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For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample<jats:italic>t<\/jats:italic>-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (<jats:italic>P\u00a0<\/jats:italic>&lt;\u00a00.05). The cortical D, D<jats:sup>*<\/jats:sup>, and<jats:italic>f<\/jats:italic>values and medullary D and R2<jats:sup>*<\/jats:sup>values had significant differences between the AH and GA groups (<jats:italic>P\u00a0<\/jats:italic>&lt;\u00a00.05). Combining the cortical D and<jats:italic>f<\/jats:italic>values and medullary R2* value gave the best diagnostic efficacy, yielding an AUC, sensitivity, and specificity of 0.967\u2009\u00b1\u20090.022, 91.67%, and 95.83%, respectively.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>A\u00a0multiparametric MR analysis plays an important role in the evaluation of renal dysfunction in hyperuricemia from multiple perspectives. It could be a promising method for noninvasive detection and identification of the early-stage renal damage induced by hyperuricemia.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12880-021-00675-4","type":"journal-article","created":{"date-parts":[[2021,9,28]],"date-time":"2021-09-28T09:03:37Z","timestamp":1632819817000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Multiparametric MRI analysis for the evaluation of renal function in patients with hyperuricemia: a preliminary study"],"prefix":"10.1186","volume":"21","author":[{"given":"You-Zhen","family":"Feng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang-Nan","family":"Dong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qi-Ting","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping-Kang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao-Qing","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"SiTu","family":"DingKun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Qian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhong-Yuan","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang-Ran","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,9,28]]},"reference":[{"key":"675_CR1","doi-asserted-by":"publisher","first-page":"318","DOI":"10.1016\/S0140-6736(09)60883-7","volume":"375","author":"P Richette","year":"2010","unstructured":"Richette P, Bardin T, Gout. 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