Cozzi, Andrea
Di Leo, Giovanni
Houssami, Nehmat
Gilbert, Fiona J.
Helbich, Thomas H.
Álvarez Benito, Marina
Balleyguier, Corinne
Bazzocchi, Massimo
Bult, Peter
Calabrese, Massimo
Camps Herrero, Julia
Cartia, Francesco
Cassano, Enrico
Clauser, Paola
de Lima Docema, Marcos F.
Depretto, Catherine
Dominelli, Valeria
Forrai, Gábor
Girometti, Rossano
Harms, Steven E.
Hilborne, Sarah
Ienzi, Raffaele
Lobbes, Marc B. I.
Losio, Claudio
Mann, Ritse M.
Montemezzi, Stefania
Obdeijn, Inge-Marie
Ozcan, Umit A.
Pediconi, Federica
Pinker, Katja
Preibsch, Heike
Raya Povedano, José L.
Rossi Saccarelli, Carolina
Sacchetto, Daniela
Scaperrotta, Gianfranco P.
Schlooz, Margrethe
Szabó, Botond K.
Taylor, Donna B.
Ulus, Özden S.
Van Goethem, Mireille
Veltman, Jeroen
Weigel, Stefanie
Wenkel, Evelyn
Zuiani, Chiara
Sardanelli, Francesco http://orcid.org/0000-0001-6545-9427
Funding for this research was provided by:
Bayer
Università degli Studi di Milano
Article History
Received: 24 September 2022
Revised: 19 January 2023
Accepted: 22 February 2023
First Online: 3 May 2023
Declarations
:
: The scientific guarantor of this publication is Prof. Francesco Sardanelli, MD.
: Outside the present work, the authors declare the following relation with companies and institutions:Francesco Sardanelli received research grants from — and is a member of the speakers’ bureau of — General Electric Healthcare, Bayer, and Bracco; he is also member of the Bracco Advisory Group.Nehmat Houssami receives research funding via a National Breast Cancer Foundation (NBCF Australia) Breast Cancer Research Leadership Fellowship.Fiona J. Gilbert received research grants from General Electric Healthcare, GSK, and Hologic, and had research collaborations with Volpara and Bayer. She is an NIHR senior investigator and receives funding from the Cambridge BRC.Marc B. I. Lobbes received research grants and is member of the speakers’ bureau of GE Healthcare.Katja Pinker declares funding by the NIH/NCI Cancer Centre Support Grant P30 CA008748, Digital Hybrid Breast PET/MRI for Enhanced Diagnosis of Breast Cancer (HYPMED), H2020—Research and Innovation Framework Programme PHC-11-2015 # 667211-2, A Body Scan for Cancer Detection using Quantum Technology (CANCERSCAN), H2020-FETOPEN-2018-2019-2020-01 # 828978, Multiparametric 18F-Fluoroestradiol PET/MRI coupled with Radiomics Analysis and Machine Learning for Prediction and Assessment of Response to Neoadjuvant Endocrine Therapy in Patients with Hormone Receptor+/HER2− Invasive Breast Cancer 02.09.2019/31.08.2020 # Nr: 18207, Jubiläumsfonds of the Austrian National Bank.Paola Clauser and Katja Pinker are part of the Scientific Editorial Board of European Radiology, and Rossano Girometti is Deputy Editor of European Radiology. As such, none of them had any role in handling this manuscript and none of them took part in the decision processes.All other authors declare that they have no conflict of interest related to the present work, and that they have nothing to disclose.
: The first three authors (A.C., G.D.L, N.H.) have significant statistical expertise.
: Written informed consent was obtained from all patients in this study, unless waived by local Ethics Committees.
: This study was approved by the Ethics Committee of the coordinating centre on January 29, 2013 (Comitato Etico Ospedale San Raffaele, Milano, Italy; protocol number 2784), and thereafter by local Ethics Committees of participating centres.
: Two study subgroups (patients who underwent MRI with preoperative intent and patients who did not undergo MRI, for a total of 5204 patients) were already included in the main paper of the MIPA study results (Sardanelli et al, European Radiology 2022; ExternalRef removed) and are used in this paper in a comparative analysis with patients from two other subgroups that are first reported here (patients who underwent screening MRI and patients who underwent diagnostic/problem-solving MRI).
: • Prospective• Observational• Multicentre study