Care practices and outcomes of extremely preterm neonates born at 22-24 weeks - A single centre experience.

BACKGROUND: Wide variation in the care practices and survival rates of neonates born at peri-viable gestational ages of 22+0 - 24+6 weeks. This study elucidates the postnatal risk factors for morbidity/mortality, contrasts the care practices and short-term outcomes of this vulnerable group of preterm neonates from a single center with others. METHODS: Retrospective study of neonates born at 22+0 -24+6 weeks in a level 3 neonatal intensive care unit in UK, over a period of 4 years (2016-2019). RESULTS: 94 neonates given active care were studied. Survival until discharge was 51.1%(22-23 wks -44%, 24 wks -59.1%) and survival with no major brain injury (MBI) [grade III/IV IVH, cystic periventricular leukomalacia] was 38.3%(22-23 wks -32%, 24 wks -45.4%). Of those who survived until discharge, 75%had no MBI (22-23 wks -72.7%, 24 wks -76.9%). Neonates requiring significant respiratory support within first 72 hours as well as needing rescue high frequency ventilation had significantly high risk of mortality or MBI [aOR -7.17 (2.24-25.79), p = 0.00; 4.76 (1.43-20.00), p = 0.01]. CONCLUSIONS: Survival rate differed from other centres. MBI was low amongst survivors. Severe respiratory disease in the initial days was associated with a higher risk of death or MBI.

Deep Learning for Pediatric Posterior Fossa Tumor Detection and Classification: A Multi-Institutional Study.

BACKGROUND AND PURPOSE: Posterior fossa tumors are the most common pediatric brain tumors. MR imaging is key to tumor detection, diagnosis, and therapy guidance. We sought to develop an MR imaging-based deep learning model for posterior fossa tumor detection and tumor pathology classification. MATERIALS AND METHODS: The study cohort comprised 617 children (median age, 92 months; 56% males) from 5 pediatric institutions with posterior fossa tumors: diffuse midline glioma of the pons (n = 122), medulloblastoma (n = 272), pilocytic astrocytoma (n = 135), and ependymoma (n = 88). There were 199 controls. Tumor histology served as ground truth except for diffuse midline glioma of the pons, which was primarily diagnosed by MR imaging. A modified ResNeXt-50-32x4d architecture served as the backbone for a multitask classifier model, using T2-weighted MRIs as input to detect the presence of tumor and predict tumor class. Deep learning model performance was compared against that of 4 radiologists. RESULTS: Model tumor detection accuracy exceeded an AUROC of 0.99 and was similar to that of 4 radiologists. Model tumor classification accuracy was 92% with an F1 score of 0.80. The model was most accurate at predicting diffuse midline glioma of the pons, followed by pilocytic astrocytoma and medulloblastoma. Ependymoma prediction was the least accurate. Tumor type classification accuracy and F1 score were higher than those of 2 of the 4 radiologists. CONCLUSIONS: We present a multi-institutional deep learning model for pediatric posterior fossa tumor detection and classification with the potential to augment and improve the accuracy of radiologic diagnosis.

A Metabolic Intravascular Platform to Study FDG Uptake in Vascular Injury.

PURPOSE: Metabolic alterations underlie many pathophysiological conditions, and their understanding is critical for the development of novel therapies. Although the assessment of metabolic changes in vivo has been historically challenging, recent developments in molecular imaging have allowed us to study novel metabolic research concepts directly in the living subject, bringing us closer to patients. However, in many instances, there is need for sensors that are in close proximity to the organ under investigation, for example to study vascular metabolism. METHODS: In this study, we developed and validated a metabolic detection platform directly in the living subject under an inflammatory condition. The signal collected by a scintillating fiber is amplified using a photomultiplier tube and decodified by an in-house tunable analysis platform. For in vivo testing, we based our experiments on the metabolic characteristics of macrophages, cells closely linked to inflammation and avid for glucose and its analog 18F-fluorodeoxyglucose (18F-FDG). The sensor was validated in New Zealand rabbits, in which inflammation was induced by either a) high cholesterol (HC) diet for 16 weeks or b) vascular balloon endothelial denudation followed by HC diet. RESULTS: There was no difference in weight, hemodynamics, blood pressure, or heart rate between the groups. Vascular inflammation was detected by the metabolic sensor (Inflammation: 0.60 ± 0.03 AU vs. control: 0.48 ± 0.03 AU, p = 0.01), even though no significant inflammation/atherosclerosis was detected by intravascular ultrasound, underscoring the high sensitivity of the system. These findings were confirmed by the presence of macrophages on ex vivo aortic tissue staining. CONCLUSION: In this study, we validated a tunable very sensitive metabolic sensor platform that can be used for the detection of vascular metabolism, such as inflammation. This sensor can be used not only for the detection of macrophage activity but, with alternative probes, it could allow the detection of other pathophysiological processes.

MR Imaging-Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma.

BACKGROUND AND PURPOSE: Distinct molecular subgroups of pediatric medulloblastoma confer important differences in prognosis and therapy. Currently, tissue sampling is the only method to obtain information for classification. Our goal was to develop and validate radiomic and machine learning approaches for predicting molecular subgroups of pediatric medulloblastoma. MATERIALS AND METHODS: In this multi-institutional retrospective study, we evaluated MR imaging datasets of 109 pediatric patients with medulloblastoma from 3 children's hospitals from January 2001 to January 2014. A computational framework was developed to extract MR imaging-based radiomic features from tumor segmentations, and we tested 2 predictive models: a double 10-fold cross-validation using a combined dataset consisting of all 3 patient cohorts and a 3-dataset cross-validation, in which training was performed on 2 cohorts and testing was performed on the third independent cohort. We used the Wilcoxon rank sum test for feature selection with assessment of area under the receiver operating characteristic curve to evaluate model performance. RESULTS: Of 590 MR imaging-derived radiomic features, including intensity-based histograms, tumor edge-sharpness, Gabor features, and local area integral invariant features, extracted from imaging-derived tumor segmentations, tumor edge-sharpness was most useful for predicting sonic hedgehog and group 4 tumors. Receiver operating characteristic analysis revealed superior performance of the double 10-fold cross-validation model for predicting sonic hedgehog, group 3, and group 4 tumors when using combined T1- and T2-weighted images (area under the curve = 0.79, 0.70, and 0.83, respectively). With the independent 3-dataset cross-validation strategy, select radiomic features were predictive of sonic hedgehog (area under the curve = 0.70-0.73) and group 4 (area under the curve = 0.76-0.80) medulloblastoma. CONCLUSIONS: This study provides proof-of-concept results for the application of radiomic and machine learning approaches to a multi-institutional dataset for the prediction of medulloblastoma subgroups.

MRI Characteristics of Primary Tumors and Metastatic Lesions in Molecular Subgroups of Pediatric Medulloblastoma: A Single-Center Study.

BACKGROUND AND PURPOSE: Molecular grouping of medulloblastoma correlates with prognosis and supports the therapeutic strategy. We provide our experience with the imaging features of primary and metastatic disease in relation to the molecular groups. MATERIALS AND METHODS: One hundred nineteen consecutive patients (mean age, 7.3 ± 3.8 years at diagnosis; male, 79 [66.4%]) with a confirmed diagnosis of medulloblastoma and interpretable pretreatment MRIs were retrieved from our data base from January 2000 to December 2016. Each patient was assigned to wingless, sonic hedgehog, group 3, or group 4 molecular groups. Then, we determined the imaging features of both primary and metastatic/recurrent disease predictive of molecular groups. RESULTS: In addition to recently reported predictors based on primary tumor, including cerebellar peripheral location for sonic hedgehog (adjusted odds ratio = 9, P < .0001), minimal enhancement of primary group 4 tumor (adjusted odds ratio = 5.2, P < .0001), and cerebellopontine angle location for wingless (adjusted odds ratio = 1.4, P = .03), ependymal metastasis with diffusion restriction and minimal postcontrast enhancement ("mismatching pattern") (adjusted odds ratio = 2.8, P = .001) for group 4 and spinal metastasis for group 3 (adjusted odds ratio = 1.9, P = .01) also emerged as independent predictors of medulloblastoma molecular groups. Specifically, the presence of a metastasis in the third ventricular infundibular recess showing a mismatching pattern was significantly associated with group 4 (P = .02). CONCLUSIONS: In addition to imaging features of primary tumors, some imaging patterns of metastatic dissemination in medulloblastoma seem characteristic, perhaps even specific to certain groups. This finding could further help in differentiating molecular groups, specifically groups 3 and 4, when the characteristics of the primary tumor overlap.

A compartmentalized phosphoinositide signaling axis at cilia is regulated by INPP5E to maintain cilia and promote Sonic Hedgehog medulloblastoma.

Sonic Hedgehog (SHH) signaling at primary cilia drives the proliferation and progression of a subset of medulloblastomas, the most common malignant paediatric brain tumor. Severe side effects associated with conventional treatments and resistance to targeted therapies has led to the need for new strategies. SHH signaling is dependent on primary cilia for signal transduction suggesting the potential for cilia destabilizing mechanisms as a therapeutic target. INPP5E is an inositol polyphosphate 5-phosphatase that hydrolyses PtdIns(4,5)P2 and more potently, the phosphoinositide (PI) 3-kinase product PtdIns(3,4,5)P3. INPP5E promotes SHH signaling during embryonic development via PtdIns(4,5)P2 hydrolysis at cilia, that in turn regulates the cilia recruitment of the SHH suppressor GPR161. However, the role INPP5E plays in cancer is unknown and the contribution of PI3-kinase signaling to cilia function is little characterized. Here, we reveal INPP5E promotes SHH signaling in SHH medulloblastoma by negatively regulating a cilia-compartmentalized PI3-kinase signaling axis that maintains primary cilia on tumor cells. Conditional deletion of Inpp5e in a murine model of constitutively active Smoothened-driven medulloblastoma slowed tumor progression, suppressed cell proliferation, reduced SHH signaling and promoted tumor cell cilia loss. PtdIns(3,4,5)P3, its effector pAKT and the target pGSK3ß, which when non-phosphorylated promotes cilia assembly/stability, localized to tumor cell cilia. The number of PtdIns(3,4,5)P3/pAKT/pGSK3ß-positive cilia was increased in cultured Inpp5e-null tumor cells relative to controls. PI3-kinase inhibition or expression of wild-type, but not catalytically inactive HA-INPP5E partially rescued cilia loss in Inpp5e-null tumor cells in vitro. INPP5E mRNA and copy number were reduced in human SHH medulloblastoma compared to other molecular subtypes and consistent with the murine model, reduced INPP5E was associated with improved overall survival. Therefore our study identifies a compartmentalized PtdIns(3,4,5)P3/AKT/GSK3ß signaling axis at cilia in SHH-dependent medulloblastoma that is regulated by INPP5E to maintain tumor cell cilia, promote SHH signaling and thereby medulloblastoma progression.

WIP1 modulates responsiveness to Sonic Hedgehog signaling in neuronal precursor cells and medulloblastoma.

High-level amplification of the protein phosphatase PPM1D (WIP1) is present in a subset of medulloblastomas (MBs) that have an expression profile consistent with active Sonic Hedgehog (SHH) signaling. We found that WIP1 overexpression increased expression of Shh target genes and cell proliferation in response to Shh stimulation in NIH3T3 and cerebellar granule neuron precursor cells in a p53-independent manner. Thus, we developed a mouse in which WIP1 is expressed in the developing brain under control of the Neurod2 promoter (ND2:WIP1). The external granule layer (EGL) in early postnatal ND2:WIP1 mice exhibited increased proliferation and expression of Shh downstream targets. MB incidence increased and survival decreased when ND2:WIP1 mice were crossed with an Shh-activated MB mouse model. Conversely, Wip1 knockout significantly suppressed MB formation in two independent mouse models of Shh-activated MB. Furthermore, Wip1 knockdown or treatment with a WIP1 inhibitor suppressed the effects of Shh stimulation and potentiated the growth inhibitory effects of SHH pathway-inhibiting drugs in Shh-activated MB cells in vitro. This suggests an important cross-talk between SHH and WIP1 pathways that accelerates tumorigenesis and supports WIP1 inhibition as a potential treatment strategy for MB.

MRI surrogates for molecular subgroups of medulloblastoma.

BACKGROUND AND PURPOSE: Recently identified molecular subgroups of medulloblastoma have shown potential for improved risk stratification. We hypothesized that distinct MR imaging features can predict these subgroups. MATERIALS AND METHODS: All patients with a diagnosis of medulloblastoma at one institution, with both pretherapy MR imaging and surgical tissue, served as the discovery cohort (n = 47). MR imaging features were assessed by 3 blinded neuroradiologists. NanoString-based assay of tumor tissues was conducted to classify the tumors into the 4 established molecular subgroups (wingless, sonic hedgehog, group 3, and group 4). A second pediatric medulloblastoma cohort (n = 52) from an independent institution was used for validation of the MR imaging features predictive of the molecular subtypes. RESULTS: Logistic regression analysis within the discovery cohort revealed tumor location (P < .001) and enhancement pattern (P = .001) to be significant predictors of medulloblastoma subgroups. Stereospecific computational analyses confirmed that group 3 and 4 tumors predominated within the midline fourth ventricle (100%, P = .007), wingless tumors were localized to the cerebellar peduncle/cerebellopontine angle cistern with a positive predictive value of 100% (95% CI, 30%-100%), and sonic hedgehog tumors arose in the cerebellar hemispheres with a positive predictive value of 100% (95% CI, 59%-100%). Midline group 4 tumors presented with minimal/no enhancement with a positive predictive value of 91% (95% CI, 59%-98%). When we used the MR imaging feature-based regression model, 66% of medulloblastomas were correctly predicted in the discovery cohort, and 65%, in the validation cohort. CONCLUSIONS: Tumor location and enhancement pattern were predictive of molecular subgroups of pediatric medulloblastoma and may potentially serve as a surrogate for genomic testing.

Epigenomic alterations define lethal CIMP-positive ependymomas of infancy.

Ependymomas are common childhood brain tumours that occur throughout the nervous system, but are most common in the paediatric hindbrain. Current standard therapy comprises surgery and radiation, but not cytotoxic chemotherapy as it does not further increase survival. Whole-genome and whole-exome sequencing of 47 hindbrain ependymomas reveals an extremely low mutation rate, and zero significant recurrent somatic single nucleotide variants. Although devoid of recurrent single nucleotide variants and focal copy number aberrations, poor-prognosis hindbrain ependymomas exhibit a CpG island methylator phenotype. Transcriptional silencing driven by CpG methylation converges exclusively on targets of the Polycomb repressive complex 2 which represses expression of differentiation genes through trimethylation of H3K27. CpG island methylator phenotype-positive hindbrain ependymomas are responsive to clinical drugs that target either DNA or H3K27 methylation both in vitro and in vivo. We conclude that epigenetic modifiers are the first rational therapeutic candidates for this deadly malignancy, which is epigenetically deregulated but genetically bland.

Rapid serodiagnosis of leptospirosis by latex agglutination test and flow-through assay.

PURPOSE: Diagnosis of leptospirosis facilitates patient management and initiation of therapy. The microscopic agglutination test (MAT) is the serological test used in reference laboratories because of its high degree of sensitivity and specificity. But the results are not available quickly for patient management. In the present study, in order to develop a simple, rapid immunodiagnostic assay, one of the outer membrane proteins (OMPs), recombinant LipL41 (rLipL41) has been utilised in latex agglutination test (LAT) and flow-through assay. METHODS: Part of LipL41 gene was expressed in Escherichia coli system and purified. The rLipL41 antigen of pathogenic Leptospira interrogans serovar Icterohaemorrhagiae, which is conserved in all pathogenic Leptospira spp. was used as capture antigen in the LAT and flow-through test. Both tests are very rapid and could be completed within 5 minutes. The sensitivity and specificity of rLipL41 was assessed and evaluated in LAT and flow-through assay in comparison with standard MAT. RESULTS: The sensitivity and specificity of the LAT were 89.70 and 90.45% and flow-through assay were 89.09 and 77.70%, respectively. CONCLUSIONS: The developed LAT and flow-through assays were simple, rapid and economical for the detection of leptospira infection and suitable for large-scale screening of samples in endemic areas without any sophisticated equipment.

Gas-liquid chromatographic determination of T-2 toxin in plasma.

A gas-liquid chromatographic method for the determination of T-2 toxin in plasma is described. The toxin is extracted with benzene, washed with aqueous sodium hydroxide, and chromatographed on a small Florisil column; the heptafluorobutyryl derivative is prepared by reaction with heptafluorobutyrylimidazole. The T-2 HFB derivative is chromatographed on OV-1 at 230 degrees C and measured with an electron capture detector. Iso-T-2, an isomer of T-2 toxin, is added to samples as an internal standard before extraction. Recoveries averaged 98.0 +/- 5.5% at levels ranging from 50 to 1000 ng/mL. The limit of detection is 25 ng/mL.