{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T05:20:50Z","timestamp":1789017650070,"version":"build-2803163510"},"reference-count":39,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T00:00:00Z","timestamp":1694044800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2024,6]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Accurate identification of high\u2010risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Retrospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Subjects<\/jats:title><jats:p>Totally, 180 patients (79 HRMM and 101 standard\u2010risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and\/or p53 mutations was considered to indicate HRMM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>3.<jats:styled-content style=\"fixed-case\">0\u2009T<\/jats:styled-content>\/diffusion\u2010weighted whole\u2010body imaging with background body signal suppression (<jats:styled-content style=\"fixed-case\">DWIBS<\/jats:styled-content>), modified Dixon chemical\u2010shift imaging Quant (<jats:styled-content style=\"fixed-case\">mDIXON<\/jats:styled-content> Quant), and short <jats:styled-content style=\"fixed-case\">TI<\/jats:styled-content> inversion recovery (<jats:styled-content style=\"fixed-case\">STIR<\/jats:styled-content>).<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Qualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, \u03b22\u2010microglobulin, and bone marrow plasma cells (BMPCs) were also included.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Univariate and multivariate analyses, receiver operating characteristic (ROC) curve. <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05 was considered statistically significant.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The high\u2010risk group had significantly higher ADC and T2* and lower FF compared with the standard\u2010risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR)\u2009=\u20091.019, 95% CI 1.004\u20131.033), while FF was a significant independent protective factor associated with HRMM (OR\u2009=\u20090.972, 95% CI 0.946\u20130.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>Compared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Level of Evidence<\/jats:title><jats:p>3<\/jats:p><\/jats:sec><jats:sec><jats:title>Technical Efficacy<\/jats:title><jats:p>Stage 2<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.28962","type":"journal-article","created":{"date-parts":[[2023,9,7]],"date-time":"2023-09-07T12:45:42Z","timestamp":1694090742000},"page":"2035-2045","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Quantitative Analysis of Whole\u2010Body <scp>MRI<\/scp> for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma"],"prefix":"10.1002","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6884-247X","authenticated-orcid":false,"given":"Mengtian","family":"Sun","sequence":"first","affiliation":[{"name":"Department of 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