A Computer Aided Detection system for mammographic images implemented on a GRID infrastructure

The use of an automatic system for the analysis of mammographic images has proven to be very useful to radiologists in the investigation of breast cancer, especially in the framework of mammographic-screening programs. A breast neoplasia is often marked by the presence of microcalcification clusters and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. In the framework of the GPCALMA (GRID Platform for Computer Assisted Library for MAmmography) project, the co-working of italian physicists and radiologists built a large distributed database of digitized mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) system, able to make an automatic search of massive lesions and microcalcification clusters. The CAD is implemented in the GPCALMA integrated station, which can be used also for digitization, as archive and to perform statistical analyses. Some GPCALMA integrated stations have already been implemented and are currently on clinical trial in some italian hospitals. The emerging GRID technology can been used to connect the GPCALMA integrated stations operating in different medical centers. The GRID approach will support an effective tele- and co-working between radiologists, cancer specialists and epidemiology experts by allowing remote image analysis and interactive online diagnosis.Comment: 5 pages, 5 figures, to appear in the Proceedings of the 13th IEEE-NPSS Real Time Conference 2003, Montreal, Canada, May 18-23 200

Long-term assessment of plasma lipids in transplant recipients treated with tacrolimus in relation to fatty liver.

Immunosuppression has improved graft and recipient survival in transplantation but is associated with possible adverse effects including cardiovascular diseases. The impact of tacrolimus on the lipidic profile has been debated for several years. Twenty-nine kidney transplant recipients on tacrolimus treatment were monitored for six years, and multiple laboratory parameters investigating the lipid asset, as well as glucose profile, were carried out. Tacrolimus has been responsible for significant changes in plasma lipid concentrations only for the first six months, but not for the remaining time of observation. Similarly, in the same periods, glycemic imbalance was highlighted. The liver enzyme activity showed a modest derangement during the tacrolimus treatment, suggesting the presence of lipid accumulation in the liver. Fatty liver reversed in the long term follow-up. Tacrolimus, although it is not a completely safe option in the first months of the immunosuppressive protocols in organ transplanted recipients, still retains a certain role in the long-term post-transplantation immunosuppressive approach with high cardiovascular risk

Ventricular-vascular coupling in hypertension: methodological considerations and clinical implications

The present review is addressed to analyse the complex interplay between left ventricle and arterial tree in hypertension. The different methodological approaches to the analysis of ventricular vascular coupling in the time and frequency domain are discussed. Moreover, the role of hypertension-related changes of arterial structure and function (stiffness and wave reflection) on arterial load and how ventricular-vascular coupling modulates the process of left ventricular adaptation to hypertension are analysed.The different interplay between vascular bed and left ventricle emerges as the pathophysiological basis for the development of the multiple patterns of ventricular structural adaptation in hypertension and provides a pathway for the interpretation of systolic and diastolic functional abnormalities observed in hypertensive patients. Targeting the therapeutic approach to improve ventricular-vascular coupling may have relevant impact on reversing left ventricular hypertrophy and improving systolic and diastolic dysfunctio

Hypertrophic Cardiomyopathy in Children: Pathophysiology, Diagnosis, and Treatment of Non-sarcomeric Causes

Hypertrophic cardiomyopathy (HCM) is a myocardial disease characterized by left ventricular hypertrophy not solely explained by abnormal loading conditions. Despite its rare prevalence in pediatric age, HCM carries a relevant risk of mortality and morbidity in both infants and children. Pediatric HCM is a large heterogeneous group of disorders. Other than mutations in sarcomeric genes, which represent the most important cause of HCM in adults, childhood HCM includes a high prevalence of non-sarcomeric causes, including inherited errors of metabolism (i.e., glycogen storage diseases, lysosomal storage diseases, and fatty acid oxidation disorders), malformation syndromes, neuromuscular diseases, and mitochondrial disease, which globally represent up to 35% of children with HCM. The age of presentation and the underlying etiology significantly impact the prognosis of children with HCM. Moreover, in recent years, different targeted approaches for non-sarcomeric etiologies of HCM have emerged. Therefore, the etiological diagnosis is a fundamental step in designing specific management and therapy in these subjects. The present review aims to provide an overview of the non-sarcomeric causes of HCM in children, focusing on the pathophysiology, clinical features, diagnosis, and treatment of these rare disorders

CADe tools for early detection of breast cancer

A breast neoplasia is often marked by the presence of microcalcifications and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. Our collaboration, among italian physicists and radiologists, has built a large distributed database of digitized mammographic images and has developed a Computer Aided Detection (CADe) system for the automatic analysis of mammographic images and installed it in some Italian hospitals by a GRID connection. Regarding microcalcifications, in our CADe digital mammogram is divided into wide windows which are processed by a convolution filter; after a self-organizing map analyzes each window and produces 8 principal components which are used as input of a neural network (FFNN) able to classify the windows matched to a threshold. Regarding massive lesions we select all important maximum intensity position and define the ROI radius. From each ROI found we extract the parameters which are used as input in a FFNN to distinguish between pathological and non-pathological ROI. We present here a test of our CADe system, used as a second reader and a comparison with another (commercial) CADe system.Comment: 4 pages, Proceedings of the 4th International Symposium on Nuclear and Related Techniques 2003, Vol. unico, pp. d10/1-d10/4 Havana, Cub

Molecular Basis of Inflammation in the Pathogenesis of Cardiomyopathies

Cardiomyopathies (CMPs) represent a diverse group of heart muscle diseases, grouped into specific morphological and functional phenotypes. CMPs are associated with mutations in sarcomeric and non-sarcomeric genes, with several suspected epigenetic and environmental mechanisms involved in determining penetrance and expressivity. The understanding of the underlying molecular mechanisms of myocardial diseases is fundamental to achieving a proper management and treatment of these disorders. Among these, inflammation seems to play an important role in the pathogenesis of CMPs. The aim of the present study is to review the current knowledge on the role of inflammation and the immune system activation in the pathogenesis of CMPs and to identify potential molecular targets for a tailored anti-inflammatory treatment

GPCALMA: A Tool For Mammography With A GRID-Connected Distributed Database

The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed database of digitised mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) software which is integrated in a station that can also be used for acquire new images, as archive and to perform statistical analysis. The images are completely described: pathological ones have a consistent characterization with radiologist's diagnosis and histological data, non pathological ones correspond to patients with a follow up at least three years. The distributed database is realized throught the connection of all the hospitals and research centers in GRID tecnology. In each hospital local patients digital images are stored in the local database. Using GRID connection, GPCALMA will allow each node to work on distributed database data as well as local database data. Using its database the GPCALMA tools perform several analysis. A texture analysis, i.e. an automated classification on adipose, dense or glandular texture, can be provided by the system. GPCALMA software also allows classification of pathological features, in particular massive lesions analysis and microcalcification clusters analysis. The performance of the GPCALMA system will be presented in terms of the ROC (Receiver Operating Characteristic) curves. The results of GPCALMA system as "second reader" will also be presented.Comment: 6 pages, Proceedings of the Seventh Mexican Symposium on Medical Physics 2003, Vol. 682/1, pp. 67-72, Mexico City, Mexic

Preclinical atherosclerosis, metabolic syndrome and risk of cardiovascular events

Atherosclerotic disease is a chronic disorder developing insidiously throughout the life and usually progressing to an advanced stage by the time symptoms occur. In order to realize cardiovascular (CV) prevention, the detection of asymptomatic but diseased patients is crucial for an early intervention, since in these subjects there are opportunities to alter the progression of disease and the outcome (1). However, the simply analysis of risk factors don’t permits to identify always these subjects since it doesn’t informs about the effect that risk factors (RF) had already provoked and may more provoke on the individual vasculature. Besides, the risk factors known predict can explain only the 90 percent of cardiovascular disease (CVD) and traditional algorithms for prediction of CV risk failed to predict a proportion of cardiovascular events (CVE), realizing a “risk factors prediction gap” (2). It may be explained by several reasons: the epidemiology-derived models, based on the prediction of long-term risk, may not accurately predict short-term events, they don’t take into consideration emerging and novel risk factors; risk algorithms don’t identify, among patients with neither a previous history of CVD nor an high risk for atherosclerotic disease, those who will develop acute myocardial infarction and/or sudden coronary death as first CVD manifestation, and this may be due to the fact that the factors responsible of plaque formation and growth are not necessarily the same responsible of its instability and rupture, being the latter related to inflammation, thrombosis and plaque morphology (3).So, a possible approach to evaluate the individual global cardiovascular risk with more accurateness is to identify risk factors combination that more easily produces vascular damage, or alternatively, to evaluate directly the arterial wall and its damage degree. The former approach is performed by the evaluation of metabolic syndrome, the latter by the non-invasive study of pre-ATS markers

GPCALMA: a Grid-based tool for Mammographic Screening

The next generation of High Energy Physics (HEP) experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the Virtual Organisation (VO), a group of distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and proved to be useful in improving the radiologists' performances in the diagnosis. GRID technologies allow remote image analysis and interactive online diagnosis, with a potential for a relevant reduction of the delays presently associated to screening programs. A prototype of the system, based on AliEn GRID Services, is already available, with a central Server running common services and several clients connecting to it. Mammograms can be acquired in any location; the related information required to select and access them at any time is stored in a common service called Data Catalogue, which can be queried by any client. The result of a query can be used as input for analysis algorithms, which are executed on nodes that are in general remote to the user (but always local to the input images) thanks to the PROOF facility. The selected approach avoids data transfers for all the images with a negative diagnosis (about 95% of the sample) and allows an almost real time diagnosis for the 5% of images with high cancer probability.Comment: 9 pages, 4 figures; Proceedings of the HealthGrid Workshop 2004, January 29-30, Clermont-Ferrand, Franc