Standardization of penile angle estimation with a semi-automated algorithm.

INTRODUCTION: Penile curvature (PC) refers to an abnormal bending of the main longitudinal axis of the penis. It is frequently associated to hypospadias. To date, accurate and objective evaluation of PC is not easily reproducible amongst surgeons and there are no stablished protocols on how to measure PC in a standard way and in real-time to guide intraoperative decision making. For this reason, we want to present the results of creating a semi-automated algorithm to establish a reproducible and objective assessment of PC and propose it as a standard protocol for clinical applicability using inanimate 3-D penile models. METHODS: This project consisted in two different phases. 1. Creation of an automated algorithm to estimate penile angle based on digital images. 2 Use of the algorithm to estimate penile angle on 3-D models and estimate interrater agreement using the algorithm. The algorithm was created to initially identify the geometrical centerline of the penile model to establish an automated output for angle estimation. 3-D printed penile models with known curvature angles ranging from 10 to 90° were used to test the algorithm (total of 9 penile models. These models were curved at one hinge as opposed to an arc type model. For each inanimate model, a set of 5 pictures were obtained from a lateral view at different camera angles (00, 150, 300, 450 and 600) at a standard distance of 75 cm. Angle estimation using our designed PC algorithm was performed by a total of 10 different evaluators. Inter-rater reliability analysis in using the semiautomated algorithm was performed using the inter-class correlation coefficient (ICC) with two-way mixed effect model. RESULTS: If the camera angle was greater than 30°, the absolute angle mean difference was greater than 10°. Camera angle with the smallest mean difference was at 00 with a mean difference of 7.83°. Agreement between raters showed greater variability towards the higher camera angles. Nonetheless, a high degree of between evaluator reliability was found between the measurements at different camera angles. Single measures ICC ranges from .873 to .946, p-values were all <.0001. CONCLUSION: Our results help standardize PC assessment using digital images and reduce subjectivity using an algorithm for PC estimation. Optimal camera position between 00 to 300 vertical from the penis gives the least variable and most accurate angle estimation. Future studies using algorithms will help define predictive PC cutoff values and evaluate postoperative outcomes.

Towards optimal flow diverter porosity for the treatment of intracranial aneurysm.

PURPOSE: Low-porosity endovascular stents, known as flow diverters (FDs), have been proposed as an effective and minimally invasive treatment for sidewall intracranial aneurysms (IAs). Although it has been reported that the efficacy of a FD is substantially influenced by its porosity, clinical doctors would clearly prefer to do their interventions optimally based on refined quantitative data. This study focuses on the association between the porosity configurations and the FD efficacy, in order to provide practical data to help the clinical doctors optimize the interventions. METHOD: Numerical simulations in fluid dynamics were performed using four patient-specific IA geometries, pulsatile velocity profiles and braided fully resolved FDs. The variation of velocity and wall shear stress within the IAs, were investigated in this study. Lattice Boltzmann method (LBM) was used to solve the main challenge centered on the diversity of spatial scales since the typical diameter of struts of FDs is only 25µm while the artery normally can be larger by a hundred times. RESULTS: Numerical simulations revealed that the blood flow within IA sac was substantially reduced when the porosity is less than 86%. In particular, the flow condition within each IA sac is favorite to initialize thrombus formation when porosity is less than 70%. CONCLUSION: Our study suggests the existence of a porosity threshold below which the efficacy of a FD will be sufficient for the patients to initialize the thrombus formation. Therefore, by estimating the porosity of FD on patient-specific information, it may be potentially to predict whether or the blood flow condition will successfully become prothrombotic after the FD intervention.

A tree-matching algorithm: Application to airways in CT images of subjects with the acute respiratory distress syndrome.

To match anatomical trees such as airways, we propose a graph-based strategy combined with an appropriate distance function. The strategy was devised to cope with topological and geometrical differences that may arise between trees corresponding to the same subject, but extracted from images acquired in different conditions. The proposed distance function, called father/family distance, combines topological and geometrical information in a single measure, by calculating a sum of path-to-path distances between sub-trees of limited extent. To use it successfully, the branches of these sub-trees need to be brought closer, which is obtained by successively translating the roots of these sub-trees prior to their actual matching. The work herein presented contributes to a study of the acute respiratory distress syndrome, where a series of pulmonary CT images from the same subject is acquired at varying settings (pressure and volume) of the mechanical ventilation. The method was evaluated on 45 combinations of synthetic trees, as well as on 15 pairs of real airway trees: nine corresponding to end-expiration and end-inspiration with the same pressure, and six corresponding to end-inspiration with significantly different pressures. It achieved a high rate of successful matches with respect to a hand-made reference containing a total of 2391 matches in real data: sensitivity of 94.3% and precision of 92.8%, when using the basic parameter settings of the algorithm.

Creatools: una plataforma para el desarrollo de software de procesamiento de imágenes médicas. Aplicación a la segmentación de arterias coronarias y a la detección automática de lesiones en imágenes de angiotac / Creatools: a framework for the development of medical image processing software. Application for the segmentation of coronary arteries and for the automatic detection of lesions in CT images

En este artículo se presenta un software de código abierto, llamado CreaTools, cuyo principal objetivo es el procesar y facilitar la visualización de imágenes médicas. Este software flexible funciona en diferentes sistemas operativos (Linux, Mac OS X, Windows), se desarrolla en el lenguaje de programación C++ para asegurar una fácil integración de módulos C++ y proporciona a los usuarios herramientas computacionales para construir interfaces gráficas de usuario (GUI), incluidos los datos de entrada/salida (manejo de archivos), la visualización, la interacción y el procesamiento de datos. Este artículo muestra también la utilidad de CreaTools mediante un proyecto de investigación que consiste en la detección automática de lesiones arteriales. Los algoritmos desarrollados han sido implementados en una interfaz gráfica amigable con visualización 3D e interacción. Ejemplos de tales algoritmos incluyen la extracción de ejes de arterias y la generación de modelos descriptivos de arterias con lesiones y sin lesiones.