Percorrer por autor "Cuocolo, Renato"
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- ESR Essentials: using the right scoring system in prostate MRI-practice recommendations by ESURPublication . Ponsiglione, Andrea; Brembilla, Giorgio; Cuocolo, Renato; Gutierrez, Patricia; Moreira, Ana Sofia; Pecoraro, Martina; Zawaideh, Jeries; Barentsz, Jelle; Giganti, Francesco; Padhani, Anwar R; Panebianco, Valeria; Puech, Philippe; Villeirs, GeertMRI has gained prominence in the diagnostic workup of prostate cancer (PCa) patients, with the Prostate Imaging Reporting and Data System (PI-RADS) being widely used for cancer detection. Beyond PI-RADS, other MRI-based scoring tools have emerged to address broader aspects within the PCa domain. However, the multitude of available MRI-based grading systems has led to inconsistencies in their application within clinical workflows. The Prostate Cancer Radiological Estimation of Change in Sequential Evaluation (PRECISE) assesses the likelihood of clinically significant radiological changes of PCa during active surveillance, and the Prostate Imaging for Local Recurrence Reporting (PI-RR) scoring system evaluates the risk of local recurrence after whole-gland therapies with curative intent. Underlying any system is the requirement to assess image quality using the Prostate Imaging Quality Scoring System (PI-QUAL). This article offers practicing radiologists a comprehensive overview of currently available scoring systems with clinical evidence supporting their use for managing PCa patients to enhance consistency in interpretation and facilitate effective communication with referring clinicians. KEY POINTS: Assessing image quality is essential for all prostate MRI interpretations and the PI-QUAL score represents the standardized tool for this purpose. Current urological clinical guidelines for prostate cancer diagnosis and localization recommend adhering to the PI-RADS recommendations. The PRECISE and PI-RR scoring systems can be used for assessing radiological changes of prostate cancer during active surveillance and the likelihood of local recurrence after radical treatments respectively.
- Multinational attitudes toward AI in Health Care and diagnostics among Hospital patients.Publication . Busch, Felix; Hoffmann, Lena; Xu, Lina; Zhang, Long Jiang; Hu, Bin; García-Juárez, Ignacio; Toapanta-Yanchapaxi, Liz; Gorelik, Natalia; Gorelik, Valérie; Rodriguez-Granillo, Gaston; Ferrarotti, Carlos; Cuong, Nguyen; Thi, Chau; Tuncel, Murat; Kaya, Gürsan; Solis-Barquero, Sergio; Mendez Avila, Maria; Ivanova, Nevena; Kitamura, Felipe; Hayama, Karina; Puntunet Bates, Monserrat; Torres, Pedro Iturralde; Ortiz-Prado, Esteban; Izquierdo-Condoy, Juan; Schwarz, Gilbert; Hofstaetter, Jochen; Hide, Michihiro; Takeda, Konagi; Peric, Barbara; Pilko, Gašper; Thulesius, Hans; Lindow, Thomas; Kolawole, Israel; Olatoke, Samuel Adegboyega; Grzybowski, Andrzej; Corlateanu, Alexandru; Iaconi, Oana-Simina; Li, Ting; Domitrz, Izabela; Kepczynska, Katarzyna; Mihalcin, Matúš; Fašaneková, Lenka; Zatonski, Tomasz; Fulek, Katarzyna; Molnár, András; Maihoub, Stefani; da Silva Gama, Zenewton; Saba, Luca; Sountoulides, Petros; Makowski, Marcus; Aerts, Hugo; Adams, Lisa; Bressem, Keno; Navarro, Álvaro Aceña; Águas, Catarina; Aineseder, Martina; Alomar, Muaed; Al Sliman, Rashid; Anand, Gautam; Angkurawaranon, Salita; Aoki, Shuhei; Arkoh, Samuel; Ashraf, Gizem; Astri, Yesi; Bakhshi, Sameer; Bayramov, Nuru; Billis, Antonis; Bitencourt, Almir; Bolejko, Anetta; Bollas Becerra, Antonio; Bwambale, Joe; Capela, Andreia; Cau, Riccardo; Chacon-Acevedo, Kelly; Chaunzwa, Tafadzwa; Chojniak, Rubens; Clements, Warren; Cuocolo, Renato; Dahlblom, Victor; Sousa, Kelienny de Meneses; Villarrubia, Jorge Esteban; Desai, Vijay; Dhakal, Ajaya; Dignum, Virginia; Andrade, Rubens G. Feijo; Ferraioli, Giovanna; Ganguly, Shuvadeep; Garg, Harshit; Savevska, Cvetanka Gjerakaroska; Radovikj, Marija Gjerakaroska; Gkartzoni, Anastasia; Gorospe, Luis; Griffin, Ian; Hadamitzky, Martin; Ndahiro, Martin Hakorimana; Hering, Alessa; Hochhegger, Bruno; Huseynova, Mehriban; Ishida, Fujimaro; Jha, Nisha; Jiang, Lili; Kader, Rawen; Kavnoudias, Helen; Klein, Clément; Kolostoumpis, George; Koshy, Abraham; Kruger, NicholaS; Löser, Alexander; Lucijanic, Marko; Mantziari, Despoina; Margue, Gaelle; McFadden, Sonyia; Miyake, Masahiro; Morakote, Wipawee; Ngabonziza, Issa; Nguyen, Thao; Niehues, Stefan; Nortje, Marc; Palaian, Subish; Pentara, Natalia; Poma, Gianluigi; Almeida, Rui; Purwoko, Mitayani; Pyrgidis, Nikolaos; Rafailidis, Vasileios; Rainey, Clare; Ribeiro, João; Agudelo, Nicolás Rozo; Sado, Keina; Saidman, Julia; Saturno-Hernandez, Pedro; Suryadevara, Vidyani; Schulz, Gerald; Soric, Ena; Soto-Pérez-Olivares, Javier; Stanzione, Arnaldo; Struck, Julian Peter; Takaoka, Hiroyuki; Tanioka, Satoru; Huyen, Tran; Truhn, Daniel; van Dijk, Elon; van Wijngaarden, Peter; Wang, Yuan-Cheng; Weidlich, Matthias; Zhang, ShuhangThe successful implementation of artificial intelligence (AI) in health care depends on its acceptance by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes. OBJECTIVES To survey hospital patients to investigate their trust, concerns, and preferences toward the use of AI in health care and diagnostics and to assess the sociodemographic factors associated with patient attitudes. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study developed and implemented an anonymous quantitative survey between February 1 and November 1, 2023, using a nonprobability sample at 74 hospitals in 43 countries. Participants included hospital patients 18 years of age or older who agreed with voluntary participation in the survey presented in 1 of 26 languages. EXPOSURE Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations. MAIN OUTCOMES AND MEASURES The primary outcome was participant responses to a 26-item instrument containing a general data section (8 items) and 3 dimensions (trust in AI, AI and diagnosis, preferences and concerns toward AI) with 6 items each. Subgroup analyses used cumulative link mixed and binary mixed-effects models.