{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T03:40:59Z","timestamp":1790480459646,"version":"4.1.0"},"reference-count":26,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2020,9,23]],"date-time":"2020-09-23T00:00:00Z","timestamp":1600819200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2021,2]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Screening for rapidly progressing autosomal dominant polycystic kidney disease (ADPKD) is necessary for assigning and monitoring therapies. Height\u2010adjusted total kidney volume (ht\u2010TKV) is an accepted biomarker for clinical prognostication, but represents only a small fraction of information on abdominal MRI.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>To investigate the utility of other MR features of ADPKD to predict progression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>Single\u2010center retrospective.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population<\/jats:title><jats:p>Longitudinal data from 186 ADPKD subjects with baseline serum creatinine, PKD gene testing, abdominal MRI measurements, and\u2009\u22652 follow\u2010up serum creatinine were reviewed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>1.5T, <jats:styled-content style=\"fixed-case\">T<jats:sub>2<\/jats:sub><\/jats:styled-content>\u2010weighted single\u2010shot fast spin echo, <jats:styled-content style=\"fixed-case\">T<jats:sub>1<\/jats:sub><\/jats:styled-content>\u2010weighted <jats:styled-content style=\"fixed-case\">3D<\/jats:styled-content> spoiled gradient echo (liver accelerated volume acquisition) and <jats:styled-content style=\"fixed-case\">2D<\/jats:styled-content> cine velocity encoded gradient echo (phase contrast <jats:styled-content style=\"fixed-case\">MRA<\/jats:styled-content>).<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Ht\u2010TKV, renal blood flow (RBF), number and fraction of renal and hepatic cysts, bright T<jats:sub>1<\/jats:sub> hemorrhagic renal cysts, and liver and spleen volumes were independently assessed by three observers blinded to estimated glomerular filtration rate (eGFR) data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Linear mixed\u2010effect models were applied to predict eGFR over time using MRI features at baseline adjusted for confounders. Validation was performed in 158 patients who had follow\u2010up MRI using receiver operator characteristic, sensitivity, and specificity.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Hemorrhagic cysts, fraction of renal and hepatic cysts, height\u2010adjusted liver and spleen volumes were significant independent predictors of future eGFR (final prediction model R<jats:sup>2<\/jats:sup> = 0.88 <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05). The number of hemorrhagic cysts significantly improved the prediction compared to ht\u2010TKV in predicting future eGFR (area under the curve [AUC] = 0.94, 95% confidence interval [CI]: 0.9\u20130.94 vs. R<jats:sup>2<\/jats:sup> = 0.9, 95% CI: 0.85\u20130.9, <jats:italic>P<\/jats:italic> = 0.045). For baseline eGFR \u226560\u2009ml\/min\/1.73m<jats:sup>2<\/jats:sup>, sensitivity for predicting eGFR&lt;45\u2009ml\/min\/1.73m<jats:sup>2<\/jats:sup> by ht\u2010TKV alone was 29%. Sensitivity increased to 72% with all MRI variables in the model (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.05 = 0.019), whereas specificity was unchanged, 100% vs. 99%.<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>Combining multiple MR features including hemorrhagic renal cysts, renal cyst fraction, liver and spleen volume, hepatic cyst fraction, and renal blood flow enhanced sensitivity for predicting eGFR decline in ADPKD compared to the standard model including only ht\u2010TKV.<\/jats:p><jats:p><jats:bold>Level of Evidence<\/jats:bold> 2<\/jats:p><jats:p><jats:bold>Technical Efficacy Stage<\/jats:bold> 2<\/jats:p><jats:p>J. MAGN. RESON. IMAGING 2021;53:564\u2013576.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.27360","type":"journal-article","created":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T03:46:26Z","timestamp":1600919186000},"page":"564-576","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Hemorrhagic Cysts and Other <scp>MR<\/scp> Biomarkers for Predicting Renal Dysfunction Progression in Autosomal Dominant Polycystic Kidney Disease"],"prefix":"10.1002","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7212-223X","authenticated-orcid":false,"given":"Sadjad","family":"Riyahi","sequence":"first","affiliation":[{"name":"Department of Radiology Weill Cornell Medicine  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5341-8350","authenticated-orcid":false,"given":"Hreedi","family":"Dev","sequence":"additional","affiliation":[{"name":"Department of 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