METHODS: Anatomical MRI and structural DTI were performed cross-sectionally on 26 normal children (newborn to 48 months old), using 1.5-T MRI. The automated processing pipeline was implemented to convert diffusion-weighted images into the NIfTI format. DTI-TK software was used to register the processed images to the ICBM DTI-81 atlas, while AFNI software was used for automated atlas-based volumes of interest (VOIs) and statistical value extraction.
RESULTS: DTI exhibited consistent grey-white matter contrast. Triphasic temporal variation of the FA and MD values was noted, with FA increasing and MD decreasing rapidly early in the first 12 months. The second phase lasted 12-24 months during which the rate of FA and MD changes was reduced. After 24 months, the FA and MD values plateaued.
CONCLUSION: DTI is a superior technique to conventional MR imaging in depicting WM maturation. The use of the automated processing pipeline provides a reliable environment for quantitative analysis of high-throughput DTI data.
KEY POINTS: Diffusion tensor imaging outperforms conventional MRI in depicting white matter maturation. • DTI will become an important clinical tool for diagnosing paediatric neurological diseases. • DTI appears especially helpful for developmental abnormalities, tumours and white matter disease. • An automated processing pipeline assists quantitative analysis of high throughput DTI data.
CASE SUMMARY: We report two cases of anti-E hemolytic diseases in neonates. One of the neonates had severe hemolysis presenting with severe anemia, thrombocytopenia, and conjugated hyperbilirubinemia, while the other had moderate anemia and unconjugated hyperbilrubinemia. Although both the neonates were treated by phototherapy and intravenous immunoglobulin, one of them received double volume exchange transfusion.
CONCLUSION: There appeared to be an increase in the occurrence of hemolytic disease of the fetus and newborn caused by Rh antibodies other than anti-D. In this case report, both patients presented with anemia and hyperbilirubinemia but were successfully treated, with a favorable outcome.
METHODS: 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3.
RESULTS: Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified.
CONCLUSION: Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD.
KEY POINTS: • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.
MATERIALS AND METHODS: One hundred and twenty primary school children were included. They were divided into caries and caries-free groups. Unstimulated whole saliva was collected from each participant using spitting method. The salivary elements were measured using an Atomic Absorption Spectrophotometer. Descriptive statistics, bivariate and Pearson's correlation analysis were performed.
RESULTS: Salivary Cu and Zn levels were significantly higher in children with dental caries compared to those caries-free (p < 0.05). Moreover, these elements had a positive correlation with dental caries (Cu: r=0.698, p<0.001; Zn: r=0.181, p<0.05). No significant variations in Mn and Fe were observed between caries and caries-free group (p>0.05). Additionally, there were significant differences in salivary Zn and Fe among different age groups (p<0.05) and highly significant differences in salivary Cu, Mn and Fe among different ethnic groups (p<0.001). However, all elements exhibited no significant differences between males and females.
CONCLUSION: The salivary Cu and Zn levels showed significant differences between caries and caries-free groups. The findings also revealed significant variations in the levels of salivary Cu, Mn and Fe among different ethnic groups and salivary Zn and Fe among different age groups.