Multiparametric Analysis of Permeability and ADC Histogram Metrics for Classification of Pediatric Brain Tumors by Tumor Grade.

BACKGROUND AND PURPOSE: Accurate tumor grading is essential for treatment planning of pediatric brain tumors. We hypothesized that multiparametric analyses of a combination of permeability metrics and ADC histogram metrics would differentiate high- and low-grade tumors with high accuracy. MATERIALS AND METHODS: DTI and dynamic contrast-enhanced MR imaging using T1-mapping with flip angles of 2°, 5°, 10°, and 15°, followed by a 0.1-mmol/kg body weight gadolinium-based bolus was performed on all patients in addition to standard MR imaging. Permeability data were processed and transfer constant from the blood plasma into the extracellular extravascular space, rate constant from the extracellular extravascular space back into blood plasma, extravascular extracellular volume fraction, and fractional blood plasma volume were calculated from 3D tumor volumes. Apparent diffusion coefficient histogram metrics were calculated for 3 separate tumor volumes derived from T2-FLAIR sequences, T1 contrast-enhanced sequences, and permeability maps, respectively. RESULTS: Results from 41 patients (0.3-16.76 years of age; mean, 6.22 years) with newly diagnosed contrast-enhancing brain tumors (16 low-grade; 25 high-grade) were included in the institutional review board-approved retrospective analysis. Wilcoxon tests showed a higher transfer constant from blood plasma into extracellular extravascular space and rate constant from extracellular extravascular space back into blood plasma, and lower extracellular extravascular volume fraction (P < .001) in high-grade tumors. The mean ADCs of FLAIR and enhancing tumor volumes were significantly lower in high-grade tumors (P < .001). ROC analysis showed that a combination of extravascular volume fraction and mean ADC of FLAIR volume differentiated high- and low-grade tumors with high accuracy (area under receiver operating characteristic curve = 0.918). CONCLUSIONS: ADC histogram metrics combined with permeability metrics differentiate low- and high-grade pediatric brain tumors with high accuracy.

Primary gamma-sarcoglycanopathy (LGMD 2C): broadening of the mutational spectrum guided by the immunohistochemical profile.

An important step in the diagnostic evaluation of a patient with recessive limb-girdle muscular dystrophy is the immunohistochemical analysis of the components of the sarcoglycan complex in a muscle biopsy specimen. Even though a primary mutation in any of the four sarcoglycan genes (alpha-, beta-,gamma-, delta-sarcoglycan) may cause secondary deficiencies in all the other sarcoglycan proteins, more specific immunohistochemical patterns have emerged with the potential to guide and abbreviate the necessary molecular genetic investigations. In gamma-sarcoglycan mutations, the pattern consists of absent or prominently reduced gamma-sarcoglycan immunoreactivity in combination with reduced but detectable immunoreactivity for the other components, with preservation of delta-sarcoglycan. In five consecutive patients, this pattern was able to predict primary gamma-sarcoglycan mutations. Five different mutations were found, including a recurrent novel splice mutation, a large deletion of the entire gene and a novel missense mutation (Leu90Ser). The mutation Cys283Tyr, previously restricted to Gypsy populations was found in compound heterozygosity with del521T, common in north Africa. The variety of known and novel mutations found indicates that the immunohistochemical profile of gamma-sarcoglycan mutations is not restricted to a particular mutation or type of mutation, but rather is a general reflection of the effect of gamma-sarcoglycan mutations on the composition of the sarcoglycan complex. Complete immunohistochemical analysis with all available sarcoglycan antibodies, therefore, is a useful tool to guide the molecular genetic investigations that are necessary to arrive at the correct genetic diagnosis in a given case.