Usefulness of quantitative echocardiographic techniques to predict recovery of regional and global left ventricular function after acute myocardial infarction

The left ventricular response to dobutamine may be quantified using tissue Doppler measurement of myocardial velocity or displacement or 3-dimensional echocardiography to measure ventricular volume and ejection fraction. This study sought to explore the accuracy of these methods for predicting segmental and global responses to therapy. Standard dobutamine and 3-dimensional echocardiography were performed in 92 consecutive patients with abnormal left ventricular function at rest. Recovery of function was defined by comparison with follow-up echocardiography at rest 5 months later. Segments that showed improved regional function at follow-up showed a higher increment in peak tissue Doppler velocity with dobutamine therapy than in nonviable segments (1.2 +/- 0.4 vs 0.3 +/- 0.2 cm/s, p = 0.001). Similarly, patients who showed a > 5% improvement of ejection fraction at follow-up showed a greater displacement response to dobutamine (6.9 +/- 3.2 vs 2.1 +/- 2.3 mm, p = 0.001), as well as a higher rate of ejection fraction, response to dobutamine (9 +/- 3% vs 2 +/- 2%, p = 0.001). The optimal cutoff values for predicting subsequent recovery of function at rest were an increment of peak velocity > 1 cm/s, >5 mm of displacement, and a >5% improvement of ejection fraction with low-dose dobutamine. (C) 2003 by Excerpta Medica, Inc.

Parvalbumin-, calbindin-, and calretinin-immunoreactive neurons in the prefrontal cortex of the owl monkey (Aotus trivirgatus): A standardized quantitative comparison with sensory and motor areas

Recent studies have revealed regional variation in the density and distribution of inhibitory neurons in different cortical areas, which are thought to reflect area-specific specializations in cortical circuitry. However, there are as yet few standardized quantitative data regarding how the inhibitory circuitry in prefrontal cortex (PFC), which is thought to be involved in executive functions such as cognition, emotion and decision making, compares to that in other cortical areas. Here we used immunohistochemical techniques to determine the density and distribution of parvalbumin (PV)-, calbindin (CB)-, and calretinin (CR)-immunoreactive (ir) neurons and axon terminals in the dorsolateral and orbital PFC of the owl monkey (Aotus trivirgatus), and compared them directly with data obtained using the same techniques in 11 different visual, somatosensory and motor areas. We found marked differences in the density of PV-ir, CB-ir, and CR-ir interneurons in several cortical areas. One hundred and twenty eight of all 234 possible between-area pairwise comparisons were significantly different. The density of specific subpopulations of these cells also varied among cortical areas, as did the density of axon terminals. Comparison of PFC with other cortical areas revealed that 40 of all 66 possible statistical comparisons of the density of PV-ir, CB-ir, and CR-ir cells were significantly different. We also found evidence for heterogeneity in the pattern of labeling of PV-ir, CB-ir, and CR-ir cells and axon terminals between the dorsolateral and orbital subdivisions of PFC. These data are likely to reflect basic differences in interneuron circuitry, which are likely to influence inhibitory function in the cortex. Copyright (C) 2003 S. Karger AG, Basel.

Thoracic wall reconstruction using ultrasound images to model/bend the thoracic prosthesis for correction of pectus excavatum

Pectus excavatum is the most common congenital deformity of the anterior thoracic wall. The surgical correction of such deformity, using Nuss procedure, consists in the placement of a personalized convex prosthesis into sub-sternal position to correct the deformity. The aim of this work is the CT-scan substitution by ultrasound imaging for the pre-operative diagnosis and pre-modeling of the prosthesis, in order to avoid patient radiation exposure. To accomplish this, ultrasound images are acquired along an axial plane, followed by a rigid registration method to obtain the spatial transformation between subsequent images. These images are overlapped to reconstruct an axial plane equivalent to a CT-slice. A phantom was used to conduct preliminary experiments and the achieved results were compared with the corresponding CT-data, showing that the proposed methodology can be capable to create a valid approximation of the anterior thoracic wall, which can be used to model/bend the prosthesis

The use of quantitative performance information by local elected politicians in top managers’ performance evaluation: case studies

This paper studies the use of results oriented performance information (outputs and outcomes) by local elected politicians (aldermen) in top managers’ performance evaluation. The main goal is to understand the top managers’ performance evaluation process conducted by Portuguese aldermen and to identify the dominant evaluation style. In line with Bogt (2001), an exploratory field research was developed in three large municipalities: Porto, Braga and Matosinhos. We intend to answer the following research questions: to what extent are local politicians (aldermen) 1 using results information (about outputs and outcomes) to evaluate top managers’ performance? Do aldermen give any importance to quantitative output information and report them on current planning and control documents? Will the output performance information be used on performance evaluation in a different way concerning policy field (task orientation)? Based on the Hopwood evaluation styles (adapted from the private to the public sector by Bogt, 2001), we have found that the performance evaluation process of top managers is more featured by the ‘operations-conscious styles’ (or ‘implicit style’). Portuguese aldermen recognize the importance to quantify outputs and outcomes, but these days they focus on the information about activities and the realized operations when they evaluate performance. We haven´t found significant differences between different tasks (some exceptions for culture and environment areas). However, the municipality of Matosinhos paid more attention on quantitative performance information. This finding is reinforced by the quality of quantitative data on outputs reported on its management report. Generally speaking, aldermen are aware that more attention should be paid to quantitative information about results and performance, taking into account recent reforms introduced in Portuguese municipalities (PLG) on this field, but the ‘implicit’ style is dominant.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.

A-scan ultrasound system for real-time puncture safety assessment during percutaneous nephrolithotomy

Background: Kidney stone is a major universal health problem, affecting 10% of the population worldwide. Percutaneous nephrolithotomy is a first-line and established procedure for disintegration and removal of renal stones. Its surgical success depends on the precise needle puncture of renal calyces, which remains the most challenging task for surgeons. This work describes and tests a new ultrasound based system to alert the surgeon when undesirable anatomical structures are in between the puncture path defined through a tracked needle. Methods: Two circular ultrasound transducers were built with a single 3.3-MHz piezoelectric ceramic PZT SN8, 25.4 mm of radius and resin-epoxy matching and backing layers. One matching layer was designed with a concave curvature to work as an acoustic lens with long focusing. The A-scan signals were filtered and processed to automatically detect reflected echoes. Results: The transducers were mapped in water tank and tested in a study involving 45 phantoms. Each phantom mimics different needle insertion trajectories with a percutaneous path length between 80 and 150 mm. Results showed that the beam cross-sectional area oscillates around the ceramics radius and it was possible to automatically detect echo signals in phantoms with length higher than 80 mm. Conclusions: This new solution may alert the surgeon about anatomical tissues changes during needle insertion, which may decrease the need of X-Ray radiation exposure and ultrasound image evaluation during percutaneous puncture.

Validation of percutaneous puncture trajectory during renal access using 4D ultrasound reconstruction

Background: An accurate percutaneous puncture is essential for disintegration and removal of renal stones. Although this procedure has proven to be safe, some organs surrounding the renal target might be accidentally perforated. This work describes a new intraoperative framework where tracked surgical tools are superimposed within 4D ultrasound imaging for security assessment of the percutaneous puncture trajectory (PPT). Methods: A PPT is first generated from the skin puncture site towards an anatomical target, using the information retrieved by electromagnetic motion tracking sensors coupled to surgical tools. Then, 2D ultrasound images acquired with a tracked probe are used to reconstruct a 4D ultrasound around the PPT under GPU processing. Volume hole-filling was performed in different processing time intervals by a tri-linear interpolation method. At spaced time intervals, the volume of the anatomical structures was segmented to ascertain if any vital structure is in between PPT and might compromise the surgical success. To enhance the volume visualization of the reconstructed structures, different render transfer functions were used. Results: Real-time US volume reconstruction and rendering with more than 25 frames/s was only possible when rendering only three orthogonal slice views. When using the whole reconstructed volume one achieved 8-15 frames/s. 3 frames/s were reached when one introduce the segmentation and detection if some structure intersected the PPT. Conclusions: The proposed framework creates a virtual and intuitive platform that can be used to identify and validate a PPT to safely and accurately perform the puncture in percutaneous nephrolithotomy.

Accessing Planktothrix species diversity and associated toxins using quantitative real-time PCR in natural waters

Tese de Doutoramento em Biologia apresentada à Faculdade de Ciências da Universidade do Porto, 2015.

Estudo da função sistólica do ventrículo direito por ecocardiografia transtorácica: relatório de projecto

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular. Área de especialização - Ultrassonografia Cardiovascular

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Global and local detection of liver steatosis from ultrasound

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. Steatosis is usually a diffuse liver disease, since it is globally affected. However, steatosis can also be focal affecting only some foci difficult to discriminate. In both cases, steatosis is detected by laboratorial analysis and visual inspection of ultrasound images of the hepatic parenchyma. Liver biopsy is the most accurate diagnostic method but its invasive nature suggest the use of other non-invasive methods, while visual inspection of the ultrasound images is subjective and prone to error. In this paper a new Computer Aided Diagnosis (CAD) system for steatosis classification and analysis is presented, where the Bayes Factor, obatined from objective intensity and textural features extracted from US images of the liver, is computed in a local or global basis. The main goal is to provide the physician with an application to make it faster and accurate the diagnosis and quantification of steatosis, namely in a screening approach. The results showed an overall accuracy of 93.54% with a sensibility of 95.83% and 85.71% for normal and steatosis class, respectively. The proposed CAD system seemed suitable as a graphical display for steatosis classification and comparison with some of the most recent works in the literature is also presented.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.