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Abstract Background Endovascular treatment can be a fast and safe option in the case of acute, internal bleeding – but it requires special knowledge and technical skills. Interventionalists must consider the anatomy and potential complications. As in this case report, the anterior spinal artery, for example, can be a crucial vessel that must always be considered when embolizing intercostal or lumbar arteries. The risk of spinal ischemia has to be taken into account and should be minimized by choosing the appropriate treatment option. Case presentation We report about a 77 year old, male patient with upper gastrointestinal bleeding after esophagectomy and gastric conduit reconstruction. A CT scan identified a pseudoaneurysm of an intercostal artery penetrating the gastric conduit as the bleeding source. In the DSA, a direct connection between the intercostal artery and the anterior spinal artery appeared to be likely. Due to the associated risk of spinal ischemia, an embolization of the intercostal artery was not an option. We decided to implant a stentgraft that would stop the perfusion of the pseudoaneurysm, but preserve the perfusion of the intercostal artery. Due to the small diameter of the vessel, we could not implant our commonly used stentgrafts in this case. Therefore, we chose an uncommon solution and used a stentgraft that is designed primarily for coronary arteries. Conclusions Whenever intercostal or lumbar arteries need to be embolized, a possible connection to the anterior spinal artery must be considered and interventionalists have to be aware of possible ischemic complications. In this case, a stentgraft designed primarily for coronary arteries offered a good endovascular treatment option for the pseudoaneurysm of an intercostal artery. The risk of spinal ischemia could be minimized by using this stentgraft.

ObjectiveLiver cancer is one of the most commonly diagnosed cancer, and energy-based tumor ablation is a widely accepted treatment. Automatic and robust segmentation of liver tumors and ablation zones would facilitate the evaluation of treatment success. The purpose of this study was to develop and evaluate an automatic deep learning based method for (1) segmentation of liver and liver tumors in both arterial and portal venous phase for pre-treatment CT, and (2) segmentation of liver and ablation zones in both arterial and portal venous phase for after ablation treatment.Materials and Methods252 CT images from 63 patients undergoing liver tumor ablation at a large University Hospital were retrospectively included; each patient had pre-treatment and post-treatment multi-phase CT images. 3D voxel-wise manual segmentation of the liver, tumors and ablation region by the radiologist provided reference standard. Deep learning models for liver and lesion segmentation were initially trained on the public Liver Tumor Segmentation Challenge (LiTS) dataset to obtain base models. Then, transfer learning was applied to adapt the base models on the clinical training-set, to obtain tumor and ablation segmentation models both for arterial and portal venous phase images. For modeling, 2D residual-attention Unet (RA-Unet) was employed for liver segmentation and a multi-scale patch-based 3D RA-Unet for tumor and ablation segmentation.ResultsOn the independent test-set, the proposed method achieved a dice similarity coefficient (DSC) of 0.96 and 0.95 for liver segmentation on arterial and portal venous phase, respectively. For liver tumors, the model on arterial phase achieved detection sensitivity of 71%, DSC of 0.64, and on portal venous phase sensitivity of 82%, DSC of 0.73. For liver tumors >0.5cm3 performance improved to sensitivity 79%, DSC 0.65 on arterial phase and, sensitivity 86%, DSC 0.72 on portal venous phase. For ablation zone, the model on arterial phase achieved detection sensitivity of 90%, DSC of 0.83, and on portal venous phase sensitivity of 90%, DSC of 0.89.ConclusionThe proposed deep learning approach can provide automated segmentation of liver tumors and ablation zones on multi-phase (arterial and portal venous) and multi-time-point (before and after treatment) CT enabling quantitative evaluation of treatment success.

ObjectivesTo investigate whether virtual monoenergetic images (VMI) and iodine maps derived from spectral detector computed tomography (SDCT) improve early assessment of technique efficacy in patients who underwent microwave ablation (MWA) for hepatocellular carcinoma (HCC) in liver cirrhosis.MethodsThis retrospective study comprised 39 patients with 49 HCC lesions treated with MWA. Biphasic SDCT was performed 7.7±4.0 days after ablation. Conventional images (CI), VMI and IM were reconstructed. Signal- and contrast-to-noise ratio (SNR, CNR) in the ablation zone (AZ), hyperemic rim (HR) and liver parenchyma were calculated using regions-of-interest analysis and compared between CI and VMI between 40-100 keV. Iodine concentration and perfusion ratio of HR and residual tumor (RT) were measured. Two readers evaluated subjective contrast of AZ and HR, technique efficacy (complete vs. incomplete ablation) and diagnostic confidence at determining technique efficacy.ResultsAttenuation of liver parenchyma, HR and RT, SNR of liver parenchyma and HR, CNR of AZ and HR were significantly higher in low-keV VMI compared to CI (all pConclusionsSpectral detector computed tomography derived low-keV virtual monoenergetic images and iodine maps provide superior early assessment of technique efficacy of MWA in HCC compared to CI.

Background/Aims: Heart rate variability (HRV) refers to the fluctuation of the time interval between consecutive heartbeats in humans. It has recently been discovered that cardiomyocytes derived from human embryonic and induced pluripotent stem cells show beat rate variability (BRV) that is similar to the HRV in humans. In the present study, clinical aspects of HRV were transferred to an in vitro model. The aims of the study were to explore the BRV in murine embryonic stem cell (mESC)-derived cardiomyocytes and to demonstrate the influence of antiarrhythmic drugs on BRV as has been shown in clinical trials previously. Methods: The Microelectrode Array (MEA) technique was used to perform short-term recordings of extracellular field potentials (FPs) of spontaneously beating cardiomyocytes derived from mESCs (D3 cell line, αPig-44). Offline analysis was focused on time domain and nonlinear methods. Results: The Poincaré-Plot analysis of measurements without pharmacological intervention revealed that three different shapes of scatter plots occurred most frequently. Comparable shapes have been described in clinical studies before. The antiarrhythmic drugs Ivabradine, Verapamil and Sotalol augmented BRV, whereas Flecainide decreased BRV parameters at low concentrations (SDSD 79.0 ± 8.7% of control at 10-9 M, p -5 M, p Conclusions: Spontaneously beating cardiomyocytes derived from mESCs showed BRV that appears to be similar to the HRV known from humans. Antiarrhythmic drugs affected BRV parameters similar to clinical observations. Therefore, our study demonstrates that this in vitro model can contribute to a better understanding of electrophysiological properties of mESC-derived cardiomyocytes and might serve as a valuable tool for drug safety screening.