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      Added value of radiomics analysis in MRI invisible early-stage cervical cancers

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          Abstract

          Objectives:

          To determine the diagnostic ability of cervical mucosa radiomics signature of sagittal T 2WI and T 1 contrast-enhanced (CE) imaging in detecting early-stage cervical cancers with negative MRI.

          Methods:

          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 2WI, T 1CE and DWI were deleted. Regions of interests (ROIs) were delineated on cervical mucosa (from cervical canal to cervical dome) with 5 mm width on sagittal T 2WI and T 1CE. 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 1CE; model 2: T 2WI; model 3: model one combined with model 2). Differential diagnostic ability of radiomics signature in detecting lymphatic vascular space invasion (LVSI) was further explored.

          Results:

          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).

          Conclusions:

          Radiomics analysis of cervical mucosa combining T 1CE and T 2WI is promising for predicting MRI invisible early-stage cervical cancers, however further ability in detecting LVSI was not apparent.

          Advances in knowledge:

          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.

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          Most cited references30

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          Radiomics Strategy for Molecular Subtype Stratification of Lower-Grade Glioma: Detecting IDH and TP53 Mutations Based on Multimodal MRI.

          Noninvasive detection of isocitrate dehydrogenase (IDH) and TP53 mutations are meaningful for molecular stratification of lower-grade gliomas (LrGG).
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            Is Open Access

            Is cervical screening preventing adenocarcinoma and adenosquamous carcinoma of the cervix?

            While the incidence of squamous carcinoma of the cervix has declined in countries with organised screening, adenocarcinoma has become more common. Cervical screening by cytology often fails to prevent adenocarcinoma. Using prospectively recorded cervical screening data in England and Wales, we conducted a population‐based case–control study to examine whether cervical screening leads to early diagnosis and down‐staging of adenocarcinoma. Conditional logistic regression modelling was carried out to provide odds ratios (ORs) and 95% confidence intervals (CIs) on 12,418 women with cervical cancer diagnosed between ages 30 and 69 and 24,453 age‐matched controls. Of women with adenocarcinoma of the cervix, 44.3% were up to date with screening and 14.6% were non‐attenders. The overall OR comparing women up to date with screening with non‐attenders was 0.46 (95% CI: 0.39–0.55) for adenocarcinoma. The odds were significantly decreased (OR: 0.22, 95% CI: 0.15–0.33) in up to date women with Stage 2 or worse adenocarcinoma, but not for women with Stage1A adenocarcinoma 0.71 (95% CI: 0.46–1.09). The odds of Stage 1A adenocarcinoma was double among lapsed attenders (OR: 2.35, 95% CI: 1.52–3.62) compared to non‐attenders. Relative to women with no negative cytology within 7 years of diagnosis, women with Stage1A adenocarcinoma were very unlikely to be detected within 3 years of a negative cytology test (OR: 0.08, 95% CI: 0.05–0.13); however, the odds doubled 3–5 years after a negative test (OR: 2.30, 95% CI: 1.67–3.18). ORs associated with up to date screening were smaller for squamous and adenosquamous cervical carcinoma. Although cytology screening is inefficient at preventing adenocarcinomas, invasive adenocarcinomas are detected earlier than they would be in the absence of screening, substantially preventing Stage 2 and worse adenocarcinomas.
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              MR‐Based Radiomics Nomogram of Cervical Cancer in Prediction of the Lymph‐Vascular Space Invasion preoperatively

              Background Lymph‐vascular space invasion (LVSI) is an unfavorable prognostic factor in cervical cancer. Unfortunately, there are no current clinical tools for the preoperative prediction of LVSI. Purpose To develop and validate an axial T1 contrast‐enhanced (CE) MR‐based radiomics nomogram that incorporated a radiomics signature and some clinical parameters for predicting LVSI of cervical cancer preoperatively. Study Type Retrospective. Population In all, 105 patients were randomly divided into two cohorts at a 2:1 ratio. Field Strength/Sequence T1 CE MRI sequences at 1.5T. Assessment Univariate analysis was performed on the radiomics features and clinical parameters. Multivariate analysis was performed to determine the optimal feature subset. The receiver operating characteristic (ROC) analysis was performed to evaluate the performance of prediction model and radiomics nomogram. Statistical Tests The Mann–Whitney U‐test and the chi‐square test were used to evaluate the performance of clinical characteristics and LVSI status by pathology. The minimum‐redundancy/maximum‐relevance and recursive feature elimination methods were applied to select the features. The radiomics model was constructed using logistic regression. Results Three radiomics features and one clinical characteristic were selected. The radiomics nomogram showed favorable discrimination between LVSI and non‐LVSI groups. The AUC was 0.754 (95% confidence interval [CI], 0.6326–0.8745) in the training cohort and 0.727 (95% CI, 0.5449–0.9097) in the validation cohort. The specificity and sensitivity were 0.756 and 0.828 in the training cohort and 0.773 and 0.692 in the validation cohort. Data Conclusion T1 CE MR‐based radiomics nomogram serves as a noninvasive biomarker in the prediction of LVSI in patients with cervical cancer preoperatively. Level of Evidence: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1420–1426.
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                Author and article information

                Journal
                The British Journal of Radiology
                BJR
                British Institute of Radiology
                0007-1285
                1748-880X
                May 01 2022
                May 01 2022
                : 95
                : 1133
                Affiliations
                [1 ]Department of Obstetrics & Gynecology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
                [2 ]Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China
                [3 ]GE Healthcare, Precision Health Institution, Shanghai, China
                Article
                10.1259/bjr.20210986
                35143254
                8cf261cd-60b7-4182-ab61-ace6ad4ee740
                © 2022
                History

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