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However, GBCA administration entails periprocedural effort and environmental impact, prompting exploration of contrast-agent-free approaches. Deep learning-based virtual DCE (vDCE) offers a potential solution. This study evaluated vDCE against multiparametric DCE protocols, focusing on BI-RADS, background parenchymal enhancement (BPE), and lesion size.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>This IRB-approved retrospective study included 592 3\u2009T examinations divided into training, validation, and test sets. A 2D U-Net generated vDCE series from unenhanced T1-weighted, T2-weighted, and diffusion-weighted acquisitions. Two board-certified radiologists evaluated vDCE and DCE examinations using a BI-RADS-adapted reading protocol. Diagnostic and ordinal outcomes were compared using McNemar and Wilcoxon signed-rank tests with Bonferroni correction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Mean BI-RADS-based diagnostic accuracy was 76% for vDCE and 77% for DCE. Mean sensitivity was 92% vs 96%, and mean specificity was 65% vs 64%, respectively, without significant differences (both readers,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.0). The mean paired lesion-size difference (DCE minus vDCE) was \u22122.2\u2009mm in the holdout test set and 0.5\u2009mm in the secondary test set. BPE (R1\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.0; R2\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.0) and artefact ratings (R1\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.0; R2\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20091.0) did not differ significantly. Reader confidence was high for both protocols, although lower for vDCE for one reader (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.072).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>vDCE showed four-percentage-point lower mean sensitivity and small, cohort-dependent lesion-size biases relative to GBCA-enhanced imaging. Further research is warranted to determine its potential role as a contrast-agent-free approach for selected breast imaging indications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Breast MRI relies on GBCAs, creating procedural and environmental burdens, while clinically validated contrast-agent-free approaches for BI-RADS-based assessment remain unavailable<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Virtual DCE MRI showed lower sensitivity than standard DCE, no significant difference in BPE, but more variable reader confidence and lesion size presentation<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Virtual DCE breast MRI currently demonstrates limited diagnostic performance and requires further optimisation, while additional clinical validation studies are needed to determine its potential as a non-contrast alternative<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-026-12953-2","type":"journal-article","created":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T12:08:55Z","timestamp":1792238935000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Influence of virtual dynamic contrast enhanced breast MRI on lesion size, BI-RADS scores and reader confidence"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8450-3021","authenticated-orcid":false,"given":"Andrzej","family":"Liebert","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hannes","family":"Schreiter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenz A.","family":"Kapsner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica","family":"Eberle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chris M.","family":"Ehring","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominique","family":"Hadler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sabine","family":"Ohlmeyer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frederik B.","family":"Laun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramona","family":"Erber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julius","family":"Emons","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Uder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evelyn","family":"Wenkel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sebastian","family":"Bickelhaupt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,17]]},"reference":[{"key":"12953_CR1","doi-asserted-by":"publisher","first-page":"520","DOI":"10.1148\/radiol.2019182947","volume":"292","author":"RM Mann","year":"2019","unstructured":"Mann RM, Cho N, Moy L (2019) Breast MRI: state of the art. 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N Engl J Med 381:2091\u20132102. https:\/\/doi.org\/10.1056\/NEJMoa1903986","journal-title":"N Engl J Med"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-026-12953-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-026-12953-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-026-12953-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T22:02:45Z","timestamp":1792274565000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-026-12953-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,17]]},"references-count":45,"alternative-id":["12953"],"URL":"https:\/\/doi.org\/10.1007\/s00330-026-12953-2","relation":{},"ISSN":["1432-1084"],"issn-type":[{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,17]]},"assertion":[{"value":"21 May 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 October 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The scientific guarantor of this publication is Andrzej Liebert.","order":1,"name":"Ethics","label":"Guarantor","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"S.B., A.L., and H. S. have a patent pending EPO No. 21197259.1 on methods associated with the topic of this article.","order":2,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Two of the authors (A.L. and L.A.K.) have significant statistical expertise.","order":3,"name":"Ethics","label":"Statistics and biometry","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The study protocol was approved by the ethics committee of the Friedrich-Alexander Universit\u00e4t Erlangen-N\u00fcrnberg, waiving the need for informed consent.","order":4,"name":"Ethics","label":"Informed consent","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Institutional Review Board approval was obtained from the ethics committee of Friedrich-Alexander Universit\u00e4t Erlangen.","order":5,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"All study subjects or cohorts have been previously reported in: Kapsner LA et al [\n                      \n                      ];\n                      \n                      . Liebert A et al (2024) Smart forecasting of artefacts in contrast-enhanced breast MRI before contrast agent administration. Eur Radiol 34:4752\u20134763\n                      \n                      . Kapsner LA et al (2022) Automated artefact detection in abbreviated dynamic contrast-enhanced (dce) MRI-derived maximum intensity projections (MIP) of the breast. Eur Radiol (in press)\n                      \n                      . Liebert A et al [\n                      \n                      ]\n                      \n                      . Some study subjects or cohorts have been previously reported in: Schreiter H et al [\n                      \n                      ]\n                      \n                      .","order":6,"name":"Ethics","label":"Study subjects or cohorts overlap","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"order":7,"name":"Ethics","label":"Methodology","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}}]}}