{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T09:14:50Z","timestamp":1773047690913,"version":"3.50.1"},"reference-count":39,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T00:00:00Z","timestamp":1725926400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003524","name":"Ministry of Business, Innovation and Employment","doi-asserted-by":"publisher","award":["Catalyst: Strategic Fund"],"award-info":[{"award-number":["Catalyst: Strategic Fund"]}],"id":[{"id":"10.13039\/501100003524","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Anatomy"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Contractions of the uterus play an important role in menstruation and fertility, and contractile dysfunction can lead to chronic diseases such as endometriosis. However, the structure and function of the uterus are difficult to interrogate in humans, and thus animal studies are often employed to understand its function. In rats, anatomical studies of the uterus have typically been based on histological assessment, have been limited to small segments of the uterine structure, and have been time\u2010consuming to reconstruct at the organ scale. This study used micro\u2010computed tomography imaging to visualise the muscle structures in the entire non\u2010pregnant rat uterus and assess its use for 3D virtual histology. An assessment of the rodent uterus is presented to (i) quantify muscle thickness variations along the horns, (ii) identify predominant fibre orientations of the muscles and (iii) demonstrate how the anatomy of the uterus can be mapped to 3D volumetric meshes via virtual histology. Micro\u2010computed tomography measurements were validated against measurements from histological sections. The average thickness of the myometrium was found to be 0.33\u2009\u00b1\u20090.11\u2009mm and 0.31\u2009\u00b1\u20090.09\u2009mm in the left and right horns, respectively. The micro\u2010computed tomography and histology thickness calculations were found to correlate strongly at different locations in the uterus: at the cervix, <jats:italic>r<\/jats:italic>\u2009=\u20090.87, and along the horn from the cervical end to the ovarian end, respectively, <jats:italic>r<\/jats:italic>\u2009=\u20090.77, <jats:italic>r<\/jats:italic>\u2009=\u20090.89 and <jats:italic>r<\/jats:italic>\u2009=\u20090.54, with <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001 in every location. This study shows that micro\u2010computed tomography can be used to quantify the musculature in the whole non\u2010pregnant uterus and can be used for 3D virtual histology.<\/jats:p>","DOI":"10.1111\/joa.14131","type":"journal-article","created":{"date-parts":[[2024,9,10]],"date-time":"2024-09-10T10:09:26Z","timestamp":1725962966000},"page":"134-147","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Three\u2010dimensional virtual histology of the rat uterus musculature using micro\u2010computed tomography"],"prefix":"10.1111","volume":"246","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2703-6284","authenticated-orcid":false,"given":"Mathias W.","family":"Roesler","sequence":"first","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amy S.","family":"Garrett","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark L.","family":"Trew","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dane","family":"Gerneke","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Satya","family":"Amirapu","sequence":"additional","affiliation":[{"name":"Department of Pathology, Dunedin School of Medicine University of Otago  Dunedin New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leo K.","family":"Cheng","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5908-2862","authenticated-orcid":false,"given":"Alys R.","family":"Clark","sequence":"additional","affiliation":[{"name":"Auckland Bioengineering Institute University of Auckland  Auckland New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2024,9,10]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/S40738\u2010020\u201000074\u20103"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/HROPEN\/HOAC009"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1083\/JCB.36.3.639"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/3\u2010540\u201031272\u20102_2\/COVER"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/wsbm.1353"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1111\/JOA.13587"},{"key":"e_1_2_10_8_1","first-page":"320","volume-title":"Templates for the solution of algebraic eigenvalue problems: a practical guide","author":"Dongarra J.","year":"2000"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1371\/JOURNAL.PONE.0170597"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.823819"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.semcdb.2007.05.004"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.3389\/fphys.2022.1017649"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010024\u201057734\u20103"},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2012.6346859"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1113\/JPHYSIOL.1959.SP006304"},{"key":"e_1_2_10_16_1","volume-title":"Digital image processing","author":"J\u00e4hne B.","year":"2005"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1569\u20102590(00)08009\u20105"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1038\/S41596\u2010020\u20100313\u20109"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010020\u201065299\u20100"},{"key":"e_1_2_10_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1472\u20106483(12)60108\u20104"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1152\/ajpregu.00187.2015"},{"key":"e_1_2_10_22_1","doi-asserted-by":"publisher","DOI":"10.1113\/JP275688"},{"key":"e_1_2_10_23_1","doi-asserted-by":"publisher","DOI":"10.1371\/JOURNAL.PONE.0173404"},{"key":"e_1_2_10_24_1","doi-asserted-by":"publisher","DOI":"10.1111\/APHA.13607"},{"key":"e_1_2_10_25_1","doi-asserted-by":"publisher","DOI":"10.1007\/S10735\u2010013\u20109485\u20108\/FIGURES\/3"},{"key":"e_1_2_10_26_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010018\u201019773\u20105"},{"key":"e_1_2_10_27_1","first-page":"478","volume-title":"Deep learning for multi\u2010task medical image segmentation in multiple modalities. 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