased contrast-to-noise ratio (CNR) by more than 2.5 times and achieved <1.2% error for electron density values. On the anthropomorphic head phantom, the proposed method greatly improved the soft-tissue contrast and the fine detail differentiation ability. In the selected ROIs on different human tissues, the differences between the CT number obtained by the proposed method and that by the two-scan method were less than 4 HU. In the material images, the proposed method suppressed noise by over 75.5% compared with two-scan results, and by over 40.4% compared with HYPR-LR results. Implementation of the whole algorithm took 44.5 s for volumetric imaging, including projection preprocessing, FBP reconstruction, joint bilateral filtering, and material decomposition.

CONCLUSIONS

Using down-sampled projections in single-scan DE-CBCT, the proposed method could effectively and efficiently produce high-quality DE-CBCT images and low-noise material decomposition images. This method demonstrated superior performance on spatial resolution enhancement, NPS preservation, noise reduction, and electron density accuracy, indicating better prospect in material differentiation and dose calculation.

Principal Component Analysis in Projection and Image Domains-Another Form of Spectral Imaging in Photon-Counting CT

OBJECTIVE

We explore the feasibility of principal component analysis (PCA) as a form of spectral imaging in photon-counting CT.

METHODS

Using the data acquired by a prototype system and simulated by computer, we investigate the feasibility of spectral imaging in photon-counting CT via PCA for feature extraction and study the impacts made by data standardization and de-noising on its performance.

RESULTS

The PCA in the projection domain maintains the data consistence that is essential for tomographic image reconstruction and performs virtually the same as that in the image domain. The first three primary components account for more than 99.99% covariance of the data. Within anticipation, the contrast-to-noise ratio (CNR) between the target and background in the first principal component image can be larger than that in the image generated from the data acquired in each energy bin. More importantly, the CNR in the first principal component image may be larger than that in the image formed by the summed data acquired in all energy bins (i.e., the conventional polychromatic CT image). In addition, de-noising can not only reduce the noise in images but also improve the effectiveness/efficiency of PCA in feature extraction.

CONCLUSION

The PCA in either projection or image domain provides another form of spectral imaging in photon-counting CT that fits the essential requirements on spectral imaging in true color.

SIGNIFICANCE

The verification of PCA's feasibility in CT as a form spectral imaging and observation of its potential superiority in CNR over conventional polychromatic CT are meaningful in theory and practice.

DXA-equivalent quantification of bone mineral density using dual-layer spectral CT scout scans

OBJECTIVES

To develop and evaluate a method for areal bone mineral density (aBMD) measurement based on dual-layer spectral CT scout scans.

METHODS

A post-processing algorithm using a pair of 2D virtual mono-energetic scout images (VMSIs) was established in order to semi-automatically compute the aBMD at the spine similarly to DXA, using manual soft tissue segmentation, semi-automatic segmentation for the vertebrae, and automatic segmentation for the background. The method was assessed based on repetitive measurements of the standardized European Spine Phantom (ESP) using the standard scout scan tube current (30 mA) and other tube currents (10 to 200 mA), as well as using fat-equivalent extension rings simulating different patient habitus, and was compared to dual-energy X-ray absorptiometry (DXA). Moreover, the feasibility of the method was assessed in vivo in female patients.

RESULTS

Derived from standard scout scans, aBMD values measured with the proposed method significantly correlated with DXA measurements (r = 0.9925, p < 0.001), and mean accuracy (DXA, 4.12%; scout, 1.60%) and precision (DXA, 2.64%; scout, 2.03%) were comparable between the two methods. Moreover, aBMD values assessed at different tube currents did not differ significantly (p ≥ 0.20 for all), suggesting that the presented method could be applied to scout scans with different settings. Finally, data derived from sample patients were concordant with BMD values from a reference age-matched population.

CONCLUSIONS

Based on dual-layer spectral scout scans, aBMD measurements were fast and reliable and significantly correlated with the according DXA measurements in phantoms. Considering the number of CT acquisitions performed worldwide, this method could allow truly opportunistic osteoporosis screening.

KEY POINTS

• 2D scout scans (localizer radiographs) from a dual-layer spectral CT scanner, which are mandatory parts of a CT examination, can be used to automatically determine areal bone mineral density (aBMD) at the spine. • The presented method allowed fast (< 25 s/patient), semi-automatic, and reliable DXA-equivalent aBMD measurements for state-of-the-art DXA phantoms at different tube settings and for various patient habitus, as well as for sample patients. • Considering the number of CT scout scan acquisitions performed worldwide on a daily basis, the presented technique could enable truly opportunistic osteoporosis screening with DXA-equivalent metrics, without involving higher radiation exposure since it only processes existing data that is acquired during each CT scan.

Current and Novel Techniques for Metal Artifact Reduction at CT: Practical Guide for Radiologists

Artifacts caused by metallic implants appear as dark and bright streaks at computed tomography (CT), which severely degrade the image quality and decrease the diagnostic value of the examination. When x-rays pass through a metal object, depending on its size and composition, different physical effects negatively affect the measurements in the detector, most notably the effects of photon starvation and beam hardening. To improve image quality and recover information about underlying structures, several artifact reduction methods have been introduced in modern CT systems. Projection-based metal artifact reduction (MAR) algorithms act in projection space and replace corrupted projections caused by metal with interpolation from neighboring uncorrupted projections. MAR algorithms primarily suppress artifacts that are due to photon starvation. The dual-energy CT technique is characterized by data acquisition at two different energy spectra. Dual-energy CT provides synthesized virtual monochromatic images at different photon energy (kiloelectron volt) levels, and virtual monochromatic images obtained at high kiloelectron volt levels are known to reduce the effects of beam hardening. In clinical practice, although MAR algorithms can be applied after image acquisition, the decision whether to apply dual-energy CT for the patient usually needs to be made before image acquisition. Radiologists should be more familiar with the clinical and technical features of each method and should be able to choose the optimal method according to the clinical situation. ^©RSNA, 2018.

Image quality of conventional images of dual-layer SPECTRAL CT: A phantom study

PURPOSE

Spectral CT using a dual layer detector offers the possibility of retrospectively introducing spectral information to conventional CT images. In theory, the dual-layer technology should not come with a dose or image quality penalty for conventional images. In this study, we evaluate the influence of a dual-layer detector (IQon Spectral CT, Philips Healthcare) on the image quality of conventional CT images, by comparing these images with those of a conventional but otherwise technically comparable single-layer CT scanner (Brilliance iCT, Philips Healthcare), by means of phantom experiments.

METHODS

For both CT scanners, conventional CT images were acquired using four adult scanning protocols: (a) body helical, (b) body axial, (c) head helical, and (d) head axial. A CATPHAN 600 phantom was scanned to conduct an assessment of image quality metrics at equivalent (CTDI) dose levels. Noise was characterized by means of noise power spectra (NPS) and standard deviation (SD) of a uniform region, and spatial resolution was evaluated with modulation transfer functions (MTF) of a tungsten wire. In addition, contrast-to-noise ratio (CNR), image uniformity, CT number linearity, slice thickness, slice spacing, and spatial linearity were measured and evaluated. Additional measurements of CNR, resolution and noise were performed in two larger phantoms.

RESULTS

The resolution levels at 50%, 10%, and 5% MTF of the iCT and IQon showed small, but significant differences up to 0.25 lp/cm for body scans, and up to 0.2 lp/cm for head scans in favor of the IQon. The iCT and IQon showed perfect CT linearity for body scans, but for head scans both scanners showed an underestimation of the CT numbers of materials with a high opacity. Slice thickness was slightly overestimated for both scanners. Slice spacing was comparable and reconstructed correctly. In addition, spatial linearity was excellent for both scanners, with a maximum error of 0.11 mm. CNR was higher on the IQon compared to the iCT for both normal and larger phantoms with differences up to 0.51. Spatial resolution did not change with phantom size, but noise levels increased significantly. For head scans, IQon had a noise level that was significantly lower than the iCT, on the other hand IQon showed noise levels significantly higher than the iCT for body scans. Still, these differences were well within the specified range of performance of iCT scanners.

CONCLUSIONS

At equivalent dose levels, this study showed similar quality of conventional images acquired on iCT and IQon for medium-sized phantoms and slightly degraded image quality for (very) large phantoms at lower tube voltages on the IQon. Accordingly, it may be concluded that the introduction of a dual-layer detector neither compromises image quality of conventional images nor increases radiation dose for normal-sized patients, and slightly degrades dose efficiency for large patients at 120 kVp and lower tube voltages.

Dual-energy CT: a phantom comparison of different platforms for abdominal imaging

OBJECTIVES

Evaluation of imaging performance across dual-energy CT (DECT) platforms, including dual-layer CT (DLCT), rapid-kVp-switching CT (KVSCT) and dual-source CT (DSCT).

METHODS

A semi-anthropomorphic abdomen phantom was imaged on these DECT systems. Scans were repeated three times for CTDIvol levels of 10 mGy, 20 mGy, 30 mGy and different fat-simulating extension rings. Over the available range of virtual-monoenergetic images (VMI), noise as well as quantitative accuracy of hounsfield units (HU) and iodine concentrations were evaluated.

RESULTS

For all VMI levels, HU values could be determined with high accuracy compared to theoretical values. For KVSCT and DSCT, a noise increase was observed towards lower VMI levels. A patient-size dependent increase in the uncertainty of quantitative iodine concentrations is observed for all platforms. For a medium patient size the iodine concentration root-mean-square deviation at 20 mGy is 0.17 mg/ml (DLCT), 0.30 mg/ml (KVSCT) and 0.77mg/ml (DSCT).

CONCLUSION

Noticeable performance differences are observed between investigated DECT systems. Iodine concentrations and VMI HUs are accurately determined across all DECT systems. KVSCT and DLCT deliver slightly more accurate iodine concentration values than DSCT for investigated scenarios. In DLCT, low-noise and high-image contrast at low VMI levels may help to increase diagnostic information in abdominal CT.

KEY POINTS

• Current dual-energy CT platforms provide accurate, reliable quantitative information. • Dual-energy CT cross-platform evaluation revealed noticeable performance differences between different systems. • Dual-layer CT offers constant noise levels over the complete energy range.

Proton radiography for inline treatment planning and positioning verification of small animals

INTRODUCTION

As proton therapy becomes increasingly well established, there is a need for high-quality clinically relevant in vivo data to gain better insight into the radiobiological effects of proton irradiation on both healthy and tumor tissue. This requires the development of easily applicable setups that allow for efficient, fractionated, image-guided proton irradiation of small animals, the most widely used pre-clinical model.

MATERIAL AND METHODS

Here, a method is proposed to perform dual-energy proton radiography for inline positioning verification and treatment planning. Dual-energy proton radiography exploits the differential enhancement of object features in two successively measured two-dimensional (2D) dose distributions at two different proton energies. The two raw images show structures that are dominated by energy absorption (absorption mode) or scattering (scattering mode) of protons in the object, respectively. Data post-processing allowed for the separation of both signal contributions in the respective images. The images were evaluated regarding recognizable object details and feasibility of rigid registration to acquired planar X-ray scans.

RESULTS

Robust, automated rigid registration of proton radiography and planar X-ray images in scattering mode could be reliably achieved with the animal bedding unit used as registration landmark. Distinguishable external and internal features of the imaged mouse included the outer body contour, the skull with substructures, the lung, abdominal structures and the hind legs. Image analysis based on the combined information of both imaging modes allowed image enhancement and calculation of 2D water-equivalent path length (WEPL) maps of the object along the beam direction.

DISCUSSION

Fractionated irradiation of exposed target volumes (e.g., subcutaneous tumor model or brain) can be realized with the suggested method being used for daily positioning and range determination. Robust registration of X-ray and proton radiography images allows for the irradiation of tumor entities that require conventional computed tomography (CT)-based planning, such as orthotopic lung or brain tumors, similar to conventional patient treatment.