Virtual monochromatic images of dual-energy CT as an alternative to single-energy CT: performance comparison using a detectability index for different acquisition techniques.

OBJECTIVES: To investigate the performance of virtual monochromatic (VM) images with the same dose and iodine contrast as those for single-energy (SE) images using five dual-energy (DE) scanners with DE techniques: two generations of fast kV switching (FKS), two generations of dual source (DS), and one split filter (SF). METHODS: A water-bath phantom with a diameter of 300 mm, which contains one rod-shaped phantom made of a material equivalent to soft-tissue and two rod-shaped phantoms made of diluted iodine (2 and 12 mg/mL), was scanned using both SE (120, 100, and 80 kV) and DE techniques with the same CT dose index in each scanner. The VM energy at which the CT number of the iodine rod is closest to that of each SE tube voltage was determined as the equivalent energy (Eeq). A detectability index (d') was calculated from the noise power spectrum, the task transfer functions, and a task function corresponding to each rod. The percentage of the d' value of the VM image to that of the corresponding SE image was calculated for performance comparison. RESULTS: The average percentages of d' of FKS1, FKS2, DS1, DS2, and SF were 84.6%, 96.2%, 94.3%, 107%, and 104% for 120 kV-Eeq; 75.9%, 91.2%, 88.2%, 99.2%, and 82.6% for 100 kV-Eeq; 71.6%, 88.9%, 82.6%, 85.2%, and 62.3% for 80 kV-Eeq, respectively. CONCLUSION: The performance of VM images was on the whole inferior to that of SE images especially at low equivalent energy levels, depending on the DE techniques and their generations. KEY POINTS: • This study evaluated the performance of VM images with the same dose and iodine contrast as those for SE images using five DE scanners. • The performance of VM images varied with the DE techniques and their generations and was mostly inferior at low equivalent energy levels. • The results highlight the importance of distribution of available dose over the two energy levels and spectral separation for the performance improvement of VM images.

Reduction of streak artifacts caused by low photon counts utilizing an image-based forward projection in computed tomography.

BACKGROUND: The streak artifacts in computed tomography (CT) images caused by low photon counts are known to be effectively suppressed by raw-data-based techniques. This study aims to propose a technique to reduce the streak artifact without accessing the raw data. METHODS: The proposed streak artifact reduction (SAR) technique consists of three steps: numerical forward projection to a CT image, adaptive filtering of the generated sinogram, and image reconstruction from the processed sinogram. The authors have expanded the two-dimensional method (2D-SAR) to three dimensions (3D-SAR) by using consecutive CT images. The modulation transfer function (MTF), the image noise (standard deviation), and the visibility of comb-shaped objects were evaluated at a low dose of 5 mGy. Using anthropomorphic abdominal and chest phantoms, CT images and the artifact index (AI) were compared between 3D-SAR and two types of iterative reconstruction (IR). RESULTS: Sufficient artifact reductions associated with 54% and 61% reduction of noise for 2D- and 3D-SAR, respectively, were obtained in the phantom images, although the 50%MTF decreased by 28%. The visibility of the combs was improved with both the 2D- and 3D-SAR methods. The AI results of 3D-SAR were better than one type of IR and almost equal to the other type of IR, which was consistent with observed artifacts. CONCLUSION: Both 2D-SAR and 3D-SAR have turned out to be effective in reducing streak artifacts. The proposed technique will be an effective tool since it needs no raw data, and thus can be applied to any CT images produced by a wide variety of CT systems.

Performance of clinically available deep learning image reconstruction in computed tomography: a phantom study.

Purpose: To assess the physical performance of deep learning image reconstruction (DLIR) compared with those of filtered back projection (FBP) and iterative reconstruction (IR) and to estimate the dose reduction potential of the technique. Approach: A cylindrical water bath phantom with a diameter of 300 mm including two rods composed of acrylic and soft tissue-equivalent material was scanned using a clinical computed tomography (CT) scanner at four dose levels (CT dose index of 20, 15, 10, and 5 mGy). Phantom images were reconstructed using FBP, DLIR, and IR. The in-plane and z axis task transfer functions (TTFs) and in-plane noise power spectrum (NPS) were measured. The dose reduction potential was estimated by evaluating the system performance function calculated from TTF and NPS. The visibilities of a bar pattern phantom placed in the same water bath phantom were compared. Results: The use of DLIR resulted in a notable decrease in noise magnitude. The shift in peak NPS frequency was reduced compared with IR. Preservation of in-plane TTF was superior using DLIR than using IR. The estimated dose reduction potentials of DLIR and IR were 39% to 54% and 19% to 29%, respectively. However, the z axis resolution was decreased with DLIR by 6% to 21% compared with FBP. The bar pattern visibilities were approximately consistent with the TTF results in both planes. Conclusions: The in-plane edge-preserving noise reduction performance of DLIR is superior to that of IR. Moreover, DLIR enables approximately half-dose acquisitions with no deterioration in noise texture in cases that permit some z axis resolution reduction.

Algorithm-based artifact reduction in patients with arms-down positioning in computed tomography.

PURPOSE: Arm-artifact, a type of streak artifact frequently observed in computed tomography (CT) images obtained at arms-down positioning in polytrauma patients, is known to degrade image quality. This study aimed to develop a novel arm-artifact reduction algorithm (AAR) applied to projection data. METHODS: A phantom resembling an adult abdomen with two arms was scanned using a 16-row CT scanner. The projection data were processed by AAR, and CT images were reconstructed. The artifact reduction for the same phantom was compared with that achieved by two latest iterative reconstruction (IR) techniques (IR1 and IR2) using a normalized artifact index (nAI) at two locations (ventral and dorsal side). Image blurring as a processing side effect was compared with IR2 of the model-based IR using a plastic needle phantom. Additionally, the projection data of two clinical cases were processed using AAR, and the image noise was evaluated. RESULTS: AAR and IR2 significantly reduced nAI by 87.5% and 74.0%, respectively at the ventral side and 84.2% and 69.6%, respectively, at the dorsal side compared with each filtered back projection (P < 0.01), whereas IR1 did not. The proposed algorithm mostly maintained the original spatial resolution, compared with IR2, which yielded apparent image blurring. The image noise in the clinical cases was also reduced significantly (P < 0.01). CONCLUSIONS: AAR was more effective and superior than the latest IR techniques and is expected to improve the image quality of polytrauma CT imaging with arms-down positioning.

Object shape dependency of in-plane resolution for iterative reconstruction of computed tomography.

The present study aimed to investigate whether the in-plane resolution property of iterative reconstruction (IR) of computed tomography (CT) data is object shape-dependent by testing columnar shapes with diameters of 3, 7, and 10cm (circular edge method) and a cubic shape with 5-cm side lengths (linear edge method). For each shape, objects were constructed of acrylic (contrast in Hounsfield units [ΔHU]=120) as well as a soft tissue equivalent material (ΔHU=50). For each shape, we measured the modulation transfer functions (MTFs) of IR and filtered back projection (FBP) using two multi-slice CT scanners at scan doses of 5 and 10mGy. In addition, we evaluated a thin metal wire using the conventional method at 10mGy. For FBP images, the MTF results of the tested objects and the wire method showed substantial agreement, thus demonstrating the validity of our analysis technique. For IR images, the MTF results of different shapes were nearly identical for each object contrast and dose combination, and we did not observe shape-dependent effects of the resolution properties of either tested IR. We conclude that both the circular edge method and linear edge method are equally useful for evaluating the resolution properties of IRs.

[Image quality evaluation of new image reconstruction methods applying the iterative reconstruction].

The purpose of this study was to evaluate the image quality of an iterative reconstruction method, the iterative reconstruction in image space (IRIS), which was implemented in a 128-slices multi-detector computed tomography system (MDCT), Siemens Somatom Definition Flash (Definition). We evaluated image noise by standard deviation (SD) as many researchers did before, and in addition, we measured modulation transfer function (MTF), noise power spectrum (NPS), and perceptual low-contrast detectability using a water phantom including a low-contrast object with a 10 Hounsfield unit (HU) contrast, to evaluate whether the noise reduction of IRIS was effective. The SD and NPS were measured from the images of a water phantom. The MTF was measured from images of a thin metal wire and a bar pattern phantom with the bar contrast of 125 HU. The NPS of IRIS was lower than that of filtered back projection (FBP) at middle and high frequency regions. The SD values were reduced by 21%. The MTF of IRIS and FBP measured by the wire phantom coincided precisely. However, for the bar pattern phantom, the MTF values of IRIS at 0.625 and 0.833 cycle/mm were lower than those of FBP. Despite the reduction of the SD and the NPS, the low-contrast detectability study indicated no significant difference between IRIS and FBP. From these results, it was demonstrated that IRIS had the noise reduction performance with exact preservation for high contrast resolution and slight degradation of middle contrast resolution, and could slightly improve the low contrast detectability but with no significance.

[New method of measuring effective energy using copper-pipe absorbers in X-ray CT].

The general method of measuring the half-value layer (HVL) for X-ray computed tomography (CT) using square aluminum-sheet filters is inconvenient in that the X-ray tube has to be set to stationary mode. To avoid this inconvenience, we investigated a new method using copper-pipe filters that cover the ionization chamber (copper-pipe method). Using this method, the HVL can be measured at the isocenter in the rotation modes of CT. We examined the accuracy and reproducibility of the copper-pipe method compared with those of the general method. The effective energy measured using the copper-pipe method correlated well with the general method (y=1.064x, r=0.987), and its error was 1.81±1.38%. The results indicate that the copper-pipe method enables accurate measurement of the effective energy of X-ray CT and is a convenient method suited to all general X-ray equipment as well as all X-ray CT.