{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T04:12:14Z","timestamp":1754107934366,"version":"3.41.2"},"reference-count":32,"publisher":"Oxford University Press (OUP)","issue":"1133","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BJR"],"published-print":{"date-parts":[[2022,5,1]]},"abstract":"<jats:sec><jats:title>Objectives:<\/jats:title><jats:p> To determine the diagnostic ability of cervical mucosa radiomics signature of sagittal T<jats:sub>2<\/jats:sub>WI and T<jats:sub>1<\/jats:sub> contrast-enhanced (CE) imaging in detecting early-stage cervical cancers with negative MRI. <\/jats:p><\/jats:sec><jats:sec><jats:title>Methods:<\/jats:title><jats:p> Preoperative images of postoperative pathology confirmed early-stage cervical cancer patients and normal cervix patients admitted to our hospital between January 2013 and December 2020 were retrospectively reviewed. Patients with cancer signals on T<jats:sub>2<\/jats:sub>WI, T<jats:sub>1<\/jats:sub>CE and DWI were deleted. Regions of interests (ROIs) were delineated on cervical mucosa (from cervical canal to cervical dome) with 5\u2009mm width on sagittal T<jats:sub>2<\/jats:sub>WI and T<jats:sub>1<\/jats:sub>CE. The maximum-relevance and minimumredundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods were used for the calculation of radiomics signature scores. Diagnostic performance was assessed and compared between radiomics prediction models (model 1: T<jats:sub>1<\/jats:sub>CE; model 2: T<jats:sub>2<\/jats:sub>WI; model 3: model one combined with model 2). Differential diagnostic ability of radiomics signature in detecting lymphatic vascular space invasion (LVSI) was further explored. <\/jats:p><\/jats:sec><jats:sec><jats:title>Results:<\/jats:title><jats:p> Diagnostic performance of model three was higher than model 1 and model 2 both in primary (model 3 0.874, model 1 0.857, model 2 0.816) and validation (model 3 0.853, model 1 0.847, model 2 0.634) cohorts. Model 3 showed statistical diagnostic difference compared with model 2 (primary p = 0.008, validation p = 0.000). However, the diagnostic improvement ability of model 3 showed no statistical difference compared with model 1 (primary p = 0.351, validation p = 0.739). Diagnostic efficiency of model 3 in detecting LVSI was not apparent (AUC 0.64). <\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions:<\/jats:title><jats:p> Radiomics analysis of cervical mucosa combining T<jats:sub>1<\/jats:sub>CE and T<jats:sub>2<\/jats:sub>WI is promising for predicting MRI invisible early-stage cervical cancers, however further ability in detecting LVSI was not apparent. <\/jats:p><\/jats:sec><jats:sec><jats:title>Advances in knowledge:<\/jats:title><jats:p> Conventional MRI was originally defined as meaningless in very early-stage cervical cancers. However, whether MRI radiomics analysis of cervical mucosa can detecting tiny changes of invisible early stage cervical cancers has not been researched yet. <\/jats:p><\/jats:sec>","DOI":"10.1259\/bjr.20210986","type":"journal-article","created":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T18:27:53Z","timestamp":1644517673000},"source":"Crossref","is-referenced-by-count":8,"title":["Added value of radiomics analysis in MRI invisible early-stage cervical cancers"],"prefix":"10.1093","volume":"95","author":[{"given":"Qiming","family":"Hu","sequence":"first","affiliation":[{"name":"Department of Obstetrics & Gynecology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinming","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, 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