TY - JOUR A1 - Hock, Michael A1 - Terekhov, Maxim A1 - Stefanescu, Maria Roxana A1 - Lohr, David A1 - Herz, Stefan A1 - Reiter, Theresa A1 - Ankenbrand, Markus A1 - Kosmala, Aleksander A1 - Gassenmaier, Tobias A1 - Juchem, Christoph A1 - Schreiber, Laura Maria T1 - B\(_{0}\) shimming of the human heart at 7T JF - Magnetic Resonance in Medicine N2 - Purpose Inhomogeneities of the static magnetic B\(_{0}\) field are a major limiting factor in cardiac MRI at ultrahigh field (≥ 7T), as they result in signal loss and image distortions. Different magnetic susceptibilities of the myocardium and surrounding tissue in combination with cardiac motion lead to strong spatio‐temporal B\(_{0}\)‐field inhomogeneities, and their homogenization (B0 shimming) is a prerequisite. Limitations of state‐of‐the‐art shimming are described, regional B\(_{0}\) variations are measured, and a methodology for spherical harmonics shimming of the B\(_{0}\) field within the human myocardium is proposed. Methods The spatial B\(_{0}\)‐field distribution in the heart was analyzed as well as temporal B\(_{0}\)‐field variations in the myocardium over the cardiac cycle. Different shim region‐of‐interest selections were compared, and hardware limitations of spherical harmonics B\(_{0}\) shimming were evaluated by calibration‐based B0‐field modeling. The role of third‐order spherical harmonics terms was analyzed as well as potential benefits from cardiac phase–specific shimming. Results The strongest B\(_{0}\)‐field inhomogeneities were observed in localized spots within the left‐ventricular and right‐ventricular myocardium and varied between systolic and diastolic cardiac phases. An anatomy‐driven shim region‐of‐interest selection allowed for improved B\(_{0}\)‐field homogeneity compared with a standard shim region‐of‐interest cuboid. Third‐order spherical harmonics terms were demonstrated to be beneficial for shimming of these myocardial B\(_{0}\)‐field inhomogeneities. Initial results from the in vivo implementation of a potential shim strategy were obtained. Simulated cardiac phase–specific shimming was performed, and a shim term‐by‐term analysis revealed periodic variations of required currents. Conclusion Challenges in state‐of‐the‐art B\(_{0}\) shimming of the human heart at 7 T were described. Cardiac phase–specific shimming strategies were found to be superior to vendor‐supplied shimming. KW - 7 T KW - B KW - cardiac MRI KW - shimming KW - ultrahigh field Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-218096 VL - 85 IS - 1 SP - 182 EP - 196 ER - TY - JOUR A1 - Ankenbrand, Markus Johannes A1 - Lohr, David A1 - Schlötelburg, Wiebke A1 - Reiter, Theresa A1 - Wech, Tobias A1 - Schreiber, Laura Maria T1 - Deep learning-based cardiac cine segmentation: Transfer learning application to 7T ultrahigh-field MRI JF - Magnetic Resonance in Medicine N2 - Purpose Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians. Methods A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning. Results Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805). Conclusions This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available. KW - 7T KW - ultrahigh-field KW - transfer learning KW - segmentation KW - neural networks KW - deep learning KW - cardiac magnetic resonance KW - cardiac function Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-257604 VL - 86 IS - 4 ER - TY - JOUR A1 - Bartmann, Catharina A1 - Fischer, Leah-Maria A1 - Hübner, Theresa A1 - Müller-Reiter, Max A1 - Wöckel, Achim A1 - McNeill, Rhiannon V. A1 - Schlaiss, Tanja A1 - Kittel-Schneider, Sarah A1 - Kämmerer, Ulrike A1 - Diessner, Joachim T1 - The effects of the COVID-19 pandemic on psychological stress in breast cancer patients JF - BMC Cancer N2 - Background: The majority of breast cancer patients are severely psychologically affected by breast cancer diagnosis and subsequent therapeutic procedures. The COVID-19 pandemic and associated restrictions on public life have additionally caused significant psychological distress for much of the population. It is therefore plausible that breast cancer patients might be particularly susceptible to the additional psychological stress caused by the pandemic, increasing suffering. In this study we therefore aimed to assess the level of psychological distress currently experienced by a defined group of breast cancer patients in our breast cancer centre, compared to distress levels preCOVID-19 pandemic. Methods: Female breast cancer patients of all ages receiving either adjuvant, neoadjuvant, or palliative therapies were recruited for the study. All patients were screened for current or previous COVID-19 infection. The participants completed a self-designed COVID-19 pandemic questionnaire, the Stress and Coping Inventory (SCI), the National Comprehensive Cancer Network (R) (NCCN (R)) Distress Thermometer (DT), the European Organization for Research and Treatment of Cancer (EORTC) QLQ C30, and the BR23. Results: Eighty-two breast cancer patients were included. Therapy status and social demographic factors did not have a significant effect on the distress caused by the COVID-19 pandemic. The results of the DT pre and during COVID-19 pandemic did not differ significantly. Using the self-designed COVID-19 pandemic questionnaire, we detected three distinct subgroups demonstrating different levels of concerns in relation to SARS-CoV-2. The subgroup with the highest levels of concern reported significantly decreased life quality, related parameters and symptoms. Conclusions: This monocentric study demonstrated that the COVID-19 pandemic significantly affected psychological health in a subpopulation of breast cancer patients. The application of a self-created "COVID-19 pandemic questionnaire"could potentially be used to help identify breast cancer patients who are susceptible to increased psychological distress due to the COVID-19 pandemic, and therefore may need additional intensive psychological support. KW - COVID-19 KW - breast cancer KW - psychological distress Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-265802 VL - 21 ER -