DOSIMETRY IN DIGITAL BREAST TOMOSYNTHESIS: COST-EFFICIENT APPROACH FOR THE SOUTH AMERICAN PERSPECTIVES.

The measurement of air kerma in air (Kair) to estimate average glandular dose (AGD) received during digital breast tomosynthesis (DBT) studies is sometimes a difficult task. In this work, a novel methodology was implemented to measure Kair and half-value layer while the X-ray tube is rotating. A low economic cost support (LCS) was built to place aluminium sheets and a calibrated dosemeter. Three Fujifilm Innovality equipment were used and two dosemeters calibrated on W-Al energies. Validation of the new methodology was made against standard scheme and it was applied to estimate AGD for 300 patients and 7 phantoms. Validation analysis was satisfactory. The difference in the AGD calculated with the LCS and DICOM Header was lower than ±10%. AGD values ranged from 0.77 to 2.11 mGy and 0.85 to 2.15 mGy for phantoms and patients, respectively. The novel methodology has a potential use for DBT equipment without stationary mode.

Clasificación de cáncer de mama con técnicas de análisis de la componente principal-Kernel PCA, algoritmos de máquina de vectores de soporte y regresión logística

RESUMEN Fundamento: existen muchas herramientas computacionales para administrar imágenes y conjuntos de datos; reducir la dimensión de estos favorece el manejo de la información. Objetivo: reducir la dimensión de un conjunto de datos para un mejor manejo de la información. Métodos: se utilizó el conjunto de datos de Breast Cancer Wisconsin (información de biopsias - células nucleares) y la plataforma Python Jupyter. Se implementaron técnicas de análisis de la componente principal (PCA) y Kernel PCA (kPCA) para reducir la dimensión a 2, 4, 6. Se hizo una validación cruzada para seleccionar los mejores hiperparámetros de los algoritmos de máquina de vectores de soporte y regresión logística. La clasificación se realizó con el training test original, training test (PCA y kPCA) y training test (datos transformados de PCA y kPCA). Se analizó la exactitud, precisión, exhaustividad, recuperación y el área bajo la curva. Resultados: la PCA con seis componentes explicó la tasa de variación casi en 90 %. Los mejores hiperparámetros hallados para máquina de soporte de vectores: kernel lineal y C = 100, para regresión logística fueron C = 100, Newton-cg solución (solver) e I2. Los mejores resultados de las métricas fueron para PCA 2 y 4(0,99; 0,99; 1; 0,99; 0,99). Para el training set con datos originales fueron 0,96; 0,95; 0,99; 0,97; 0,95. Para regresión logística los mejores resultados fueron para kPCA con seis componentes. Los resultados estadísticos fueron iguales a 1. Para el training set con datos originales, esos valores fueron 0,96; 0,95; 0,99; 0,97; 0.95. Conclusiones: los resultados de las métricas mejoraron utilizando PCA y kPCA.

ABSTRACT Background: there are many computational tools for managing images and data sets; reducing the size of these favors the management of information. Objective: reduce the data set size for better information management. Methods: the Breast Cancer Wisconsin data set (biopsy information - nuclear cells) and the Python Jupyter platform were used. Principal Component Analysis (PCA) and Kernel PCA (kPCA) techniques were implemented to reduce the dimension to 2, 4, 6. Cross-validation was made to select the best hyperparameters of the regression and support vector machine algorithms Logistics. The classification was carried out with the original training test, training test (PCA and kPCA) and training test (data transformed from PCA and kPCA). Accuracy, precision, completeness, recovery, and area under the curve were analyzed. Results: the PCA with six components explained the variation rate by almost 90%. The best hyperparameters found for the vector support machine: linear kernel and C = 100, for logistic regression were C = 100, Newton-cg solution (solver) and I2. The best results of the metrics were for PCA 2 and 4 (0.99, 0.99, 1, 0.99, 0.99). For the training set with original data they were 0.96; 0.95; 0.99; 0.97; 0.95. For logistic regression the best results were for kPCA with 6 components. The statistical results were equal to 1. For the training set with original data, these values were 0.96; 0.95; 0.99; 0.97; 0.95. Conclusions: the results of the metrics improved using PCA and kPCA.

Bioevaluation of 32P patch designed for the treatment of skin diseases.

OBJECTIVE: The objective of this study was to design and evaluate a 32P patch for the treatment of skin diseases. MATERIALS AND METHODS: The patch was prepared from chromic phosphate 32P and silicone. Bioelimination and biodistribution in healthy and treated animals, and the therapeutic efficacy of two treatment schemes (single dose and fractionated dose) in an animal model of skin cancer were studied. RESULTS: Based on the bioelimination and biodistribution studies, no leakage of 32P from the patch was observed. The treated tumors reduced their mean diameter compared to controls. The single-dose therapeutic scheme showed a higher number of complete and partial remissions compared to the fractionated scheme. These results were confirmed by histopathological analysis of the samples. CONCLUSION: The 32P patch was designed and produced according to specifications for the treatment of superficial lesions of the skin. Although the 32P patch is an open source, it behaves like a sealed one for use in brachytherapy treatments.

On the physical, spectral, and dosimetric characteristics of a new 125I brachytherapy source.

A new 125I source under the name Braquibac has been developed in Argentina for interstitial brachytherapy applications. The aim of this work is to study the new seed's design and to calculate its dosimetric parameters. Radiographic and destructive tests were carried out on inactive seeds to determine the physical characteristics of the source. Values of g(r), Lambda, F(r, Theta), and phi(an)(r), were obtained in water and air by simulation using the MCNP5 Monte Carlo code according to the methodology recommended in TG-43 and updated in TG-43U1. The dose rate constant was determined to be 0.937+/-0.004 cGy h(-1) U(-1) (overall statistical uncertainty +/-2.7%). Sk per unity activity was calculated to be 0.671+/-0.003 cGy cm2 h(-1) mCi(-1) by simulation of the seed in dry air using point detectors. Spectroscopic studies for both the new and the Amersham model 6711 seed were performed using an HPGe planar detector. The emission spectra of both seeds proved to be very similar. The anisotropy of the total photon intensity in air was measured in planes containing the seed's short and long axes using the HPGe detector. The minimum photon intensity for the new seed was 31.14+/-3.10% of the transverse intensity.

Intravascular brachytherapy: a model for the calculation of the dose

In this study we present the radiation dose distribution for a theoretical model with Montecarlo simulation, and based on an experimental model developed for the study of the prevention of restenosis post-angioplasty employing intravascular brachytherapy. In the experimental in vivo model, the atherosclerotic plaques were induced in femoral arteries of male New Zealand rabbits through surgical intervention and later administration of cholesterol enriched diet. For the intravascular irradiation we employed a 32P source contained within the balloon used for the angioplasty. The radiation dose distributions were calculated using the Monte Carlo code MCNP4B according to a segment of a simulated artery. We studied the radiation dose distribution in the axial and radial directions for different thickness of the atherosclerotic plaques. The results will be correlated with the biologic effects observed by means of histological analysis of the irradiated arteries