Spontaneous ischemic neuropathy of the sciatic nerve due to arterial occlusion - a rare cause of acute neuropathy not to be missed, a report of two cases.

BACKGROUND Ischemic neuropathy of the sciatic nerve without preceding vascular surgical procedures is a rare condition and may be due to arterial occlusion in one limb. CASE PRESENTATIONS We present two cases with acute onset of pain and sensory symptoms such as pins and needles and numbness in the foot with no or mild motor symptoms. In the neurological work-up, electrophysiological signs of axonal neuropathy of both peroneal and tibial nerves were demonstrated and T2 hyperintensity was seen in the distal sciatic nerves on MR neurography as well as signs indicating arterial thrombosis in the corresponding vessels. Recanalization was obtained in both patients angiographically with significant improvement in one patient. CONCLUSIONS Spontaneous arterial occlusion of major or peripheral arteries is a rare but important cause of acute onset of single or multiple axonal mononeuropathies of one extremity. Recognition of this infrequent cause is essential since it requires immediate and specific therapeutic options

pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis

Background and Objective: Deep learning enables tremendous progress in medical image analysis. One driving force of this progress are open-source frameworks like TensorFlow and PyTorch. However, these frameworks rarely address issues specific to the domain of medical image analysis, such as 3-D data handling and distance metrics for evaluation. pymia, an open-source Python package, tries to address these issues by providing flexible data handling and evaluation independent of the deep learning framework. Methods: The pymia package provides data handling and evaluation functionalities. The data handling allows flexible medical image handling in every commonly used format (e.g., 2-D, 2.5-D, and 3-D; full- or patch-wise). Even data beyond images like demographics or clinical reports can easily be integrated into deep learning pipelines. The evaluation allows stand-alone result calculation and reporting, as well as performance monitoring during training using a vast amount of domain-specific metrics for segmentation, reconstruction, and regression. Results: The pymia package is highly flexible, allows for fast prototyping, and reduces the burden of implementing data handling routines and evaluation methods. While data handling and evaluation are independent of the deep learning framework used, they can easily be integrated into TensorFlow and PyTorch pipelines. The developed package was successfully used in a variety of research projects for segmentation, reconstruction, and regression. Conclusions: The pymia package fills the gap of current deep learning frameworks regarding data handling and evaluation in medical image analysis. It is available at https://github.com/rundherum/pymia and can directly be installed from the Python Package Index using pip install pymia.Comment: first and last author contributed equall

Quantitative water T2 relaxometry in the early detection of neuromuscular diseases: a retrospective biopsy-controlled analysis.

OBJECTIVES To assess quantitative water T2 relaxometry for the early detection of neuromuscular diseases (NMDs) in comparison to standard qualitative MR imaging in a clinical setting. METHODS This retrospective study included 83 patients with suspected NMD who underwent multiparametric MRI at 3 T with a subsequent muscle biopsy between 2015 and 2019. Qualitative T1-weighted and T2-TIRM images were graded by two neuroradiologists to be either pathological or normal. Mean and median water T2 relaxation times (water T2) were obtained from manually drawn volumes of interests in biopsied muscle from multi-echo sequence. Histopathologic pattern of corresponding muscle biopsies was used as a reference. RESULTS In 34 patients, the T1-weighted images showed clear pathological alternations indicating late-stage fatty infiltration in NMDs. In the remaining 49 patients without late-stage changes, T2-TIRM grading achieved a sensitivity of 56.4%, and mean and median water T2 a sensitivity of 87.2% and 97.4% to detect early-stage NMDs. Receiver operating characteristic (ROC) analysis revealed an area under the curve (AUC) of 0.682, 0.715, and 0.803 for T2-TIRM, mean water T2, and median water T2, respectively. Median water T2 ranged between 36 and 42 ms depending on histopathologic pattern. CONCLUSIONS Quantitative water T2 relaxometry had a significantly higher sensitivity in detecting muscle abnormalities than subjective grading of T2-TIRM, prior to late-stage fatty infiltration signal alternations in T1-weighted images. Normal-appearing T2-TIRM does not rule out early-stage NMDs. Our findings suggest considering water T2 relaxometry complementary to T2-TIRM for early detection of NMDs in clinical diagnostic routine. KEY POINTS • Quantitative water T2 relaxometry is more sensitive than subjective assessment of fat-suppressed T2-weighted images for the early detection of neuromuscular diseases, prior to late-stage fatty infiltration signal alternations in T1-weighted images. • Normal-appearing muscles in fat-suppressed T2-weighted images do not rule out early-stage neuromuscular diseases. • Quantitative water T2 relaxometry should be considered complementary to subjectively rated fat-suppressed T2-weighted images in clinical practice

Effects of high resistance muscle training on corticospinal output during motor fatigue assessed by transcranial magnetic stimulation.

Introduction: Central fatigue refers to a reduced drive of motor cortical output during exercise, and performance can be enhanced after training. However, the effects of training on central fatigue remain unclear. Changes in cortical output can be addressed non-invasively using transcranial magnetic stimulation (TMS). The aim of the study was to compare responses to TMS during a fatiguing exercise before and after a 3 weeks lasting resistance training, in healthy subjects. Methods: The triple stimulation technique (TST) was used to quantify a central conduction index (CCI = amplitude ratio of central conduction response and peripheral nerve response) to the abductor digiti minimi muscle (ADM) in 15 subjects. The training consisted of repetitive isometric maximal voluntary contractions (MVC) of ADM for 2 min twice a day. Before and after this training, TST recordings were obtained every 15 s during an 2 min exercise of MVC of the ADM, where subjects performed repetitive contractions of the ADM, and repeatedly during a recovery period of 7 min. Results: There was a consistent decrease of force to approximately 40% of MVC in all experiments and in all subjects, both before and after training. In all subjects, CCI decreased during exercise. While before training, theCCI decreased to 49% (SD 23.7%) after 2 min of exercise, it decreased after training onlyto 79% (SD 26.4%) after exercise (p < 0.01). Discussion: The training regimen increased the proportion of target motor units that could be activated by TMS during a fatiguing exercise. The results point to a reduced intracortical inhibition, which may be a transient physiological response to facilitate the motor task. Possible underlying mechanisms at spinal and supraspinal sites are discussed

Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks

Magnetic resonance fingerprinting (MRF) enables fast and multiparametric MR imaging. Despite fast acquisition, the state-of-the-art reconstruction of MRF based on dictionary matching is slow and lacks scalability. To overcome these limitations, neural network (NN) approaches estimating MR parameters from fingerprints have been proposed recently. Here, we revisit NN-based MRF reconstruction to jointly learn the forward process from MR parameters to fingerprints and the backward process from fingerprints to MR parameters by leveraging invertible neural networks (INNs). As a proof-of-concept, we perform various experiments showing the benefit of learning the forward process, i.e., the Bloch simulations, for improved MR parameter estimation. The benefit especially accentuates when MR parameter estimation is difficult due to MR physical restrictions. Therefore, INNs might be a feasible alternative to the current solely backward-based NNs for MRF reconstruction.Comment: Accepted at MICCAI MLMIR 202

Feasibility of transesophageal phrenic nerve stimulation

Background Every year, more than 2.5 million critically ill patients in the ICU are dependent on mechanical ventilation. The positive pressure in the lungs generated by the ventilator keeps the diaphragm passive, which can lead to a loss of myofibers within a short time. To prevent ventilator-induced diaphragmatic dysfunction (VIDD), phrenic nerve stimulation may be used. Objective The goal of this study is to show the feasibility of transesophageal phrenic nerve stimulation (TEPNS). We hypothesize that selective phrenic nerve stimulation can efficiently activate the diaphragm with reduced co-stimulations. Methods An in vitro study in saline solution combined with anatomical findings was performed to investigate relevant stimulation parameters such as inter-electrode spacing, range to target site, or omnidirectional vs. sectioned electrodes. Subsequently, dedicated esophageal electrodes were inserted into a pig and single stimulation pulses were delivered simultaneously with mechanical ventilation. Various stimulation sites and response parameters such as transdiaphragmatic pressure or airway flow were analyzed to establish an appropriate stimulation setting. Results Phrenic nerve stimulation with esophageal electrodes has been demonstrated. With a current amplitude of 40 mA, similar response figures of the diaphragm activation as compared to conventional stimulation with needle electrodes at 10mA were observed. Directed electrodes best aligned with the phrenic nerve resulted in up to 16.9 % higher amplitude at the target site in vitro and up to 6 cmH20 higher transdiaphragmatic pressure in vivo as compared to omnidirectional electrodes. The activation efficiency was more sensitive to the stimulation level inside the esophagus than to the inter-electrode spacing. Most effective and selective stimulation was achieved at the level of rib 1 using sectioned electrodes 40 mm apart. Conclusion Directed transesophageal phrenic nerve stimulation with single stimuli enabled diaphragm activation. In the future, this method might keep the diaphragm active during, and even support, artificial ventilation. Meanwhile, dedicated sectioned electrodes could be integrated into gastric feeding tubes

Pearls & Oy-sters: Bilateral Mononeuropathic Neuralgic Amyotrophy Triggered by Bartonella henselae Infection Responsive to Immunoglobulin.

We present a case of a cat owner with a scar on his right thenar eminence, followed by lymphadenopathy in the right axilla, general malaise and fever, and subsequent onset of bilateral neuralgic amyotrophy within one week. After a comprehensive workup, cat scratch disease caused by Bartonella henselae was confirmed serologically and adequately treated. Despite antibiotic treatment, the patient presented clinically with persistent bilateral, asymmetric neuropathy of the median nerve, predominantly the interosseous anterior nerve, which was confirmed by multifocal swelling and hyperintense signal of the nerves on T2-weighted MR neurography. Electrophysiological examination confirmed axonal median neuropathies bilaterally. After an unsuccessful steroid treatment trial, the patient showed an excellent and sustained response to intravenous immunoglobulin despite a delay from symptom onset to treatment of 10 months

Feasibility of transesophageal phrenic nerve stimulation.

BACKGROUND Every year, more than 2.5 million critically ill patients in the ICU are dependent on mechanical ventilation. The positive pressure in the lungs generated by the ventilator keeps the diaphragm passive, which can lead to a loss of myofibers within a short time. To prevent ventilator-induced diaphragmatic dysfunction (VIDD), phrenic nerve stimulation may be used. OBJECTIVE The goal of this study is to show the feasibility of transesophageal phrenic nerve stimulation (TEPNS). We hypothesize that selective phrenic nerve stimulation can efficiently activate the diaphragm with reduced co-stimulations. METHODS An in vitro study in saline solution combined with anatomical findings was performed to investigate relevant stimulation parameters such as inter-electrode spacing, range to target site, or omnidirectional vs. sectioned electrodes. Subsequently, dedicated esophageal electrodes were inserted into a pig and single stimulation pulses were delivered simultaneously with mechanical ventilation. Various stimulation sites and response parameters such as transdiaphragmatic pressure or airway flow were analyzed to establish an appropriate stimulation setting. RESULTS Phrenic nerve stimulation with esophageal electrodes has been demonstrated. With a current amplitude of 40 mA, similar response figures of the diaphragm activation as compared to conventional stimulation with needle electrodes at 10mA were observed. Directed electrodes best aligned with the phrenic nerve resulted in up to 16.9 % higher amplitude at the target site in vitro and up to 6 cmH20 higher transdiaphragmatic pressure in vivo as compared to omnidirectional electrodes. The activation efficiency was more sensitive to the stimulation level inside the esophagus than to the inter-electrode spacing. Most effective and selective stimulation was achieved at the level of rib 1 using sectioned electrodes 40 mm apart. CONCLUSION Directed transesophageal phrenic nerve stimulation with single stimuli enabled diaphragm activation. In the future, this method might keep the diaphragm active during, and even support, artificial ventilation. Meanwhile, dedicated sectioned electrodes could be integrated into gastric feeding tubes

Hot Topics on COVID-19 and Its Possible Association with Guillain-Barré Syndrome

As the COVID-19 pandemic progresses, reports of neurological manifestations are increasing. However, despite a high number of case reports and case series on COVID-19 and Guillain-Barré-Syndrome (GBS), a causal association is still highly debated, due to the lack of case-control studies. In this opinion paper, we focus on a few clinically relevant questions regarding the possible link between GBS and SARS-CoV-2 infection or vaccination based on our personal clinical experience and literature review

Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks

Magnetic resonance fingerprinting (MRF) quantifies multiple nuclear magnetic resonance parameters in a single and fast acquisition. Standard MRF reconstructs parametric maps using dictionary matching, which lacks scalability due to computational inefficiency. We propose to perform MRF map reconstruction using a spatiotemporal convolutional neural network, which exploits the relationship between neighboring MRF signal evolutions to replace the dictionary matching. We evaluate our method on multiparametric brain scans and compare it to three recent MRF reconstruction approaches. Our method achieves state-of-the-art reconstruction accuracy and yields qualitatively more appealing maps compared to other reconstruction methods. In addition, the reconstruction time is significantly reduced compared to a dictionary-based approach.Comment: Accepted for Machine Learning for Medical Image Reconstruction (MLMIR) workshop at MICCAI 2018. The revision corrects Amaresha's last name and Section 2.1 (scanner type and flip angles