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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. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to compare vertebral failure loads, predicted from finite element (FE) analysis of patients with and without osteoporotic vertebral fractures (OVF) at virtually reduced dose levels, compared to standard-dose exposure from multidetector computed tomography (MDCT) imaging and evaluate whether ultra-low dose derived FE analysis can still differentiate patient groups. Materials and Methods: An institutional review board (IRB) approval was obtained for this retrospective study. A total of 16 patients were evaluated at standard-dose MDCT; eight with and eight without OVF. Images were reconstructed at virtually reduced dose levels (i. e. half, quarter and tenth of the standard dose). Failure load was determined at L1–3 from FE analysis and compared between standard, half, quarter, and tenth doses and used to differentiate between fracture and control groups. Results: Failure load derived at standard dose (3254 ± 909 N and 3794 ± 984 N) did not significantly differ from half (3390 ± 890 N and 3860 ± 1063 N) and quarter dose (3375 ± 915 N and 3925 ± 990 N) but was significantly higher for one tenth dose (4513 ± 1762 N and 4766 ± 1628 N) for fracture and control groups, respectively. Failure load differed significantly between the two groups at standard, half and quarter doses, but not at tenth dose. Receiver operating characteristic (ROC) curve analysis also demonstrated that standard, half, and quarter doses can significantly differentiate the fracture from the control group. Conclusion: The use of MDCT enables a dose reduction of at least 75% compared to standard-dose for an adequate prediction of vertebral failure load based on non-invasive FE analysis. [ABSTRACT FROM AUTHOR]

Objectives: Evaluation of sparse sampling computed tomography (SpSCT) regarding subjective and objective image criteria for the detection of pulmonary embolism (PE) at different simulated dose levels.Methods: Computed tomography pulmonary angiography (CTPA) scans of 20 clinical patients were used to obtain simulated low-dose scans with 100%-50%-25%-12.5%-6.3%-3.1% of the clinical dose, resulting in a total of six dose levels (DL). From these full sampling (FS) data, every second (2-SpSCT) or fourth (4-SpSCT) projection was used to obtain simulated sparse sampling scans. Each image set was evaluated by four blinded radiologists regarding subjective image criteria (artifacts, image quality) and diagnostic performance (confidence, sensitivity, specificity, accuracy, and area under the curve). Additionally, the contrast-to-noise ratio (CNR) was evaluated for objective image quality.Results: Sensitivity was 100% with 2-SpSCT and 4-SpSCT at the 25% DL and the 12.5% DL for all localizations of PE (one subgroup 98.5%). With FS, the sensitivity decreased to 90% at the 12.5% DL. 2-SpSCT and 4-SpSCT showed higher values for sensitivity, specificity, accuracy, and the area under the curve at all DL compared with FS. Subjective image quality was significantly higher for 4-SpSCT compared with FS at each dose level (p < 0.01, paired t test). Only with 4-SpSCT, all examinations were rated as showing diagnostic image quality at the 12.5% DL.Conclusions: Via SpSCT, a dose reduction down to a 12.5% dose level (corresponding to a mean effective dose of 0.38 mSv in the current study) for CTPA is possible while maintaining high image quality and full diagnostic confidence.Key Points: • With sparse sampling CT, radiation dose could be significantly reduced in clinical routine. • Sparse sampling CT is a novel hardware solution with which less projection images are acquired. • In the current study, a dose reduction of 87.5% (corresponding to a mean effective dose of 0.38 mSv) for CTPA could be achieved while maintaining excellent diagnostic performance. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Disorders of the lungs such as chronic obstructive pulmonary disease (COPD) are a major cause of chronic morbidity and mortality and the third leading cause of death in the world. The absence of sensitive diagnostic tests for early disease stages of COPD results in under-diagnosis of this treatable disease in an estimated 60–85% of the patients. In recent years a grating-based approach to X-ray dark-field contrast imaging has shown to be very sensitive for the detection and quantification of pulmonary emphysema in small animal models. However, translation of this technique to imaging systems suitable for humans remains challenging and has not yet been reported. In this manuscript, we present the first X-ray dark-field images of in-situ human lungs in a deceased body, demonstrating the feasibility of X-ray dark-field chest radiography on a human scale. Results were correlated with findings of computed tomography imaging and autopsy. The performance of the experimental radiography setup allows acquisition of multi-contrast chest X-ray images within clinical boundary conditions, including radiation dose. Upcoming clinical studies will have to demonstrate that this technology has the potential to improve early diagnosis of COPD and pulmonary diseases in general. [ABSTRACT FROM AUTHOR]

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 CTDIvol 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 CTDIvol-levels into account, the mean absolute percentage difference (MAPD) showed less accuracy for low CTDIvol-levels (2.5 mGy: 34.72%) than for high CTDIvol-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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Macrocycles are key structural elements in numerous bioactive small molecules and are attractive targets in the diversity-oriented synthesis of natural product-based libraries. However, efficient and systematic access to diverse collections of macrocycles has proven difficult using classical macrocyclization reactions. To address this problem, we have developed a concise, modular approach to the diversity-oriented synthesis of macrolactones and macrolactams involving oxidative cleavage of a bridging double bond in polycyclic enol ethers and enamines. These substrates are assembled in only four or five synthetic steps and undergo ring expansion to afford highly functionalized macrocycles bearing handles for further diversification. In contrast to macrocyclization reactions of corresponding seco acids, the ring expansion reactions are efficient and insensitive to ring size and stereochemistry, overcoming key limitations of conventional approaches to systematic macrocycle synthesis. Cheminformatic analysis indicates that these macrocycles access regions of chemical space that overlap with natural products, distinct from currently targeted synthetic drugs. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate sparse sampling computed tomography (SpSCT) for detection of endoleak after endovascular aortic repair (EVAR) at different dose levels in terms of subjective image criteria and diagnostic accuracy.Methods: Twenty clinically indicated computed tomography aortic angiography (CTA) scans were used to obtain simulated low-dose scans with 100%, 50%, 25%, 12.5% and 6.25% of the applicated clinical dose, resulting in five dose levels (DL). From full sampling (FS) data sets, every second (2-SpSCT) or fourth (4-SpSCT) projection was used to generate simulated sparse sampling scans. All examinations were evaluated by four blinded radiologists regarding subjective image criteria and diagnostic performance.Results: Sensitivity was higher than 93% in 4-SpSCT at the 25% DL which is the same as with FS at full dose (100% DL). High accuracies and relative high AUC-values were obtained for 2- and 4-SpSCT down to the 12.5% DL, while for FS similar values were shown down to 25% DL only. Subjective image quality was significantly higher for 4-SpSCT compared to FS at each dose level. More than 90% of all cases were rated with a high or medium confidence for FS and 2-SpSCT at the 50% DL and for 4-SpSCT at the 25% DL. At DL 25% and 12.5%, more cases showed a high confidence using 2- and 4-SpSCT compared with FS.Conclusions: Via SpSCT, a dose reduction down to a 25% dose level (mean effective dose of 1.49 mSv in the current study) for CTA is possible while maintaining high image quality and full diagnostic confidence. [ABSTRACT FROM AUTHOR]

The presence of LiCl allows the convenient preparation of magnesiated imidazoles starting from unprotected iodoimid�azoles. They react with various electrophiles in satisfactory yields. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effect of dose reduction, by means of tube exposure reduction, on bone strength prediction from finite-element (FE) analysis. Fresh thoracic mid-vertebrae specimens (n = 11) were imaged, using multi-detector computed tomography (MDCT), at different intensities of X-ray tube exposures (80, 150, 220 and 500 mAs). Bone mineral density (BMD) was estimated from the mid-slice of each specimen from MDCT images. Differences in image quality and geometry of each specimen were measured. FE analysis was performed on all specimens to predict fracture load. Paired t-tests were used to compare the results obtained, using the highest CT dose (500 mAs) as reference. Dose reduction had no significant impact on FE-predicted fracture loads, with significant correlations obtained with reference to 500 mAs, for 80 mAs (R2 = 0.997, p < 0.001), 150 mAs (R2 = 0.998, p < 0.001) and 220 mAs (R2 = 0.987, p < 0.001). There were no significant differences in volume quantification between the different doses examined. CT imaging radiation dose could be reduced substantially to 64% with no impact on strength estimates obtained from FE analysis. Reduced CT dose will enable early diagnosis and advanced monitoring of osteoporosis and associated fracture risk. [ABSTRACT FROM AUTHOR]