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However, it is difficult to diagnose a small pituitary adenoma using conventional MR sequence. Deep learning-based reconstruction (DLR) using magnetic resonance imaging (MRI) enables high-resolution thin-section imaging with noise reduction. In the present single-institution retrospective study of 201 patients, conducted between August 2019 and October 2020, we compared the performance of 1\u00a0mm DLR MRI with that of 3\u00a0mm routine MRI, using a combined imaging protocol to detect and delineate pituitary adenoma. Four readers assessed the adenomas in a pairwise fashion, and diagnostic performance and image preferences were compared between inexperienced and experienced readers. The signal-to-noise ratio (SNR) was quantitatively assessed. New detection of adenoma, achieved using 1\u00a0mm DLR MRI, was not visualised using 3\u00a0mm routine MRI (overall: 6.5% [13\/201]). There was no significant difference depending on the experience of the readers in new detections. Readers preferred 1\u00a0mm DLR MRI over 3\u00a0mm routine MRI (overall superiority 56%) to delineate normal pituitary stalk and gland, with inexperienced readers more preferred 1\u00a0mm DLR MRI than experienced readers. The SNR of 1\u00a0mm DLR MRI was 1.25-fold higher than that of the 3\u00a0mm routine MRI. In conclusion, the 1\u00a0mm DLR MRI achieved higher sensitivity in the detection of pituitary adenoma and provided better delineation of normal pituitary gland than 3\u00a0mm routine MRI.<\/jats:p>","DOI":"10.1038\/s41598-021-00558-2","type":"journal-article","created":{"date-parts":[[2021,10,29]],"date-time":"2021-10-29T10:02:46Z","timestamp":1635501766000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Deep learning-based thin-section MRI reconstruction improves tumour detection and delineation in pre- and post-treatment pituitary adenoma"],"prefix":"10.1038","volume":"11","author":[{"given":"Da Hyun","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji Eun","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yeo Kyung","family":"Nam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joonsung","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seonok","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Young-Hoon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ho Sung","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,10,29]]},"reference":[{"key":"558_CR1","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1111\/j.1365-2265.2006.02562.x","volume":"65","author":"FF Casanueva","year":"2006","unstructured":"Casanueva, F. 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