Recursive numerical calculus of one-loop tensor integrals

A numerical approach to compute tensor integrals in one-loop calculations is presented. The algorithm is based on a recursion relation which allows to express high rank tensor integrals as a function of lower rank ones. At each level of iteration only inverse square roots of Gram determinants appear. For the phase-space regions where Gram determinants are so small that numerical problems are expected, we give general prescriptions on how to construct reliable approximations to the exact result without performing Taylor expansions. Working in 4+epsilon dimensions does not require an analytic separation of ultraviolet and infrared/collinear divergences, and, apart from trivial integrals that we compute explicitly, no additional ones besides the standard set of scalar one-loop integrals are needed.Comment: Typo corrected in formula 79. 22 pages, Latex, 1 figure, uses axodraw.st

Neuropathophysiological potential of Guillain-Barré syndrome anti-ganglioside-complex antibodies at mouse motor nerve terminals

Objectives:  Anti-ganglioside antibodies are present in approximately half of Guillain–Barré syndrome (GBS) patients. Recently, it has been shown that a considerable proportion of these patients has serum antibodies against antigenic epitopes formed by a complex of two different gangliosides. However, direct experimental evidence for neuropathogenicity of this special category of antibodies is currently lacking. Here, we explored a series of GBS and GBS-variant sera with anti-ganglioside-complex antibodies for their ability to induce complement-dependent deleterious effects at the living neuronal membrane. Methods:  The neuropathophysiological potential of 31 GBS sera containing either anti-GM1/GD1a- or anti-GM1/GQ1b-ganglioside-complex antibodies was studied at motor nerve terminal presynaptic membranes in the mouse phrenic nerve/diaphragm muscle ex vivo experimental model. With electrophysiological measurements and confocal fluorescence microscopy, we assessed and quantified the damaging effect on neuronal membranes by anti-ganglioside-complex antibodies. Results:  We show that anti-GM1/GD1a- and anti-GM1/GQ1b-ganglioside-complex positive sera can induce complement-mediated functional and morphological injury at mouse motor nerve terminals ex vivo. Of the 31 investigated anti-ganglioside-complex patient sera, 17 sera induced increases in miniature end-plate potential frequency in this experimental model, mostly associated with muscle fibre twitches. Variability in potency was observed, with the anti-GM1/GD1a-complex sera inducing the most outspoken effects.<b></b> Conclusions:  The present study shows the presence of ganglioside-complexes as available antigens in living neuronal membranes and supplies proof-of-principle that anti-ganglioside-complex antibodies in sera from GBS patients can induce complement-mediated damage. This strongly supports the hypothesis that autoimmune targeting of ganglioside-complexes is of pathogenic relevance in a proportion of GBS patients

Host-pathogen Interactions in Guillain-Barré Syndrome

Guillain-Barré syndrome (GBS) is a neurological illness in which patients become rapidly paralyzed and require long-term rehabilitation. At present, it is the world’s most frequent cause of acute ascending paralysis in those countries where poliomyelitis has been eradicated (1). GBS is a post-infectious immune-mediated disease and in the last twenty years much progress has been made in elucidating the immune response to infections and peripheral nerves, the types of infection and the mechanism of nerve damage (2). As a consequence, GBS is regarded a model disease for other post-infectious diseases. The aim of the following paragraphs is to present a comprehensive framework for reading the remaining chapters of this thesis. It will focus on the role of infections, antibodies to neural antigens and the presumed immunological and molecular factors that determine why some individuals may develop GBS after infections whereas most do not. A general introduction about the history and clinical aspects of GBS and related disorders will be presented first. Next, the pathogenesis of GBS will be addressed in more detail. The role of serum anti-neural antibodies in the diagnosis of GBS and other immune-mediated neuropathies will be discussed separately. Central to this thesis is the thought that interactions between patients (the host) and microorganisms (pathogens) contribute to the development of this post-infectious syndrome. At the end of this chapter the outline and aims of the studies described in this thesis will be presented

Effect of latent space distribution on the segmentation of images with multiple annotations

We propose the Generalized Probabilistic U-Net, which extends the Probabilistic U-Net by allowing more general forms of the Gaussian distribution as the latent space distribution that can better approximate the uncertainty in the reference segmentations. We study the effect the choice of latent space distribution has on capturing the variation in the reference segmentations for lung tumors and white matter hyperintensities in the brain. We show that the choice of distribution affects the sample diversity of the predictions and their overlap with respect to the reference segmentations. We have made our implementation available at https://github.com/ishaanb92/GeneralizedProbabilisticUNetComment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:005. arXiv admin note: text overlap with arXiv:2207.1287

Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for Parkinson's disease (PD). Side-effects may, however, be induced when the DBS lead is placed suboptimally. Currently, lower field magnetic resonance imaging (MRI) at 1.5 or 3 Tesla (T) is used for targeting. Ultra-high-field MRI (7 T and above) can obtain superior anatomical information and might therefore be better suited for targeting. This study aims to test whether optimized 7 T imaging protocols result in less variable targeting of the STN for DBS compared to clinically utilized 3 T images. Three DBS-experienced neurosurgeons determined the optimal STN DBS target site on three repetitions of 3 T-T2, 7 T-T2*, 7 T-R2* and 7 T-QSM images for five PD patients. The distance in millimetres between the three repetitive coordinates was used as an index of targeting variability and was compared between field strength, MRI contrast and repetition with a Bayesian ANOVA. Further, the target coordinates were registered to MNI space, and anatomical coordinates were compared between field strength, MRI contrast and repetition using a Bayesian ANOVA. The results indicate that the neurosurgeons are stable in selecting the DBS target site across MRI field strength, MRI contrast and repetitions. The analysis of the coordinates in MNI space however revealed that the actual selected location of the electrode is seemingly more ventral when using the 3 T scan compared to the 7 T scans

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of eXplainable Artificial Intelligence (XAI) used in deep learning-based medical image analysis. A framework of XAI criteria is introduced to classify deep learning-based medical image analysis methods. Papers on XAI techniques in medical image analysis are then surveyed and categorized according to the framework and according to anatomical location. The paper concludes with an outlook of future opportunities for XAI in medical image analysis.Comment: Submitted for publication. Comments welcome by email to first autho

Implications of quantitative susceptibility mapping at 7 Tesla MRI for microbleeds detection in cerebral small vessel disease

BACKGROUND: Cerebral microbleeds (MBs) are a hallmark of cerebral small vessel disease (CSVD) and can be found on T2*-weighted sequences on MRI. Quantitative susceptibility mapping (QSM) is a postprocessing method that also enables MBs identification and furthermore allows to differentiate them from calcifications. AIMS: We explored the implications of using QSM at submillimeter resolution for MBs detection in CSVD. METHODS: Both 3 and 7 Tesla (T) MRI were performed in elderly participants without MBs and patients with CSVD. MBs were quantified on T2*-weighted imaging and QSM. Differences in the number of MBs were assessed, and subjects were classified in CSVD subgroups or controls both on 3T T2*-weighted imaging and 7T QSM. RESULTS: 48 participants [mean age (SD) 70.9 (8.8) years, 48% females] were included: 31 were healthy controls, 6 probable cerebral amyloid angiopathy (CAA), 9 mixed CSVD, and 2 were hypertensive arteriopathy [HA] patients. After accounting for the higher number of MBs detected at 7T QSM (Median = Mdn; Mdn7T−QSM = 2.5; Mdn3T−T2 = 0; z = 4.90; p < 0.001) and false positive MBs (6.1% calcifications), most healthy controls (80.6%) demonstrated at least one MB and more MBs were discovered in the CSVD group. CONCLUSIONS: Our observations suggest that QSM at submillimeter resolution improves the detection of MBs in the elderly human brain. A higher prevalence of MBs than so far known in healthy elderly was revealed