Interpretable surface-based detection of focal cortical dysplasias:a Multi-centre Epilepsy Lesion Detection study

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy

The Developing Human Connectome Project Neonatal Data Release

The Developing Human Connectome Project has created a large open science resource which provides researchers with data for investigating typical and atypical brain development across the perinatal period. It has collected 1228 multimodal magnetic resonance imaging (MRI) brain datasets from 1173 fetal and/or neonatal participants, together with collateral demographic, clinical, family, neurocognitive and genomic data from 1173 participants, together with collateral demographic, clinical, family, neurocognitive and genomic data. All subjects were studied in utero and/or soon after birth on a single MRI scanner using specially developed scanning sequences which included novel motion-tolerant imaging methods. Imaging data are complemented by rich demographic, clinical, neurodevelopmental, and genomic information. The project is now releasing a large set of neonatal data; fetal data will be described and released separately. This release includes scans from 783 infants of whom: 583 were healthy infants born at term; as well as preterm infants; and infants at high risk of atypical neurocognitive development. Many infants were imaged more than once to provide longitudinal data, and the total number of datasets being released is 887. We now describe the dHCP image acquisition and processing protocols, summarize the available imaging and collateral data, and provide information on how the data can be accessed

SIADH versus adrenal insufficiency: a life-threatening misdiagnosis

Abstract Background Primary adrenal insufficiency (PAI) in children is an uncommon but severe condition which can be either inherited or acquired. It consists in clinical manifestation of defective production or ineffective action of endogenous glucocorticoids; deficiency in mineralocorticoids and adrenal androgens may coexist. Diagnosis of PAI in children and young people can be challenging; while adrenal crisis (acute decompensation) is a life-threatening condition, with patient presenting with characteristic features of hypoglycemia, hypotension, collapse and coma, chronic adrenal insufficiency may present with vague and non-specific symptoms, making the diagnosis more difficult.1 Gastroenteritis and Syndrome of Inappropriate Secretion of Antidiuretic hormone (SIADH) are the most frequent reported misdiagnosis in patients with adrenal insufficiency (AI). While intravenous fluid replacement in the suspect of a gastroenteritis would be beneficial, a SIADH misdiagnosis can be harmful since the treatment of this condition is based primarily on fluid restriction. Case presentation We report the case of a child admitted to the emergency department whose condition was ultimately diagnosed as autoimmune adrenal insufficiency after few hours of inappropriate fluid restriction following a SIADH misdiagnosis. Conclusions AI is a rare condition in children and the diagnosis can be challenging. A missed diagnosis of AI or an inadequate treatment may cause severe complications, especially if a SIADH is erroneously diagnosed. Emergency physicians and pediatricians should be familiar with this diagnosis to enhance early recognition of this potentially life-threatening condition

Insufficienza surrenalica: Rara ma non troppo

Adrenal insufficiency is a rare condition in childhood. Clinical characteristics of adrenal insufficiency in children may be non-specific. Therefore, the diagnosis may be suspected late. If unrecognized, adrenal insufficiency may present with life-threatening cardiovascular collapse. In this article, current knowledge of the clinical manifestations, diagnosis, and treatment of adrenal insufficiency in children and factors precipitating adrenal crisis are summarized

Functional analysis of the third identified SLC25A19 mutation causative for the thiamine metabolism dysfunction syndrome 4

Thiamine metabolism dysfunction syndrome-4 (THMD4) includes episodic encephalopathy, often associated with a febrile illness, causing transient neurologic dysfunction and a slowly progressive axonal polyneuropathy. Until now only two mutations (G125S and S194P) have been reported in the SLC25A19 gene as causative for this disease and a third mutation (G177A) as related to the Amish lethal microcephaly. In this work, we describe the clinical and molecular features of a patient carrying a novel mutation (c.576G>C; Q192H) on SLC25A19 gene. Functional studies on this mutation were performed explaining the pathogenetic role of c.576G>C in affecting the translational efficiency and/or stability of hMTPPT protein instead of the mRNA expression. These findings support the pathogenetic role of Q192H (c.576G>C) mutation on SLC25A19 gene. Moreover, despite in other patients the thiamine supplementation leaded to a substantial improvement of peripheral neuropathy, our patient did not show a clinical improvement

Widespread, depth-dependent cortical microstructure alterations in paediatric focal epilepsy

Objective Tissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes, treatment-related side-effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilised quantitative MRI, which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. Methods To assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy [age-range=4-18 years] and 46 typically-developing children [age-range=2-18 years]. We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically-defined abnormalities (MRI-positive) and healthy controls, and tested if this could classify patients without reported radiological abnormalities (MRI-negative). Results We uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 71.4% at 89.4% specificity on held-out MRI-negative patients. Significance These findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically identified abnormalities

Differences in lung function between children with sickle cell anaemia from West Africa and Europe

Lung function abnormalities are common in sickle cell anaemia (SCA) but data from sub-Saharan Africa are limited. We hypothesised that children with SCA from West Africa had worse lung function than their counterparts from Europe