Comparison of a contrast-to-noise ratio-driven exposure control and a regular detector dose-driven exposure control in abdominal imaging in a clinical angiography system.

PURPOSE: The first purpose of this phantom study was to verify whether a contrast-to-noise ratio (CNR)-driven exposure control (CEC) can maintain target CNR in angiography more precisely compared to a conventional detector dose-driven exposure control (DEC). The second purpose was to estimate the difference between incident air kerma produced by CEC and DEC when both exposure controls reach the same CNR. METHODS: A standardized 3D-printed phantom with an iron foil and a cavity, filled with iodinated contrast material, was developed to measure CNR using different image acquisition settings. This phantom was placed into a stack of polymethylmethacrylate and aluminum plates, simulating a patient equivalent thickness (PET) of 2.5-40 cm. Images were acquired using fluoroscopy and digital radiography modes with CEC using one image quality level and four image quality gradients and DEC having three different detector dose levels. The spatial frequency weighted CNR and incident air kerma were determined. The differences in incident air kerma between DEC and CEC were estimated. RESULTS: When using DEC, CNR decreased continuously with increasing attenuation, while CEC within physical limits maintained a predefined CNR level. Furthermore, CEC could be parameterized to deliver the CNR as a predefined function of PET. To provide a given CNR level, CEC used equal or lower air kerma than DEC. The mean estimated incident air kerma of CEC compared to DEC was between 3% (PET 20 cm) and 40% (PET 27.5 cm) lower in fluoroscopy and between 1% (PET 20 cm) and 55% (PET 2.5 cm) lower in digital radiography while maintaining CNR. CONCLUSION: Within physical and legislative limits, the CEC allows for a flexible adjustment of the CNR as a function of PET. Thus, the CEC enables task-dependent examination protocols with predefined image quality in order to easier achieve the as low as reasonably achievable principle. CEC required equal or lower incident air kerma than DEC to provide similar CNR, which allows for a substantial reduction of skin radiation dose in these situations.

Impact of a contrast-to-noise ratio driven and material specific exposure control on image quality and radiation exposure in angiography.

Conventional detector-dose driven exposure controls (DEC) do not consider the contrasting material of interest in angiography. Considering the latter when choosing the acquisition parameters should allow for optimization of x-ray quality and consecutively lead to a substantial reduction of radiation exposure. Therefore, the impact of a material-specific, contrast-to-noise ratio (CNR) driven exposure control (CEC) compared to DEC on radiation exposure was investigated. A 3D-printed phantom containing iron, tantalum, and platinum foils and cavities, filled with iodine, barium, and gas (carbon dioxide), was developed to measure the CNR. This phantom was placed within a stack of polymethylmethacrylate and aluminum plates simulating a patient equivalent thickness (PET) of 2.5-40 cm. Fluoroscopy and digital radiography (DR) were conducted applying either CEC or three, regular DEC protocols with parameter settings used in abdominal interventions. CEC protocols where chosen to achieve material-specific CNR values similar to those of DEC. Incident air kerma at the reference point(Ka,r), using either CEC or DEC, was assessed and possible Ka,r reduction for similar CNR was estimated. We show that CEC provided similar CNR as DEC at the same or lower Ka,r. When imaging barium, iron, and iodine Ka,r was substantially reduced below a PET of 20 cm and between 25 cm and 30 cm for fluoroscopy and Dr When imaging platinum and tantalum using fluoroscopy and DR and gas using DR, the Ka,r reduction was substantially higher. We estimate the Ka,r reduction for these materials between 15% and 84% for fluoroscopy and DR between 15% and 93% depending on the PET. The results of this study demonstrate a high potential for skin dose reduction in abdominal radiology when using a material-specific CEC compared to DEC. This effect is substantial in imaging materials with higher energy K-edges, which is beneficial, for example, in long-lasting embolization procedures with tantalum-based embolization material in young patients with arterio-venous malformations.

Metal artifact reduction for flat panel detector intravenous CT angiography in patients with intracranial metallic implants after endovascular and surgical treatment.

BACKGROUND: Flat panel detector CT angiography with intravenous contrast agent injection (IV CTA) allows high-resolution imaging of cerebrovascular structures. Artifacts caused by metallic implants like platinum coils or clips lead to degradation of image quality and are a significant problem. OBJECTIVE: To evaluate the influence of a prototype metal artifact reduction (MAR) algorithm on image quality in patients with intracranial metallic implants. METHODS: Flat panel detector CT after intravenous application of 80 mL contrast agent was performed with an angiography system (Artis zee; Siemens, Forchheim, Germany) using a 20 s rotation protocol (200° rotation angle, 20 s acquisition time, 496 projections). The data before and after MAR of 26 patients with a total of 34 implants (coils, clips, stents) were independently evaluated by two blinded neuroradiologists. RESULTS: MAR improved the assessability of the brain parenchyma and small vessels (diameter <1 mm) in the neighborhood of metallic implants and at a distance of 6 cm (p<0.001 each, Wilcoxon test). Furthermore, MAR significantly improved the assessability of parent vessel patency and potential aneurysm remnants (p<0.005 each, McNemar test). MAR, however, did not improve assessability of stented vessels. CONCLUSIONS: When an intravenous contrast protocol is used, MAR significantly ameliorates the assessability of brain parenchyma, vessels, and treated aneurysms in patients with intracranial coils or clips.

Impact of a new metal artefact reduction algorithm in the noninvasive follow-up of intracranial clips, coils, and stents with flat-panel angiographic CTA: initial results.

INTRODUCTION: Flat-panel angiographic CT after intravenous contrast agent application (ivACT) is increasingly used as a follow-up examination after coiling, clipping, or stenting. The purpose of this study was to evaluate the feasibility of a new metal artefact reduction algorithm (MARA) in patients treated for intracranial aneurysms and stenosis. METHODS: IvACT was performed on a flat-panel detector angiography system after intravenous application of 80 ml contrast media. The uncorrected raw images were transferred to a prototype reconstruction workstation where the MARA was applied. Two experienced neuroradiologists examined the corrected and uncorrected images on a commercially available workstation. RESULTS: Artefacts around the implants were detected in all 16 uncorrected cases, while eight cases showed remaining artefacts after correction with the MARA. In the cases without correction, there were 11 cases with "extensive" artefacts and five cases with "many" artefacts. After correction, seven cases showed "few" and only one case "many" artefacts (Wilcoxon test, P < 0.001). Parent vessels were characterized as "not identifiable" in 62% of uncorrected images, while the delineation of parent vessels were classified as "excellent" in 50% of the cases after correction (Wilcoxon test, P = 0.001). CONCLUSIONS: Use of the MARA in our study significantly reduced artefacts around metallic implants on ivACT images and allowed for the delineation of surrounding structures.

Does preinterventional flat-panel computer tomography pooled blood volume mapping predict final infarct volume after mechanical thrombectomy in acute cerebral artery occlusion?

PURPOSE: Decreased cerebral blood volume is known to be a predictor for final infarct volume in acute cerebral artery occlusion. To evaluate the predictability of final infarct volume in patients with acute occlusion of the middle cerebral artery (MCA) or the distal internal carotid artery (ICA) and successful endovascular recanalization, pooled blood volume (PBV) was measured using flat-panel detector computed tomography (FPD CT). MATERIALS AND METHODS: Twenty patients with acute unilateral occlusion of the MCA or distal ACI without demarcated infarction, as proven by CT at admission, and successful Thrombolysis in cerebral infarction score (TICI 2b or 3) endovascular thrombectomy were included. Cerebral PBV maps were acquired from each patient immediately before endovascular thrombectomy. Twenty-four hours after recanalization, each patient underwent multislice CT to visualize final infarct volume. Extent of the areas of decreased PBV was compared with the final infarct volume proven by follow-up CT the next day. RESULTS: In 15 of 20 patients, areas of distinct PBV decrease corresponded to final infarct volume. In 5 patients, areas of decreased PBV overestimated final extension of ischemia probably due to inappropriate timing of data acquisition and misery perfusion. CONCLUSION: PBV mapping using FPD CT is a promising tool to predict areas of irrecoverable brain parenchyma in acute thromboembolic stroke. Further validation is necessary before routine use for decision making for interventional thrombectomy.

Performance evaluation of a C-Arm CT perfusion phantom.

PURPOSE: Brain perfusion measurement in stroke patients provides important information on the infarct area and state of involved tissue. Interventional C-Arm angiography systems can provide perfusion measurements. A CT perfusion phantom was developed for C-Arm perfusion imaging to test and evaluate this method and to aid in the design and validation of scan protocols. METHODS: A phantom test device was designed based on the anatomy of the human head. Four feeding arteries divided into sixteen sub-branches that lead into a sintered board simulating brain parenchyma. Perfusion measurements were performed using two conventional clinical CT scanners as the gold standard and with a C-Arm CT system to test and compare the implementations. The phantom's input parameters, contrast medium and flow properties were varied. A cerebral perfusion deficit was simulated by occlusion of a feeding artery tube. RESULTS: CT perfusion maps of the sintered board brain tissue surrogate were computed and qualitatively compared for both conventional CT and C-Arm CT systems. A characteristic flow pattern of the tissue board was identifiable in both modalities. The characteristic flow pattern of the resulting perfusion maps is reproducible. The calculated flow and volume were directly related. CONCLUSIONS: A new CT perfusion phantom was developed and tested. This phantom is an appropriate model for CT-based tissue perfusion measurements in both conventional CT scanners and C-Arm CT scanners. The influence of input parameter changes can be visualized. Perfusion deficits after occlusion of a feeding artery are readily simulated and identified with CT.

Image features for misalignment correction in medical flat-detector CT.

PURPOSE: Misalignment artifacts are a serious problem in medical flat-detector computed tomography. Generally, the geometrical parameters, which are essential for reconstruction, are provided by preceding calibration routines. These procedures are time consuming and the later use of stored parameters is sensitive toward external impacts or patient movement. The method of choice in a clinical environment would be a markerless online-calibration procedure that allows flexible scan trajectories and simultaneously corrects misalignment and motion artifacts during the reconstruction process. Therefore, different image features were evaluated according to their capability of quantifying misalignment. METHODS: Projections of the FORBILD head and thorax phantoms were simulated. Additionally, acquisitions of a head phantom and patient data were used for evaluation. For the reconstruction different sources and magnitudes of misalignment were introduced in the geometry description. The resulting volumes were analyzed by entropy (based on the gray-level histogram), total variation, Gabor filter texture features, Haralick co-occurrence features, and Tamura texture features. The feature results were compared to the back-projection mismatch of the disturbed geometry. RESULTS: The evaluations demonstrate the ability of several well-established image features to classify misalignment. The authors elaborated the particular suitability of the gray-level histogram-based entropy on identifying misalignment artifacts, after applying an appropriate window level (bone window). CONCLUSIONS: Some of the proposed feature extraction algorithms show a strong correlation with the misalignment level. Especially, entropy-based methods showed very good correspondence, with the best of these being the type that uses the gray-level histogram for calculation. This makes it a suitable image feature for online-calibration.

Comparison of extended field-of-view reconstructions in C-arm flat-detector CT using patient size, shape or attenuation information.

In C-arm-based flat-detector computed tomography (FDCT) it frequently happens that the patient exceeds the scan field of view (SFOV) in the transaxial direction because of the limited detector size. This results in data truncation and CT image artefacts. In this work three truncation correction approaches for extended field-of-view (EFOV) reconstructions have been implemented and evaluated. An FDCT-based method estimates the patient size and shape from the truncated projections by fitting an elliptical model to the raw data in order to apply an extrapolation. In a camera-based approach the patient is sampled with an optical tracking system and this information is used to apply an extrapolation. In a CT-based method the projections are completed by artificial projection data obtained from the CT data acquired in an earlier exam. For all methods the extended projections are filtered and backprojected with a standard Feldkamp-type algorithm. Quantitative evaluations have been performed by simulations of voxelized phantoms on the basis of the root mean square deviation and a quality factor Q (Q = 1 represents the ideal correction). Measurements with a C-arm FDCT system have been used to validate the simulations and to investigate the practical applicability using anthropomorphic phantoms which caused truncation in all projections. The proposed approaches enlarged the FOV to cover wider patient cross-sections. Thus, image quality inside and outside the SFOV has been improved. Best results have been obtained using the CT-based method, followed by the camera-based and the FDCT-based truncation correction. For simulations, quality factors up to 0.98 have been achieved. Truncation-induced cupping artefacts have been reduced, e.g., from 218% to less than 1% for the measurements. The proposed truncation correction approaches for EFOV reconstructions are an effective way to ensure accurate CT values inside the SFOV and to recover peripheral information outside the SFOV.

Empirical beam hardening correction (EBHC) for CT.

PURPOSE: Due to x-ray beam polychromaticity and scattered radiation, attenuation measurements tend to be underestimated. Cupping and beam hardening artifacts become apparent in the reconstructed CT images. If only one material such as water, for example, is present, these artifacts can be reduced by precorrecting the rawdata. Higher order beam hardening artifacts, as they result when a mixture of materials such as water and bone, or water and bone and iodine is present, require an iterative beam hardening correction where the image is segmented into different materials and those are forward projected to obtain new rawdata. Typically, the forward projection must correctly model the beam polychromaticity and account for all physical effects, including the energy dependence of the assumed materials in the patient, the detector response, and others. We propose a new algorithm that does not require any knowledge about spectra or attenuation coefficients and that does not need to be calibrated. The proposed method corrects beam hardening in single energy CT data. METHODS: The only a priori knowledge entering EBHC is the segmentation of the object into different materials. Materials other than water are segmented from the original image, e.g., by using simple thresholding. Then, a (monochromatic) forward projection of these other materials is performed. The measured rawdata and the forward projected material-specific rawdata are monomially combined (e.g., multiplied or squared) and reconstructed to yield a set of correction volumes. These are then linearly combined and added to the original volume. The combination weights are determined to maximize the flatness of the new and corrected volume. EBHC is evaluated using data acquired with a modern cone-beam dual-source spiral CT scanner (Somatom Definition Flash, Siemens Healthcare, Forchheim, Germany), with a modern dual-source micro-CT scanner (Tomo-Scope Synergy Twin, CT Imaging GmbH, Erlangen, Germany), and with a modern C-arm CT scanner (Axiom Artis dTA, Siemens Healthcare, Forchheim, Germany). A large variety of phantom, small animal, and patient data were used to demonstrate the data and system independence of EBHC. RESULTS: Although no physics apart from the initial segmentation procedure enter the correction process, beam hardening artifacts were significantly reduced by EBHC. The image quality for clinical CT, micro-CT, and C-arm CT was highly improved. Only in the case of C-arm CT, where high scatter levels and calibration errors occur, the relative improvement was smaller. CONCLUSIONS: The empirical beam hardening correction is an interesting alternative to conventional iterative higher order beam hardening correction algorithms. It does not tend to over- or undercorrect the data. Apart from the segmentation step, EBHC does not require assumptions on the spectra or on the type of material involved. Potentially, it can therefore be applied to any CT image.

Reducing metal artifacts in computed tomography caused by hip endoprostheses using a physics-based approach.

PURPOSE: Metal-induced artifacts may cause severe problems in clinical computed tomography (CT) imaging and may impair diagnosis as well as overall image quality. Many approaches for reducing these artifacts tackle the problem by simply ignoring or interpolating the metal traces in the raw data, which results in a general information loss and additional artifacts in the corrected image. It was the objective of this study to develop an approach aiming at correcting several physical artifact sources. We have also tried to minimize the impact on spatial resolution and attempted to avoid new artifacts resulting from the correction. MATERIALS AND METHODS: The algorithm works with a first volumetric reconstruction followed by threshold-based metal prostheses segmentation. The segmented metal implants are then forward projected and the resulting sinogram entries are squared and combined, followed by a second reconstruction to yield correction volumes. The resulting volumes are then combined linearly with a combination weight determined to minimize the flatness of the initial image. A directional filtering algorithm following the beam hardening correction applies a nonlinear convolution in the metal traces of the sinogram which reduces existing metal-induced noise artifacts. Phantom measurements on a polyethylene (PE) disc with different inserts and a semi-anthropomorphic hip phantom with optional bone and titanium inserts were used for evaluating the algorithm. Patient datasets containing uni- and bilateral hip endoprostheses verified the applicability and efficiency on realistic clinical cases. RESULTS: Deviations in CT values were reduced to below 3 HU on average. Image noise reduction of up to 70% was achieved (average noise reduction of 37%) with a more homogeneous CT value distribution in soft-tissue areas. A comparison to standard interpolation methods showed superior artifact suppression without producing artifacts caused by interpolation and without the general information loss in the close vicinity to the implants. The impact on spatial resolution was minimized as compared with interpolation algorithms. CONCLUSIONS: Metal artifacts caused by hip-endoprostheses were strongly reduced. Soft tissue areas and skeletal structures surrounding the implants were well restored. The correction works by postprocessing CT datasets and it is applicable to any reconstructed image without a priori knowledge.

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.

Robot arm based flat panel CT-guided electromagnetic tracked spine interventions: phantom and animal model experiments.

PURPOSE: To evaluate accuracy and procedure times of electromagnetic tracking (EMT) in a robotic arm mounted flat panel setting using phantom and animal cadaveric models. METHODS AND MATERIALS: A robotic arm mounted flat panel (RMFP) was used in combination with EMT to perform anthropomorphic phantom (n = 90) and ex vivo pig based punctures (n = 120) of lumbar facet joints (FJ, n = 120) and intervertebral discs (IVD, n = 90). Procedure accuracies and times were assessed and evaluated. RESULTS: FJ punctures were carried out with a spatial accuracy of 0.8 ± 0.9 mm (phantom) and 0.6 ± 0.8 mm (ex vivo) respectively. While IVD punctures showed puncture deviations of 0.6 ± 1.2 mm (phantom) and 0.5 ± 0.6 mm (ex vivo), direct and angulated phantom based punctures had accuracies of 0.8 ± 0.9 mm and 1.0 ± 1.3 mm. Planning took longer for ex vivo IVD punctures compared to phantom model interventions (39.3 ± 17.3 s vs. 20.8 ± 5.0 s, p = 0.001) and for angulated vs. direct phantom FJ punctures (19.7 ± 5.1 s vs. 28.6 ± 7.8 s, p < 0.001). Puncture times were longer for ex vivo procedures when compared to phantom model procedures in both FJ (37.9 ± 9.0 s vs. 23.6 ± 7.2 s, p = 0.001) and IVD punctures (43.9 ± 16.1 s vs. 31.1 ± 6.4 s, p = 0.026). CONCLUSION: The combination of RMFP with EMT provides an accurate method of navigation for spinal interventions such as facet joint punctures and intervertebral disc punctures.

A fast and pragmatic approach for scatter correction in flat-detector CT using elliptic modeling and iterative optimization.

Scattered radiation is a major source of artifacts in flat detector computed tomography (FDCT) due to the increased irradiated volumes. We propose a fast projection-based algorithm for correction of scatter artifacts. The presented algorithm combines a convolution method to determine the spatial distribution of the scatter intensity distribution with an object-size-dependent scaling of the scatter intensity distributions using a priori information generated by Monte Carlo simulations. A projection-based (PBSE) and an image-based (IBSE) strategy for size estimation of the scanned object are presented. Both strategies provide good correction and comparable results; the faster PBSE strategy is recommended. Even with such a fast and simple algorithm that in the PBSE variant does not rely on reconstructed volumes or scatter measurements, it is possible to provide a reasonable scatter correction even for truncated scans. For both simulations and measurements, scatter artifacts were significantly reduced and the algorithm showed stable behavior in the z-direction. For simulated voxelized head, hip and thorax phantoms, a figure of merit Q of 0.82, 0.76 and 0.77 was reached, respectively (Q = 0 for uncorrected, Q = 1 for ideal). For a water phantom with 15 cm diameter, for example, a cupping reduction from 10.8% down to 2.1% was achieved. The performance of the correction method has limitations in the case of measurements using non-ideal detectors, intensity calibration, etc. An iterative approach to overcome most of these limitations was proposed. This approach is based on root finding of a cupping metric and may be useful for other scatter correction methods as well. By this optimization, cupping of the measured water phantom was further reduced down to 0.9%. The algorithm was evaluated on a commercial system including truncated and non-homogeneous clinically relevant objects.

A novel forward projection-based metal artifact reduction method for flat-detector computed tomography.

Metallic implants generate streak-like artifacts in flat-detector computed tomography (FD-CT) reconstructed volumetric images. This study presents a novel method for reducing these disturbing artifacts by inserting discarded information into the original rawdata using a three-step correction procedure and working directly with each detector element. Computation times are minimized by completely implementing the correction process on graphics processing units (GPUs). First, the original volume is corrected using a three-dimensional interpolation scheme in the rawdata domain, followed by a second reconstruction. This metal artifact-reduced volume is then segmented into three materials, i.e. air, soft-tissue and bone, using a threshold-based algorithm. Subsequently, a forward projection of the obtained tissue-class model substitutes the missing or corrupted attenuation values directly for each flat detector element that contains attenuation values corresponding to metal parts, followed by a final reconstruction. Experiments using tissue-equivalent phantoms showed a significant reduction of metal artifacts (deviations of CT values after correction compared to measurements without metallic inserts reduced typically to below 20 HU, differences in image noise to below 5 HU) caused by the implants and no significant resolution losses even in areas close to the inserts. To cover a variety of different cases, cadaver measurements and clinical images in the knee, head and spine region were used to investigate the effectiveness and applicability of our method. A comparison to a three-dimensional interpolation correction showed that the new approach outperformed interpolation schemes. Correction times are minimized, and initial and corrected images are made available at almost the same time (12.7 s for the initial reconstruction, 46.2 s for the final corrected image compared to 114.1 s and 355.1 s on central processing units (CPUs)).

Ring artifact correction for high-resolution micro CT.

In high-resolution micro CT using flat detectors (FD), imperfect or defect detector elements may cause concentric-ring artifacts due to their continuous over- or underestimation of attenuation values, which often disturb image quality. We here present a dedicated image-based ring artifact correction method for high-resolution micro CT, based on median filtering of the reconstructed image and working on a transformed version of the reconstructed images in polar coordinates. This post-processing method reduced ring artifacts in the reconstructed images and improved image quality for phantom and in in vivo scans. Noise and artifacts were reduced both in transversal and in multi-planar reformations along the longitudinal axis.

Comparison of ring artifact correction methods for flat-detector CT.

In flat-detector CT, imperfect or defect detector elements may cause concentric ring artifacts due to their continuous over- or underestimation of attenuation values, which often disturb image quality. Especially due to the demand for high-spatial resolution images and the necessary pixel read-out without arbitrary pixel-binning, ring artifacts become more pronounced and the reduction of these artifacts becomes a necessity. We here present a comparison of two dedicated ring artifact correction methods for flat-detector CT, on the basis of different median and mean filterings of the reconstructed image but each working in different geometric planes. While the first method works in Cartesian coordinates, the second method performs a transformation to polar coordinates. Both post-processing methods efficiently reduce ring artifacts in the reconstructed images and improve image quality. The transformation to polar coordinates turned out to be a necessary step for efficient ring artifact correction, since correction in Cartesian coordinates suffers from newly introduced artifacts as well as insufficient correction of artifacts close to the center of rotation.

Respiratory phase-correlated micro-CT imaging of free-breathing rodents.

We provide a dedicated phase-correlated imaging procedure for respiratory gating in micro-CT imaging with automatic detection of the optimal data window providing the least amount of motion blurring. A rawdata-based motion function (kymogram) was used for synchronization purposes and for identification of the optimal data window used for phase-correlated image reconstruction. Measurements were performed on a dual-source micro-CT scanner. Projection data were acquired over ten rotations for multi-segment phase-correlated reconstruction. Visual assessment was performed on datasets of ten free-breathing subjects. The kymogram approach provided a reliable synchronization signal for phase-correlated image reconstruction. Also, it allowed for the identification of phase intervals of increased and decreased motion and the corresponding detection of the optimal reconstruction phase. Phase-correlated images showed a strong improvement with respect to motion blurring compared to standard image reconstruction. A reconstruction for the calculated optimal data window provided the least amount of motion blurring and even allowed for the assessment of small structures in the lung. The dedicated retrospective phase-correlated image reconstruction procedure for respiratory gating is a feasible approach for motion-free imaging. A subject-specific optimal reconstruction phase can minimize motion blurring and further improve image quality.

Technical note: raw data-based approach to identify the optimal reconstruction phase in coronary computed tomography angiography.

For coronary computed tomography (CT) angiography, the reconstruction phase finally used has to be iteratively adapted to the patient-specific heart motion to provide optimal image quality and therewith to improve the diagnostic value. The purpose was to provide an automatically raw data-based identification of the patient-specific optimal reconstruction phase for cardiac computed tomography imaging. We validated our method by a visual assessment of 65 patient data sets. In 52% of all cases, the highest correlation of the computed and the visually identified optimal reconstruction phase was ensured. In 30% of the cases, our method provided a higher image quality compared with the results obtained in routine clinical work. Our identification of the optimal reconstruction phase is a reliable method and can improve the medical workflow by providing optimal image quality with the initial image reconstruction, making multiple time-consuming image reconstructions obsolete.

Cardiac phase-correlated image reconstruction and advanced image processing in pulmonary CT imaging.

Image quality in pulmonary CT imaging is commonly degraded by cardiac motion artifacts. Phase-correlated image reconstruction algorithms known from cardiac imaging can reduce motion artifacts but increase image noise and conventionally require a concurrently acquired ECG signal for synchronization. Techniques are presented to overcome these limitations. Based on standard and phase-correlated images that are reconstructed using a raw data-derived synchronization signal, image-merging and temporal-filtering techniques are proposed that combine the input images automatically or interactively. The performance of the approaches is evaluated in patient and phantom datasets. In the automatic approach, areas of strong motion and static areas were well detected, providing an optimal combination of standard and phase-correlated images with no visible border between the merged regions. Image noise in the non-moving regions was reduced to the noise level of the standard reconstruction. The application of the interactive filtering allowed for an optimal adaptation of image noise and motion artifacts. Noise content after interactive filtering decreased with increasing temporal filter width used. We conclude that a combination of our motion-free merging approach and a dedicated interactive filtering procedure can highly improve pulmonary imaging with respect to motion artifacts and image noise.

Modulation transfer function-based assessment of temporal resolution: validation for single- and dual-source CT.

The purpose of this study was to determine a manufacturer-independent quality assurance measurement for temporal resolution with a three-dimensional cardiac motion robot; validation was with single-source (SS) and dual-source (DS) computed tomography (CT). Image acquisition was performed by using standard cardiac protocols. Image contrast-based modulation transfer function (MTF) was assessed as function of time. For motion frequency of 60 beats per minute, MTF slightly decreased by 14% and 6% for SS CT and DS CT, respectively. For higher frequencies, a stronger decrease of MTF (eg, by 50% [SS CT] and 18% [DS CT] at 120 beats per minute) was detected. Effect of manufacturer's adaptive bisegment algorithm for SS CT and corresponding resonance effects of rotation time and heart rate were quantified. The robot-based approach is a reproducible, objective way to assess temporal resolution; it allows practical measurement of temporal resolution and comparison of CT scanners and protocols.