{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T07:15:07Z","timestamp":1761290107118,"version":"build-2065373602"},"reference-count":37,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T00:00:00Z","timestamp":1759795200000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Clinical Transplantation"],"published-print":{"date-parts":[[2025,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Living kidney donation is a crucial option for addressing the global organ shortage and providing kidney transplantation for patients suffering from end\u2010stage kidney disease. Ensuring donor safety necessitates a comprehensive preoperative assessment of kidney anatomy and function. This study evaluates the relationship between kidney volumes derived from deep learning\u2010based MRI volumetry, intraoperative kidney volume measurements, split renal function measured by renal scintigraphy, and post\u2010donation eGFR. Deep learning\u2010based MRI volumetry is hypothesized to be a reliable method with good correlation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective study analyzed 178 living kidney donors. Deep learning MRI volumetry\u2010based kidney volumes were compared with intraoperative volumes of the explanted donor kidneys obtained using the water displacement method. Additionally, MRI\u2010based volume ratios were compared with scintigraphy\u2010based split renal function ratios to determine their ability to predict the kidney with poorer renal function and post\u2010donation eGFR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Deep learning\u2010based MRI volumetry strongly correlated with intraoperatively measured kidney volumes (Pearson's correlation;\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.7671;\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.0001), confirming its precision in volume estimation. Although MRI\u2010based kidney volume ratios demonstrated only a moderate correlation with scintigraphy\u2010based split renal function ratios (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.4798), MRI volumetry correlated with 1\u2010year post\u2010donation eGFR. It tended to be better than renal scintigraphy (\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.6829 versus\n                      <jats:italic>r<\/jats:italic>\n                      \u00a0=\u00a00.6191).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Deep learning\u2010based MRI volumetry is a reliable, non\u2010invasive tool for estimating kidney volumes in living donors, offering a radiation\u2010free alternative for preoperative assessment. While it differs from renal scintigraphy in evaluating split renal function ratios, its correlation with post\u2010donation eGFR tends to be better, supporting its potential role in living kidney donor assessment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ctr.70338","type":"journal-article","created":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T00:17:13Z","timestamp":1759882633000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning\u2010Based MRI Volumetry for Living Kidney Donor Assessment: A New Tool for Predicting Post\u2010Donation Renal Function"],"prefix":"10.1111","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7409-0032","authenticated-orcid":false,"given":"Dominik Thomas","family":"Koch","sequence":"first","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix Oliver","family":"Hofmann","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4940-6909","authenticated-orcid":false,"given":"Dimitrios","family":"Trompoukis","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Malte","family":"Schirren","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Severin","family":"Jacobi","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tobias","family":"Seibt","sequence":"additional","affiliation":[{"name":"Transplant Center LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1242-4914","authenticated-orcid":false,"given":"Stephan","family":"Kemmner","sequence":"additional","affiliation":[{"name":"Transplant Center LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maximilian","family":"Scheifele","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthias","family":"Ilmer","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"},{"name":"Division of General Surgery Mayo Clinic  Rochester Minnesota USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernhard","family":"Renz","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jens","family":"Werner","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manfred","family":"Stangl","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markus","family":"Guba","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dionysios","family":"Koliogiannis","sequence":"additional","affiliation":[{"name":"Department of General, Visceral and Transplantation Surgery LMU University Hospital LMU Munich  Munich Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,10,7]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.transproceed.2015.10.058"},{"key":"e_1_2_12_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.294.21.2726"},{"key":"e_1_2_12_4_1","article-title":"A Statistical Prediction Model for Survival After Kidney Transplantation From Deceased Donors","volume":"28","author":"Pan J. 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