Identification of direct connections between the dura and the brain.

The arachnoid barrier delineates the border between the central nervous system and dura mater. Although the arachnoid barrier creates a partition, communication between the central nervous system and the dura mater is crucial for waste clearance and immune surveillance1,2. How the arachnoid barrier balances separation and communication is poorly understood. Here, using transcriptomic data, we developed transgenic mice to examine specific anatomical structures that function as routes across the arachnoid barrier. Bridging veins create discontinuities where they cross the arachnoid barrier, forming structures that we termed arachnoid cuff exit (ACE) points. The openings that ACE points create allow the exchange of fluids and molecules between the subarachnoid space and the dura, enabling the drainage of cerebrospinal fluid and limited entry of molecules from the dura to the subarachnoid space. In healthy human volunteers, magnetic resonance imaging tracers transit along bridging veins in a similar manner to access the subarachnoid space. Notably, in neuroinflammatory conditions such as experimental autoimmune encephalomyelitis, ACE points also enable cellular trafficking, representing a route for immune cells to directly enter the subarachnoid space from the dura mater. Collectively, our results indicate that ACE points are a critical part of the anatomy of neuroimmune communication in both mice and humans that link the central nervous system with the dura and its immunological diversity and waste clearance systems.

Imaging of brain barrier inflammation and brain fluid drainage in human neurological diseases.

The intricate relationship between the central nervous system (CNS) and the immune system plays a crucial role in the pathogenesis of various neurological diseases. Understanding the interactions among the immunopathological processes at the brain borders is essential for advancing our knowledge of disease mechanisms and developing novel diagnostic and therapeutic approaches. In this review, we explore the emerging role of neuroimaging in providing valuable insights into brain barrier inflammation and brain fluid drainage in human neurological diseases. Neuroimaging techniques have enabled us not only to visualize and assess brain structures, but also to study the dynamics of the CNS in health and disease in vivo. By analyzing imaging findings, we can gain a deeper understanding of the immunopathology observed at the brain-immune interface barriers, which serve as critical gatekeepers that regulate immune cell trafficking, cytokine release, and clearance of waste products from the brain. This review explores the integration of neuroimaging data with immunopathological findings, providing valuable insights into brain barrier integrity and immune responses in neurological diseases. Such integration may lead to the development of novel diagnostic markers and targeted therapeutic approaches that can benefit patients with neurological disorders.

Highly Sensitive 3-Tesla Real Inversion Recovery MRI Detects Leptomeningeal Contrast Enhancement in Chronic Active Multiple Sclerosis.

BACKGROUND: Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive. PURPOSE: To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME. MATERIALS AND METHODS: We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data. RESULTS: We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume. CONCLUSIONS: Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation.

Dilated Virchow-Robin spaces are a marker for arterial disease in multiple sclerosis.

BACKGROUND: Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. METHODS: In a cohort study comprising 142 MS patients and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) outcomes. Findings were corroborated in a validation cohort comprising 63 MS patients. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. FINDINGS: In our actively treated clinical cohort, the count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, in our ex vivo cohort comprising mostly progressive MS patients, dilated VRS in MS were associated with signs of small vessel disease. INTERPRETATION: Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with an accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature. FUNDING: NIH, Swedish Society for Medical Research, Swiss National Science Foundation and University of Zurich.

The etiology and evolution of magnetic resonance imaging-visible perivascular spaces: Systematic review and meta-analysis.

Objectives: Perivascular spaces have been involved in neuroinflammatory and neurodegenerative diseases. Upon a certain size, these spaces can become visible on magnetic resonance imaging (MRI), referred to as enlarged perivascular spaces (EPVS) or MRI-visible perivascular spaces (MVPVS). However, the lack of systematic evidence on etiology and temporal dynamics of MVPVS hampers their diagnostic utility as MRI biomarker. Thus, the goal of this systematic review was to summarize potential etiologies and evolution of MVPVS. Methods: In a comprehensive literature search, out of 1,488 unique publications, 140 records assessing etiopathogenesis and dynamics of MVPVS were eligible for a qualitative summary. 6 records were included in a meta-analysis to assess the association between MVPVS and brain atrophy. Results: Four overarching and partly overlapping etiologies of MVPVS have been proposed: (1) Impairment of interstitial fluid circulation, (2) Spiral elongation of arteries, (3) Brain atrophy and/or perivascular myelin loss, and (4) Immune cell accumulation in the perivascular space. The meta-analysis in patients with neuroinflammatory diseases did not support an association between MVPVS and brain volume measures [R: -0.15 (95%-CI -0.40-0.11)]. Based on few and mostly small studies in tumefactive MVPVS and in vascular and neuroinflammatory diseases, temporal evolution of MVPVS is slow. Conclusion: Collectively, this study provides high-grade evidence for MVPVS etiopathogenesis and temporal dynamics. Although several potential etiologies for MVPVS emergence have been proposed, they are only partially supported by data. Advanced MRI methods should be employed to further dissect etiopathogenesis and evolution of MVPVS. This can benefit their implementation as an imaging biomarker. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346564, identifier CRD42022346564.

Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T.

MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.

Dilated Virchow-Robin Spaces are a Marker for Arterial Disease in Multiple Sclerosis.

Virchow-Robin spaces (VRS) have been associated with neurodegeneration and neuroinflammation. However, it remains uncertain to what degree non-dilated or dilated VRS reflect specific features of neuroinflammatory pathology. Thus, we aimed at investigating the clinical relevance of VRS as imaging biomarker in multiple sclerosis (MS) and to correlate VRS to their histopathologic signature. In a cohort study comprising 205 MS patients (including a validation cohort) and 30 control subjects, we assessed the association of non-dilated and dilated VRS to clinical and magnetic resonance imaging (MRI) out-comes. Brain blocks from 6 MS patients and 3 non-MS controls were histopathologically processed to correlate VRS to their tissue substrate. The count of dilated centrum semiovale VRS was associated with increased T1 and T2 lesion volumes. There was no systematic spatial colocalization of dilated VRS with MS lesions. At tissue level, VRS mostly corresponded to arteries and were not associated with MS pathological hallmarks. Interestingly, dilated VRS in MS were associated with signs of small vessel disease. Contrary to prior beliefs, these observations suggest that VRS in MS do not associate with accumulation of immune cells. But instead, these findings indicate vascular pathology as a driver and/or consequence of neuroinflammatory pathology for this imaging feature.

Multi-contrast high-field quality image synthesis for portable low-field MRI using generative adversarial networks and paired data.

Introduction: Portable low-field strength (64mT) MRI scanners promise to increase access to neuroimaging for clinical and research purposes, however these devices produce lower quality images compared to high-field scanners. In this study, we developed and evaluated a deep learning architecture to generate high-field quality brain images from low-field inputs using a paired dataset of multiple sclerosis (MS) patients scanned at 64mT and 3T. Methods: A total of 49 MS patients were scanned on portable 64mT and standard 3T scanners at Penn (n=25) or the National Institutes of Health (NIH, n=24) with T1-weighted, T2-weighted and FLAIR acquisitions. Using this paired data, we developed a generative adversarial network (GAN) architecture for low- to high-field image translation (LowGAN). We then evaluated synthesized images with respect to image quality, brain morphometry, and white matter lesions. Results: Synthetic high-field images demonstrated visually superior quality compared to low-field inputs and significantly higher normalized cross-correlation (NCC) to actual high-field images for T1 (p=0.001) and FLAIR (p<0.001) contrasts. LowGAN generally outperformed the current state-of-the-art for low-field volumetrics. For example, thalamic, lateral ventricle, and total cortical volumes in LowGAN outputs did not differ significantly from 3T measurements. Synthetic outputs preserved MS lesions and captured a known inverse relationship between total lesion volume and thalamic volume. Conclusions: LowGAN generates synthetic high-field images with comparable visual and quantitative quality to actual high-field scans. Enhancing portable MRI image quality could add value and boost clinician confidence, enabling wider adoption of this technology.

Perivascular spaces and their role in neuroinflammation.

It is uncontested that perivascular spaces play critical roles in maintaining homeostasis and priming neuroinflammation. However, despite more than a century of intense research on perivascular spaces, many open questions remain about the anatomical compartment surrounding blood vessels within the CNS. The goal of this comprehensive review is to summarize the literature on perivascular spaces in human neuroinflammation and associated animal disease models. We describe the cell types taking part in the morphological and functional aspects of perivascular spaces and how those spaces can be visualized. Based on this, we propose a model of the cascade of events occurring during neuroinflammatory pathology. We also discuss current knowledge gaps and limitations of the available evidence. An improved understanding of perivascular spaces could advance our comprehension of the pathophysiology of neuroinflammation and open a new therapeutic window for neuroinflammatory diseases such as multiple sclerosis.

Sensitivity of portable low-field magnetic resonance imaging for multiple sclerosis lesions.

Magnetic resonance imaging (MRI) is a fundamental tool in the diagnosis and management of neurological diseases such as multiple sclerosis (MS). New portable, low-field strength, MRI scanners could potentially lower financial and technical barriers to neuroimaging and reach underserved or disabled populations, but the sensitivity of these devices for MS lesions is unknown. We sought to determine if white matter lesions can be detected on a portable 64mT scanner, compare automated lesion segmentations and total lesion volume between paired 3T and 64mT scans, identify features that contribute to lesion detection accuracy, and explore super-resolution imaging at low-field. In this prospective, cross-sectional study, same-day brain MRI (FLAIR, T1w, and T2w) scans were collected from 36 adults (32 women; mean age, 50 ± 14 years) with known or suspected MS using Siemens 3T (FLAIR: 1 mm isotropic, T1w: 1 mm isotropic, and T2w: 0.34-0.5 × 0.34-0.5 × 3-5 mm) and Hyperfine 64mT (FLAIR: 1.6 × 1.6 × 5 mm, T1w: 1.5 × 1.5 × 5 mm, and T2w: 1.5 × 1.5 × 5 mm) scanners at two centers. Images were reviewed by neuroradiologists. MS lesions were measured manually and segmented using an automated algorithm. Statistical analyses assessed accuracy and variability of segmentations across scanners and systematic scanner biases in automated volumetric measurements. Lesions were identified on 64mT scans in 94% (31/33) of patients with confirmed MS. The average smallest lesions manually detected were 5.7 ± 1.3 mm in maximum diameter at 64mT vs 2.1 ± 0.6 mm at 3T, approaching the spatial resolution of the respective scanner sequences (3T: 1 mm, 64mT: 5 mm slice thickness). Automated lesion volume estimates were highly correlated between 3T and 64mT scans (r = 0.89, p < 0.001). Bland-Altman analysis identified bias in 64mT segmentations (mean = 1.6 ml, standard error = 5.2 ml, limits of agreement = -19.0-15.9 ml), which over-estimated low lesion volume and under-estimated high volume (r = 0.74, p < 0.001). Visual inspection revealed over-segmentation was driven venous hyperintensities on 64mT T2-FLAIR. Lesion size drove segmentation accuracy, with 93% of lesions > 1.0 ml and all lesions > 1.5 ml being detected. Using multi-acquisition volume averaging, we were able to generate 1.6 mm isotropic images on the 64mT device. Overall, our results demonstrate that in established MS, a portable 64mT MRI scanner can identify white matter lesions, and that automated estimates of total lesion volume correlate with measurements from 3T scans.

Logistic Regression-Based Model Is More Efficient Than U-Net Model for Reliable Whole Brain Magnetic Resonance Imaging Segmentation.

OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest. The purpose of this study was to compare the performance of the prototypical deep learning segmentation architecture (U-Net) with a previously published atlas-free traditional machine learning method, Classification using Derivative-based Features (C-DEF) for whole brain segmentation, in the setting of limited training data. MATERIALS AND METHODS: C-DEF and U-Net models were evaluated after training on manually curated data from 5, 10, and 15 participants in 2 research cohorts: (1) people living with clinically diagnosed HIV infection and (2) relapsing-remitting multiple sclerosis, each acquired at separate institutions, and between 5 and 295 participants' data using a large, publicly available, and annotated data set of glioblastoma and lower grade glioma (brain tumor segmentation). Statistics was performed on the Dice similarity coefficient using repeated-measures analysis of variance and Dunnett-Hsu pairwise comparison. RESULTS: C-DEF produced better segmentation than U-Net in lesion (29.2%-38.9%) and cerebrospinal fluid (5.3%-11.9%) classes when trained with data from 15 or fewer participants. Unlike C-DEF, U-Net showed significant improvement when increasing the size of the training data (24%-30% higher than baseline). In the brain tumor segmentation data set, C-DEF produced equivalent or better segmentations than U-Net for enhancing tumor and peritumoral edema regions across all training data sizes explored. However, U-Net was more effective than C-DEF for segmentation of necrotic/non-enhancing tumor when trained on 10 or more participants, probably because of the inconsistent signal intensity of the tissue class. CONCLUSIONS: These results demonstrate that classical machine learning methods can produce more accurate brain segmentation than the far more complex deep learning methods when only small or moderate amounts of training data are available (n ≤ 15). The magnitude of this advantage varies by tissue and cohort, while U-Net may be preferable for deep gray matter and necrotic/non-enhancing tumor segmentation, particularly with larger training data sets (n ≥ 20). Given that segmentation models often need to be retrained for application to novel imaging protocols or pathology, the bottleneck associated with large-scale manual annotation could be avoided with classical machine learning algorithms, such as C-DEF.

Toscana virus associated with Guillain-Barré syndrome: a case-control study.

Guillain-Barré syndrome (GBS) is an acute-onset, immune-mediated polyradiculoneuropathy, often precipitated by an antecedent infection. An association of GBS with vector-borne viral infections has been suggested, with evidence for the involvement of Zika, Dengue, Chikungunya and West Nile virus (WNV). This prospective case-control study was conducted to identify vector-borne viral infections in GBS. Thirteen individuals newly diagnosed as GBS were enrolled. Disease severity, prognostic factors and nerve conduction patterns were assessed. Eleven individuals with non-infectious conditions requiring cerebrospinal fluid (CSF) analysis were included as controls. Plasma, CSF and urine specimens were evaluated via nucleic acid amplification assays aimed to detect a broad spectrum of viruses. WNV and Toscana virus (TOSV) IgM/IgG antibodies were screened using commercial immunofluorescence assays and confirmed via virus neutralization tests (VNT). Partial TOSV nucleocapsid and genotype 1 polymerase sequences were detected in CSF of a patient with normal pressure hydrocephalus. Two control subjects had VNT-confirmed TOSV IgM in plasma. VNT-confirmed WNV and TOSV IgG were detected in 15.4% and 61.5% of GBS patients, respectively. Variations in WNV IgG and TOSV IgM detection rates were not statistically significant among study cohorts. However, TOSV IgG was significantly more frequent in GBS patients. No difference was observed for disease form or prognostic scores for virus markers. Follow-up serological profiles were identical to the initial findings. We have identified TOSV as a potential precipitating agent in GBS, with some rare clinical presentations of symptomatic TOSV infections.

Post-stroke inflammatory response is linked to volume loss in the contralateral hemisphere.

OBJECTIVES: There is a delicate homeostatic balance between the central nervous system and immune system. Stroke triggers an immunodepressive state to suppress a potential immune reaction directed against neuroglial tissue; however, this supposedly protective response inadvertently results in an infection-prone, and thereby a pro-inflammatory setting. In this study, we assessed the magnitude of cerebral volume loss in the unaffected contralateral hemisphere following stroke, and determined its relationship with inflammatory cascades. METHODS: The volume of the hemisphere contralateral to the ischemic insult was measured on admission and follow-up MRI's in 50 ischemic stroke patients. Information related to clinical features, infectious complications, and markers of inflammation (erythrocyte sedimentation rate, neutrophil/lymphocyte ratio, C-reactive protein) were prospectively collected, and their relationship with hemispheric volume change was evaluated using bivariate and multivariate statistics. RESULTS: The contralateral hemisphere volume decreased by a median (interquartile range) of 14 (4-32) mL after a follow-up duration of 101 (63-123) days (p < .001); the volume reduction was 0.8 (0.2-1.8) % per month with respect to baseline. Old age, atrial fibrillation, stroke severity, C-reactive protein level, neutrophil/lymphocyte ratio, and development of infections during hospitalization were significantly associated with volume loss (p < .05). Stroke severity (NIHSS score or infarct volume) and inflammation related parameters (neutrophil/lymphocyte ratio or systemic infections) remained independently and positively associated with volume loss in multivariate regression models. CONCLUSIONS: Cerebral tissue changes following stroke are not limited to the ischemic hemisphere. Apart from stroke severity, a pro-inflammatory state and post-stroke infections contribute to cerebral volume loss in the non-ischemic hemisphere.

Retinal degeneration is associated with brain volume reduction and prognosis in radiologically isolated syndrome.

BACKGROUND: The extent of neurodegeneration in the earliest stages of central nervous system (CNS) demyelination is not known. Optical coherence tomography (OCT) is a powerful tool to study neurodegeneration in demyelinating disorders. OBJECTIVES: To study neuroaxonal loss in the retina of individuals with radiologically isolated syndrome (RIS) and investigate whether OCT measurements are associated with brain volumetrics and clinical conversion to multiple sclerosis (MS). METHODS: Subjects fulfilling the Okuda criteria for RIS (n = 15 patients, 30 eyes) and age- and sex-matched healthy controls (HC) underwent spectral-domain OCT and magnetic resonance imaging for volumetric measurement of brain structures. RESULTS: Macular ganglion cell-inner plexiform layer (mGCIPL), macular retinal nerve fiber layer (mRNFL), and temporal peripapillary RNFL (pRNFL) thickness; normalized total brain volume (nTBV); and normalized thalamic volume (nTV) were reduced in RIS compared to HC. mGCIPL, mRNFL, and pRNFL measurements were associated with nTBV, nTV, and normalized gray and white matter volumes in the RIS group. pRNFL was thinner in individuals with RIS who converted to MS in 5 years. CONCLUSIONS: Retinal neurodegeneration can be detected in the papillomacular region in the earliest stages of CNS demyelination and reflects global disease processes in the brain. OCT can be potentially useful for predicting prognosis in RIS.

Neuroinvasive Listeriosis: Could Petechial Hemorrhages be a Diagnostic Clue?

INTRODUCTION: Listeria monocytogenes-related central nervous system infections may involve the cerebral parenchyma. Meningitis and meningoencephalitis are the most commonly seen forms and mainly affect immunocompromised patients; however, a less frequent form, rhombencephalitis, can occur in otherwise healthy people. Early treatment with appropriate antibiotic therapy is crucial for this otherwise fatal disorder. However, it is not always possible to rapidly establish the diagnosis because of varying presentations and discrepancies in diagnostic tests. CASE REPORT: Herein we report 3 cases of listerial infections involving the central nervous system parenchyma, with versatile diagnostic challenges and related possible solutions and radiologic hints to overcome similar issues in the future. CONCLUSIONS: We point out the importance of nonconventional magnetic resonance imaging techniques in the diagnosis, as we detected petechial hemorrhages in the brain parenchyma in all cases, which can be a diagnostic clue.

Urinary detection of toscana virus nucleic acids in neuroinvasive infections.

BACKGROUND: Toscana virus (TOSV) is a sandfly-borne pathogen causing febrile diseases and neuroinvasive infections in humans. Definitive diagnosis of TOSV infections frequently requires the detection of viral RNA in cerebrospinal fluid (CSF) or in circulation, which can be achieved prior to seroconversion. OBJECTIVES: To evaluate TOSV excretion in urine and impact of urine as a diagnostic specimen. STUDY DESIGN: A total of 82 plasma, CSF and urine samples were collected from 24 individuals with a preliminary diagnosis of atypical viral encephalitis, where frequent bacterial fungal and viral causes were ruled out. Phlebovirus and WNV nucleic acids were investigated via real-time and nested polymerase chain reaction (PCR) assays. Commercial immunofluorescence assays were employed for viral IgM detection. Amplicons were characterized via cloning and sequencing. RESULTS: Phlebovirus PCR yielded positive results in 7 out of 14 samples that comprise 4 plasma and 3 urine specimens from 3 individuals. Amplicons were characterized as TOSV genotype A. Investigation of the follow-up samples suggested that virus shedding in urine coincides or follows viremia. Despite conserved sequences observed in paired or sequential plasma-urine specimens, L693S substitution in the viral polymerase was characterized in a urine sample. CONCLUSIONS: These preliminary findings indicate that urine can be employed as a additional clinical sample for TOSV RNA detection in suspected cases, especially in individuals where specimens for viral diagnostics during the early stages of the infection are not available.