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Linearity and bias of fat fraction estimates from clinically available Dixon sequences were assessed against a 6-point PDw gradient echo (q-Dixon) sequence measuring the reference standard proton density fat fraction. Lesion fat fraction estimates were cross-compared using the Friedman test. Repeatability in volunteers was evaluated with Bland-Altman plots. Sensitivity of fat fraction estimates using TSE-Dixon sequences to specific absorption rate (SAR) related modifications were evaluated with correlation plots.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Thirty-three patients were recruited for this study. Significant (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05) absolute bias (12.4%) was demonstrated in the T1-weighted (T1w) Dixon measurements against the q-Dixon. Significant differences (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05) between fat fraction estimates provided by the T1w Dixon and PDw Dixon sequences were observed in 13 active and 6 treated lesions. Repeatability coefficients for fat fraction estimates ranged from 5.9 to 9.0% in the pelvic tissues of healthy volunteers. Reduction of slice number with repetition time for SAR had the greatest effect, reaching a maximum difference in fat fraction of 14.7% from the q-Dixon for the T2w-TSE Dixon in bone marrow.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>T1w Dixon methods can detect post-treatment changes but remain confounded by relaxation time biases. While all Dixon methods showed good repeatability, careful choice of SAR-related modifications is critical to maintaining accuracy for PD- and T2-weighted TSE sequences.<\/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>The clinical validity of signal-weighted fat fraction estimates versus proton density fat fraction for characterising metastatic bone lesions has not been fully assessed.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>T1-weighted Dixon sequences in line with whole-body MRI international guidelines demonstrate significant fat fraction bias, particularly in lesions and muscle.<\/jats:italic>\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Fat fraction estimation using T1-weighted Dixon sequences recommended in international guidelines are highly sensitive to relaxation time biases, making underlying physiological changes potentially ambiguous.<\/jats:italic>\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-025-11564-7","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T10:21:56Z","timestamp":1744366916000},"page":"6039-6051","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Influence of imaging method on fat fraction estimation for assessing bone marrow in metastatic prostate cancer"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-4429-2828","authenticated-orcid":false,"given":"Yassine N.","family":"Azma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nada","family":"Boci","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katarzyna","family":"Abramowicz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Russo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew R.","family":"Orton","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Tunariu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dow-Mu","family":"Koh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Geoffrey","family":"Charles-Edwards","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David J.","family":"Collins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica M.","family":"Winfield","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,4,11]]},"reference":[{"key":"11564_CR1","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1016\/j.eururo.2016.05.033","volume":"71","author":"AR Padhani","year":"2017","unstructured":"Padhani AR, Lecouvet FE, Tunariu N et al (2017) METastasis Reporting and Data System for Prostate Cancer: practical guidelines for acquisition, interpretation, and reporting of whole-body magnetic resonance imaging-based evaluations of multiorgan involvement in advanced prostate cancer. 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