SummaryBackgroundThere are thousands of survivors of the 2014 Ebola outbreak in west Africa. Ebola virus can persist in survivors for months in immune-privileged sites; however, viral relapse causing life-threatening and potentially transmissible disease has not been described. We report a case of late relapse in a patient who had been treated for severe Ebola virus disease with high viral load (peak cycle threshold value 13·2).MethodsA 39-year-old female nurse from Scotland, who had assisted the humanitarian effort in Sierra Leone, had received intensive supportive treatment and experimental antiviral therapies, and had been discharged with undetectable Ebola virus RNA in peripheral blood. The patient was readmitted to hospital 9 months after discharge with symptoms of acute meningitis, and was found to have Ebola virus in cerebrospinal fluid (CSF). She was treated with supportive therapy and experimental antiviral drug GS-5734 (Gilead Sciences, San Francisco, Foster City, CA, USA). We monitored Ebola virus RNA in CSF and plasma, and sequenced the viral genome using an unbiased metagenomic approach.FindingsOn admission, reverse transcriptase PCR identified Ebola virus RNA at a higher level in CSF (cycle threshold value 23·7) than plasma (31·3); infectious virus was only recovered from CSF. The patient developed progressive meningoencephalitis with cranial neuropathies and radiculopathy. Clinical recovery was associated with addition of high-dose corticosteroids during GS-5734 treatment. CSF Ebola virus RNA slowly declined and was undetectable following 14 days of treatment with GS-5734. Sequencing of plasma and CSF viral genome revealed only two non-coding changes compared with the original infecting virus.InterpretationOur report shows that previously unanticipated, late, severe relapses of Ebola virus can occur, in this case in the CNS. This finding fundamentally redefines what is known about the natural history of Ebola virus infection. Vigilance should be maintained in the thousands of Ebola survivors for cases of relapsed infection. The potential for these cases to initiate new transmission chains is a serious public health concern.FundingRoyal Free London NHS Foundation Trust.

The segmentation from MRI of macroscopically ill-defined and highly variable structures, such as the hippocampus (Hc) and the amygdala (Am), requires the use of specific constraints. Here, we describe and evaluate a fast fully automatic hybrid segmentation that uses knowledge derived from probabilistic atlases and anatomical landmarks, adapted from a semi-automatic method. The algorithm was designed at the outset for application on images from healthy subjects and patients with hippocampal sclerosis. Probabilistic atlases were built from 16 healthy subjects, registered using SPM5. Local mismatch in the atlas registration step was automatically detected and corrected. Quantitative evaluation with respect to manual segmentations was performed on the 16 young subjects, with a leave-one-out strategy, a mixed cohort of 8 controls and 15 patients with epilepsy with variable degrees of hippocampal sclerosis, and 8 healthy subjects acquired on a 3 T scanner. Seven performance indices were computed, among which error on volumes RV and Dice overlap K. The method proved to be fast, robust and accurate. For Hc, results with the new method were: 16 young subjects {RV = 5%, K = 87%}; mixed cohort {RV = 8%, K = 84%}; 3 T cohort {RV = 9%, K = 85%}. Results were better than with atlas-based (thresholded probability map) or semi-automatic segmentations. Atlas mismatch detection and correction proved efficient for the most sclerotic Hc. For Am, results were: 16 young controls {RV = 7%, K = 85%}; mixed cohort {RV = 19%, K = 78%}; 3 T cohort {RV = 10%, K = 77%}. Results were better than with the semi-automatic segmentation, and were also better than atlas-based segmentations for the 16 young subjects.

Our objective was to determine the pattern and extent of generalized and focal neocortical atrophy that develops in patients with epilepsy and the factors associated with such changes. As part of a prospective, longitudinal follow-up study of 122 patients with chronic epilepsy, 68 newly diagnosed patients, and 90 controls, serial magnetic resonance imaging scans were obtained 3.5 years apart. Image subtraction was used to identify diffuse and focal neocortical change that was quantified with a regional brain atlas and a fully automated segmentation algorithm. New focal or generalized neocortical volume losses were identified in 54% of patients with chronic epilepsy, 39% of newly diagnosed patients and 24% of controls. Patients with chronic epilepsy were significantly more likely to develop neocortical atrophy than control subjects. The increased risk of cerebral atrophy in epilepsy was not related to a history of documented seizures. Risk factors for neocortical atrophy were age and multiple antiepileptic drug exposure. Focal and generalized neocortical atrophy commonly develops in chronic epilepsy. Neocortical changes seen in a quarter of our control group over 3.5 years were likely to reflect physiological changes. Our results show that ongoing cerebral atrophy may be widespread and remote from the putative epileptic focus, possibly reflecting extensive networks and interconnections between cortical regions.

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