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Objective The literature study the setup errors of head and neck, thoracic, abdominal and pelvic tumors by megavoltage fan-beam CT based image guidance in TOMO-HD to provide the margin enlarging from clinic target volume (CTV) to planning target volume (PTV) in treatment planning system of TOMO-HD. Methods 103 patients with head and neck (30 patients), thoracic (42 patients), abdominal and pelvic (31 patients) carcinoma were enrolled. Megavoltage fan-beam CT based image guidance in tomotherapy-HD was used to acquire CT scan before every treatment. The left-right (X), superior-inferior (Y), anterior-posterior (Z) and rotation (Fy) setup errors of patients can be obtained from the tomography image automatically restructured by the system. Calculating the systematic error and the random error in the three dimensions and check whether the setup data accord with the normal distribution or not, then acquire the data expand in the three directions. Results According to 2593 fan-beam CT scans, the shift errors (µ ± s) in X, Y, Z and Fy (rotation) of three study group were [(−0.31 ± 2.16) mm、(1.09 ± 3.56) mm、(2.36 ± 2.27) mm, (0.29 ± 0.96)°] (head and neck tumor), [(−0.98 ± 2.95) mm、(0.45 ± 6.86) mm、(3.79 ± 2.47) mm, (0.18 ± 0.60)°] (thoracic cancer) and [(−0.86 ± 2.85) mm、(−1.59 ± 6.91) mm、(5.77 ± 2.40) mm, (0.20 ± 0.68)°](abdominal and pelvic carcinoma). The systematic errors (∑) and random errors (σ) in X, Y, Z dimensions of patients with head and neck, thoracic, abdominal and pelvic tumors were (1.06 mm and 1.84 mm), (1.93 mm and 3.43 mm), (2.41 mm and 2.71 mm), (1.10 mm and 2.56 mm), (3.79 mm and 5.46 mm), (1.38 mm and 1.99 mm) and (1.39 mm and 0.87 mm), (4.98 mm and 5.69 mm), (1.19 mm and 2.05 mm), respectively. Conclusion It is recommended as a reference for image guidance in TOMO-HD according to the frequency distribution of setup errors, for patients with head and neck, chest and abdominal and pelvic tumors, the maximum range of motion in three dimensions are (5.00, 5.00, 5.00) mm, (6.63, 17.25, 16.00) mm and (6.49, 16.24, 13.60) mm.
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Background: The accuracy of radiotherapy is based on the matching of 2D portal/CBCT image with a reference image. The aim of this study is to determine the random and systematic setup errors (in cm) in radiotherapy of head and neck cancer patients and to derive the setup margin and its clinical implications.Methods: Author retrospectively reviewed the records of 25 head and neck cancer (HNC) patients treated with radiotherapy between Dec 2017 and July 2018. After immobilization, setup accuracy was assessed by registration of XVI image with planning reference image using Elekta XVI image guidance system and the isocenter correction was applied. For each patient 10 CBCT image sets were taken. The translational errors in X, Y and Z directions were used to estimate systematic (Σ) and random (σ) errors and to derive the final setup margin by using van Herk’s formula (2.5Σ + 0.7σ).Results: The mean translational errors ranges from -0.23 cm to 0.32 cm in Lateral (X), -0.15 to 0.16 cm in Longitudinal (Y) and -0.11 to 0.17 cm in vertical (Z) directions. The Mean and SD for systematic errors 0.21±0.13, 0.11±0.18, 0.14±0.11 and random error (in cm) are -0.03±0.33, 0.00±0.21 and 0.05±0.30 in X, Y and Z axis respectively. The final total margin for CTV to PTV including setup margin in the X, Y and Z directions (in cm) were 0.56, 0.61, and 0.47 respectively.Conclusion: Thus, the precise immobilization techniques are very important to reduce the setup margins, and the number of CBCTs during head and neck radiotherapy treatment.
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Las tablas y bases de datos de composición de alimentos (TCA/BDCA) son herramientas de valoración dietética. Objetivo: identificar las diferentes TCA empleadas como instrumento para estimar ingesta de nutrientes en Ecuador. La recogida de información se realizó a través de informadores-clave, cuestionarios auto-administrados, complementadas con búsquedas webs institucionales. A las TCA/BDCA identificadas se realizó análisis de contenido sobre variables generales y metodológicas. TCA referidas: Ecuatoriana-1965 (70%), INCAP (60%), México (60%). Se reportaron 7 TCA y 3 BDCA, 8 Latinoamericanas y 2 Españolas. Una TCA elaborada por método-directo (ecuatoriana), 7 por método-indirecto, 2 sin-información. 6 TCA/BDCA definieron nutrientes, 9 refirieron valores (100g/ porción-comestible). Para realizar una correcta estimacion de ingesta, es necesario contar con una TCA ecuatoriana actualizada. Ecuatoriana-1965 presenta pocos alimentos analizados y, métodos analíticos no-actualizados. Las autoras aconsejan el uso de TCA-INCAP, dado que la lista de alimentos refleja similitud con alimentos ecuatorianos. Además INCAP dispone BDCA para incorporar recetas.
Tables and food composition databases (FCT/FCDB) are tools used for dietetic evaluation. Objective: to identify different FCT used as an instrument to estimate the nutrient intake in Ecuador. The collection of data was made through key informants -self completed questionnaires-, supplemented with institutional web research. An analysis of content was performed to the identified FCT/FCDB by general and methodological variables. Referenced tables were: Ecuadorian-1965 (70%), INCAP (60%), México (60%). 7 FCT and 3 FCDB were reported, 8 from Latin America and 2 from Spain. One table was constructed by direct method (Ecuadorian-table), 7 by indirect, and 1 had no Information. 6 FCT/FCDB defined the nutrients, 9 expressed values per (100g/ edible portion). In order to asses a proper ingest in Ecuador, it is necessary to have an updated ecuadorian FCT, Ecuadorian-1965 shows few analyzed foods and, not updated analytic techniques. The authors recommend the usage of FCT-INCAP, due to its food list reflects similarities with ecuadorian foods. In addition, INCAP disposes of a FCDB in which ecuadorian recipes can be included.
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Humanos , Alimentos , Ingestión de Alimentos , Composición de Alimentos , Alimentos , Estado Nutricional , Información NutricionalRESUMEN
Based on the law of large numbers which is derived from probability theory, we tend to increase the sample size to the maximum. Central limit theorem is another inference from the same probability theory which approves largest possible number as sample size for better validity of measuring central tendencies like mean and median. Sometimes increase in sample-size turns only into negligible betterment or there is no increase at all in statistical relevance due to strong dependence or systematic error. If we can afford a little larger sample, statistically power of 0.90 being taken as acceptable with medium Cohen’s d (<0.5) and for that we can take a sample size of 175 very safely and considering problem of attrition 200 samples would suffice.
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El procesamiento del lenguaje natural proporciona instrumentos eficaces para ayudar a investigadores a enfrentarse con el cuerpo creciente de literatura científica. Uno de los usos más acertados y bien establecidos es la extracción de la información, por ejemplo, la extracción de entidades y hechos. Esta aplicación, sin embargo, no es del todo aplicable a las ciencias sociales, ya que los mensajes principales de las publicaciones no son hechos sino argumentos. En este artículo proponemos una metodología de procesamiento del lenguaje natural destinado a detectar oraciones que comunican mensajes salientes en trabajos de investigación pertenecientes a las ciencias sociales. Consideramos dos tipos de oraciones que contienen mensajes salientes: oraciones que resumen el artículo en su totalidad o partes del artículo y las oraciones que comunican cuestiones de investigación. Tales oraciones son detectadas usando un analizador gramatical de dependencia y reglas especiales de unión de conceptos. En un experimento de prueba-de-concepto hemos mostrado la eficacia de nuestra proposición: buscando artículos en la base de documentos de ciencia educativa construida por el proyecto EERQI hemos descubierto que la presencia de la(s) palabra(s) de pregunta en las oraciones salientes detectadas por nuestro instrumento es un indicador importante de la importancia del artículo. Hemos comparado la importancia de los artículos recuperados con nuestro método con aquellos recuperados por el motor de búsqueda Lucene como configurado para la base de contenido de EERQI, con el ranking de importancia de omisión, que está basado en medidas de frecuencia de palabras. Los resultados son complementarios, lo cual señala la utilidad de la integración de nuestro instrumento en el Lucene.
Natural language processing provides effective tools to help researchers cope with the growing body of scientific literature. One of the most successful and well-established applications is information extraction, i.e. the extraction of named entities andfacts. This application, however, is not well suited to social sciences, since the main messages of the publications are not facts, but rather arguments. In this article we propose a natural language processing methodology in order to detect sentences that convey salient messages in social science research papers. We consider two sentencetypes that bear salient messages: sentences that sum up the entire article or parts of the article and sentences that convey research issues. Such sentences are detected using a dependency parser and special concept-matching rules. In a proof-of-concept experiment we have shown the effectiveness of our proposition: searching for articles in the educational science document base built by the EERQI project we have found that the presence of the query word(s) in the salient sentences detected by our tool isan important indicator of the relevance of the article. We have compared the relevance of the articles retrieved with our method with those retrieved by the Lucene search engine as configured for the EERQI content base with the default relevance ranking which is based on word frequency measures. The results are complementary, which points to the utility of the integration of our tool into Lucene.