Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Lorenza, Meneghetti"'
Autor:
Luca Nicosia, Ottavia Battaglia, Massimo Venturini, Federico Fontana, Manuela Minenna, Aurora Pesenti, Diana Budascu, Filippo Pesapane, Anna Carla Bozzini, Maria Pizzamiglio, Lorenza Meneghetti, Antuono Latronico, Giulia Signorelli, Luciano Mariano, Enrico Cassano
Publikováno v:
Insights into Imaging, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Contrast-enhanced mammography (CEM) is a relatively recent diagnostic technique increasingly being utilized in clinical practice. Until recently, there was a lack of standardized reporting for CEM findings. However, this has changed with the
Externí odkaz:
https://doaj.org/article/f18c0aee2c5a478c96bcc57fe0b419d9
Autor:
Filippo Pesapane, Emilia Giambersio, Benedetta Capetti, Dario Monzani, Roberto Grasso, Luca Nicosia, Anna Rotili, Adriana Sorce, Lorenza Meneghetti, Serena Carriero, Sonia Santicchia, Gianpaolo Carrafiello, Gabriella Pravettoni, Enrico Cassano
Publikováno v:
Life, Vol 14, Iss 4, p 454 (2024)
Breast cancer remains the most prevalent cancer among women worldwide, necessitating advancements in diagnostic methods. The integration of artificial intelligence (AI) into mammography has shown promise in enhancing diagnostic accuracy. However, und
Externí odkaz:
https://doaj.org/article/e74bfdb2769e48718e4d6fa3afbbc8e3
Autor:
Anna Rotili, Filippo Pesapane, Giulia Signorelli, Silvia Penco, Luca Nicosia, Anna Bozzini, Lorenza Meneghetti, Cristina Zanzottera, Sara Mannucci, Bernardo Bonanni, Enrico Cassano
Publikováno v:
Diagnostics, Vol 13, Iss 12, p 1996 (2023)
Purpose: This study aimed to investigate the use of contrast-free magnetic resonance imaging (MRI) as an innovative screening method for detecting breast cancer in high-risk asymptomatic women. Specifically, the researchers evaluated the diagnostic p
Externí odkaz:
https://doaj.org/article/022234de092547ad94d1875d7420c906
Autor:
Luca Nicosia, Giulia Gnocchi, Ilaria Gorini, Massimo Venturini, Federico Fontana, Filippo Pesapane, Ida Abiuso, Anna Carla Bozzini, Maria Pizzamiglio, Antuono Latronico, Francesca Abbate, Lorenza Meneghetti, Ottavia Battaglia, Giuseppe Pellegrino, Enrico Cassano
Publikováno v:
Healthcare, Vol 11, Iss 11, p 1596 (2023)
Breast cancer is the most common forms of cancer and a leading cause of mortality in women. Early and correct diagnosis is, therefore, essential to save lives. The development of diagnostic imaging applied to the breast has been impressive in recent
Externí odkaz:
https://doaj.org/article/a3ecddf1e3424aaea4b2230414a7ccb3
Autor:
Luca Nicosia, Anna Carla Bozzini, Giulia Signorelli, Simone Palma, Filippo Pesapane, Samuele Frassoni, Vincenzo Bagnardi, Maria Pizzamiglio, Mariagiorgia Farina, Chiara Trentin, Silvia Penco, Lorenza Meneghetti, Claudia Sangalli, Enrico Cassano
Publikováno v:
Healthcare, Vol 11, Iss 4, p 511 (2023)
The aim of this study was to evaluate the diagnostic performance of contrast-enhanced spectral mammography (CESM) in predicting breast lesion malignancy due to microcalcifications compared to lesions that present with other radiological findings. Thr
Externí odkaz:
https://doaj.org/article/a30b64586dc840dfb449bc9594e7c780
Autor:
Luca Nicosia, Anna Carla Bozzini, Daniela Ballerini, Simone Palma, Filippo Pesapane, Sara Raimondi, Aurora Gaeta, Federica Bellerba, Daniela Origgi, Paolo De Marco, Giuseppe Castiglione Minischetti, Claudia Sangalli, Lorenza Meneghetti, Giuseppe Curigliano, Enrico Cassano
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 23, p 15322 (2022)
We aimed to investigate the association between the radiomic features of contrast-enhanced spectral mammography (CESM) images and a specific receptor pattern of breast neoplasms. In this single-center retrospective study, we selected patients with ne
Externí odkaz:
https://doaj.org/article/97a1f25bebd942d18beed0a02e0b5c4c
Autor:
Filippo Pesapane, Chiara Trentin, Marta Montesano, Federica Ferrari, Luca Nicosia, Anna Rotili, Silvia Penco, Mariagiorgia Farina, Irene Marinucci, Francesca Abbate, Lorenza Meneghetti, Anna Bozzini, Antuono Latronico, Alessandro Liguori, Giuseppe Carrafiello, Enrico Cassano
Publikováno v:
Clinical and Experimental Obstetrics & Gynecology, Vol 49, Iss 11, p 237 (2022)
Objective: During the last decades, advances in computing power, structured data, and algorithm development, developed a technology based on Artificial intelligence (AI) which is currently applied in medicine. Nowadays, the main use of AI in breast i
Externí odkaz:
https://doaj.org/article/81a74519da9e4b06b49f0a48e96eb1e9
Autor:
Cassano, Anna Rotili, Filippo Pesapane, Giulia Signorelli, Silvia Penco, Luca Nicosia, Anna Bozzini, Lorenza Meneghetti, Cristina Zanzottera, Sara Mannucci, Bernardo Bonanni, Enrico
Publikováno v:
Diagnostics; Volume 13; Issue 12; Pages: 1996
Purpose: This study aimed to investigate the use of contrast-free magnetic resonance imaging (MRI) as an innovative screening method for detecting breast cancer in high-risk asymptomatic women. Specifically, the researchers evaluated the diagnostic p
Autor:
Luca Nicosia, Anna Carla Bozzini, Simone Palma, Filippo Pesapane, Lorenza Meneghetti, Maria Pizzamiglio, Francesca Abbate, Antuono Latronico, Vincenzo Bagnardi, Samuele Frassoni, Claudia Sangalli, Enrico Cassano
Rationale and Objectives: The new version of the Contrast Enhanced Mammography (CEM) Breast imaging Reporting and Data System (BIRADs) encourages investigations of a new enhancement descriptor: “Lesion Conspicuity” (LC). The study aims to assess
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e7dc92175528bddfdccf98f36a44c52
https://hdl.handle.net/10281/407575
https://hdl.handle.net/10281/407575
Autor:
Filippo Pesapane, Anna Rotili, Elena Valconi, Giorgio Maria Agazzi, Marta Montesano, Silvia Penco, Luca Nicosia, Anna Bozzini, Lorenza Meneghetti, Antuono Latronico, Maria Pizzamiglio, Eleonora Rossero, Aurora Gaeta, Sara Raimondi, Silvia Francesca Maria Pizzoli, Roberto Grasso, Gianpaolo Carrafiello, Gabriella Pravettoni, Enrico Cassano
Publikováno v:
The British journal of radiology.
Objective: Although breast cancer screening can benefit from Artificial Intelligence (AI), it is still unknown whether, to which extent or under which conditions, the use of AI is going to be accepted by the general population. The aim of our study i