Cerebral perfusion and automated individual analysis using SPECT among an obsessive-compulsive population

OBJECTIVE: To make individual assessments using automated quantification methodology in order to screen for perfusion abnormalities in cerebral SPECT examinations among a sample of subjects with OCD. METHODS: Statistical parametric mapping (SPM) was used to compare 26 brain SPECT images from patients with OCD individually with an image bank of 32 normal subjects, using the statistical threshold of p < 0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). The maps were analyzed, and regions presenting voxels that remained above this threshold were sought. RESULTS: Six patients from a sample of 26 OCD images showed abnormalities at cluster or voxel level, considering the criteria described above, which represented 23.07%. However, seven images from the normal group of 32 were also indicated as cases of perfusional abnormality, representing 21.8% of the sample. CONCLUSION: The automated quantification method was not considered to be a useful tool for clinical practice, for analyses complementary to visual inspection.

Automated sugar analysis

Abstract Sugarcane monosaccharides are reducing sugars, and classical analytical methodologies (Lane-Eynon, Benedict, complexometric-EDTA, Luff-Schoorl, Musson-Walker, Somogyi-Nelson) are based on reducing copper ions in alkaline solutions. In Brazil, certain factories use Lane-Eynon, others use the equipment referred to as “REDUTEC”, and additional factories analyze reducing sugars based on a mathematic model. The objective of this paper is to understand the relationship between variations in millivolts, mass and tenors of reducing sugars during the analysis process. Another objective is to generate an automatic model for this process. The work herein uses the equipment referred to as “REDUTEC”, a digital balance, a peristaltic pump, a digital camcorder, math programs and graphics programs. We conclude that the millivolts, mass and tenors of reducing sugars exhibit a good mathematical correlation, and the mathematical model generated was benchmarked to low-concentration reducing sugars (<0.3%). Using the model created herein, reducing sugars analyses can be automated using the new equipment.

Automated static image analysis as a novel tool in describing the physical properties of dietary fiber

Abstract The growing interest in the usage of dietary fiber in food has caused the need to provide precise tools for describing its physical properties. This research examined two dietary fibers from oats and beets, respectively, in variable particle sizes. The application of automated static image analysis for describing the hydration properties and particle size distribution of dietary fiber was analyzed. Conventional tests for water holding capacity (WHC) were conducted. The particles were measured at two points: dry and after water soaking. The most significant water holding capacity (7.00 g water/g solid) was achieved by the smaller sized oat fiber. Conversely, the water holding capacity was highest (4.20 g water/g solid) in larger sized beet fiber. There was evidence for water absorption increasing with a decrease in particle size in regards to the same fiber source. Very strong correlations were drawn between particle shape parameters, such as fiber length, straightness, width and hydration properties measured conventionally. The regression analysis provided the opportunity to estimate whether the automated static image analysis method could be an efficient tool in describing the hydration properties of dietary fiber. The application of the method was validated using mathematical model which was verified in comparison to conventional WHC measurement results.

Automated system of seedling image analysis (SVIS) and electrical conductivity to assess sun hemp seed vigor

The development of new procedures for quickly obtaining accurate information on the physiological potential of seed lots is essential for developing quality control programs for the seed industry. In this study, the effectiveness of an automated system of seedling image analysis (Seed Vigor Imaging System - SVIS) in determining the physiological potential of sun hemp seeds and its relationship with electrical conductivity tests, were evaluated. SVIS evaluations were performed three and four days after sowing and data on the vigor index and the length and uniformity of seedling growth were collected. The electrical conductivity test was made on 50 seed replicates placed in containers with 75 mL of deionised water at 25 ºC and readings were taken after 1, 2, 4, 8 and 16 hours of imbibition. Electrical conductivity measurements at 4 or 8 hours and the use of the SVIS on 3-day old seedlings can effectively detect differences in vigor between different sun hemp seed lots.

Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

Comparison between the HemoCue® and an automated counter for measuring hemoglobin

To determine the precision and agreement of the hemoglobin (Hb) measurements in capillary and venous blood samples by the HemoCue® and an automated counter. Hb was determined by both equipaments in blood samples of 29 pregnant women. The HemoCue® showed low repeatability of Hb measurements in duplicate in capillary (CR=0.53 g/dL, CV=13.6%) and venous blood (CR=0.53 g/dL, CV=13.6%). Hb measurements in capillary blood were higher than those in venous blood (12.4 and 11.7 g/dL, respectively; p<0.05). There was high agreement between Hb in capillary blood by the HemoCue® and in venous blood by the counter (r icc=0.86; p<0.01), and also between the diagnosis of anemia by both equipments (k=0.81; p<0.01). The HemoCue® seems to be more appropriate for capillary blood and require training of the measurers.

Endobronchial valves in severe emphysematous patients: CT evaluation of lung fissures completeness, treatment radiological response and quantitative emphysema analysis

OBJECTIVE: To evaluate lung fissures completeness, post-treatment radiological response and quantitative CT analysis (QCTA) in a population of severe emphysematous patients submitted to endobronchial valves (EBV) implantation. MATERIALS AND METHODS: Multi-detectors CT exams of 29 patients were studied, using thin-section low dose protocol without contrast. Two radiologists retrospectively reviewed all images in consensus; fissures completeness was estimated in 5% increments and post-EBV radiological response (target lobe atelectasis/volume loss) was evaluated. QCTA was performed in pre and post-treatment scans using a fully automated software. RESULTS: CT response was present in 16/29 patients. In the negative CT response group, all 13 patients presented incomplete fissures, and mean oblique fissures completeness was 72.8%, against 88.3% in the other group. QCTA most significant results showed a reduced post-treatment total lung volume (LV) (mean 542 ml), reduced EBV-submitted LV (700 ml) and reduced emphysema volume (331.4 ml) in the positive response group, which also showed improved functional tests. CONCLUSION: EBV benefit is most likely in patients who have complete interlobar fissures and develop lobar atelectasis. In patients with no radiological response we observed a higher prevalence of incomplete fissures and a greater degree of incompleteness. The fully automated QCTA detected the post-treatment alterations, especially in the treated lung analysis.

THE APPLICATION OF AUTOMATED CORRELATION OPTIMIZED WARPING TO THE QUALITY EVALUATION OF Radix Puerariae thomsonii: CORRECTING RETENTION TIME SHIFT IN THE CHROMATOGRAPHIC FINGERPRINTS

The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.

Sensibility analysis of the pearl model for pesticide leaching in the State of Mato Grosso do Sul, Brazil

For an accurate use of pesticide leaching models it is necessary to assess the sensitivity of input parameters. The aim of this work was to carry out sensitivity analysis of the pesticide leaching model PEARL for contrasting soil types of Dourados river watershed in the state of Mato Grosso do Sul, Brazil. Sensitivity analysis was done by carrying out many simulations with different input parameters and calculating their influence on the output values. The approach used was called one-at-a-time sensitivity analysis, which consists in varying independently input parameters one at a time and keeping all others constant with the standard scenario. Sensitivity analysis was automated using SESAN tool that was linked to the PEARL model. Results have shown that only soil characteristics influenced the simulated water flux resulting in none variation of this variable for scenarios with different pesticides and same soil. All input parameters that showed the greatest sensitivity with regard to leached pesticide are related to soil and pesticide properties. Sensitivity of all input parameters was scenario dependent, confirming the need of using more than one standard scenario for sensitivity analysis of pesticide leaching models.

Automated grading of left ventricular segmental wall motion by an artificial neural network using color kinesis images

The present study describes an auxiliary tool in the diagnosis of left ventricular (LV) segmental wall motion (WM) abnormalities based on color-coded echocardiographic WM images. An artificial neural network (ANN) was developed and validated for grading LV segmental WM using data from color kinesis (CK) images, a technique developed to display the timing and magnitude of global and regional WM in real time. We evaluated 21 normal subjects and 20 patients with LVWM abnormalities revealed by two-dimensional echocardiography. CK images were obtained in two sets of viewing planes. A method was developed to analyze CK images, providing quantitation of fractional area change in each of the 16 LV segments. Two experienced observers analyzed LVWM from two-dimensional images and scored them as: 1) normal, 2) mild hypokinesia, 3) moderate hypokinesia, 4) severe hypokinesia, 5) akinesia, and 6) dyskinesia. Based on expert analysis of 10 normal subjects and 10 patients, we trained a multilayer perceptron ANN using a back-propagation algorithm to provide automated grading of LVWM, and this ANN was then tested in the remaining subjects. Excellent concordance between expert and ANN analysis was shown by ROC curve analysis, with measured area under the curve of 0.975. An excellent correlation was also obtained for global LV segmental WM index by expert and ANN analysis (R² = 0.99). In conclusion, ANN showed high accuracy for automated semi-quantitative grading of WM based on CK images. This technique can be an important aid, improving diagnostic accuracy and reducing inter-observer variability in scoring segmental LVWM.

Genomic analysis of Brazilian patients with Fabry disease

Fabry disease is an X-linked lysosomal disorder due to a-galactosidase A deficiency that causes storage of globotriaosylceramide. The gene coding for this lysosomal enzyme is located on the long arm of the X chromosome, in region Xq21.33-Xq22. Disease progression leads to vascular disease secondary to involvement of kidney, heart and the central nervous system. Detection of female carriers based solely on enzyme assays is often inconclusive. Therefore, mutation analysis is a valuable tool for diagnosis and genetic counseling. Many mutations of the a-galactosidase A gene have been reported with high genetic heterogeneity, being most mutations private found in only one family. The disease is panethnic, and estimates of incidence range from about 1 in 40,000 to 60,000 males. Our objective was to describe the analysis of 6 male and 7 female individuals belonging to 4 different Fabry disease families by automated sequencing of the seven exons of the a-galactosidase gene. Sequencing was performed using PCR fragments for each exon amplified from DNA extracted from peripheral blood. Three known mutations and one previously described in another Brazilian family were detected. Of 7 female relatives studied, 4 were carriers. Although the present study confirms the heterogeneity of mutations in Fabry disease, the finding of the same mutation previously detected in another Fabry family from our region raises the possibility of some founder effect, or genetic drift. Finally, the present study highlights the importance of molecular analysis for carrier detection and genetic counseling.