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Rolo D.,University of Barcelona | Rolo D.,CIBER ISCIII | Fenoll A.,National Center for Microbiology | Fontanals D.,Center Diagnostic | And 9 more authors.
Journal of Clinical Microbiology | Year: 2013

In this study, we analyzed the clinical and molecular epidemiology of invasive serotype 5 (Ser5) pneumococcal isolates in four teaching hospitals in the Barcelona, Spain, area (from 1997 to 2011). Among 5,093 invasive pneumococcal isolates collected, 134 (2.6%) Ser5 isolates were detected. Although the overall incidence of Ser5-related invasive pneumococcal disease (IPD) was low (0.25 cases/100,000 inhabitants), three incidence peaks were detected: 0.63/100,000 in 1999, 1.15/100,000 in 2005, and 0.37/100,000 in 2009. The rates of Ser5 IPD were higher among young adults (18 to 64 years old) and older adults (>64 years old) in the first two peaks, whereas they were higher among children in 2009. The majority (88.8%) of the patients presented with pneumonia. Comorbid conditions were present in young adults (47.6%) and older adults (78.7%), the most common comorbid conditions being chronic obstructive pulmonary disease (20.6% and 38.3%, respectively) and cardiovascular diseases (11.1% and 38.3%, respectively). The mortality rates were higher among older adults (8.5%). All Ser5 pneumococci tested were fully susceptible to penicillin, cefotaxime, erythromycin, and ciprofloxacin. The resistance rates were 48.5% for co-trimoxazole, 6.7% for chloramphenicol, and 6% for tetracycline. Two major related sequence types (STs), ST1223 (n-65) and ST289 (n-61), were detected. The Colombia5-ST289 clone was responsible for all the cases in the Ser5 outbreak in 1999, whereas the ST1223 clone accounted for 73.8% and 61.5% of the isolates in 2005 and 2009, respectively. Ser5 pneumococci are a frequent cause of IPD outbreaks in the community and involve children and adults with or without comorbidities. The implementation of the new pneumococcal conjugated vaccines (PCV10 and PCV13) might prevent such outbreaks. Copyright © 2013, American Society for Microbiology. All Rights Reserved.


Elawady M.,CNRS Hubert Curien Laboratory | Sadek I.,Image and Pervasive Access Laboratory | Shabayek A.E.R.,Suez Canal University | Pons G.,University of Girona | Ganau S.,Center Diagnostic
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2016

Breast cancer is one of the leading causes of cancer death among women worldwide. The proposed approach comprises three steps as follows. Firstly, the image is preprocessed to remove speckle noise while preserving important features of the image. Three methods are investigated, i.e., Frost Filter, Detail Preserving Anisotropic Diffusion, and Probabilistic Patch-Based Filter. Secondly, Normalized Cut or Quick Shift is used to provide an initial segmentation map for breast lesions. Thirdly, a postprocessing step is proposed to select the correct region from a set of candidate regions. This approach is implemented on a dataset containing 20 B-mode ultrasound images, acquired from UDIAT Diagnostic Center of Sabadell, Spain. The overall system performance is determined against the ground truth images. The best system performance is achieved through the following combinations: Frost Filter with Quick Shift, Detail Preserving Anisotropic Diffusion with Normalized Cut and Probabilistic Patch-Based with Normalized Cut. © Springer International Publishing Switzerland 2016.


Pons G.,University of Girona | Marti J.,University of Girona | Marti R.,University of Girona | Ganau S.,Center Diagnostic | Noble J.A.,University of Oxford
Ultrasonic Imaging | Year: 2015

Breast ultrasound (BUS) imaging has become a crucial modality, especially for providing a complementary view when other modalities (i.e., mammography) are not conclusive in the task of assessing lesions. The specificity in cancer detection using BUS imaging is low. These false-positive findings often lead to an increase of unnecessary biopsies. In addition, increasing sensitivity is also challenging given that the presence of artifacts in the B-mode ultrasound (US) images can interfere with lesion detection. To deal with these problems and improve diagnosis accuracy, ultrasound elastography was introduced. This paper validates a novel lesion segmentation framework that takes intensity (B-mode) and strain information into account using a Markov Random Field (MRF) and a Maximum a Posteriori (MAP) approach, by applying it to clinical data. A total of 33 images from two different hospitals are used, composed of 14 cancerous and 19 benign lesions. Results show that combining both the B-mode and strain data in a unique framework improves segmentation results for cancerous lesions (Dice Similarity Coefficient of 0.49 using B-mode, while including strain data reaches 0.70), which are difficult images where the lesions appear with blurred and not well-defined boundaries. © SAGE Publications.


Tortajada M.,University of Girona | Oliver A.,University of Girona | Marti R.,University of Girona | Ganau S.,Center Diagnostic | And 4 more authors.
Computers in Biology and Medicine | Year: 2014

Digital mammograms may present an overexposed area in the peripheral part of the breast, which is visually shown as a darker area with lower contrast. This has a direct impact on image quality and affects image visualisation and assessment. This paper presents an automatic method to enhance the overexposed peripheral breast area providing a more homogeneous and improved view of the whole mammogram. The method automatically restores the overexposed area by equalising the image using information from the intensity of non-overexposed neighbour pixels. The correction is based on a multiplicative model and on the computation of the distance map from the breast boundary. A total of 334 digital mammograms were used for evaluation. Mammograms before and after enhancement were evaluated by an expert using visual comparison. In 90.42% of the cases, the enhancement obtained improved visualisation compared to the original image in terms of contrast and detail. Moreover, results show that lesions found in the peripheral area after enhancement presented a more homogeneous intensity distribution. Hence, peripheral enhancement is shown to improve visualisation and will play a role in further development of CAD systems in mammography. © 2014 Elsevier Ltd.


Oliver A.,University of Girona | Torrent A.,University of Girona | Tortajada M.,University of Girona | Llado X.,University of Girona | And 4 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

In this paper we present a boosting based approach for automatic detection of micro-calcifications in mammographic images. Our proposal is based on using local features extracted from a bank of filters for obtaining a description of the different micro-calcifications morphology. The approach performs an initial training step in order to automatically learn and select the most salient features, which are subsequently used in a boosting classifier to perform the detection. The validity of our method is demonstrated using 112 mammograms of the well-known digitised MIAS database and 280 mammograms of a full-field digital database. The experimental evaluation is performed in terms of ROC analysis, obtaining Az = 0.88 and Az = 0.90 respectively, and FROC analysis. The obtained results show the feasibility of our approach for detecting micro-calcifications in both digitised and digital technologies. © 2010 Springer-Verlag.


PubMed | Center Diagnostic, University of Oxford and University of Girona
Type: Journal Article | Journal: Ultrasonic imaging | Year: 2016

Breast ultrasound (BUS) imaging has become a crucial modality, especially for providing a complementary view when other modalities (i.e., mammography) are not conclusive in the task of assessing lesions. The specificity in cancer detection using BUS imaging is low. These false-positive findings often lead to an increase of unnecessary biopsies. In addition, increasing sensitivity is also challenging given that the presence of artifacts in the B-mode ultrasound (US) images can interfere with lesion detection. To deal with these problems and improve diagnosis accuracy, ultrasound elastography was introduced. This paper validates a novel lesion segmentation framework that takes intensity (B-mode) and strain information into account using a Markov Random Field (MRF) and a Maximum a Posteriori (MAP) approach, by applying it to clinical data. A total of 33 images from two different hospitals are used, composed of 14 cancerous and 19 benign lesions. Results show that combining both the B-mode and strain data in a unique framework improves segmentation results for cancerous lesions (Dice Similarity Coefficient of 0.49 using B-mode, while including strain data reaches 0.70), which are difficult images where the lesions appear with blurred and not well-defined boundaries.


Pons G.,University of Girona | Marti R.,University of Girona | Ganau S.,Center Diagnostic | Sentis M.,Center Diagnostic | Marti J.,University of Girona
Ultrasound in Medicine and Biology | Year: 2014

Ultrasound imaging is considered an important complementary technique for the screening of dense breasts. Detection of lesions at an early stage is a key step in which computerized lesion detection systems could play an important role in the analysis of US images. In this article, we propose adaptation of a generic object detection technique, deformable part models, to detect lesions in breast US images. The data set used in this study included 326 images, all from different patients (54 malignant lesions, 109 benign lesions and 163 healthy breasts). In terms of lesion detection, our proposal outperformed some of the most relevant approaches described in the literature; we obtained a sensitivity of 86% with 0.28 false-positive detection per image and an Az value of 0.975. In the detection of malignant lesions, our proposed approached had an Az value of 0.93 and a sensitivity of 78% at a 1.15 false-positive detections per image. © 2014 World Federation for Ultrasound in Medicine & Biology.


PubMed | Center Diagnostic and University of Girona
Type: Journal Article | Journal: Ultrasound in medicine & biology | Year: 2014

Ultrasound imaging is considered an important complementary technique for the screening of dense breasts. Detection of lesions at an early stage is a key step in which computerized lesion detection systems could play an important role in the analysis of US images. In this article, we propose adaptation of a generic object detection technique, deformable part models, to detect lesions in breast US images. The data set used in this study included 326 images, all from different patients (54 malignant lesions, 109 benign lesions and 163 healthy breasts). In terms of lesion detection, our proposal outperformed some of the most relevant approaches described in the literature; we obtained a sensitivity of 86% with 0.28 false-positive detection per image and an Az value of 0.975. In the detection of malignant lesions, our proposed approached had an Az value of 0.93 and a sensitivity of 78% at a 1.15 false-positive detections per image.


PubMed | Erasmus Medical Center, Center Diagnostic and University of Toronto
Type: | Journal: BMC medical genetics | Year: 2015

Ataxia with oculomotor apraxia type 1 is an autosomal-recessive neurodegenerative disorder characterized by a childhood onset of slowly progressive cerebellar ataxia, followed by oculomotor apraxia and a severe primary motor peripheral axonal motor neuropathy. Ataxia with oculomotor apraxia type 1 is caused by bi-allelic mutations in APTX (chromosome 9p21.1).Our patient has a clinical presentation that is typical for ataxia with oculomotor apraxia type 1 with no particularly severe phenotype. Multiplex Ligation-dependent Probe Amplification analysis resulted in the identification of a homozygous deletion of all coding APTX exons (3 to 9). SNP array analysis using the Illumina Infinium CytoSNP-850K microarray indicated that the deletion was about 62kb. Based on the SNP array results, the breakpoints were found using direct sequence analysis: c.-5+1225_*44991del67512, p.0?. Both parents were heterozygous for the deletion. Homozygous complete APTX deletions have been described in literature for two other patients. We obtained a sample from one of these two patients and characterized the deletion (156kb) as c.-23729_*115366del155489, p.0?, including the non-coding exons 1A and 2 of APTX. The more severe phenotype reported for this patient is not observed in our patient. It remains unclear whether the larger size of the deletion (156kb vs 62kb) plays a role in the phenotype (no extra genes are deleted).Here we described an ataxia with oculomotor apraxia type 1 patient who has a homozygous deletion of the complete coding region of APTX. In contrast to the patient with the large deletion, our patient does not have a severe phenotype. More patients with deletions of APTX are required to investigate a genotype-phenotype effect.


PubMed | Center Diagnostic and University of Girona
Type: Journal Article | Journal: Journal of digital imaging | Year: 2015

Breast density is a strong risk factor for breast cancer. In this paper, we present an automated approach for breast density segmentation in mammographic images based on a supervised pixel-based classification and using textural and morphological features. The objective of the paper is not only to show the feasibility of an automatic algorithm for breast density segmentation but also to prove its potential application to the study of breast density evolution in longitudinal studies. The database used here contains three complete screening examinations, acquired 2 years apart, of 130 different patients. The approach was validated by comparing manual expert annotations with automatically obtained estimations. Transversal analysis of the breast density analysis of craniocaudal (CC) and mediolateral oblique (MLO) views of both breasts acquired in the same study showed a correlation coefficient of =0.96 between the mammographic density percentage for left and right breasts, whereas a comparison of both mammographic views showed a correlation of =0.95. A longitudinal study of breast density confirmed the trend that dense tissue percentage decreases over time, although we noticed that the decrease in the ratio depends on the initial amount of breast density.

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