Improved Detection of Subtle Mesial Temporal Sclerosis: Validation of a Commercially Available Software for Automated Segmentation of Hippocampal Volume.

BACKGROUND AND PURPOSE: Identification of mesial temporal sclerosis is critical in the evaluation of individuals with temporal lobe epilepsy. Our aim was to assess the performance of FDA-approved software measures of hippocampal volume to identify mesial temporal sclerosis in patients with medically refractory temporal lobe epilepsy compared with the initial clinical interpretation of a neuroradiologist. MATERIALS AND METHODS: Preoperative MRIs of 75 consecutive patients who underwent a temporal resection for temporal lobe epilepsy from 2011 to 2016 were retrospectively reviewed, and 71 were analyzed using Neuroreader, a commercially available automated segmentation and volumetric analysis package. Volume measures, including hippocampal volume as a percentage of total intracranial volume and the Neuroreader Index, were calculated. Radiologic interpretations of the MR imaging and pathology from subsequent resections were classified as either mesial temporal sclerosis or other, including normal findings. These measures of hippocampal volume were evaluated by receiver operating characteristic curves on the basis of pathologic confirmation of mesial temporal sclerosis in the resected temporal lobe. Sensitivity and specificity were calculated for each method and compared by means of the McNemar test using the optimal threshold as determined by the Youden J point. RESULTS: Optimized thresholds of hippocampal percentage of a structural volume relative to total intracranial volume (<0.19%) and the Neuroreader Index (≤-3.8) were selected to optimize sensitivity and specificity (89%/71% and 89%/78%, respectively) for the identification of mesial temporal sclerosis in temporal lobe epilepsy compared with the initial clinical interpretation of the neuroradiologist (50% and 87%). Automated measures of hippocampal volume predicted mesial temporal sclerosis more accurately than radiologic interpretation (McNemar test, P < .0001). CONCLUSIONS: Commercially available automated segmentation and volume analysis of the hippocampus accurately identifies mesial temporal sclerosis and performs significantly better than the interpretation of the radiologist.

Discordant Observation of Brain Injury by MRI and Malignant Electroencephalography Patterns in Comatose Survivors of Cardiac Arrest following Therapeutic Hypothermia.

BACKGROUND AND PURPOSE: Malignant electroencephalography patterns are considered predictive of poor outcome in comatose survivors of cardiac arrest. We hypothesized that malignant patterns on electroencephalography are associated with evidence of more severe brain injury on MR imaging. MATERIALS AND METHODS: Retrospective review of clinical, imaging, and electroencephalography data of 33 adult comatose survivors of cardiac arrest following therapeutic hypothermia was performed. Outcomes measured included discharge destination and survival. Imaging studies were visually scored for severity of brain injury. Mean whole-brain apparent diffusion coefficient and percentage of severely injured brain (ADC < 700 × 10-6 mm2/s) were calculated. Continuous electroencephalographic interpretation was characterized as malignant or nonmalignant. Nonparametric tests were performed to assess the relationship of patient outcome, MR imaging, and electroencephalography patterns. RESULTS: Subjects with anatomic evidence of diffuse brain injury were less likely to have malignant electroencephalography patterns. Subjects with malignant electroencephalography patterns, invariably associated with bad outcomes, were observed to have whole-brain apparent diffusion coefficient measures similar to those in subjects with nonmalignant electroencephalography patterns and good outcome and different from those in subjects with nonmalignant electroencephalography patterns and bad outcomes. Regional hippocampal or basal ganglia injury was associated with a bad outcome regardless of electroencephalography findings. CONCLUSIONS: We found discordant evidence of brain injury by MR imaging and electroencephalography, refuting our initial hypothesis. Malignant electroencephalography patterns were generally more frequent in subjects with less severe brain injury by MR imaging. These findings suggest a complementary role of MR imaging and electroencephalography and support the aggressive treatment of malignant electroencephalography patterns in this population.

Identical or overlapping sequences in the primary structure of human alpha(2)-macroglobulin are responsible for the binding of nerve growth factor-beta, platelet-derived growth factor-BB, and transforming growth factor-beta.

alpha(2)-Macroglobulin (alpha(2)M) functions as a proteinase inhibitor and as a carrier of diverse growth factors. In this study, we localized binding sites for platelet-derived growth factor-BB (PDGF-BB) and nerve growth factor-beta (NGF-beta) to a linear sequence in the 180-kDa human alpha(2)M subunit which includes amino acids 591-774. A glutathione S-transferase fusion protein containing amino acids 591-774 (FP3) bound PDGF-BB and NGF-beta in ligand blotting assays whereas five other fusion proteins, which collectively include amino acids 99-590 and 775-1451 did not. The K(D) values for PDGF-BB and NGF-beta binding to immobilized FP3 were 300 +/- 40 and 180 +/- 30 nM, respectively; these values were comparable with those determined using methylamine-modified alpha(2)M, suggesting that higher-order alpha(2)M structure is not necessary for PDGF-BB and NGF-beta binding. PDGF-BB and NGF-beta blocked the binding of transforming growth factor-beta1 (TGF-beta1) to FP3. Furthermore, murinoglobulin, which is the only known member of the alpha-macroglobulin family that does not bind TGF-beta, also failed to bind PDGF-BB and NGF-beta. These results support the hypothesis that either a single linear sequence in human alpha(2)M or overlapping sequences are responsible for the binding of TGF-beta, PDGF-BB, and NGF-beta, even though there is minimal sequence identity between these three growth factors. FP3 blocked the binding of PDGF-BB to a purified chimeric protein, in which the extracellular domain of the PDGF beta receptor was fused to the IgG(1) Fc domain, and to PDGF receptors on NIH 3T3 cells. Thus, FP3 may inhibit the activity of PDGF-BB.

Use of antibiotic resistance analysis to identify nonpoint sources of fecal pollution.

A study was conducted to determine the reliability and repeatability of antibiotic resistance analysis as a method of identifying the sources of fecal pollution in surface water and groundwater. Four large sets of isolates of fecal streptococci (from 2,635 to 5,990 isolates per set) were obtained from 236 samples of human sewage and septage, cattle and poultry feces, and pristine waters. The patterns of resistance of the isolates to each of four concentrations of up to nine antibiotics were analyzed by discriminant analysis. When isolates were classified individually, the average rate of correct classification (ARCC) into four possible types (human, cattle, poultry, and wild) ranged from 64 to 78%. When the resistance patterns of all isolates from each sample were averaged and the resulting sample-level resistance patterns were classified, the ARCCs were much higher (96 to 100%). These data confirm that there are measurable and consistent differences in the antibiotic resistance patterns of fecal streptococci isolated from various sources of fecal pollution and that antibiotic resistance analysis can be used to classify and identify these sources.