Posterior reversible encephalopathy syndrome in a patient with mixed connective tissue disease: A case report

Background: Posterior reversible encephalopathy is a syndrome highly associated with hypertension and cytotoxic therapy. The syndrome typically presents with headache, visual abnormality, seizures and characteristic vasogenic edema on magnetic resonance imaging. The entity warrants a prompt diagnosis to avoid deteriorating consequences. Case presentation: In this report, we describe a 15-year-old Iranian boy who was diagnosed with mixed connective tissue disease, and cyclophosphamide pulse therapy was administered. Three days after the second pulse of cyclophosphamide, when he was receiving prednisolone and hydroxycholoroquine, our patient developed generalized tonic-clonic seizures. Magnetic resonance imaging findings showed high signal intensities in the posterior areas of his brain. After 8 days, the brain magnetic resonance imaging abnormalities were resolved following the control of his blood pressure and antiepileptic treatment. These observations have been indicative of posterior reversible encephalopathy syndrome. Nevertheless, our patient developed uncontrollable respiratory distress and eventually died. Conclusions: To the best of our knowledge, this case is the first report of posterior reversible encephalopathy syndrome in a patient with mixed connective tissue disease. As the patient developed posterior reversible encephalopathy syndrome 3 days after cyclophosphamide pulse therapy to reduce the disease activity, it is hard to accurately determine whether posterior reversible encephalopathy syndrome in this case is a complication of cyclophosphamide or a condition that resulted from the mixed connective tissue disease flare-up. © 2016 The Author(s)

Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE.

The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortical lesions are hardly visible in conventional magnetic resonance imaging (MRI) at 3T, and thus their automated detection has been so far little explored. In this study, we propose a fully-convolutional deep learning approach, based on the 3D U-Net, for the automated segmentation of cortical and white matter lesions at 3T. For this purpose, we consider a clinically plausible MRI setting consisting of two MRI contrasts only: one conventional T2-weighted sequence (FLAIR), and one specialized T1-weighted sequence (MP2RAGE). We include 90 patients from two different centers with a total of 728 and 3856 gray and white matter lesions, respectively. We show that two reference methods developed for white matter lesion segmentation are inadequate to detect small cortical lesions, whereas our proposed framework is able to achieve a detection rate of 76% for both cortical and white matter lesions with a false positive rate of 29% in comparison to manual segmentation. Further results suggest that our framework generalizes well for both types of lesion in subjects acquired in two hospitals with different scanners

RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis.

In multiple sclerosis (MS), the presence of a paramagnetic rim at the edge of non-gadolinium-enhancing lesions indicates perilesional chronic inflammation. Patients featuring a higher paramagnetic rim lesion burden tend to have more aggressive disease. The objective of this study was to develop and evaluate a convolutional neural network (CNN) architecture (RimNet) for automated detection of paramagnetic rim lesions in MS employing multiple magnetic resonance (MR) imaging contrasts. Imaging data were acquired at 3 Tesla on three different scanners from two different centers, totaling 124 MS patients, and studied retrospectively. Paramagnetic rim lesion detection was independently assessed by two expert raters on T2*-phase images, yielding 462 rim-positive (rim+) and 4857 rim-negative (rim-) lesions. RimNet was designed using 3D patches centered on candidate lesions in 3D-EPI phase and 3D FLAIR as input to two network branches. The interconnection of branches at both the first network blocks and the last fully connected layers favors the extraction of low and high-level multimodal features, respectively. RimNet's performance was quantitatively evaluated against experts' evaluation from both lesion-wise and patient-wise perspectives. For the latter, patients were categorized based on a clinically relevant threshold of 4 rim+ lesions per patient. The individual prediction capabilities of the images were also explored and compared (DeLong test) by testing a CNN trained with one image as input (unimodal). The unimodal exploration showed the superior performance of 3D-EPI phase and 3D-EPI magnitude images in the rim+/- classification task (AUC = 0.913 and 0.901), compared to the 3D FLAIR (AUC = 0.855, Ps < 0.0001). The proposed multimodal RimNet prototype clearly outperformed the best unimodal approach (AUC = 0.943, P < 0.0001). The sensitivity and specificity achieved by RimNet (70.6% and 94.9%, respectively) are comparable to those of experts at the lesion level. In the patient-wise analysis, RimNet performed with an accuracy of 89.5% and a Dice coefficient (or F1 score) of 83.5%. The proposed prototype showed promising performance, supporting the usage of RimNet for speeding up and standardizing the paramagnetic rim lesions analysis in MS

GAMER MRI: Gated-attention mechanism ranking of multi-contrast MRI in brain pathology.

During the last decade, a multitude of novel quantitative and semiquantitative MRI techniques have provided new information about the pathophysiology of neurological diseases. Yet, selection of the most relevant contrasts for a given pathology remains challenging. In this work, we developed and validated a method, Gated-Attention MEchanism Ranking of multi-contrast MRI in brain pathology (GAMER MRI), to rank the relative importance of MR measures in the classification of well understood ischemic stroke lesions. Subsequently, we applied this method to the classification of multiple sclerosis (MS) lesions, where the relative importance of MR measures is less understood. GAMER MRI was developed based on the gated attention mechanism, which computes attention weights (AWs) as proxies of importance of hidden features in the classification. In the first two experiments, we used Trace-weighted (Trace), apparent diffusion coefficient (ADC), Fluid-Attenuated Inversion Recovery (FLAIR), and T1-weighted (T1w) images acquired in 904 acute/subacute ischemic stroke patients and in 6,230 healthy controls and patients with other brain pathologies to assess if GAMER MRI could produce clinically meaningful importance orders in two different classification scenarios. In the first experiment, GAMER MRI with a pretrained convolutional neural network (CNN) was used in conjunction with Trace, ADC, and FLAIR to distinguish patients with ischemic stroke from those with other pathologies and healthy controls. In the second experiment, GAMER MRI with a patch-based CNN used Trace, ADC and T1w to differentiate acute ischemic stroke lesions from healthy tissue. The last experiment explored the performance of patch-based CNN with GAMER MRI in ranking the importance of quantitative MRI measures to distinguish two groups of lesions with different pathological characteristics and unknown quantitative MR features. Specifically, GAMER MRI was applied to assess the relative importance of the myelin water fraction (MWF), quantitative susceptibility mapping (QSM), T1 relaxometry map (qT1), and neurite density index (NDI) in distinguishing 750 juxtacortical lesions from 242 periventricular lesions in 47 MS patients. Pair-wise permutation t-tests were used to evaluate the differences between the AWs obtained for each quantitative measure. In the first experiment, we achieved a mean test AUC of 0.881 and the obtained AWs of FLAIR and the sum of AWs of Trace and ADC were 0.11 and 0.89, respectively, as expected based on previous knowledge. In the second experiment, we achieved a mean test F1 score of 0.895 and a mean AW of Trace = 0.49, of ADC = 0.28, and of T1w = 0.23, thereby confirming the findings of the first experiment. In the third experiment, MS lesion classification achieved test balanced accuracy = 0.777, sensitivity = 0.739, and specificity = 0.814. The mean AWs of T1map, MWF, NDI, and QSM were 0.29, 0.26, 0.24, and 0.22 (p < 0.001), respectively. This work demonstrates that the proposed GAMER MRI might be a useful method to assess the relative importance of MRI measures in neurological diseases with focal pathology. Moreover, the obtained AWs may in fact help to choose the best combination of MR contrasts for a specific classification problem

BDNF modifies hippocampal KCC2 and NKCC1 expression in a temporal lobe epilepsy model

Excitatory GABA actions, induced by altered expression of chloride transporters (KCC2/NKCC1), can contribute to seizure generation in temporal lobe epilepsy. In the present study, we evaluated whether BDNF administration can affect KCC2/ NKCC1 expression, ictogenesis and behavioral alterations in this paradigm. Status epilepticus was induced in male rats with pilocarpine, followed by a treatment of either a single high dose or multiple injections of BDNF during the latent phase of temporal lobe epilepsy. Chloride transporters expression, spontaneous recurrent seizures, and hyperexcitability post-seizural behaviors were evaluated after treatment. NKCC1 protein expression was markedly upregulated, whereas that of KCC2 was significantly downregulated in epileptic hippocampi compared to intact controls. Application of BDNF (both single high dose and multiple injections) increased KCC2 expression in epileptic hippocampi, while NKCC1 expression was downregulated exclusively by the single high dose injection of BDNF. Development of spontaneous recurrent seizures was delayed but not prevented by the treatment, and hyperexcitability behaviors were ameliorated for a short period of time. To prevent GABA-A mediated depolarization and design appropriate treatment strategies for temporal lobe epilepsy, chloride transporters can be considered as a target. Future studies are warranted to investigate any possible therapeutic effects of BDNF via altering chloride transporters expression. © 2014 by Polish Neuroscience Society - PTBUN, Nencki Institute of Experimental Biology

Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study

Background: Serum neurofilament light chain (sNfL) is a biomarker of neuronal damage that is used not only to monitor disease activity and response to drugs and to prognosticate disease course in people with multiple sclerosis on the group level. The absence of representative reference values to correct for physiological age-dependent increases in sNfL has limited the diagnostic use of this biomarker at an individual level. We aimed to assess the applicability of sNfL for identification of people at risk for future disease activity by establishing a reference database to derive reference values corrected for age and body-mass index (BMI). Furthermore, we used the reference database to test the suitability of sNfL as an endpoint for group-level comparison of effectiveness across disease-modifying therapies. Methods: For derivation of a reference database of sNfL values, a control group was created, comprising participants with no evidence of CNS disease taking part in four cohort studies in Europe and North America. We modelled the distribution of sNfL concentrations in function of physiological age-related increase and BMI-dependent modulation, to derive percentile and Z score values from this reference database, via a generalised additive model for location, scale, and shape. We tested the reference database in participants with multiple sclerosis in the Swiss Multiple Sclerosis Cohort (SMSC). We compared the association of sNfL Z scores with clinical and MRI characteristics recorded longitudinally to ascertain their respective disease prognostic capacity. We validated these findings in an independent sample of individuals with multiple sclerosis who were followed up in the Swedish Multiple Sclerosis registry. Findings: We obtained 10 133 blood samples from 5390 people (median samples per patient 1 [IQR 1–2] in the control group). In the control group, sNfL concentrations rose exponentially with age and at a steeper increased rate after approximately 50 years of age. We obtained 7769 samples from 1313 people (median samples per person 6·0 [IQR 3·0–8·0]). In people with multiple sclerosis from the SMSC, sNfL percentiles and Z scores indicated a gradually increased risk for future acute (eg, relapse and lesion formation) and chronic (disability worsening) disease activity. A sNfL Z score above 1·5 was associated with an increased risk of future clinical or MRI disease activity in all people with multiple sclerosis (odds ratio 3·15, 95% CI 2·35–4·23; p<0·0001) and in people considered stable with no evidence of disease activity (2·66, 1·08–6·55; p=0·034). Increased Z scores outperformed absolute raw sNfL cutoff values for diagnostic accuracy. At the group level, the longitudinal course of sNfL Z score values in people with multiple sclerosis from the SMSC decreased to those seen in the control group with use of monoclonal antibodies (ie, alemtuzumab, natalizumab, ocrelizumab, and rituximab) and, to a lesser extent, oral therapies (ie, dimethyl fumarate, fingolimod, siponimod, and teriflunomide). However, longitudinal sNfL Z scores remained elevated with platform compounds (interferons and glatiramer acetate; p<0·0001 for the interaction term between treatment category and treatment duration). Results were fully supported in the validation cohort (n=4341) from the Swedish Multiple Sclerosis registry. Interpretation: The use of sNfL percentiles and Z scores allows for identification of individual people with multiple sclerosis at risk for a detrimental disease course and suboptimal therapy response beyond clinical and MRI measures, specifically in people with disease activity-free status. Additionally, sNfL might be used as an endpoint for comparing effectiveness across drug classes in pragmatic trials. Funding: Swiss National Science Foundation, Progressive Multiple Sclerosis Alliance, Biogen, Celgene, Novartis, Roche

Killing Hypoxic Cell Populations in a 3D Tumor Model with EtNBS-PDT

An outstanding problem in cancer therapy is the battle against treatment-resistant disease. This is especially true for ovarian cancer, where the majority of patients eventually succumb to treatment-resistant metastatic carcinomatosis. Limited perfusion and diffusion, acidosis, and hypoxia play major roles in the development of resistance to the majority of front-line therapeutic regimens. To overcome these limitations and eliminate otherwise spared cancer cells, we utilized the cationic photosensitizer EtNBS to treat hypoxic regions deep inside in vitro 3D models of metastatic ovarian cancer. Unlike standard regimens that fail to penetrate beyond ∼150 µm, EtNBS was found to not only penetrate throughout the entirety of large (>200 µm) avascular nodules, but also concentrate into the nodules' acidic and hypoxic cores. Photodynamic therapy with EtNBS was observed to be highly effective against these hypoxic regions even at low therapeutic doses, and was capable of destroying both normoxic and hypoxic regions at higher treatment levels. Imaging studies utilizing multiphoton and confocal microscopies, as well as time-lapse optical coherence tomography (TL-OCT), revealed an inside-out pattern of cell death, with apoptosis being the primary mechanism of cell killing. Critically, EtNBS-based photodynamic therapy was found to be effective against the model tumor nodules even under severe hypoxia. The inherent ability of EtNBS photodynamic therapy to impart cytotoxicity across a wide range of tumoral oxygenation levels indicates its potential to eliminate treatment-resistant cell populations