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Purpose: Evaluation of dual-layer spectral computed tomography (CT) for contrast enhancement during image-guided biopsy of liver lesions using virtual monoenergetic images (VMI) and virtual non-contrast (VNC) images., Methods: Spectral CT data of 20 patients receiving CT-guided needle biopsy of focal liver lesions were used to generate VMI at energy levels from 40 to 200 keV and VNC images. Images were analyzed objectively regarding contrast-to-noise ratio between lesion center (CNR cent ) or periphery (CNR peri ) and normal liver parenchyma. Lesion visibility and image quality were evaluated on a 4-point Likert scale by two radiologists., Results: Using VMI/VNC images, readers reported an increased visibility of the lesion compared to the conventional CT images in 18/20 cases. In 75% of cases, the highest visibility was derived by VMI-40. Showing all reconstructions simultaneously, VMI-40 offered the highest visibility in 75% of cases, followed by VNC in 12.5% of cases. Either CNR cent (17/20) or/and CNR peri (17/20) was higher (CNR increase > 50%) in 19/20 cases for VMI-40 or VNC images compared to conventional CT images. VMI-40 showed the highest CNR cent in 14 cases and the highest CNR peri in 12 cases. High image quality was present for all reconstructions with a minimum median of 3.5 for VMI-40 and VMI-50., Conclusions: When implemented in the CT scanner software, automated contrast enhancement of liver lesions during image-guided biopsy may facilitate the procedure., (© 2023. The Author(s).)

Automatic evaluation of 3D volumes is a topic of importance in order to speed up clinical decision making. We describe a method to classify computed tomography scans on volume level for the presence of non-acute cerebral infarction. This is not a trivial task, as the lesions are often similar to other areas in the brain regarding shape and intensity. A three stage architecture is used for classification: 1) A cranial cavity segmentation network is developed, trained and applied. 2) Region proposals are generated 3) Connected regions are classified using a multi-resolution, densely connected 3D convolutional network. Mean area under curve values for subject level classification are 0.95 for the unstratified test set, 0.88 for stratification by patient age and 0.93 for stratification by CT scanner model. We use a partly segmented dataset of 555 scans of which 186 scans are used in the unstratified test set. Furthermore we examine possible dataset bias for scanner model and patient age parameters. We show a successful application of the proposed three-stage model for full volume classification. In contrast to black-box approaches, the convolutional network's decision can be further assessed by examination of intermediate segmentation results., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: FT is an employee of Philips Research. MS, PBN, IR, FKK, BR, FP, EJR and DP have declared that no competing interests exist. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Purpose: To evaluate the benefit of the additional available information present in spectral CT datasets, as compared to conventional CT datasets, when utilizing convolutional neural networks for fully automatic localisation and classification of liver lesions in CT images., Materials and Methods: Conventional and spectral CT images (iodine maps, virtual monochromatic images (VMI)) were obtained from a spectral dual-layer CT system. Patient diagnosis were known from the clinical reports and classified into healthy, cyst and hypodense metastasis. In order to compare the value of spectral versus conventional datasets when being passed as input to machine learning algorithms, we implemented a weakly-supervised convolutional neural network (CNN) that learns liver lesion localisation without pixel-level ground truth annotations. Regions-of-interest are selected automatically based on the localisation results and are used to train a second CNN for liver lesion classification (healthy, cyst, hypodense metastasis). The accuracy of lesion localisation was evaluated using the Euclidian distances between the ground truth centres of mass and the predicted centres of mass. Lesion classification was evaluated by precision, recall, accuracy and F1-Score., Results: Lesion localisation showed the best results for spectral information with distances of 8.22 ± 10.72 mm, 8.78 ± 15.21 mm and 8.29 ± 12.97 mm for iodine maps, 40 keV and 70 keV VMIs, respectively. With conventional data distances of 10.58 ± 17.65 mm were measured. For lesion classification, the 40 keV VMIs achieved the highest overall accuracy of 0.899 compared to 0.854 for conventional data., Conclusion: An enhanced localisation and classification is reported for spectral CT data, which demonstrates that combining machine-learning technology with spectral CT information may in the future improve the clinical workflow as well as the diagnostic accuracy.

Objective: To investigate the in vivo applicability of non-contrast-enhanced hydroxyapatite (HA)-specific bone mineral density (BMD) measurements based on dual-layer CT (DLCT)., Methods: A spine phantom containing three artificial vertebral bodies with known HA densities was measured to obtain spectral data using DLCT and quantitative CT (QCT), simulating different patient positions and grades of obesity. BMD was calculated from virtual monoenergetic images at 50 and 200 keV. HA-specific BMD values of 174 vertebrae in 33 patients (66 ± 18 years; 33% women) were determined in non-contrast routine DLCT and compared with corresponding QCT-based BMD values., Results: Examining the phantom, HA-specific BMD measurements were on a par with QCT measurements. In vivo measurements revealed strong correlations between DLCT and QCT (r = 0.987 [95% confidence interval, 0.963-1.000]; p < 0.001) and substantial agreement in a Bland-Altman plot., Conclusion: DLCT-based HA-specific BMD measurements were comparable with QCT measurements in in vivo analyses. This suggests that opportunistic DLCT-based BMD measurements are an alternative to QCT, without requiring phantoms and specific protocols., Key Points: • DLCT-based hydroxyapatite-specific BMD measurements show a substantial agreement with QCT-based BMD measurements in vivo. • DLCT-based hydroxyapatite-specific measurements are on a par with QCT in spine phantom measurements. • Opportunistic DLCT-based BMD measurements may be a feasible alternative for QCT, without requiring dedicated examination protocols or a phantom.

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.

Dual-Energy Computed Tomography is of significant clinical interest due to the possibility of material differentiation and quantification. In current clinical routine, primarily two materials are differentiated, e.g., iodine and soft-tissue. A ventilation-perfusion-examination acquired within a single CT scan requires two contrast agents, e.g., xenon and gadolinium, and a three-material differentiation. In the current study, we have developed a solution for three-material differentiation for a ventilation-perfusion-examination. A landrace pig was examined using a dual-layer CT, and three scans were performed: (1) native; (2) xenon ventilation only; (3) xenon ventilation and gadolinium perfusion. An in-house developed algorithm was used to obtain xenon- and gadolinium-density maps. Firstly, lung tissue was segmented from other tissue. Consequently, a two-material decomposition was performed for lung tissue (xenon/soft-tissue) and for remaining tissue (gadolinium/soft-tissue). Results reveal that it was possible to differentiate xenon and gadolinium in a ventilation/perfusion scan of a pig, resulting in xenon and gadolinium density maps. By summation of both density maps, a three-material differentiation (xenon/gadolinium/soft tissue) can be performed and thus, xenon ventilation and gadolinium perfusion can be visualized in a single CT scan. In an additionally performed phantom study, xenon and gadolinium quantification showed very accurate results (r > 0.999 between measured and known concentrations).

Objectives: To evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with benign and malignant bone tumors., Methods: In 32 patients with a benign or malignant bone lesion (mean age 33.9 ± 18.5 years, 17 females), 3-T MR imaging was performed including a 3D T1-weighted gradient echo sequence as the basis for the CT-like images. From these, intensity-inverted MR image volumes were converted into 2D images via a forward projection to obtain simulated radiographs. Two radiologists assessed these images as well as conventional radiographs for the type of periosteal reaction, matrix mineralization and destruction pattern. Agreement between the modalities was calculated using Cohen's κ., Results: The agreement between conventional radiographs and MR-derived CT-like images in combination with simulated radiographs was substantial (periosteal reaction, κ = 0.67; destruction pattern, κ = 0.75), and the sensitivity of both modalities for the final diagnosis of the lesion (aggressive vs. nonaggressive) was high (MR-derived CT-like images, 86.2% vs. conventional radiographs, 90.0%). Additional information on soft tissue extension (MR-derived CT-like images, 21.9% vs. conventional radiographs, 12.5%; p = 0.009) and lobulation (9.4% vs. 0%; p < 0.001) was significantly more often found on MR-derived CT-like images compared with conventional radiographs., Conclusions: The assessment of the destruction patterns, periosteal reaction and distinction between aggressive and nonaggressive tumors was feasible using MR-derived CT-like images and simulated radiographs and is comparable to that of conventional radiographs. Moreover, MR-derived CT-like images provided additional information on soft tissue extension and tumor architecture., Key Points: • CT-like images and simulated radiographs can be generated from 3D MRI. • Evaluation of bone tumors is feasible with MR-derived images. • CT-like images and simulated radiographs provide additional information on bone tumors.

The purpose of this study was to investigate a preclinical spectral photon-counting CT (SPCCT) prototype compared to conventional CT for pulmonary imaging. A custom-made lung phantom, including nodules of different sizes and shapes, was scanned with a preclinical SPCCT and a conventional CT in standard and high-resolution (HR-CT) mode. Volume estimation was evaluated by linear regression. Shape similarity was evaluated with the Dice similarity coefficient. Spatial resolution was investigated via MTF for each imaging system. In-vivo rabbit lung images from the SPCCT system were subjectively reviewed. Evaluating the volume estimation, linear regression showed best results for the SPCCT compared to CT and HR-CT with a root mean squared error of 21.3 mm 3 , 28.5 mm 3 and 26.4 mm 3 for SPCCT, CT and HR-CT, respectively. The Dice similarity coefficient was superior for SPCCT throughout nodule shapes and all nodule sizes (mean, SPCCT: 0.90; CT: 0.85; HR-CT: 0.85). 10% MTF improved from 10.1 LP/cm for HR-CT to 21.7 LP/cm for SPCCT. Visual investigation of small pulmonary structures was superior for SPCCT in the animal study. In conclusion, the SPCCT prototype has the potential to improve the assessment of lung structures due to higher resolution compared to conventional CT.

Objectives: To assess whether bone marrow edema in patients with acute vertebral fractures can be accurately diagnosed based on three-material decomposition with dual-layer spectral CT (DLCT)., Materials and Methods: Acute (n = 41) and chronic (n = 18) osteoporotic thoracolumbar vertebral fractures as diagnosed by MRI (hyperintense signal in STIR sequences) in 27 subjects (72 ± 11 years; 17 women) were assessed with DLCT. Spectral data were decomposed into hydroxyapatite, edema-equivalent, and fat-equivalent density maps using an in-house-developed algorithm. Two radiologists, blinded to clinical and MR findings, assessed DLCT and conventional CT independently, using a Likert scale (1 = no edema; 2 = likely no edema; 3 = likely edema; 4 = edema). For DLCT and conventional CT, accuracy, sensitivity, and specificity for identifying acute fractures (Likert scale, 3 and 4) were analyzed separately using MRI as standard of reference., Results: For the identification of acute fractures, conventional CT showed a sensitivity of 0.73-0.76 and specificity of 0.78-0.83, whereas the sensitivity (0.93-0.95) and specificity (0.89) of decomposed DLCT images were substantially higher. Accuracy increased from 0.76 for conventional CT to 0.92-0.93 using DLCT. Interreader agreement for fracture assessment was high in conventional CT (weighted κ [95% confidence interval]; 0.81 [0.70; 0.92]) and DLCT (0.96 [0.92; 1.00])., Conclusions: Material decomposition of DLCT data substantially improved accuracy for the diagnosis of acute vertebral fractures, with a high interreader agreement. This may spare patients additional examinations and facilitate the diagnosis of vertebral fractures.

Purpose: The purpose of this study was the evaluation of anthropomorphic model observers trained with neural networks for the prediction of a human observer's performance., Methods: To simulate liver lesions, a phantom with contrast targets (acrylic spheres, varying diameters, +30 HU) was repeatedly scanned on a computed tomography scanner. Image data labeled with confidence ratings assessed in a reader study for a detection task of liver lesions were used to build several anthropomorphic model observers. Models were trained with images reconstructed with iterative reconstruction and evaluated with images reconstructed with filtered backprojection. A neural network, based on softmax regression (SR-MO), and convolutional neural networks (CNN-MO) were used to predict the performance of a human observer and compared to a channelized Hotelling observer [with Gabor channels and internal channel noise (CHOi)]. Model observers were evaluated by a receiver operating characteristic curve analysis and compared to the results in the reader study. Two strategies were used to train the SR-MO and CNN-MO: A) building a separate model for each lesion size; B) building one model that was applied to lesions of all sizes., Results: All tested model observers and the human observer were highly correlated at each lesion size and dose level. With strategy A, Pearson's product-moment correlation coefficients r were 0.926 (95% confidence interval (CI): 0.679-0.985) for SR-MO and 0.979 (95% CI: 0.902-0.996) for CNN-MO. With strategy B, r was 0.860 (95% CI: 0.454-0.970) for SR-MO and 0.918 (95% CI: 0.651-0.983) for CNN-MO. For CHOi, r was 0.945 (95% CI: 0.755-0.989). With strategy A, mean absolute percentage differences (MAPD) between the model observers and the human observer were 3.7% for SR-MO and 1.2% for CNN-MO. With strategy B, MAPD were 3.7% for SR-MO and 3.0% for CNN-MO. For the CHOi the MAPD was 2.2%., Conclusion: Convolutional neural network model observers can accurately predict the performance of a human observer for all lesion sizes and dose levels in the evaluated signal detection task., (© 2018 American Association of Physicists in Medicine.)

Objectives: After endovascular aortic repair (EVAR), discrimination of endoleaks and intra-aneurysmatic calcifications within the aneurysm often requires multiphase computed tomography (CT). Spectral photon-counting CT (SPCCT) in combination with a two-contrast agent injection protocol may provide reliable detection of endoleaks with a single CT acquisition., Methods: To evaluate the feasibility of SPCCT, the stent-lined compartment of an abdominal aortic aneurysm phantom was filled with a mixture of iodine and gadolinium mimicking enhanced blood. To represent endoleaks of different flow rates, the adjacent compartments contained either one of the contrast agents or calcium chloride to mimic intra-aneurysmatic calcifications. After data acquisition with a SPCCT prototype scanner with multi-energy bins, material decomposition was performed to generate iodine, gadolinium and calcium maps., Results: In a conventional CT slice, Hounsfield units (HU) of the compartments were similar ranging from 147 to 168 HU. Material-specific maps differentiate the distributions within the compartments filled with iodine, gadolinium or calcium., Conclusion: SPCCT may replace multiphase CT to detect endoleaks without sacrificing diagnostic accuracy. It is a unique feature of our method to capture endoleak dynamics and allow reliable distinction from intra-aneurysmatic calcifications in a single scan, thereby enabling a significant reduction of radiation exposure., Key Points: • SPCCT might enable advanced endoleak detection. • Material maps derived from SPCCT can differentiate iodine, gadolinium and calcium. • SPCCT may potentially reduce radiation burden for EVAR patients under post-interventional surveillance.

Introduction: To evaluate the clinical potential of dual layer computed tomography (DLCT) for posterior fusions of the thoracic and lumbar spine and determine the optimal keV-settings for an improved overall image quality and effective reduction of metal artefacts affecting the implant inheriting vertebral body, the spinal canal, the paravertebral muscle and aorta., Methods and Materials: Twenty patients with posterior thoracic and lumbar spinal fusion, who underwent a 120kVp- DLCT scan were included in this study. Two independent readers evaluated axial 0.9 mm slides with soft tissue and bone window settings. Image quality of the conventional scan was compared to virtual monoenergetic images (VMI) at 40, 60, 80, 100,120, 140, 160, 180 and 200 keV. Diagnostic image quality was assessed on a four point Likert-scale overall, as well as specifically for the implant inheriting bone, paravertebral muscle, spinal canal or aorta. The Hounsfield Units (HU) of the area with the most pronounced streak artefact as well as HU of a reference area containing fat and muscle were documented for each keV-setting and compared to the conventional image. SNR and CNR were calculated for each of the four anatomic areas. Statistical analysis was conducted for the total collective and separately for the thoracic and lumbar spine level., Results: Starting from 80 keV qualitative analysis revealed significant improvement of overall image quality and benefit for each tissue separately compared to the conventional images (CI) (p-values in the range from <0.001 to 0.005). 180 keV was considered the optimal monoenergetic setting regarding the overall image quality. For the assessment of the implant inheriting bone, the spinal canal, paravertebral muscle and aorta 200, 180, 160 and 180 keV were rated to be the most sufficient. Our results reveal high inter-reader agreement for qualitative evaluations (intra-class correlation coefficients >0.927; p < 0.05). HU values within the most pronounced streak artefact increased significantly with higher keV (p < 0.001), while there was no significant alteration of HU within the reference area. A decrease in SNR and CNR for higher VMI was revealed by our results., Conclusion: VMIs of higher energies provide significant reduction of metallic artefacts from posterior spinal fusions. Dedicated keV settings to evaluate either the implant inheriting bone, the spinal canal,adjacent muscle or aorta - structures, which are frequently of particular interest after posterior spinal fusion - are recommended. In addition, an optimal keV for an improved overall image quality is proposed., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Purpose: Evaluation of the influence of iterative reconstruction, tube settings and patient habitus on the accuracy of iodine quantification with dual-layer spectral CT (DL-CT)., Material and Methods: A CT abdomen phantom with different extension rings and four iodine inserts (1, 2, 5 and 10 mg/ml) was scanned on a DL-CT. The phantom was scanned with tube-voltages of 120 and 140 kVp and CTDI vol of 2.5, 5, 10 and 20 mGy. Reconstructions were performed for eight levels of iterative reconstruction (i0-i7). Diagnostic dose levels are classified depending on patient-size and radiation dose., Results: Measurements of iodine concentration showed accurate and reliable results. Taking all CTDI vol -levels into account, the mean absolute percentage difference (MAPD) showed less accuracy for low CTDI vol -levels (2.5 mGy: 34.72%) than for high CTDI vol -levels (20 mGy: 5.89%). At diagnostic dose levels, accurate quantification of iodine was possible (MAPD 3.38%). Level of iterative reconstruction did not significantly influence iodine measurements. Iodine quantification worked more accurately at a tube voltage of 140 kVp. Phantom size had a considerable effect only at low-dose-levels; at diagnostic dose levels the effect of phantom size decreased (MAPD <5% for all phantom sizes)., Conclusion: With DL-CT, even low iodine concentrations can be accurately quantified. Accuracies are higher when diagnostic radiation doses are employed., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The performance of a recently introduced spectral computed tomography system based on a dual-layer detector has been investigated. A semi-anthropomorphic abdomen phantom for CT performance evaluation was imaged on the dual-layer spectral CT at different radiation exposure levels (CTDI vol of 10 mGy, 20 mGy and 30 mGy). The phantom was equipped with specific low-contrast and tissue-equivalent inserts including water-, adipose-, muscle-, liver-, bone-like materials and a variation in iodine concentrations. Additionally, the phantom size was varied using different extension rings to simulate different patient sizes. Contrast-to-noise (CNR) ratio over the range of available virtual mono-energetic images (VMI) and the quantitative accuracy of VMI Hounsfield Units (HU), effective-Z maps and iodine concentrations have been evaluated. Central and peripheral locations in the field-of-view have been examined. For all evaluated imaging tasks the results are within the calculated theoretical range of the tissue-equivalent inserts. Especially at low energies, the CNR in VMIs could be boosted by up to 330% with respect to conventional images using iDose/spectral reconstructions at level 0. The mean bias found in effective-Z maps and iodine concentrations averaged over all exposure levels and phantom sizes was 1.9% (eff. Z) and 3.4% (iodine). Only small variations were observed with increasing phantom size (+3%) while the bias was nearly independent of the exposure level (±0.2%). Therefore, dual-layer detector based CT offers high quantitative accuracy of spectral images over the complete field-of-view without any compromise in radiation dose or diagnostic image quality., (© 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.)

To assess whether phantomless calcium-hydroxyapatite (HA) specific bone mineral density (BMD) measurements with dual-layer spectral computed tomography are accurate in phantoms and vertebral specimens. Ex-vivo human vertebrae (n = 13) and a phantom containing different known HA concentrations were placed in a semi-anthropomorphic abdomen phantom with different extension rings simulating different degrees of obesity. Phantomless dual-layer spectral CT was performed at different tube current settings (500, 250, 125 and 50 mAs). HA-specific BMD was derived from spectral-based virtual monoenergetic images at 50 keV and 200 keV. Values were compared to the HA concentrations of the phantoms and conventional qCT measurements using a reference phantom, respectively. Above 125 mAs, errors for phantom measurements ranged between -1.3% to 4.8%, based on spectral information. In vertebral specimens, high correlations were found between BMD values assessed with spectral CT and conventional qCT (r ranging between 0.96 and 0.99; p < 0.001 for all) with different extension rings, and a high agreement was found in Bland Altman plots. Different degrees of obesity did not have a significant influence on measurements (P > 0.05 for all). These results suggest a high validity of HA-specific BMD measurements based on dual-layer spectral CT examinations in setups simulating different degrees of obesity without the need for a reference phantom, thus demonstrating their feasibility in clinical routine.

Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography., Methods: In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization., Results: Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection., Conclusions: The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.