{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T20:52:14Z","timestamp":1781643134856,"version":"3.54.5"},"reference-count":12,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cancer Imaging"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Outcomes for patients with multiple myeloma have improved substantially over the past two decades, with median overall survival more than doubling in many cohorts. Management of smouldering myeloma has also shifted, with randomised trials demonstrating that early intervention in high-risk disease delays progression and improves survival compared with observation alone. Imaging diagnostics must therefore evolve in parallel to provide minimally invasive, sensitive and quantitative insights into disease for patients who will live with myeloma for many years. Here we review the latest evidence for WB-MRI in myeloma, outline current guideline recommendations, and consider future directions.<\/jats:p>","DOI":"10.1186\/s40644-026-01017-9","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T06:36:11Z","timestamp":1773210971000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Precision medicine in myeloma demands precision imaging: is whole body MRI the solution?"],"prefix":"10.1186","volume":"26","author":[{"given":"Christina","family":"Messiou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Kaiser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"issue":"12","key":"1017_CR1","doi-asserted-by":"publisher","first-page":"e538","DOI":"10.1016\/S1470-2045(14)70442-5","volume":"15","author":"V Rajkumar","year":"2014","unstructured":"Rajkumar V, Dimopoulos M, Palumbo A, et al. International myeloma working group updated criteria for the diagnosis of multiple myeloma. Lancet Oncol. Nov; 2014;15(12):e538\u201348. Epub 2014 Oct 26.","journal-title":"Lancet Oncol"},{"issue":"1","key":"1017_CR2","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1148\/radiol.2019181949","volume":"291","author":"c Messiou","year":"2019","unstructured":"Messiou c, Hillengass J, Delorme S, et al. Guidelines for acquisition, interpretation, and reporting of whole-body MRI in Myeloma: myeloma response assessment and diagnosis system (MY-RADS). Radiology. 2019;291(1):5\u201313. https:\/\/doi.org\/10.1148\/radiol.2019181949. Epub 2019 Feb 26.PMID: 30806604.","journal-title":"Radiology"},{"key":"1017_CR3","doi-asserted-by":"publisher","first-page":"e302","DOI":"10.1016\/S1470-2045(19)30309-2","volume":"20","author":"J Hillengass","year":"2019","unstructured":"Hillengass J, Usmani S, Rajkumar SV, Durie BGM, Mateos M-V, Lonial S, et al. International myeloma working group consensus recommendations on imaging in monoclonal plasma cell disorders. Lancet Oncol. 2019;20:e302\u201312. https:\/\/doi.org\/10.1016\/S1470-2045(19)30309-2.","journal-title":"Lancet Oncol"},{"key":"1017_CR4","unstructured":"Overview | Myeloma: diagnosis and management | Guidance | NICE."},{"issue":"1160","key":"1017_CR5","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1093\/bjr\/tqae110","volume":"97","author":"S Quinn","year":"2024","unstructured":"Quinn S, Goh V, Westerland, et al. National myeloma patient survey shows continuing inappropriate imaging and geographical inequalities. BJR. 2024;97(1160):1443\u20139. https:\/\/doi.org\/10.1093\/bjr\/tqae110.","journal-title":"BJR"},{"issue":"9","key":"1017_CR6","doi-asserted-by":"publisher","first-page":"1815","DOI":"10.1007\/s00256-024-04723-2","volume":"53","author":"F Lecouvet","year":"2024","unstructured":"Lecouvet F, Chabot C, Taihi L, et al. Present and future of whole-body MRI in metastatic disease and myeloma: how and why you will do it. Skeletal Radiol. 2024;53(9):1815\u201331. https:\/\/doi.org\/10.1007\/s00256-024-04723-2. Epub 2024 Jul 15.","journal-title":"Skeletal Radiol"},{"key":"1017_CR7","doi-asserted-by":"publisher","unstructured":"Latifoltojar A, Boyd K, Riddell A, et al. Characterising spatial heterogeneity of multiple myeloma in high resolution by whole body magnetic resonance imaging: towards macro-phenotype driven patient management. Magn Reson Imaging 2021 Jan:75:60\u20134. https:\/\/doi.org\/10.1016\/j.mri.2020.10.005. Epub 2020 Oct 16.","DOI":"10.1016\/j.mri.2020.10.005"},{"issue":"17","key":"1017_CR8","doi-asserted-by":"publisher","first-page":"5859","DOI":"10.1002\/cam4.4136","volume":"10","author":"A Belotti","year":"2021","unstructured":"Belotti A, Ribolla R, Cancelli V, et al. Predictive role of diffusion-weighted whole-body MRI (DW-MRI) imaging response according to MY-RADS criteria after autologous stem cell transplantation in patients with multiple myeloma and combined evaluation with MRD assessment by flow cytometry. Cancer Med. 2021;10(17):5859\u201365. https:\/\/doi.org\/10.1002\/cam4.4136. Epub 2021 Jul 15.","journal-title":"Cancer Med"},{"issue":"1","key":"1017_CR9","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1038\/s41408-025-01327-4","volume":"15","author":"C Messiou","year":"2025","unstructured":"Messiou C, Porta N, Koh DM, et al. Whole body MRI by MY-RADS for imaging response assessment in multiple myeloma. Blood Cancer J. 2025;15(1):122. https:\/\/doi.org\/10.1038\/s41408-025-01327-4.","journal-title":"Blood Cancer J"},{"issue":"1172","key":"1017_CR10","doi-asserted-by":"publisher","first-page":"1236","DOI":"10.1093\/bjr\/tqaf089","volume":"98","author":"S Keaveney","year":"2025","unstructured":"Keaveney S, McHugh D, Rata M, et al. An open-source repository-based tool for quality control of imaging protocol compliance: demonstration in a multicentre MRI study. Br J Radiol. 2025;98(1172):1236\u201344. https:\/\/doi.org\/10.1093\/bjr\/tqaf089.","journal-title":"Br J Radiol"},{"issue":"5","key":"1017_CR11","doi-asserted-by":"publisher","first-page":"e200279","DOI":"10.1148\/ryai.2021200279","volume":"3","author":"K Zormpas-Petridis","year":"2021","unstructured":"Zormpas-Petridis K, Tunariu N, Curcean A, et al. Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning-based Denoising Image Filters. Radiol Artif Intell. 2021;3(5):e200279. https:\/\/doi.org\/10.1148\/ryai.2021200279. eCollection 2021 Sep.","journal-title":"Radiol Artif Intell"},{"key":"1017_CR12","doi-asserted-by":"publisher","unstructured":"Candito A, Holbrey R, Ribeiro A, et al. AI-driven software for automated quantification of skeletal metastases and treatment response evaluation using whole-body diffusion-weighted MRI (WB-DWI) in advanced prostate cancer. Phys Med Biol. 2025;70(22). https:\/\/doi.org\/10.1088\/1361-6560\/ae19c5.","DOI":"10.1088\/1361-6560\/ae19c5"}],"container-title":["Cancer Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-026-01017-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s40644-026-01017-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s40644-026-01017-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T19:59:16Z","timestamp":1781639956000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s40644-026-01017-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,11]]},"references-count":12,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["1017"],"URL":"https:\/\/doi.org\/10.1186\/s40644-026-01017-9","relation":{},"ISSN":["1470-7330"],"issn-type":[{"value":"1470-7330","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,11]]},"assertion":[{"value":"11 March 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Christina Messiou: None. Martin Kaiser: AbbVie: Consultancy, Honoraria. Adaptive: Consultancy, Honoraria. BMS\/Celgene: Consultancy, Honoraria, Research Support, Travel Support. Johnson and Johnson: Consultancy, Honoraria, Travel Support. GSK: Consultancy, Honoraria. Karyopharm: Consultancy. Kite: Consultancy. Pfizer: Consultancy. Poolbeg: Consultancy. Regeneron: Consultancy. Roche: Consultancy. Sanofi: Consultancy, Honoraria. Takeda: Consultancy, Honoraria, Travel Support.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"37"}}