A Comparative Analysis between Ultrasonometry and Computer-Aided Tomography to Evaluate Bone Healing

An ultrasonometric and computed-tomographic study of bone healing was undertaken using a model of a transverse mid-shaft osteotomy of sheep tibiae fixed with a semi-flexible external fixator. Fourteen sheep were operated and divided into two groups of seven according to osteotomy type, either regular or by segmental resection. The animals were killed on the 90th postoperative day and the tibiae resected for the in vitro direct contact transverse and axial measurement of ultrasound propagation velocity (UV) followed by quantitative computer-aided tomography (callus density and volume) through the osteotomy site. The intact left tibiae were used for control, being examined in a symmetrical diaphyseal segment. Regular osteotomies healed with a smaller and more mature callus than resection osteotomies. Axial UV was consistently and significantly higher (p?=?0.01) than transverse UV and both transverse and axial UV were significantly higher for the regular than for the segmental resection osteotomy. Transverse UV did not differ significantly between the intact and operated tibiae (p?=?0.20 for regular osteotomy; p?=?0.02 for resection osteotomy), but axial UV was significantly higher for the intact tibiae. Tomographic callus density was significantly higher for the regular than for the resection osteotomy and higher than both for the intact tibiae, presenting a strong positive correlation with UV. Callus volume presented an opposite behavior, with a negative correlation with UV. We conclude that UV is at least as precise as quantitative tomography for providing information about the healing state of both regular and resection osteotomy. (C) 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:10761082, 2012

Three-Dimensional Ultrasonographic Assessment of Fetal Total Lung Volume as a Prognostic Factor in Primary Pleural Effusion

Objectives-The purpose of this study was to predict perinatal outcomes using fetal total lung volumes assessed by 3-dimensional ultrasonography (3DUS) in primary pleural effusion. Methods-Between July 2005 and July 2010, total lung volumes were prospectively estimated in fetuses with primary pleural effusion by 3DUS using virtual organ computer-aided analysis software. The first and last US examinations were considered in the analysis. The observed/expected total lung volumes were calculated. Main outcomes were perinatal death (up to 28 days of life) and respiratory morbidity (orotracheal intubation with mechanical respiratory support >48 hours). Results-Twelve of 19 fetuses (63.2%) survived. Among the survivors, 7 (58.3%) had severe respiratory morbidity. The observed/expected total lung volume at the last US examination before birth was significantly associated with perinatal death (P < .01) and respiratory morbidity (P < .01) as well as fetal hydrops (P < .01) and bilateral effusion (P = .01). Conclusions-Fetal total lung volumes may be useful for the prediction of perinatal outcomes in primary pleural effusion.

Débito cardíaco e fração de ejeção fetal por meio do spatio-temporal image correlation (STIC): comparação entre fetos masculinos e femininos

OBJETIVO: Comparar do débito cardíaco (DC) e a fração de ejeção (FE) do coração de fetos masculinos e femininos obtidos por meio da ultrassonografia tridimensional, utilizando o spatio-temporal image correlation (STIC). MÉTODOS: Realizou-se um estudo de corte transversal com 216 fetos normais, entre 20 a 34 semanas de gestação, sendo 108 masculinos e 108 femininos. Os volumes ventriculares no final da sístole e diástole foram obtidos por meio do STIC, sendo as avaliações volumétricas realizadas pelo virtual organ computer-aided analysis (VOCAL) com rotação de 30º. Para o cálculo do DC utilizou-se a fórmula: DC= volume sistólico/frequência cardíaca fetal, enquanto que para a FE utilizou-se a fórmula: FE= volume sistólico/volume diastólico final. O DC (combinado, feminino e masculino) e a FE (masculina e feminina) foram comparadas utilizando-se o teste t não pareado e ANCOVA. Foram criados gráficos de dispersão com os percentis 5, 50 e 95. RESULTADOS: A média do DC combinado, DC direito, DC esquerdo, FE direita e FE esquerda, para feminino e masculino, foram 240,07 mL/min; 122,67 mL/min; 123,40 mL/min; 72,84%; 67,22%; 270,56 mL/min; 139,22 mL/min; 131,34 mL/min; 70,73% e 64,76%, respectivamente; sem diferença estatística (P> 0,05). CONCLUSÕES: O DC e a FE fetal obtidos por meio da ultrassonografia tridimensional (STIC) não apresentaram diferença significativa em relação ao gênero.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Structure- and ligand-based drug design approaches for neglected tropical diseases

Drug discovery has moved toward more rational strategies based on our increasing understanding of the fundamental principles of protein-ligand interactions. Structure( SBDD) and ligand-based drug design (LBDD) approaches bring together the most powerful concepts in modern chemistry and biology, linking medicinal chemistry with structural biology. The definition and assessment of both chemical and biological space have revitalized the importance of exploring the intrinsic complementary nature of experimental and computational methods in drug design. Major challenges in this field include the identification of promising hits and the development of high-quality leads for further development into clinical candidates. It becomes particularly important in the case of neglected tropical diseases (NTDs) that affect disproportionately poor people living in rural and remote regions worldwide, and for which there is an insufficient number of new chemical entities being evaluated owing to the lack of innovation and R&D investment by the pharmaceutical industry. This perspective paper outlines the utility and applications of SBDD and LBDD approaches for the identification and design of new small-molecule agents for NTDs.