Motion Correction Algorithm of Lung Tumors for Respiratory Gated PET Images

Respiratory gating in lung PET imaging to compensate for respiratory motion artifacts is a current research issue with broad potential impact on quantitation, diagnosis and clinical management of lung tumors. However, PET images collected at discrete bins can be significantly affected by noise as there are lower activity counts in each gated bin unless the total PET acquisition time is prolonged, so that gating methods should be combined with imaging-based motion correction and registration methods. The aim of this study was to develop and validate a fast and practical solution to the problem of respiratory motion for the detection and accurate quantitation of lung tumors in PET images. This included: (1) developing a computer-assisted algorithm for PET/CT images that automatically segments lung regions in CT images, identifies and localizes lung tumors of PET images; (2) developing and comparing different registration algorithms which processes all the information within the entire respiratory cycle and integrate all the tumor in different gated bins into a single reference bin. Four registration/integration algorithms: Centroid Based, Intensity Based, Rigid Body and Optical Flow registration were compared as well as two registration schemes: Direct Scheme and Successive Scheme. Validation was demonstrated by conducting experiments with the computerized 4D NCAT phantom and with a dynamic lung-chest phantom imaged using a GE PET/CT System. Iterations were conducted on different size simulated tumors and different noise levels. Static tumors without respiratory motion were used as gold standard; quantitative results were compared with respect to tumor activity concentration, cross-correlation coefficient, relative noise level and computation time. Comparing the results of the tumors before and after correction, the tumor activity values and tumor volumes were closer to the static tumors (gold standard). Higher correlation values and lower noise were also achieved after applying the correction algorithms. With this method the compromise between short PET scan time and reduced image noise can be achieved, while quantification and clinical analysis become fast and precise.

Identification of Neoplasias of Breast Tissues Using a Powder Diffractometer

An investigation was carried out to study the potential use of the angular distribution of scattered photons by human breast samples for a rapid identification of neoplasias of breast tissues. This technique has possible applications as diagnostic aid for breast cancer. In this work, a commercial powder diffractometer was used to obtain the scattering profiles from breast tissues histopathologically classified as normal breast tissues, fibroadenomas (benign breast diseases) and carcinomas (malignant breast diseases), in the interval 0.02 angstrom(-1) < x < 0.62 angstrom(-1). The experimental methods and data corrections are discussed in detail, and they included background subtraction, polarization, self-attenuation and geometric effects. The validation of the experimental procedure was achieved through an analysis of water sample. The results showed that the scattering profile is a unique impression of each type of tissue, being correlated with their microscopic morphological features. Multivariate analysis was applied to these profiles in order to verify if the information carried by these scattering profiles allow the differentiation between normal, benign and malignant breast tissues. The statistical analysis results showed that a correct identification of 75% of the analyzed samples is accomplished. The values of sensibility and specificity of this method in correctly differentiating between normal and neoplastic samples were 95.6% and 82.3%, respectively, while the values for differentiation between benign and malignant neoplasias were 78.6% and 62.5%. These initial results indicate the feasible use of commercial powder diffractometer to provide a rapid diagnostic with a high sensitivity.

The Ultrastructural Study of Tumorigenic Cells Using Nanobiomarkers

Despite recent advances, patients with malignant brain tumors still have a poor prognosis. Glioblastoma (WHO grade 4 astrocytoma), the most malignant brain tumor, represents 50% of all astrocytomas, with a median survival rate of <1 year. It is, therefore, extremely important to search for new diagnostic and therapeutic approaches for patients with glioblastoma. This study describes the application of superparamagnetic nano-particles of iron oxide, as well as monoclonal antibodies, of immunophenotypic significance, conjoined to quantum dots for the ultrastructural assessment of glioblastoma cells. For this proposal, an immunophenotypic study by flow cytometry was carried out, followed by transmission electron microscopy analysis. The process of tumor cell labeling using nanoparticles can successfully contribute to the identification of tumorigenic cells and consequently for better understanding of glioblastoma genesis and recurrence. In addition, this method may help further studies in tumor imaging, diagnosis, and prognostic markers detection.

New methodology to assess activity status of occlusal caries in primary teeth using laser fluorescence device

An in vivo study was conducted to verify the ability of laser fluorescence (LF) to assess the activity status of occlusal caries in primary teeth, using different air-drying times. Occlusal sites (707) were examined using LF (DIAGNOdent) after air-drying for 3 s and 15 s, and the difference between readings (DIF15 s-3 s) was calculated. For concurrent validation of LF, visual criteria-Nyvad (NY) and Lesion Activity Assessment associated with the International Caries Detection and Assessment System (LAA-ICDAS)-were the reference standards for lesion activity. Histological exam using a pH-indicator dye (0.1% methyl red) was performed in 46 exfoliated/extracted teeth for criterion validation. LF readings and DIF15 s-3 s were compared using Kruskall-Wallis and Mann-Whitney tests. Receiver operating characteristic analyses were performed and validity parameters calculated, considering the caries activity assessment. Using NY, active lesions (3 s: 30.0 +/- 29.3; 15 s: 34.2 +/- 30.6) presented higher LF readings than inactive lesions (3 s: 17.0 +/- 16.3; 15 s: 19.2 +/- 17.3; p <0.05), different from LAA-ICDAS. Active cavitated caries resulted in higher LF readings (3 s: 50.3 +/- 3.5; 15 s: 54.7 +/- 30.2) than inactive cavitated caries (3 s: 19.9 +/- 16.3; 15 s: 22.8 +/- 16.8). Therefore, LF can distinguish cavitated active and inactive lesions classified by NY, but not by LAA-ICDAS; however, this difference might be related to the visual system rather than to LF. The air-drying time could be an alternative to improve the caries activity assessment; however, longer air-drying time is suggested to be tested subsequently. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3463007]

Comparison of multispectral wide-field optical imaging modalities to maximize image contrast for objective discrimination of oral neoplasia

Multispectral widefield optical imaging has the potential to improve early detection of oral cancer. The appropriate selection of illumination and collection conditions is required to maximize diagnostic ability. The goals of this study were to (i) evaluate image contrast between oral cancer/precancer and non-neoplastic mucosa for a variety of imaging modalities and illumination/collection conditions, and (ii) use classification algorithms to evaluate and compare the diagnostic utility of these modalities to discriminate cancers and precancers from normal tissue. Narrowband reflectance, autofluorescence, and polarized reflectance images were obtained from 61 patients and 11 normal volunteers. Image contrast was compared to identify modalities and conditions yielding greatest contrast. Image features were extracted and used to train and evaluate classification algorithms to discriminate tissue as non-neoplastic, dysplastic, or cancer; results were compared to histologic diagnosis. Autofluorescence imaging at 405-nm excitation provided the greatest image contrast, and the ratio of red-to-green fluorescence intensity computed from these images provided the best classification of dysplasia/cancer versus non-neoplastic tissue. A sensitivity of 100% and a specificity of 85% were achieved in the validation set. Multispectral widefield images can accurately distinguish neoplastic and non-neoplastic tissue; however, the ability to separate precancerous lesions from cancers with this technique was limited. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3516593]

Fluorescence spectroscopy for the detection of tongue carcinoma - validation in an animal model

The efficacy of fluorescence spectroscopy to detect squamous cell carcinoma is evaluated in an animal model following laser excitation at 442 and 532 nm. Lesions are chemically induced with a topical DMBA application at the left lateral tongue of Golden Syrian hamsters. The animals are investigated every 2 weeks after the 4th week of induction until a total of 26 weeks. The right lateral tongue of each animal is considered as a control site (normal contralateral tissue) and the induced lesions are analyzed as a set of points covering the entire clinically detectable area. Based on fluorescence spectral differences, four indices are determined to discriminate normal and carcinoma tissues, based on intraspectral analysis. The spectral data are also analyzed using a multivariate data analysis and the results are compared with histology as the diagnostic gold standard. The best result achieved is for blue excitation using the KNN (K-nearest neighbor, a interspectral analysis) algorithm with a sensitivity of 95.7% and a specificity of 91.6%. These high indices indicate that fluorescence spectroscopy may constitute a fast noninvasive auxiliary tool for diagnostic of cancer within the oral cavity. (C) 2008 Society of Photo-Optical Instrumentation Engineers.

Building a Open Source Framework for Virtual Medical Training

This paper presents a framework to build medical training applications by using virtual reality and a tool that helps the class instantiation of this framework. The main purpose is to make easier the building of virtual reality applications in the medical training area, considering systems to simulate biopsy exams and make available deformation, collision detection, and stereoscopy functionalities. The instantiation of the classes allows quick implementation of the tools for such a purpose, thus reducing errors and offering low cost due to the use of open source tools. Using the instantiation tool, the process of building applications is fast and easy. Therefore, computer programmers can obtain an initial application and adapt it to their needs. This tool allows the user to include, delete, and edit parameters in the functionalities chosen as well as storing these parameters for future use. In order to verify the efficiency of the framework, some case studies are presented.

Improvement of radiology services based on the process management approach

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Modeling of functionally graded piezoelectric ultrasonic transducers

The application of functionally graded material (FGM) concept to piezoelectric transducers allows the design of composite transducers without interfaces, due to the continuous change of property values. Thus, large improvements can be achieved, as reduction of stress concentration, increasing of bonding strength, and bandwidth. This work proposes to design and to model FGM piezoelectric transducers and to compare their performance with non-FGM ones. Analytical and finite element (FE) modeling of FGM piezoelectric transducers radiating a plane pressure wave in fluid medium are developed and their results are compared. The ANSYS software is used for the FE modeling. The analytical model is based on FGM-equivalent acoustic transmission-line model, which is implemented using MATLAB software. Two cases are considered: (i) the transducer emits a pressure wave in water and it is composed of a graded piezoceramic disk, and backing and matching layers made of homogeneous materials; (ii) the transducer has no backing and matching layer; in this case, no external load is simulated. Time and frequency pressure responses are obtained through a transient analysis. The material properties are graded along thickness direction. Linear and exponential gradation functions are implemented to illustrate the influence of gradation on the transducer pressure response, electrical impedance, and resonance frequencies. (C) 2009 Elsevier B. V. All rights reserved.

AUTOMATIC CORONARY WALL SEGMENTATION IN INTRAVASCULAR ULTRASOUND IMAGES USING BINARY MORPHOLOGICAL RECONSTRUCTION

Intravascular ultrasound (IVUS) image segmentation can provide more detailed vessel and plaque information, resulting in better diagnostics, evaluation and therapy planning. A novel automatic segmentation proposal is described herein; the method relies on a binary morphological object reconstruction to segment the coronary wall in IVUS images. First, a preprocessing followed by a feature extraction block are performed, allowing for the desired information to be extracted. Afterward, binary versions of the desired objects are reconstructed, and their contours are extracted to segment the image. The effectiveness is demonstrated by segmenting 1300 images, in which the outcomes had a strong correlation to their corresponding gold standard. Moreover, the results were also corroborated statistically by having as high as 92.72% and 91.9% of true positive area fraction for the lumen and media adventitia border, respectively. In addition, this approach can be adapted easily and applied to other related modalities, such as intravascular optical coherence tomography and intravascular magnetic resonance imaging. (E-mail: matheuscardosomg@hotmail.com) (C) 2011 World Federation for Ultrasound in Medicine & Biology.

Frequency Domain Connectivity Identification: An Application of Partial Directed Coherence in fMRI

Functional magnetic resonance imaging (fMRI) has become an important tool in Neuroscience due to its noninvasive and high spatial resolution properties compared to other methods like PET or EEG. Characterization of the neural connectivity has been the aim of several cognitive researches, as the interactions among cortical areas lie at the heart of many brain dysfunctions and mental disorders. Several methods like correlation analysis, structural equation modeling, and dynamic causal models have been proposed to quantify connectivity strength. An important concept related to connectivity modeling is Granger causality, which is one of the most popular definitions for the measure of directional dependence between time series. In this article, we propose the application of the partial directed coherence (PDC) for the connectivity analysis of multisubject fMRI data using multivariate bootstrap. PDC is a frequency domain counterpart of Granger causality and has become a very prominent tool in EEG studies. The achieved frequency decomposition of connectivity is useful in separating interactions from neural modules from those originating in scanner noise, breath, and heart beating. Real fMRI dataset of six subjects executing a language processing protocol was used for the analysis of connectivity. Hum Brain Mapp 30:452-461, 2009. (C) 2007 Wiley-Liss, Inc.

Proposal for DICOM Multiframe Medical Image Integrity and Authenticity

This paper presents a novel algorithm to successfully achieve viable integrity and authenticity addition and verification of n-frame DICOM medical images using cryptographic mechanisms. The aim of this work is the enhancement of DICOM security measures, especially for multiframe images. Current approaches have limitations that should be properly addressed for improved security. The algorithm proposed in this work uses data encryption to provide integrity and authenticity, along with digital signature. Relevant header data and digital signature are used as inputs to cipher the image. Therefore, one can only retrieve the original data if and only if the images and the inputs are correct. The encryption process itself is a cascading scheme, where a frame is ciphered with data related to the previous frames, generating also additional data on image integrity and authenticity. Decryption is similar to encryption, featuring also the standard security verification of the image. The implementation was done in JAVA, and a performance evaluation was carried out comparing the speed of the algorithm with other existing approaches. The evaluation showed a good performance of the algorithm, which is an encouraging result to use it in a real environment.

A H-1 MRS study of probable Alzheimer's disease and normal aging: Implications for longitudinal monitoring of dementia progression

In order to evaluate the capability of H-1 MRS to monitor longitudinal changes in subjects with probable Alzheimer's disease (AD), the temporal stability of the metabolite measures N-acetylaspartate and N-acetylas-partylglutamate (NA), total Creatine (Cr), myo-Inositol (mI), total Choline (Chol), NA/Cr, mI/Cr, Chol/Cr and NA/mI were investigated in a cohort of normal older adults. Only the metabolite measures NA, mi, Cr, NA/Cr, mI/Cr, and NA/mI were found to be stable after a mean interval of 260 days. Relative and absolute metabolite measures from a cohort of patients with probable AD were subsequently compared with data from a sample of normal older adult control subjects, and correlated with mental status and the degree of atrophy in the localized voxel. Concentrations of NA, NA/Cr, and NA/mI were significantly reduced in the AD group with concomitant significant increases in mi and mI/Cr. There were no differences between the two groups in measures of Cr, Chol, or Chol/Cr. Significant correlations between mental status as measured by the Mini-Mental State Examination and NA/mI, mI/Cr and NA were found. These metabolite measures were also significantly correlated with the extent of atrophy (as measured by CSF and GM composition) in the spectroscopy voxel. (C) 1999 Elsevier Science Inc.

Modelling of post-irradiation events in polymer gel dosimeters

The nuclear magnetic resonance (NMR) spin-spin relaxation time (T-2) is related to the radiation-dependent concentration of polymer formed in polymer gel dosimeters manufactured from monomers in an aqueous gelatin matrix. Changes in T-2 with time post-irradiation have been reported in the literature but their nature is not fully understood. We investigated those changes with time after irradiation using FT-Raman spectroscopy and the precise determination of T-2 at high magnetic field in a polymer gel dosimeter, A model of fast exchange of magnetization taking into account ongoing gelation and strengthening of the gelatin matrix as well as the polymerization of the monomers with time is presented. Published data on the changes of T-2 in gelatin gels as a function of post-manufacture time are used and fitted closely by the model presented. The same set of parameters characterizing the variations of T-2 in gelatin gels and the increasing concentration of polymer determined from Fr-Raman spectroscopy are used successfully in the modelling of irradiated polymer gel dosimeters. Minimal variations in T-2 in an irradiated PAG dosimeter are observed after 13 h.