@phdthesis{Kleineisel2024,
  author    = {Kleineisel, Jonas},
  title     = {Variational networks in magnetic resonance imaging - Application to spiral cardiac MRI and investigations on image quality},
  doi       = {10.25972/OPUS-34737},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-347370},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Acceleration is a central aim of clinical and technical research in magnetic resonance imaging (MRI) today, with the potential to increase robustness, accessibility and patient comfort, reduce cost, and enable entirely new kinds of examinations. A key component in this endeavor is image reconstruction, as most modern approaches build on advanced signal and image processing. Here, deep learning (DL)-based methods have recently shown considerable potential, with numerous publications demonstrating benefits for MRI reconstruction. However, these methods often come at the cost of an increased risk for subtle yet critical errors. Therefore, the aim of this thesis is to advance DL-based MRI reconstruction, while ensuring high quality and fidelity with measured data. A network architecture specifically suited for this purpose is the variational network (VN). To investigate the benefits these can bring to non-Cartesian cardiac imaging, the first part presents an application of VNs, which were specifically adapted to the reconstruction of accelerated spiral acquisitions. The proposed method is compared to a segmented exam, a U-Net and a compressed sensing (CS) model using qualitative and quantitative measures. While the U-Net performed poorly, the VN as well as the CS reconstruction showed good output quality. In functional cardiac imaging, the proposed real-time method with VN reconstruction substantially accelerates examinations over the gold-standard, from over 10 to just 1 minute. Clinical parameters agreed on average. Generally in MRI reconstruction, the assessment of image quality is complex, in particular for modern non-linear methods. Therefore, advanced techniques for precise evaluation of quality were subsequently demonstrated. With two distinct methods, resolution and amplification or suppression of noise are quantified locally in each pixel of a reconstruction. Using these, local maps of resolution and noise in parallel imaging (GRAPPA), CS, U-Net and VN reconstructions were determined for MR images of the brain. In the tested images, GRAPPA delivers uniform and ideal resolution, but amplifies noise noticeably. The other methods adapt their behavior to image structure, where different levels of local blurring were observed at edges compared to homogeneous areas, and noise was suppressed except at edges. Overall, VNs were found to combine a number of advantageous properties, including a good trade-off between resolution and noise, fast reconstruction times, and high overall image quality and fidelity of the produced output. Therefore, this network architecture seems highly promising for MRI reconstruction.},
  subject      = {Kernspintomografie},
  language  = {en}
}
@article{GuggenbergerTorreLudwigetal.2022,
  author    = {Guggenberger, Konstanze Viktoria and Torre, Giulia Dalla and Ludwig, Ute and Vogel, Patrick and Weng, Andreas Max and Vogt, Marius Lothar and Fr{\"o}hlich, Matthias and Schmalzing, Marc and Raithel, Esther and Forman, Christoph and Urbach, Horst and Meckel, Stephan and Bley, Thorsten Alexander},
  title     = {Vasa vasorum of proximal cerebral arteries after dural crossing - potential imaging confounder in diagnosing intracranial vasculitis in elderly subjects on black-blood MRI},
  series = {European Radiology},
  volume    = {32},
  journal   = {European Radiology},
  number    = {2},
  issn      = {1432-1084},
  doi       = {10.1007/s00330-021-08181-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-266524},
  pages     = {1276-1284},
  year      = {2022},
  abstract  = {Objectives Vessel wall enhancement (VWE) may be commonly seen on MRI images of asymptomatic subjects. This study aimed to characterize the VWE of the proximal internal carotid (ICA) and vertebral arteries (VA) in a non-vasculitic elderly patient cohort. Methods Cranial MRI scans at 3 Tesla were performed in 43 patients (aged ≥ 50 years) with known malignancy for exclusion of cerebral metastases. For vessel wall imaging (VWI), a high-resolution compressed-sensing black-blood 3D T1-weighted fast (turbo) spin echo sequence (T1 CS-SPACE prototype) was applied post gadolinium with an isotropic resolution of 0.55 mm. Bilateral proximal intradural ICA and VA segments were evaluated for presence, morphology, and longitudinal extension of VWE. Results Concentric VWE of the proximal intradural ICA was found in 13 (30\%) patients, and of the proximal intradural VA in 39 (91\%) patients. Mean longitudinal extension of VWE after dural entry was 13 mm in the VA and 2 mm in the ICA. In 14 of 39 patients (36\%) with proximal intradural VWE, morphology of VWE was suggestive of the mere presence of vasa vasorum. In 25 patients (64 \%), morphology indicated atherosclerotic lesions in addition to vasa vasorum. Conclusions Vasa vasorum may account for concentric VWE within the proximal 2 mm of the ICA and 13 mm of the VA after dural entry in elderly subjects. Concentric VWE in these locations should not be confused with large artery vasculitis. Distal to these segments, VWE may be more likely related to pathologic conditions such as vasculitis.},
  language  = {en}
}