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Circulating tumor cells (CTCs) have considered to be promising liquid biopsy in cancer due to the intact information of whole cells and the potential to reflect micrometastasis. However, CTCs research are extremely limited in ovarian cancer, probably due to their rarity. The predictive value of CTCs and circulating tumor microemboli (CTM) in metastasis remains to be elucidated in ovarian cancer. This study tried to identify CTCs/CTM in ovarian cancer with considerably positive rate. To preliminarily identify the invasive capacity of CTCs/CTM, the epithelial-mesenchymal transition (EMT) patterns of CTCs/CTM was evaluated. Moreover, for comprehensive understanding of invasiveness of disseminated cells in ovarian cancer, EMT pattern of exfoliated tumor cells in ascites were also confirmed in this study.Peripheral blood samples and ascites samples were collected from 22 ovarian cancer patients. The Microfiltration combined with morphological analysis was used to detect CTC single cells or cell clusters. Microfiltration combined with morphological analysis was applied in the CTC isolation and identification. EMT was evaluated by immunofluorescence via markers including vimentin and cytokeratin.Microfiltration combined with morphological analysis was introduced to detect CTCs/CTM with a positivity rate of 40.9% in ovarian cancer patients. The number of CTC varied from 1 to 8, with CTM number from 4 to 30. CTCs/CTM of all samples have experienced EMT process. Vimentin was expressed in all CTC samples and all tumor cells in ascites, while cytokeratin was expressed in 44.4% (4/9) of CTC samples. There were no significant differences of the clinical parameters between the CTC-positive and CTC-negative patients.This study showed that both CTCs/CTM and detached tumor cells in ascites might have undergone complete or partial EMT in ovarian cancer. Moreover, microfiltration combined with cytomorphological analysis showed a considerable CTC detection rate.

Objective: This study aimed to investigate the optimal depth of vulvar intraepithelial neoplasia (VIN) and involved skin appendages to provide evidence for treatment. Methods: The study retrospectively enrolled and analyzed the clinical characteristics of all VINs in the obstetrics and gynecology department of a university hospital from January 1, 2019, to December 30, 2021. The study further explored the thickness of epithelium and skin appendages of 285 women with low-grade VIN (VIN 1) and 285 women with high-grade VIN (VIN 2/3). Results: The study included 1,474 VINs: 1,139 (80%) VIN 1 and 335 (20%) VIN 2/3 cases. The VIN 1 and VIN 2/3 groups showed a significant difference in HPV infection (PConclusions: VIN thickness was generally ≤1 mm for the superficial lesions in non-hairy areas. Lesions extending onto hairy areas were about 3 mm, destroying involved skin appendages.

The value of extended high-risk human papillomavirus (hrHPV) genotyping for cervical cancer screening in women with low-grade squamous intraepithelial lesion (L-SIL) cytology has been recognized, but few studies have investigated this.Women with L-SIL Papanicolaou results who underwent human papillomavirus (HPV) genotyping between October 2017 and October 2021 at the Obstetrics and Gynecology Hospital of Fudan University were identified. Their HPV results were correlated with immediate histopathologic follow-up findings.In total, 8726 women who had L-SIL cytology and extended HPV genotyping results were analyzed. The overall hrHPV-positive rate was 84% in women with L-SIL, and the most prevalent hrHPV genotypes were type 52 (HPV52) (20.7%), HPV53 (15.7%), and HPV16 (14.3%). Single and multiple coinfections of hrHPV genotypes were detected in 57.2% and 42.8% of women with positive hrHPV results, respectively. Cervical intraepithelial neoplasia grade ≥2 (CIN2+) was identified in 8.5% of hrHPV-positive women. The CIN2+ detection rate in women who had multiple hrHPV infections (9.9%) was significantly higher than the rate in those who had infection with a single HPV type (7.2%). The top 5 CIN2+-associated HPV infections were HPV16 (25.2%), HPV82 (17.8%), HPV33 (16.3%), HPV31 (14.6%), and HPV26 (13.8%). For the composite group with HPV types HPV16, HPV26, HPV82, HPV31, HPV18, HPV33, HPV58, HPV35, HPV52, and HPV51, the risk of CIN2+ was 11.5% and represented 97.1% of all CIN2+ in biopsied, hrHPV-positive patients. The composite group of 8 remaining HPV genotypes (HPV39, HPV45, HPV53, HPV56, HPV59, HPV66, HPV68, and HPV73) was identified in 29.7% of hrHPV-positive patients, and the risk of CIN2+ for this composite group was similar to the risk of CIN2+ in hrHPV-negative patients.This large retrospective study in a predominantly unvaccinated cohort demonstrated that extended hrHPV genotyping improves genotype-specific risk stratification in women with L-SIL.

Although carbon dioxide laser vaporization is frequently used for treating vaginal intraepithelial neoplasia (VaIN), the optimal depth of epithelial destruction with laser vaporization requires elucidation. We aimed to evaluate VaIN depth and better illustrate epithelial destruction during laser vaporization.We included 246 women diagnosed with VaIN (low-grade VaIN [VaIN 1], 123 women; high-grade VaIN [VaIN 2/3], 123 women) using colposcopy-directed biopsy at our hospital from January 1, 2019, to April 30, 2020. The thickness of the noninvolved epithelium, if available, was determined. All available data, including cytology and histological information, were recorded. The t test and Pearson χ 2 test were used for statistical analysis. Statistical significance was set at p.05.The involved epithelial thicknesses in VaIN 2/3 and VaIN 1 were 0.41 ± 0.21 and 0.40 ± 0.19 mm, respectively, which were both greater than their noninvolved epithelial thickness values (0.17 ± 0.10 and 0.17 ± 0.08 mm, p.01 and p.01, respectively). In subgroup comparisons between the VaIN 2/3 and VaIN 1 groups, the involved epithelial thickness did not differ between premenopausal patients, postmenopausal women receiving estrogen, and postmenopausal women who did not receive estrogen ( p.05). In the VaIN 2/3 group, the lesion thickness in premenopausal was greater than that in postmenopausal women receiving estrogen ( p = .016) and those who were not receiving estrogen ( p = .017).The thickness of VaIN is generally less than 1 mm for women of all ages, except in rare cases of visible lesions with papillary hyperplasia.

Lu Zhang, Qing Wang, Hongwei Zhang, Yu Xie, Long Sui, Qing Cong Medical Center of Diagnosis and Treatment for Cervical Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People’s Republic of ChinaCorrespondence: Qing Cong; Long SuiMedical Center of Diagnosis and Treatment for Cervical Diseases, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People’s Republic of ChinaTel +86 15900798278; +86 13801788118Fax +86 21 33189900Email 151468770@qq.com; suilong@fudan.edu.cnPurpose: To examine the screening history of vaginal intraepithelial neoplasia (VaIN) and vaginal cancer.Patients and Methods: We included women with histologically confirmed VaIN or vaginal cancer by colposcopy-directed biopsy between 1 January 2019 and 31 December 2019. The results of cytology, hrHPV, colposcopic examination and history of hysterectomy were retrospectively analysed.Results: A total of 26,432 colposcopies were performed during the study period, among which 2131 women (1835 [86.1%] with VaIN 1; 268 [12.6%] with VaIN 2/3; and 28 [1.3%] with vaginal cancer) were retrospectively studied. hrHPV test positivity was significantly higher than that of cytology for VaIN 1 (84.4% vs 67.3%; P < 0.001) and VaIN 2/3 (92.0% vs 79.9%; P < 0.001) but not for vaginal cancer (84.6% vs 78.6%; P = 0.73). Additionally, the concordance rates for colposcopic impression were 79.5%, 54.5%, and 92.8% for VaIN1, VaIN2/3, and vaginal cancer, respectively. All 372 patients had a history of hysterectomy, and 81.0% (282/348) of indications were related to cervical precancer and cancer. Although cytology test positivity was significantly higher in patients with hysterectomy than in patients without hysterectomy (76.2% vs 67.5%; P < 0.001), cytology combined with hrHPV can help to detect more than 95% of VaIN and vaginal cancer cases in both groups (96.2% for patients with hysterectomy and 96.5% for patients without hysterectomy).Conclusion: VaIN and vaginal cancer are not rare diseases. Although cytology was sensitive (67.5%– 76.2%) for detecting vaginal lesions regardless of hysterectomy, cytology combined with hrHPV improves detection accuracy up to 95% in both groups.Keywords: cytology, human papilloma virus, colposcopy, vaginal intraepithelial neoplasia, vaginal cancer

Yanyun Li,1,&ast; Ying-Xin Gong,1,&ast; Qing Wang,1 Shujun Gao,1 Hongwei Zhang,1 Feng Xie,1 Qing Cong,1 Limei Chen,1 Qi Zhou,1 Zubei Hong,2 Lihua Qiu,2 Fang Li,3 Yu Xie,1 Long Sui1 1Department of Gynecology and Obstetrics, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, People’s Republic of China; 2Department of Gynecology and Obstetrics, Renji Hospital of Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 3Department of Gynecology and Obstetrics, Shanghai Dongfang Hospital of Tongji University, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Long Sui; Yu XieObstetrics and Gynecology Hospital of Fudan University, 419 Fangxie Road, Shanghai, 200011, People’s Republic of ChinaTel +86-21-33189900Fax +86-21-63450900Email suilong@fudan.edu.cn; yuxie18@fudan.edu.cnPurpose: Early-stage cervical cancer is usually diagnosed by colposcopy-directed biopsy (CDB) and/or endocervical curettage (ECC), but some neglected lesions must be detected by conization because they are occult. This study aimed to explore the optimal method for detecting these “occult” cervical cancers.Patients and Methods: A total of 1299 patients who were high-risk for early-stage cervical cancer from five centres in China were prospectively included. We evaluated the diagnostic performance of cytology, HPV testing, colposcopy and CDB&ECC for detecting “occult” cervical cancer and discussed the diagnostic importance of transformation zone (TZ) type, conization length and the proportion of cervical cone excision.Results: The diagnostic agreement between colposcopy impression and conization was 64.5% and 72.4% between CDB&ECC and conization. Forty-two patients were finally diagnosed with pathologic cancer, and the sensitivities of cytology, colposcopy, CDB&ECC were 4.8%, 7.1%, and 47.4%, respectively. Twenty cases were neglected by CDB&ECC but further diagnosed as cancer by conization, considered to be occult cervical cancer, accounting for 1.6%. Cytologic high-grade squamous intraepithelial lesion (HSIL)+, positive HPV, biopsy HSIL+ and cervical TZ type 3 were considered risk factors for developing HSIL+, while colposcopy impression HSIL+ was not. There was a significant difference between cancerous and HSIL patients in the proportion of cervical cone excision (P< 0.001), which was recognized as a risk factor (P< 0.001) for detecting cancer, while the length of cervical cone excision was not. The average proportion was 0.62, and the minimal effective proportion was 0.56.Conclusion: Since the incidence of occult cervical cancer neglected by CDB&ECC, colposcopy and cytology was far beyond expectations, conization is necessary, especially in patients with TZ type 3, high-grade cytology and biopsy results. As the cervical length varies in patients, the proportion of cervical cone excision might be a better indicator for detecting occult cervical cancer.Keywords: cervical conization, colposcopy-directed biopsy, high-grade intraepithelial lesion, length proportion, occult cervical cancer, transformation zone

AIM To assess the performance of the apparent diffusion coefficient (ADC) and relative ADC (rADC) to differentiate benign from malignant breast lesions using the plateau pattern of the time–intensity curve (Type II TIC), including the impact of lesions-enhancement subtypes and menopausal status of patients. MATERIALS AND METHODS Between September 2016 and December 2019, 408 patients with 169 benign and 239 malignant lesions with Type II TIC underwent magnetic resonance imaging (MRI), including diffusion-weighted imaging, with b-values of 50 and 800 s/mm2. ADC and rADC values were calculated by placing regions of interest (ROIs) on the lesion, the parenchyma of the normal breast, and the pectoralis major muscle. A receiver operating characteristic (ROC) curve was generated to compare the diagnostic performance of each parameter in distinguishing between benign and malignant breast lesions. Further classification was undertaken to study the discriminatory performance of each parameter in the different lesions enhancement subtypes (mass-like enhancement [MLE] and non-MLE [NMLE]) and menopausal status of patients (pre-menopausal and post-menopausal). RESULTS There was a significant difference in the ADC and rADC values between benign and malignant lesions. The sensitivities of lesion ADC, gland rADC, and muscle rADC were 79.29%, 77.51%, and 79.29%, respectively, with specificities of 94.56%, 82.01%, and 94.98%, respectively. The area under the ROC curve (AUC) of muscle rADC was the highest (AUC=0.92), especially in the MLE subtype (AUC=0.96), and was not affected by the menopausal status. CONCLUSION Muscle rADC and lesion ADC assessment improved the diagnostic performance of breast MRI in distinguishing between benign and malignant breast lesions with Type II TIC, especially muscle rADC in the MLE subtype.

To systematically investigate the effect of imaging features at different DCE-MRI phases to optimise a radiomics model based on DCE-MRI for the prediction of tumour-infiltrating lymphocyte (TIL) levels in breast cancer. This study retrospectively collected 133 patients with pathologically proven breast cancer, including 73 patients with low TIL levels and 60 patients with high TIL levels. The volumes of breast cancer lesions were manually delineated on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and each phase of DCE-MRI, followed by 6250 quantitative feature extractions. The least absolute shrinkage and selection operator (LASSO) method was used to select predictive feature sets for the classifiers. Four models were developed for predicting TILs: (1) single enhanced phase radiomics models; (2) fusion enhanced multi-phase radiomics models; (3) fusion multi-sequence radiomics models; and (4) a combined radiomics-based clinical model. Image features extracted from the delayed phase MRI, especially DCE_Phase 6 (DCE_P6), demonstrated dominant predictive performances over features from other phases. The fusion multi-sequence radiomics model and combined radiomics-based clinical model achieved the highest predictive performances with areas under the curve (AUCs) of 0.934 and 0.950, respectively; however, the differences were not statistically significant. The DCE-MRI radiomics model, especially image features extracted from the delayed phases, can help improve the performance in predicting TILs. The radiomics nomogram is effective in predicting TILs in breast cancer. • Radiomics features extracted from DCE-MRI, especially delayed phase images, help predict TIL levels in breast cancer. • We developed a nomogram based on MRI to predict TILs in breast cancer that achieved the highest AUC of 0.950.

ObjectivesTriple-negative breast cancer (TNBC) is a heterogeneous disease, and different histological subtypes of TNBC have different clinicopathological features and prognoses. Therefore, this study aimed to establish a nomogram model to predict the histological heterogeneity of TNBC: including Metaplastic Carcinoma (MC) and Non-Metaplastic Carcinoma (NMC).MethodsWe evaluated 117 patients who had pathologically confirmed TNBC between November 2016 and December 2020 and collected preoperative multiparameter MRI and clinicopathological data. The patients were randomly assigned to a training set and a validation set at a ratio of 3:1. Based on logistic regression analysis, we established a nomogram model to predict the histopathological subtype of TNBC. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve. According to the follow-up information, disease-free survival (DFS) survival curve was estimated using the Kaplan-Meier product-limit method.ResultsOf the 117 TNBC patients, 29 patients had TNBC-MC (age range, 29–65 years; median age, 48.0 years), and 88 had TNBC-NMC (age range, 28–88 years; median age, 44.5 years). Multivariate logistic regression analysis demonstrated that lesion type (p = 0.001) and internal enhancement pattern (p = 0.001) were significantly predictive of TNBC subtypes in the training set. The nomogram incorporating these variables showed excellent discrimination power with an AUC of 0.849 (95% CI: 0.750−0.949) in the training set and 0.819 (95% CI: 0.693−0.946) in the validation set. Up to the cutoff date for this analysis, a total of 66 patients were enrolled in the prognostic analysis. Six of 14 TNBC-MC patients experienced recurrence, while 7 of 52 TNBC-NMC patients experienced recurrence. The DFS of the two subtypes was significantly different (p=0.035).ConclusionsIn conclusion, we developed a nomogram consisting of lesion type and internal enhancement pattern, which showed good discrimination ability in predicting TNBC-MC and TNBC-NMC.

Objectives. To evaluate the value of the whole volume apparent diffusion coefficient (ADC) histogram in distinguishing between benign and malignant breast lesions and differentiating different molecular subtypes of breast cancers and to assess the correlation between ADC histogram parameters and Ki-67 expression in breast cancers. Methods. The institutional review board approved this retrospective study. Between September 2016 and February 2019, 189 patients with 84 benign lesions and 105 breast cancers underwent magnetic resonance imaging (MRI). Volumetric ADC histograms were created by placing regions of interest (ROIs) on the whole lesion. The relationships between the ADC parameters and Ki-67 were analysed using Spearman’s correlation analysis. Results. Of the 189 breast lesions included, there were significant differences in patient age ( P < 0.001 ) and lesion size ( P = 0.006 ) between the benign and malignant lesions. The results also demonstrated significant differences in all ADC histogram parameters between benign and malignant lesions (all P < 0.001 ). The median and mean ADC histogram parameters performed better than the other ADC histogram parameters (AUCs were 0.943 and 0.930, respectively). The receiver operating characteristic (ROC) analysis revealed that the 10th percentile ADC value and entropy could determine the human epidermal growth factor receptor 2 (HER-2) status (both P = 0.001 ) and estrogen receptor (ER)/progesterone receptor (PR) status ( P = 0.020 and P = 0.041 , respectively). Among all breast cancer lesions, 35 tumours in the low-proliferation group ( Ki − 67 < 14 % ) and 70 tumours in the high-proliferation group ( Ki − 67 ≥ 14 ) were analysed with ROC curves and correlation analyses. The ROC analysis revealed that entropy and skewness could determine the Ki-67 status ( P = 0.007 and P < 0.001 , respectively), and there were weak correlations between ADC entropy ( r = 0.383 ) and skewness ( r = 0.209 ) and the Ki-67 index. Conclusion. The volumetric ADC histogram could serve as an imaging marker to determine breast lesion characteristics and may be a supplemental method in predicting tumour proliferation in breast cancer.