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Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441\/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510\/3065 (16.6%) D-MRI, and 114\/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (\n                      <jats:italic>p\u00a0<\/jats:italic>\n                      \u2264\u00a00.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (\n                      <jats:italic>p\u00a0<\/jats:italic>\n                      &lt;\u00a00.001) for S-MRI, 1.0 (\n                      <jats:italic>p\u00a0<\/jats:italic>\n                      =\u00a00.957) for D-MRI, and 1.9 (\n                      <jats:italic>p\u00a0<\/jats:italic>\n                      &lt;\u00a00.001) for P-MRI.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      \u2022\n                      <jats:italic>Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      \u2022\n                      <jats:italic>The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%).<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      \u2022\n                      <jats:italic>The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups.<\/jats:italic>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-023-09600-5","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T13:01:57Z","timestamp":1683118917000},"page":"6213-6225","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Screening and diagnostic breast MRI: how do they impact surgical treatment? 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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\u2019 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\u2014Research 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\u2212 Invasive Breast Cancer 02.09.2019\/31.08.2020 # Nr: 18207, Jubil\u00e4umsfonds 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.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The first three authors (A.C., G.D.L, N.H.) have significant statistical expertise.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was obtained from all patients in this study, unless waived by local Ethics Committees.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"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.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"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;\n                      \n                      ) 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).","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"value":"\u2022 Prospective\u2022 Observational\u2022 Multicentre study","order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}