{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T11:43:31Z","timestamp":1778327011548,"version":"3.51.4"},"reference-count":16,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Med Imaging"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Deep-learning (DL) reconstructions could improve image quality and reduce acquisition time in diffusion-weighted imaging (DWI). This study assessed, qualitatively and quantitatively, DL-DWI in liver metastasis of colorectal cancer patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This prospective study enrolled 50 participants from June to November 2022. Phantom and participant data were acquired on a 1.5T MR scanner using a free-breathing DL-DWI research application sequence. Three DWIs were compared: a moderately-accelerated DL-DWI (DL-1), a corresponding standard reconstruction (Standard-1) and a highly-accelerated DL-DWI (DL-2). Image quality (four features on b750 images and one feature on ADC map) was assessed by two radiologists. Region of interest (ROI) based ADC measurements were performed at three locations: liver, spleen, liver metastasis. Across the three series, median scores and ADC values were assessed using a Friedman non-parametric test and post-hoc analysis (pairwise Wilcoxon tests with Bonferroni correction). A p-value\u2009&lt;\u20090.05 was considered statistically significant.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Fifty participants with metastatic colorectal cancer (mean age 62 years, range 36\u201388 years, 26 males) were evaluated. ROIs were delineated in liver (\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u200950), spleen (\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u200948), and liver metastasis (\n                      <jats:italic>N<\/jats:italic>\n                      \u2009=\u200911). Qualitatively, across both readers, DL-1 method received the highest scores for 5\/8 features on the b750 images; all methods scored similarly on ADC maps for both readers. Quantitatively, ADCs were significantly different between DL-1 and Standard-1 series across all three organs, with DL-1-based ADC always higher (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01). This ADC increase was small: 8.9% (liver), 3.4% (spleen), 4.5% (liver metastasis).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study suggests that a DL-based reconstruction is a promising technique to enable acceleration of liver DWI considering both qualitative and quantitative results.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial registration<\/jats:title>\n                    <jats:p>NCT05118555 (Evaluation of New Magnetic Resonance Techniques); study date of registration (first submitted: 2021-10-18).<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12880-025-02030-3","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T15:30:29Z","timestamp":1764171029000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Qualitative and quantitative assessment of accelerated liver diffusion-weighted imaging using deep-learning reconstruction in oncologic patients"],"prefix":"10.1186","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4999-8038","authenticated-orcid":false,"given":"Mihaela","family":"Rata","sequence":"first","affiliation":[]},{"given":"Francesca","family":"Castagnoli","sequence":"additional","affiliation":[]},{"given":"Joshua","family":"Shur","sequence":"additional","affiliation":[]},{"given":"Emily","family":"Evans","sequence":"additional","affiliation":[]},{"given":"Georgina","family":"Hopkinson","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"Benkert","sequence":"additional","affiliation":[]},{"given":"Elisabeth","family":"Weiland","sequence":"additional","affiliation":[]},{"given":"Dow-Mu","family":"Koh","sequence":"additional","affiliation":[]},{"given":"Jessica M.","family":"Winfield","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,11,26]]},"reference":[{"issue":"3","key":"2030_CR1","doi-asserted-by":"publisher","first-page":"812","DOI":"10.1148\/radiol.2463070432","volume":"246","author":"T Parikh","year":"2008","unstructured":"Parikh T, Drew SJ, Lee VS, et al. 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Verbal informed consent was obtained from each participant. The study was conducted in accordance with the Declaration of Helsinki.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"Employment: TB and EW are employees of Siemens Healthineers AG. The authors have no relevant financial or non-financial interests to disclose.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"491"}}