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Compressed sensing (CS) with AI-based reconstruction (CSAI) reduces acquisition times whilst preserving image quality. Although CSAI has been established in various clinical applications, its performance in inner ear imaging remains unclear. This study assesses CSAI-optimized T2-DRIVE sequences at different resolutions and acquisition times for visualizing inner ear structures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In 30\u00a0healthy participants, CS T2-DRIVE was acquired at isotropic resolutions of 0.65, 0.5, and 0.4\u202fmm. 0.5 and 0.4\u202fmm datasets were also reconstructed using a\u00a0commercially available AI-based reconstruction algorithm. Three raters independently assessed the imaging quality of anatomical landmarks (cochlea, semicircular canals, vestibulocochlear nerve), artifacts, and signal-to-noise ratio (SNR) using a\u00a05-point Likert scale. Each rater re-rated a\u00a0subset of images after \u2265\u202f4\u00a0weeks. Inter- and intra-rater reliability were calculated using quadratically weighted Cohen\u2019s kappa, and differences between sequences were analyzed using cumulative link mixed models (CLMM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      0.4\u202fmm isotropic imaging exhibited lower SNR compared to CSAI 0.5\u202fmm, regardless of reconstruction algorithm (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&lt;\u20090.001). Across all raters, CSAI T2 at 0.5\u202fmm resolution significantly improved delineation of the cochlea and vestibulocochlear nerve compared to 0.65\u202fmm imaging (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&lt;\u20090.001), while assessability of semicircular canals was reduced (\n                      <jats:italic>p<\/jats:italic>\n                      \u202f=\u20090.082). Acquisition times increased with higher resolutions (0.65\/0.5\/0.4\u202fmm: 4:02\/4:25\/4:34\u202fmin).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>AI-driven reconstruction algorithms enable statistically significant improvements in imaging of key inner-ear structures with minimal increases in scan time at 0.5\u202fmm resolution.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00062-026-01716-7","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T04:56:20Z","timestamp":1788756980000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI-Assisted Compressed Sensing for Optimized Inner Ear Imaging: a\u00a0Multi-Rater MRI Evaluation of CSAI T2-DRIVE"],"prefix":"10.1007","author":[{"given":"Enrike","family":"Rosenkranz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"K\u00f6hler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nora M.","family":"Weiss","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6644-5342","authenticated-orcid":false,"given":"Martin","family":"Renz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Leukert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kilian","family":"Weiss","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barbara","family":"Wollenberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dennis M.","family":"Hedderich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan S.","family":"Kirschke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5392-2074","authenticated-orcid":false,"given":"Wilhelm","family":"Wimmer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5997-203X","authenticated-orcid":false,"given":"Jannis","family":"Bodden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,7]]},"reference":[{"issue":"4","key":"1716_CR1","doi-asserted-by":"publisher","DOI":"10.1148\/rg.220102","volume":"43","author":"SB Hiremath","year":"2023","unstructured":"Hiremath\u00a0SB, Biswas\u00a0A, Mndebele\u00a0G, Schramm\u00a0D, Ertl-Wagner\u00a0BB, et\u00a0al. 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Barbara Wollenberg has received research funding from Novartis, AstraZeneca, MSD, BioNTech, Casseliamed, and Repha Pharma; has given lectures for MSD, Regeneron, and BMS; serves as an advisor for MSD, Regeneron, and BMS; and holds patents, including EU No. 24 222 958.1. Jan S. Kirschke has received a lecture honorarium from Novartis in 2023 and is a shareholder and co-founder of Bonescreen. Wilhelm Wimmer is a member of the audiological scientific advisory board of MED-EL and has received grants from MED-EL and COCHLEAR outside the submitted work. The other authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}