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Background To evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with suspected shoulder pathology. Methods 3 T MRI of the shoulder including a 3D T1-weighted gradient echo sequence was performed in 25 patients (mean age 52.4 ± 18 years, 13 women) with suspected shoulder pathology. Subsequently a cone-beam forward projection algorithm was used to obtain intensity-inverted CT-like images and simulated radiographs. Two radiologists evaluated the simulated images separately and independently using the conventional radiographs as the standard of reference, including measurements of the image quality, acromiohumeral distance, critical shoulder angle, degenerative joint changes and the acromial type. Additionally, the CT-like MR images were evaluated for glenoid defects, subcortical cysts and calcifications. Agreement between the MR-derived simulated radiographs and conventional radiographs was calculated using Cohen’s Kappa. Results Measurements on simulated radiographs and conventional radiographs overall showed a substantial to almost perfect inter- and intra-rater agreement (κ = 0.69–1.00 and κ = 0.65–0.85, respectively). Image quality of the simulated radiographs was rated good to excellent (1.6 ± 0.7 and 1.8 ± 0.6, respectively) by the radiologists. A substantial agreement was found regarding diagnostically relevant features, assessed on Y- and anteroposterior projections (κ = 0.84 and κ = 0.69 for the measurement of the CSA; κ = 0.95 and κ = 0.60 for the measurement of the AHD; κ = 0.77 and κ = 0.77 for grading of the Samilson-Prieto classification; κ = 0.83 and κ = 0.67 for the grading of the Bigliani classification, respectively). Conclusion In this proof-of-concept study, clinically relevant features of the shoulder joint were assessed reliably using MR-derived CT-like images and simulated radiographs with an image quality equivalent to conventional radiographs. MR-derived CT-like images and simulated radiographs may provide useful diagnostic information while reducing the amount of radiation exposure.

Advancements of existing imaging methods and the development of new imaging technologies require strategies for their clinical evaluation. Besides the technical requirements that a certain spatial resolution is provided or a certain limit of image noise is guaranteed, especially the diagnostic performance of radiologists is of interest. This diagnostic image quality or diagnostic value is usually investigated for specific clinical tasks. The aim of this cumulative thesis is to investigate and implement methods for the assessment of diagnostic image quality and the clinical evaluation of novel imaging methods and devices. Um Weiter- und Neuentwicklungen im Bereich der medizinischen Bildgebung zu evaluieren werden Strategien benötigt mit denen der klinische Nutzen bestimmt werden kann. Neben der Einhaltung technischer Spezifikationen, wie beispielsweise einer bestimmten Bildauflösung, ist insbesondere die Fähigkeit eines Radiologen eine richtige Diagnose auf den Bildern zu stellen von großem Interesse. Diese diagnostische Bildqualität wird üblicherweise für bestimmte klinische Fragestellungen ermittelt. Ziel dieser publikationsbasierten Dissertation ist die Erforschung und Implementierung von Methoden zur Bestimmung der diagnostischen Bildqualität und die klinische Evaluierung neuartiger Bildgebungsverfahren.

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., Biomedical Physics & Engineering Express, 6 (1)

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).

Multidetector computed tomography-based trabecular bone microstructure analysis ensures promising results in fracture risk prediction caused by osteoporosis. Because multidetector computed tomography is associated with high radiation exposure, its clinical routine use is limited. Hence, in this study, we investigated in 11 thoracic midvertebral specimens whether trabecular texture parameters are comparable derived from (1) images reconstructed using statistical iterative reconstruction (SIR) and filtered back projection as criterion standard at different exposures (80, 150, 220, and 500 mAs) and (2) from SIR-based sparse sampling projections (12.5%, 25%, 50%, and 100%) and equivalent exposures as criterion standard. Twenty-four texture features were computed, and those that showed similar values between (1) filtered back projection and SIR at the different exposure levels and (2) sparse sampling and equivalent exposures and reconstructed with SIR were identified. These parameters can be of equal value in determining trabecular bone microstructure with lower radiation exposure using sparse sampling and SIR.

In humans, the cytosolic sulfotransferases (SULTs) catalyze regiospecific transfer of the sulfuryl moiety (-SO3) from 3'-phosphoadenosine 5'-phosphosulfate to thousands of metabolites, including numerous signaling small molecules, and thus regulates their activities and half-lives. Imbalances in the in vivo set points of these reactions leads to disease. Here, with the goal of controlling sulfonation in vivo, molecular ligand-recognition principles in the SULT and nuclear receptor families are integrated in creating a strategy that can prevent sulfonation of a compound without significantly altering its receptor affinity, or inhibiting SULTS. The strategy is validated by using it to control the sulfonation and estrogen receptor (ER) activating activity of raloxifene (a US Food and Drug Administration-approved selective estrogen receptor modulator) and its derivatives. Preventing sulfonation is shown to enhance ER-activation efficacy 10(4)-fold in studies using Ishikawa cells. The strategy offers the opportunity to control sulfuryl transfer on a compound-by-compound basis, to enhance the efficacy of sulfonated drugs, and to explore the biology of sulfuryl transfer with unprecedented precision.

We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

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A synthetic access to polymagnesiated aromatics and heteroaromatics via multiple magnesiations was developed, their reactivity towards different electrophiles was explored. A diatereoselective synthesis of functionalized cyclopropane carbenoids was developed. Soluble Lanthanide soloutions were prepared and used in the addition reactions of Grignard reagents to carbonyl compounds.

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 0.05 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.