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628 results on '"Landini L"'

2. An automatic deep learning approach for coronary artery calcium segmentation

Author

Santini, G., Della Latta, D., Martini, N., Valvano, G., Gori, A., Ripoli, A., Susini, C. L., Landini, L., and Chiappino, D.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Coronary artery calcium (CAC) is a significant marker of atherosclerosis and cardiovascular events. In this work we present a system for the automatic quantification of calcium score in ECG-triggered non-contrast enhanced cardiac computed tomography (CT) images. The proposed system uses a supervised deep learning algorithm, i.e. convolutional neural network (CNN) for the segmentation and classification of candidate lesions as coronary or not, previously extracted in the region of the heart using a cardiac atlas. We trained our network with 45 CT volumes; 18 volumes were used to validate the model and 56 to test it. Individual lesions were detected with a sensitivity of 91.24%, a specificity of 95.37% and a positive predicted value (PPV) of 90.5%; comparing calcium score obtained by the system and calcium score manually evaluated by an expert operator, a Pearson coefficient of 0.983 was obtained. A high agreement (Cohen's k = 0.879) between manual and automatic risk prediction was also observed. These results demonstrated that convolutional neural networks can be effectively applied for the automatic segmentation and classification of coronary calcifications.

Published
2017
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5. DataBrain: a web-accessible database for three-dimensional reconstructions and quantitative morphometrics of neurons

Author

Magliaro, C., Callara, A. L., Arami, N., De Maria, C., Ferrari, V., Vanello, N., Tognetti, A., Mangione, M., Viaggi, M. C., Vaglini, F., Castagna, M., De Rossi, D., Landini, L., Ahluwalia, A., Magjarevic, Ratko, Editor-in-chief, Ładyżyński, Piotr, Series editor, Ibrahim, Fatimah, Series editor, Lacković, Igor, Series editor, Rock, Emilio Sacristan, Series editor, Eskola, Hannu, editor, Väisänen, Outi, editor, Viik, Jari, editor, and Hyttinen, Jari, editor

Published
2018
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14. DataBrain: a web-accessible database for three-dimensional reconstructions and quantitative morphometrics of neurons

Author

Magliaro, C., primary, Callara, A. L., additional, Arami, N., additional, De Maria, C., additional, Ferrari, V., additional, Vanello, N., additional, Tognetti, A., additional, Mangione, M., additional, Viaggi, M. C., additional, Vaglini, F., additional, Castagna, M., additional, De Rossi, D., additional, Landini, L., additional, and Ahluwalia, A., additional

Published
2017
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34. Comparison between pulse oximetry and transthoracic impedance alarm traces during home monitoring

Author

Nassi, N., Piumelli, R., Lombardi, E., Landini, L., Donzelli, G., and de Martino, M.

Subjects
Electrocardiogram -- Usage, Electrocardiogram -- Research, Electrocardiography -- Usage, Electrocardiography -- Research, Apnea -- Risk factors, Apnea -- Demographic aspects, Apnea -- Research, Bradycardia -- Risk factors, Bradycardia -- Demographic aspects, Bradycardia -- Research, Hypoxia -- Risk factors, Hypoxia -- Demographic aspects, Hypoxia -- Research, Patient monitoring -- Methods, Patient monitoring -- Comparative analysis
Published
2008

35. TRPA1 mediates damage of the retina induced by ischemia and reperfusion in mice

Author

Souza Monteiro de Araujo, D., De Logu, F., Adembri, C., Rizzo, Stanislao, Janal, M. N., Landini, L., Magi, A., Mattei, G., Cini, N., Pandolfo, P., Geppetti, P., Nassini, R., Calaza, K. C., Rizzo S. (ORCID:0000-0001-6302-063X), Souza Monteiro de Araujo, D., De Logu, F., Adembri, C., Rizzo, Stanislao, Janal, M. N., Landini, L., Magi, A., Mattei, G., Cini, N., Pandolfo, P., Geppetti, P., Nassini, R., Calaza, K. C., and Rizzo S. (ORCID:0000-0001-6302-063X)

Abstract

Oxidative stress is implicated in retinal cell injury associated with glaucoma and other retinal diseases. However, the mechanism by which oxidative stress leads to retinal damage is not completely understood. Transient receptor potential ankyrin 1 (TRPA1) is a redox-sensitive channel that, by amplifying the oxidative stress signal, promotes inflammation and tissue injury. Here, we investigated the role of TRPA1 in retinal damage evoked by ischemia (1 hour) and reperfusion (I/R) in mice. In wild-type mice, retinal cell numbers and thickness were reduced at both day-2 and day-7 after I/R. By contrast, mice with genetic deletion of TRPA1 were protected from the damage seen in their wild-type littermates. Daily instillation of eye drops containing two different TRPA1 antagonists, an oxidative stress scavenger, or a NADPH oxidase-1 inhibitor also protected the retinas of C57BL/6J mice exposed to I/R. Mice with genetic deletion of the proinflammatory TRP channels, vanilloid 1 (TRPV1) or vanilloid 4 (TRPV4), were not protected from I/R damage. Surprisingly, genetic deletion or pharmacological blockade of TRPA1 also attenuated the increase in the number of infiltrating macrophages and in the levels of the oxidative stress biomarker, 4-hydroxynonenal, and of the apoptosis biomarker, active caspase-3, evoked by I/R. These findings suggest that TRPA1 mediates the oxidative stress burden and inflammation that result in murine retinal cell death. We also found that TRPA1 (both mRNA and protein) is expressed by human retinal cells. Thus, it is possible that inhibition of a TRPA1-dependent pathway could also attenuate glaucoma-related retinal damage.

Published
2020

44. A numerical and 3D printing framework for the in vivo mechanical assessment of patient-specific cardiovascular structures

Author

Benigno Marco Fanni, Sauvage, E., Capelli, C., Gasparotti, E., Vignali, E., Schievano, S., Landini, L., Positano, V., and Celi, S.

Subjects
Digital computer simulation, Finite element method, 3D Printing, Fluid-Structure Interaction, Material Properties, Mock Loop, Magnetic Resonance Imaging, Matemàtiques i estadística::Anàlisi numèrica::Mètodes en elements finits [Àrees temàtiques de la UPC], Simulació per ordinador digital
Abstract

Computational simulations represent a powerful tool for the pre-procedural clinical assessment of minimally invasive cardiovascular interventions [1]. Patient-specific simulations rely on the accurate numerical implementation of both geometrical and mechanical features. While current imaging techniques are able to depict accurately patient-specific anatomies, at date, a similar image-based tool capable to retrieve subject-specific material properties is missing. The scope of this study is to present a framework, involving in silico tools and 3D printing, for the refinement of an image-based technique [2] capable to retrieve in vivo patient-specific mechanical information from functional and morphological magnetic resonance imaging (MRI) data. The workflow consists in three main steps: (i) selection and mechanical testing of 3D commercially available deformable 3D printed materials; (ii) fluid-structure interaction (FSI) simulation of a vessel model under pulsatile regime; (iii) 3D printing of the model and experimental replica in MRI environment. Finally, the imagebased technique is applied to both numerical (ii) and MRI data (iii) to retrieve material information to compare to reference (i). The described workflow strategy was successfully implemented by our group. The deformable material TangBlackPlus FLX980 was selected and mechanically tested, resulting in an elastic module (E) of 0.50 0:02 MPa. A vessel model was designed for FSI simulations (E=0.50 MPa) as well as 3D printed with an Objet500 Connex machine (Stratasys, Minnesota, USA) to acquire MRI data. The image-based technique was used to retrieve the E value from numerical and experimental data. In silico, the indirect material evaluation resulted in E=0.49 MPa, while in vitro we found E=0.51 0:04 MPa. Moreover, other values of E (up to 32 MPa) were tested in silico, leading to matching results as well. Other deformable materials will be investigated, i.e. Agilus30 (Stratasys, Minnesota, USA) and Elastic and Flexible resins (Formlabs, Massachusetts, USA), by using the described framework. With further refinements, this strategy would lead to an indirect and image-based tool for the in vivo assessment of patient-specific material properties, thus enhancing the confidence of patient-specific computational models.

Published
2019

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