Effect of pancreatic and/or renal transplantation on diabetic autonomic neuropathy

Thirty-nine Type 1 (insulin-dependent) diabetic patients were studied prospectively after simultaneous pancreas and kidney (n=26) and kidney grafting alone (n=13) by measuring heart rate variation during various manoeuvers and answering a standardized questionnaire every 6 to 12 months post-transplant. While age, duration of diabetes, and serum creatinine (168.1±35.4 vs 132.7±17.7 mgrmol/l) were comparable, haemoglobin A1 levels were significantly lower (6.6±0.2 vs 8.5±0.3%; p<0.01) and the mean observation time longer (35±2 vs 25±3 months; p<0.05) in the pancreas recipients when compared with kidney transplanted patients. Heart rate variation during deep breathing, lying/standing and Valsalva manoeuver were very similar in both groups initially and did not improve during follow-up. However, there was a significant reduction in heart rate in the pancreas recipient group. Autonomic symptoms of the gastrointestinal and thermoregulatory system improved more in the pancreas grafted subjects, while hypoglycaemia unawareness deteriorated in the kidney recipients. This study suggests that long-term normoglycaemia by successful pancreatic grafting is able to halt the progression of autonomic dysfunction

Serial MR diffusion to predict treatment response in high-grade pediatric brain tumors: a comparison of regional and voxel-based diffusion change metrics

Background Assessment of treatment response by measuring tumor size is known to be a late and potentially confounded response index. Serial diffusion MRI has shown potential for allowing earlier and possibly more reliable response assessment in adult patients, with limited experience in clinical settings and in pediatric brain cancer. We present a retrospective study of clinical MRI data in children with high-grade brain tumors to assess and compare the values of several diffusion change metrics to predict treatment response. Methods Eighteen patients (age range, 1.9–20.6 years) with high-grade brain tumors and serial diffusion MRI (pre- and posttreatment interval range, 1–16 weeks posttreatment) were identified after obtaining parental consent. The following diffusion change metrics were compared with the clinical response status assessed at 6 months: (1) regional change in absolute and normalized apparent diffusivity coefficient (ADC), (2) voxel-based fractional volume of increased (fiADC) and decreased ADC (fdADC), and (3) a new metric based on the slope of the first principal component of functional diffusion maps (fDM). Results Responders (n = 12) differed significantly from nonresponders (n = 6) in all 3 diffusional change metrics demonstrating higher regional ADC increase, larger fiADC, and steeper slopes (P < .05). The slope method allowed the best response prediction (P < .01, η2 = 0.78) with a classification accuracy of 83% for a slope of 58° using receiver operating characteristic (ROC) analysis. Conclusions We demonstrate that diffusion change metrics are suitable response predictors for high-grade pediatric tumors, even in the presence of variable clinical diffusion imaging protocols

QuantiFERON®-TB gold in-tube performance for diagnosing active tuberculosis in children and adults in a high burden setting.

To determine whether QuantiFERON®-TB Gold In-Tube (QFT) can contribute to the diagnosis of active tuberculosis (TB) in children in a high-burden setting and to assess the performance of QFT and tuberculin skin test (TST) in a prospective cohort of TB suspect children compared to adults with confirmed TB in Tanzania. Sensitivity and specificity of QFT and TST for diagnosing active TB as well as indeterminate QFT rates and IFN-γ levels were assessed in 211 TB suspect children in a Tanzanian district hospital and contrasted in 90 adults with confirmed pulmonary TB. Sensitivity of QFT and TST in children with confirmed TB was 19% (5/27) and 6% (2/31) respectively. In adults sensitivity of QFT and TST was 84% (73/87) and 85% (63/74). The QFT indeterminate rate in children and adults was 27% and 3%. Median levels of IFN-γ were lower in children than adults, particularly children <2 years and HIV infected. An indeterminate result was associated with age <2 years but not malnutrition or HIV status. Overall childhood mortality was 19% and associated with an indeterminate QFT result at baseline. QFT and TST showed poor performance and a surprisingly low sensitivity in children. In contrast the performance in Tanzanian adults was good and comparable to performance in high-income countries. Indeterminate results in children were associated with young age and increased mortality. Neither test can be recommended for diagnosing active TB in children with immature or impaired immunity in a high-burden setting

Classification of paediatric brain tumours by diffusion weighted imaging and machine learning

To determine if apparent diffusion coefficients (ADC) can discriminate between posterior fossa brain tumours on a multicentre basis. A total of 124 paediatric patients with posterior fossa tumours (including 55 Medulloblastomas, 36 Pilocytic Astrocytomas and 26 Ependymomas) were scanned using diffusion weighted imaging across 12 different hospitals using a total of 18 different scanners. Apparent diffusion coefficient maps were produced and histogram data was extracted from tumour regions of interest. Total histograms and histogram metrics (mean, variance, skew, kurtosis and 10th, 20th and 50th quantiles) were used as data input for classifiers with accuracy determined by tenfold cross validation. Mean ADC values from the tumour regions of interest differed between tumour types, (ANOVA P < 0.001). A cut off value for mean ADC between Ependymomas and Medulloblastomas was found to be of 0.984 × 10-3 mm2 s-1 with sensitivity 80.8% and specificity 80.0%. Overall classification for the ADC histogram metrics were 85% using Naïve Bayes and 84% for Random Forest classifiers. The most commonly occurring posterior fossa paediatric brain tumours can be classified using Apparent Diffusion Coefficient histogram values to a high accuracy on a multicentre basis

SIOP Ependymoma I: Final results, long term follow-up and molecular analysis of the trial cohort: A BIOMECA Consortium Study

BACKGROUND: SIOP Ependymoma I was a non-randomised trial assessing event free and overall survival (EFS/OS) of non-metastatic intracranial ependymoma in children aged 3 to 21 years treated with a staged management strategy. A further aim was to assess the response rate (RR) of subtotally resected (STR) ependymoma to vincristine, etoposide and cyclophosphamide (VEC). We report final results with 12-year follow-up and post hoc analyses of recently described biomarkers. METHODS: 74 participants were eligible. Children with gross total resection (GTR) received radiotherapy, whilst those with STR received VEC before radiotherapy. DNA methylation, 1q, hTERT, ReLA, Tenascin-C, H3K27me3 and pAKT status were evaluated. RESULTS: Five- and ten-year EFS was 49.5% and 46.7%, OS was 69.3% and 60.5%. GTR was achieved in 33/74 (44.6%) and associated with improved EFS (p=0.003, HR=2.6, 95% confidence interval (CI) 1.4-5.1). Grade 3 tumours were associated with worse OS (p=0.005, HR=2.8, 95%CI 1.3-5.8). 1q gain and hTERT expression were associated with poorer EFS (p=0.003, HR=2.70, 95%CI 1.49-6.10 and p=0.014, HR=5.8, 95%CI 1.2-28) and H3K27me3 loss with worse OS (p=0.003, HR=4.6, 95%CI 1.5-13.2). Methylation profiles showed expected patterns. 12 participants with STR did not receive chemotherapy; a protocol violation. However, best chemotherapy RR was 65.5% (19/29, 95%CI 45.7-82.1), exceeding the prespecified 45%. CONCLUSIONS: Participants with totally resected ependymoma had the best outcomes. RR of STR to VEC exceeded the pre-specified efficacy criterion. However, cases of inaccurate stratification highlighted the need for rapid central review. 1q gain, H3K27me3 loss and hTERT expression were all associated with poorer survival outcomes

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors

BACKGROUND AND PURPOSE: Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. MATERIALS AND METHODS: This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. RESULTS: ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. CONCLUSIONS: Support vector machine–based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology

Relative shortening and functional tethering of spinal cord in adolescent scoliosis - result of asynchronous neuro-osseous growth, summary of an electronic focus group debate of the IBSE

Author name used in this publication: Jack C. Y. ChengVersion of RecordPublishe

Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome

BACKGROUND: Despite previous identification of pre-operative clinical and radiological predictors of post-operative paediatric cerebellar mutism syndrome (CMS), a unifying pre-operative risk stratification model for use during surgical consent is currently lacking. The aim of the project is to develop a simple imaging-based pre-operative risk scoring scheme to stratify patients in terms of post-operative CMS risk. METHODS: Pre-operative radiological features were recorded for a retrospectively assembled cohort of 89 posterior fossa tumour patients from two major UK treatment centers (age 2-23yrs; gender 28 M, 61 F; diagnosis: 38 pilocytic astrocytoma, 32 medulloblastoma, 12 ependymoma, 1 high grade glioma, 1 pilomyxoid astrocytoma, 1 atypical teratoid rhabdoid tumour, 1 hemangioma, 1 neurilemmoma, 2 oligodendroglioma). Twenty-six (29%) developed post-operative CMS. Based upon results from univariate analysis and C4.5 decision tree, stepwise logistic regression was used to develop the optimal model and generate risk scores. RESULTS: Univariate analysis identified five significant risk factors and C4.5 decision tree analysis identified six predictors. Variables included in the final model are MRI primary location, bilateral middle cerebellar peduncle involvement (invasion and/or compression), dentate nucleus invasion and age at imaging >12.4 years. This model has an accuracy of 88.8% (79/89). Using risk score cut-off of 203 and 238, respectively, allowed discrimination into low (38/89, predicted CMS probability <3%), intermediate (17/89, predicted CMS probability 3-52%) and high-risk (34/89, predicted CMS probability ≥52%). CONCLUSIONS: A risk stratification model for post-operative paediatric CMS could flag patients at increased or reduced risk pre-operatively which may influence strategies for surgical treatment of cerebellar tumours. Following future testing and prospective validation, this risk scoring scheme will be proposed for use during the surgical consenting process

A systematic autopsy survey of human infant bridging veins

In the first years of life, subdural haemorrhage (SDH) within the cranial cavity can occur through accidental and non-accidental mechanisms as well as from birth-related injury. This type of bleeding is the most common finding in victims of abusive head trauma (AHT). Historically, the most frequent cause of SDHs in infancy is suggested to be traumatic damage to bridging veins traversing from the brain to the dural membrane. However, several alternative hypotheses have been suggested for the cause and origin of subdural bleeding. It has also been suggested by some that bridging veins are too large to rupture through the forces associated with AHT. To date, there have been no systematic anatomical studies on infant bridging veins. During 43 neonatal, infant and young child post-mortem examinations, we have mapped the locations and numbers of bridging veins onto a 3D model of the surface of a representative infant brain. We have also recorded the in situ diameter of 79 bridging veins from two neonatal, one infant and two young children at post-mortem examination. Large numbers of veins, both distant from and directly entering the dural venous sinuses, were discovered travelling between the brain and dural membrane, with the mean number of veins per brain being 54.1 and the largest number recorded as 94. The mean diameter of the bridging veins was 0.93 mm, with measurements ranging from 0.05 to 3.07 mm. These data demonstrate that some veins are extremely small and subjectively, and they appear to be delicate. Characterisation of infant bridging veins will contribute to the current understanding of potential vascular sources of subdural bleeding and could also be used to further develop computational models of infant head injury