{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T20:33:14Z","timestamp":1784665994731,"version":"3.55.0"},"reference-count":38,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Stroke"],"published-print":{"date-parts":[[2025,7]]},"abstract":"<jats:sec>\n            <jats:title>BACKGROUND:<\/jats:title>\n            <jats:p>Deep learning\u2013based synthetic super-resolution magnetic resonance imaging (SynthMRI) may improve the quantitative lesion performance of portable low\u2013field strength magnetic resonance imaging (LF-MRI). The aim of this study is to evaluate whether SynthMRI improves the diagnostic performance of LF-MRI in assessing ischemic lesions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>METHODS:<\/jats:title>\n            <jats:p>We retrospectively included 178 stroke patients and 104 healthy controls with both LF-MRI and high\u2013field strength magnetic resonance imaging (HF-MRI) examinations. Using HF-MRI as the ground truth, the deep learning\u2013based super-resolution framework (SCUNet [Swin-Conv-UNet]) was pretrained using large-scale open-source data sets to generate SynthMRI images from LF-MRI images. Participants were split into a training set (64.2%) to fine-tune the pretrained SCUNet, and a testing set (35.8%) to evaluate the performance of SynthMRI. Sensitivity and specificity of LF-MRI and SynthMRI were assessed. Agreement with HF-MRI for Alberta Stroke Program Early CT Score in the anterior and posterior circulation (diffusion-weighted imaging\u2013Alberta Stroke Program Early CT Score and diffusion-weighted imaging\u2013posterior circulation Alberta Stroke Program Early CT Score) was evaluated using intraclass correlation coefficients (ICCs). Agreement with HF-MRI for lesion volume and mean apparent diffusion coefficient (ADC) within lesions was assessed using both ICCs and Pearson correlation coefficients.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>RESULTS:<\/jats:title>\n            <jats:p>\n              SynthMRI demonstrated significantly higher sensitivity and specificity than LF-MRI (89.0% [83.3%\u201394.6%] versus 77.1% [69.5%\u201384.7%];\n              <jats:italic toggle=\"yes\">P<\/jats:italic>\n              &lt;0.001 and 91.3% [84.7%\u201398.0%] versus 71.0% [60.3%\u201381.7%];\n              <jats:italic toggle=\"yes\">P<\/jats:italic>\n              &lt;0.001, respectively). The ICCs of diffusion-weighted imaging\u2013Alberta Stroke Program Early CT Score between SynthMRI and HF-MRI were also better than that between LF-MRI and HF-MRI (0.952 [0.920\u20130.972] versus 0.797 [0.678\u20130.876],\n              <jats:italic toggle=\"yes\">P<\/jats:italic>\n              &lt;0.001). For lesion volume and mean apparent diffusion coefficient within lesions, SynthMRI showed significantly higher agreement (\n              <jats:italic toggle=\"yes\">P<\/jats:italic>\n              &lt;0.001) with HF-MRI (ICC&gt;0.85,\n              <jats:italic toggle=\"yes\">r<\/jats:italic>\n              &gt;0.78) than LF-MRI (ICC&gt;0.45,\n              <jats:italic toggle=\"yes\">r<\/jats:italic>\n              &gt;0.35). Furthermore, for lesions during various poststroke phases, SynthMRI exhibited significantly higher agreement with HF-MRI than LF-MRI during the early hyperacute and subacute phases.\n            <\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>CONCLUSIONS:<\/jats:title>\n            <jats:p>SynthMRI demonstrates high agreement with HF-MRI in detecting and quantifying ischemic lesions and is better than LF-MRI, particularly for lesions during the early hyperacute and subacute phases.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1161\/strokeaha.124.050540","type":"journal-article","created":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T09:00:21Z","timestamp":1744794021000},"page":"1843-1852","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":4,"title":["Quantitative Ischemic Lesions of Portable Low\u2013Field Strength MRI Using Deep Learning\u2013Based Super-Resolution"],"prefix":"10.1161","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3322-5401","authenticated-orcid":true,"given":"Yueyan","family":"Bian","sequence":"first","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5382-5431","authenticated-orcid":true,"given":"Long","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Research and Development, Subtle Medical, Shanghai, China (L.W., L.X.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0398-6533","authenticated-orcid":true,"given":"Jin","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5078-8180","authenticated-orcid":true,"given":"Xiaoxu","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8860-9990","authenticated-orcid":true,"given":"Erling","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingying","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. Liu, Q.Y.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6618-3511","authenticated-orcid":true,"given":"Yuehong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, China (Y.B., J.L., X.Y., E.W., Y. Li, Y. 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