Associations of Single Versus Multiple Human Papillomavirus Infections With the Prevalence of Cervical Intraepithelial Neoplasia 2/3 and Squamous Cell Carcinoma Lesions: Human Papillomavirus Type-Specific Attribution.

The risk of developing cervical squamous lesions in women with multiple high-risk human papillomavirus (hrHPV) infections is uncertain. The aim of this retrospective study was to investigate the type-specific attribution and phylogenetic effects of single and multiple hrHPV subtypes in cervical squamous lesions. All cases with cervical histopathologic diagnosis and human papillomavirus (HPV) genotyping results in the 6 months preceding biopsy from October 2018 to December 2022 were studied and analyzed. Over the study period, 70,361 cases with histopathologic follow-up and prior HPV genotyping were identified. The hrHPV-positive rate was 55.6% (39,104/70,361), including single hrHPV detected in 27,182 (38.6%), 2 types of hrHPV detected in 8158 (11.6%), and 3 types of hrHPV detected in 2486 (3.5%). Among 16,457 cases with a histologically diagnosed squamous lesion (cervical intraepithelial neoplasia 1: 11411; cervical intraepithelial neoplasia 2/3: 4192; squamous cell carcinoma: 854 cases), the prevalence of single hrHPV infection increased, but the rate of multiple concomitant hrHPV infections showed negative association as the degree of squamous lesions increased. Among women with a single HPV16 infection, cervical intraepithelial neoplasia 2/3 and squamous cell carcinoma (CIN2+) diagnostic rate was 30.6%, and it increased to 47.6% when coinfected with HPV33 (P < .001) but significantly decreased when coinfected with all other hrHPV types (P < .05). By comparing CIN2+ diagnostic rates in 40 most common 2 types of hrHPV infections with related single hrHPV infection, CIN2+ rates were decreased in 12 combinations (30.0%), equivalent in 26 combinations (65.0%), and increased in 2 combinations (5.0%). The cases with 3 types of HPV infections reduced the risk for CIN2+ compared with related single HPV infections. HPV16+52+53, HPV16+52+68, HPV16+52+51, HPV16+39+52, and HPV16+58+53 significantly decreased the risk of CIN2+ compared with HPV16 single infection (P < .05). This study demonstrates that multiple hrHPV infections are not associated with cumulatively higher risk for CIN2+ development, suggesting that oncogenic progression of multiple hrHPV-associated cervical squamous lesions is neither synergistic nor a cumulative effect at the phylogenetic level, possibly a way of competitive interference.

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for improving patient care. This study contributes to this development by identifying the viability of the AICyte assistive system for cervical screening, and investigating the utility of the system in assisting with workflow and diagnostic capability. In this study, a novel scanner was developed using a Ruiqian WSI-2400, trademarked AICyte assistive system, to create an AI-generated gallery of the most diagnostically relevant images, objects of interest (OOI), and provide categorical assessment, according to Bethesda category, for cervical ThinPrep Pap slides. For validation purposes, 2 pathologists reviewed OOIs from 32,451 cases of ThinPrep Paps independently, and their interpretations were correlated with the original ThinPrep interpretations (OTPI). The analysis was focused on the comparison of reporting rates, correlation between cytological results and histologic follow-up findings, and the assessment of independent AICyte screening utility. Pathologists using the AICyte system had a mean reading time of 55.14 seconds for the first 3000 cases trending down to 12.90 seconds in the last 6000 cases. Overall average reading time was 22.23 seconds per case compared with a manual reading time approximation of 180 seconds. Usage of AICyte compared with OTPI had similar sensitivity (97.89% vs 97.89%) and a statistically significant increase in specificity (16.19% vs 6.77%) for the detection of cervical intraepithelial neoplsia 2 and above lesions. When AICyte was run alone at a 50% negative cutoff value, it was able to read slides with a sensitivity of 99.30% and a specificity of 9.87%. When AICyte was run independently at this cutoff value, no sole case of high-grade squamous intraepithelial lesions/squamous cell carcinoma squamous lesion was missed. AICyte can provide a potential tool to help pathologists in both diagnostic capability and efficiency, which remained reliable compared with the baseline standard. Also unique for AICyte is the development of a negative cutoff value for which AICyte can categorize cases as "not needed for review" to triage cases and lower pathologist workload. This is the largest case number study that pathologists reviewed OOI with an AI-assistive system. The study demonstrates that AI-assistive system can be broadly applied for cervical cancer screening.

An Ex Vivo Study of Filum Terminale in Children and Fetuses Based on Optical Coherence Tomography.

Objective: To distinguish ex vivo normal and abnormal filum terminale (FT) in pathology based on optical coherence tomography (OCT). Methods: A total of 14 ex vivo FTs, freshly imaged via OCT after being cut, were excised from the scanned region for histopathological examination (HPE). Qualitative analysis was performed by 2 blinded assessors. Results: We performed OCT imaging of all specimens and validated them qualitatively. In the fetal FTs, we observed large amounts of fibrous tissue scattered throughout with a few capillaries but no adipose tissue. In tight filum terminale syndrome (TFTS), adipose infiltration and capillaries were significantly increased, with obvious fibroplasia and disarrangement. OCT images showed increased adipose tissue in which the adipocytes were arranged in a grid-like pattern; dense, disordered fibrous tissue and vascular-like tissue were present. The diagnostic results of OCT and HPE were consistent (Kappa = 0.659; P = .009, <.01), and there was no statistically significant difference in diagnosing TFTS using a Chi-square test (P > .05). The area under the curve (AUC) for OCT (AUC = 0.966; 95% CI, 0.903 to 1.000) was better than magnetic resonance imaging (MRI) (AUC = 0.649; 95% CI, 0.403 to 0.896). Conclusion: OCT can quickly obtain clear images of FT's inner structure, contribute to diagnosing TFTS and will be an indispensable complement to MRI and HPE. More FT sample studies in vivo are needed to confirm the high accuracy rate of OCT.

Optical Coherence Tomography for Brain Imaging and Developmental Biology.

Optical coherence tomography (OCT) is a promising research tool for brain imaging and developmental biology. Serving as a three-dimensional optical biopsy technique, OCT provides volumetric reconstruction of brain tissues and embryonic structures with micrometer resolution and video rate imaging speed. Functional OCT enables label-free monitoring of hemodynamic and metabolic changes in the brain in vitro and in vivo in animal models. Due to its non-invasiveness nature, OCT enables longitudinal imaging of developing specimens in vivo without potential damage from surgical operation, tissue fixation and processing, and staining with exogenous contrast agents. In this paper, various OCT applications in brain imaging and developmental biology are reviewed, with a particular focus on imaging heart development. In addition, we report findings on the effects of a circadian gene (Clock) and high-fat-diet on heart development in Drosophila melanogaster. These findings contribute to our understanding of the fundamental mechanisms connecting circadian genes and obesity to heart development and cardiac diseases.

Comprehensive overview of genotype distribution and prevalence of human papillomavirus in cervical lesions.

Across cervical squamous and glandular lesions, a spectrum of human papillomavirus (HPV) genotypes has been identified. This review aims to provide a comprehensive summary detailing the distribution and profile of HPV genotypes detected in cervical lesions, leveraging insights from histological and cytological findings. High-risk HPV (HR-HPV) genotypes exhibit varying degrees of oncogenic potential, with HPV16 and HPV18 identified as the most prevalent and oncogenic types. The distribution of HR-HPV genotypes varies among different degrees of the cervical lesions and varies between squamous and glandular neoplasia. HPV16 is predominantly associated with severe lesions (precancers and carcinomas), while HPV18 demonstrates a significantly higher prevalence in endocervical as compared with squamous neoplasia. The distribution of HR-HPV in severe squamous lesions is complex, involving many HR-HPV genotypes in addition to HPV16, while the distribution of HR-HPV genotypes in endocervical glandular lesions is mainly limited in HPV18 and HPV16. Large datasets from China have identified the three most common HR-HPV genotypes in this population as stratified by diagnostic category: HPV52, HPV16, HPV58 in histologically negative cases and cervical intraepithelial neoplasia 1 (CIN1); HPV16, HPV52, HPV58 in CIN2/3; HPV16, HPV58, HPV52 or HPV18 in squamous cell carcinoma (SCC); HPV16, HPV18 and HPV52 in endocervical adenocarcinoma in situ (AIS), invasive adenocarcinoma, as well as mixed squamous and glandular lesions. HPV33 is the fourth most common HPV type in CIN2/3 and SCC, while HPV45 occurs more commonly in AIS and adenocarcinoma, compared with squamous lesions. The prevalence and distribution of multiple HR-HPV coinfections vary across different cervical diseases. The clinical significance and pathogenesis of these multiple HR-HPV infections remain uncertain, although recent two large studies demonstrate that multiple HR-HPV infections are not associated with cumulatively higher risk of high-grade cervical squamous lesion development, suggesting competitive and/or cooperative interactions among HPV genotypes. Extensive HPV genotyping aids in risk assessment and optimising clinical approaches for women with mild abnormalities in Pap cytology. Women with atypical squamous cells of undetermined significance (ASC-US) and low-grade squamous intraepithelial lesion (LSIL) Pap test results and with the infection of some HR-HPV genotypes carry a very low risk of high-grade cervical lesions. HPV genotyping can allow for risk stratification and triage optimisation for these HR-HPV-positive women. Women with atypical glandular cell (AGC) Pap test results showed a specific HPV genotyping pattern and extended HPV genotyping may be helpful for the clinical management of AGCs. Continual advancements in clinical guidelines integrating extended genotyping would increase diagnostic accuracy and refine strategies in clinical management.

The clinical utility of next generation sequencing in endometrial cancer: focusing on molecular subtyping and lynch syndrome.

Objective: To investigate the clinical utility of Next Generation Sequencing (NGS) in molecular typing of endometrial carcinoma and its combined screening for Lynch Syndrome (LS). Methods: 90 patients diagnosed with endometrial carcinoma (EC) and receiving treatment at the Third Affiliated Hospital of Zhengzhou University between March 2022 and December 2023 were included in this study. Molecular typing and germline evaluation for LS were conducted using NGS on the Illumina platform. A retrospective analysis was performed to examine the clinical pathological characteristics, molecular mutation spectrum, and LS screening outcomes among patients with four distinct molecular subtyping categories. Results: Among the 90 cases of EC, 11 cases (12.2%) of POLE mut type, 19 cases (21.1%) of MMRd type, 6 cases (6.7%) of p53 abn type, and 54 cases (60%) of NSMP type were detected, with detailed analysis of their respective molecular characteristics. LS screening identified 9 cases (10%) of pathogenic germline mutations in MMR genes, including 3 cases of MLH1 germline mutations, 2 cases of PMS2, 2 of MSH2, and 2 of MSH6. Of the 9 LS patients, 7 were MMRd type and 2 NSMP type, with 7 cases showing abnormal MMR protein expression. Additionally, 6 cases with germline variants of uncertain significance in MMR genes were detected, including 2 MLH1, 1 MSH6, 2 MSH6, 1 PMS2, and 1 EPCAM. Conclusion: NGS enables precise molecular typing of endometrial carcinoma through the identification of mutations in the POLE, TP53, and MMR genes. Conducting germline mutation testing for MMR genes in all patients with endometrial carcinoma can effectively prevent instances of overlooked LS diagnoses. Nevertheless, the extensive expenses associated with NGS necessitate additional validation and investigation before its clinical implementation can be fully endorsed.

Efficacy and safety of lenvatinib plus pembrolizumab in patients with advanced and recurrent endometrial cancer: a systematic review and meta-analysis.

Background: Various trials have demonstrated the clinical benefits of lenvatinib plus pembrolizumab in patients with advanced or recurrent endometrial cancer, regardless of mismatch repair (MMR) status or histologic subtype. The majority of the previously published trials had small sample sizes. Here, we aimed to assess the reported efficacy and safety profile of lenvatinib plus pembrolizumab in patients with advanced and recurrent endometrial cancer. Methods: We utilized the Cochrane Library, PubMed, Web of Science and Embase databases to identify clinical trials evaluating the efficacy and safety of lenvatinib plus pembrolizumab in patients with advanced and recurrent endometrial cancer. The outcomes analyzed were progression-free survival (PFS), overall survival (OS), the objective response rate (ORR), the disease control rate (DCR) and the incidence of adverse events (AEs). Subgroup analysis was conducted on the basis of MMR status (deficient, dMMR or proficient, pMMR). Results: Four trials (582 patients) were included. The pooled ORR was 32.7% [95% confidence interval (CI): 28.9-36.5]. Subgroup analysis revealed an ORR of 48.1% (95% CI: 26.1-70.2) for dMMR group and 33.1% (95% CI: 25.7-40.6) for pMMR group. The pooled DCR was 74.9% (95% CI: 71.3-78.4%). Subgroup analysis revealed a DCR of 81.0% (95% CI: 64.5-97.6) for the dMMR group and 76.3% (95% CI: 66.3-86.3) for the pMMR group. Follow-up was reported in all included studies. The median range time of PFS and OS was 5.3 months-258 days and 17.2 months-not reached, respectively. Regarding safety, the overall pooled proportions of any-grade AE and AEs ≥ grade 3 were 95.8% (95% CI: 89.5-100.0) and 80.2% (95% CI: 59.9-100.0), respectively. Conclusion: Lenvatinib plus pembrolizumab showed a relevant clinical benefit and significant toxicity in patients with advanced and recurrent endometrial cancer. Further studies encompassing long-term outcomes are warranted. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=522160/, identifier CRD42024522160.

Genotype profile of HPV in ASC-H cytology and histologic follow-up-prevalence, distribution, and risk: A retrospective study of 1414 cases.

BACKGROUND: A cytologic diagnosis of atypical squamous cells, cannot exclude high-grade squamous lesion (ASC-H) poses a disproportionately high risk of cervical cancer development. The objective of this study was to analyze type-specific risks by mapping human papillomavirus (HPV) genotypes in ASC-H cytology. METHODS: In total, 1,048,581 Papanicolaou tests that had ASC-H cytology were retrieved. Concurrent HPV genotyping using proprietary multiplex real-time (MRT) and polymerase chain reaction (PCR) HPV tests and histologic follow-up findings were analyzed. RESULTS: Among 1678 patients who had ASC-H findings (0.16%), 1414 (84.3%) underwent concurrent HPV genotyping (MRT, 857; HPV PCR test, 557). The overall high-risk HPV (hrHPV)-positive rate was 84.4%. Of the 857 MRT cases, 63.9% were infected with a single hrHPV, and 24.4% had multiple genotypes. The most prevalent HPV types were HPV16/52/58/33/31. Lesions that were identified as cervical intraepithelial neoplasia 2 or worse (CIN2+) were detected in 498 of 906 cases (55.0%), including 81 cervical carcinomas (8.9%). The risk of CIN2+ for the composite group of HPV16/52/58/33/31-positive cases was 62.7%, representing 90.7% (264 of 291) of total CIN2+ lesions in ASC-H/hrHPV-positive cases by MRT. CIN2+ lesions were detected in 108 of 142 (76.1%) HPV16-positive and/or HPV18-positive women by the PCR the HPV test. Among 128 hrHPV-negative ASC-H cases by both methods, CIN2+ lesions were identified in 21 of 128 (16.4%), including five cervical carcinomas (3.9%). The sensitivity, specificity, positive predictive value, and negative predictive value for patients in the composite group with HPV16/52/58/33/31 were 88.0%, 40.8%, 62.7%, and 75.0%, respectively. CONCLUSIONS: Papanicolaou tests classified as ASC-H are associated with a high CIN2+ rate and warrant colposcopy, regardless of HPV status. The extent to which the risk-stratification provided by comprehensive HPV genotyping can inform the management of ASC-H cytology remains to be explored.

AICyte-alone capabilities as an independent screener for triaging cervical cytology using a 50% negative cutoff value.

BACKGROUND: AICyte has previously demonstrated a potential role in cervical cytology screening for reducing the workload by using a 50% negative cutoff value. The aim of the current study is to evaluate this hypothesis. METHODS: The authors used the Ruiqian WSI-2400 (with the registered trademark AICyte) to evaluate a collection of 163,848 original cervical cytology cases from 2018 to 2023 that were collected from four different hospital systems in China. A breakdown of cases included 46,060 from Shenzhen, 67,472 from Zhengzhou, 25,667 from Shijiazhuang, and 24,649 from Jinan. These collected cases were evaluated using the AICyte system, and the data collected were statistically compared with the original interpretative results. RESULTS: In 98.80% of all artificial intelligence cases that were designated as not needing further review, the corresponding original diagnosis was also determined to be negative. For any cases that were designated atypical squamous cells, cannot exclude high-grade squamous intraepithelial lesion or higher, the sensitivity and negative predictive value were 90.77% and 98.80%, respectively. The sensitivity and negative predictive value were greater in cases designated as low-grade squamous intraepithelial lesion or higher at 98.92% and 99.94%, respectively. Of the 49 low-grade squamous intraepithelial lesion or higher that were designed by AICyte as not needing further review, the cytohistologic correlation revealed eight cases of cervical intraepithelial neoplasia 1 and 18 negative cases; and the remaining cases were without histologic follow-up. In practice, AICyte used at a 50% negative cutoff value could reduce the anticipated workload if a protocol were implemented to label cases that qualified within the negative cutoff value as not needing further review, thereby finalizing the case as negative for intraepithelial lesions and malignancy. CONCLUSIONS: For pathologic practices that do not have cytotechnologists or in which the workflow is sought to be optimized, the artificial intelligence system AICyte alone to be an independent screening tool by using a 50% negative cutoff value, which is a potential assistive method for cervical cancer screening.

Characteristics and utility of high-resolution optical coherence microscopy images of endocervical canal lesions.

OBJECTIVES: To investigate optical coherence microscopy (OCM) imaging features and the application value of these high-resolution images for identifying endocervical canal lesions (ECLs), which is a clinical dilemma in cervical cancer screening programs. METHODS: In total, 520 OCM images were obtained by scanning the cervical canal lesions with an ultra-high-resolution OCM system (204 specimens from 73 patients). The OCM morphologic characteristics of ECLs were observed and summarized, and then 3 researchers performed a diagnostic test of OCM images of cervical canal lesions. The accuracy, sensitivity, specificity, positive predictive value, negative predictive value, 95% confidence interval of each parameter, and interinvestigator agreement (κ) were calculated. RESULTS: Normal endocervix, cysts, squamous metaplasia, high-grade squamous intraepithelial lesions involving glands, and invasive carcinoma had distinct OCM characteristics, which correlated well with corresponding H&E histologic sections. The accuracy, sensitivity, and specificity of the 3 researchers were 90.6%, 89.3% (95% CI, 86.5%-91.7%) and 91.6% (95% CI, 89.2%-93.5%), respectively. The positive predictive value was 90.1% (95% CI, 87.3%-92.4%), and the negative predictive value was 90.9% (95% CI, 88.5%-92.9%), with almost perfect agreement (κ = 0.874). CONCLUSIONS: The application of the OCM system in cervical canal lesions is feasible and could help improve detection of occult ECLs in cervical cancer screening programs. This study lays the foundation for further research on OCM in cervical canal lesions in vivo, which also has a potential impact on projecting pathologic evaluation beyond what is currently possible, perhaps globally.

AP-2α suppresses invasion in BeWo cells by repression of matrix metalloproteinase-2 and -9 and up-regulation of E-cadherin.

Preeclampsia complicates 5-10% of pregnancies and is a leading cause of maternal/fetal morbidity and mortality. Although the cause is unknown, the reduced migration/invasion of extravillous trophoblasts is generally regarded as a key feature of preeclampsia genesis. The present study examined the expression of activator protein-2α (AP-2α), tissue inhibitor of metalloproteinase 2 (TIMP-2), matrix metalloproteinase-2 (MMP-2), matrix metalloproteinase-9 (MMP-9), and E-cadherin in severe preeclamptic placentas and normal placentas using real-time PCR and immunohistochemistry. The expression levels of AP-2α, TIMP-2, and E-cadherin were elevated, while MMP-2 and MMP-9 levels were decreased in severe preeclamptic placentas when compared with normal placentas. To explore the underlying molecular mechanisms, BeWo cells were transfected with an AP-2α-expression construct as well as a siRNA against AP-2α. The over-expression of AP-2α decreased the invasive abilities of BeWo cells. AP-2α induction was followed by the induction of TIMP-2 and E-cadherin and a significant reduction of MMP-2 and MMP-9. Whereas in AP-2α-silencing BeWo cells, we observed the decreased expression of TIMP-2 and E-cadherin and the increased expression of MMP-2 and MMP-9. We presume that AP-2α may suppress trophoblast invasion by repression of MMP-2 and MMP-9 and up-regulation of E-cadherin, thus leading to shallow placentation in severe preeclampsia.

A real-time computer-aided diagnosis method for hydatidiform mole recognition using deep neural network.

BACKGROUND AND OBJECTIVE: Hydatidiform mole (HM) is one of the most common gestational trophoblastic diseases with malignant potential. Histopathological examination is the primary method for diagnosing HM. However, due to the obscure and confusing pathology features of HM, significant observer variability exists among pathologists, leading to over- and misdiagnosis in clinical practice. Efficient feature extraction can significantly improve the accuracy and speed of the diagnostic process. Deep neural network (DNN) has been proven to have excellent feature extraction and segmentation capabilities, which is widely used in clinical practice for many other diseases. We constructed a deep learning-based CAD method to recognize HM hydrops lesions under the microscopic view in real-time. METHODS: To solve the challenge of lesion segmentation due to difficulties in extracting effective features from HM slide images, we proposed a hydrops lesion recognition module that employs DeepLabv3+ with our novel compound loss function and a stepwise training strategy to achieve great performance in recognizing hydrops lesions at both pixel and lesion level. Meanwhile, a Fourier transform-based image mosaic module and an edge extension module for image sequences were developed to make the recognition model more applicable to the case of moving slides in clinical practice. Such an approach also addresses the situation where the model has poor results for image edge recognition. RESULTS: We evaluated our method using widely adopted DNNs on an HM dataset and chose DeepLabv3+ with our compound loss function as the segmentation model. The comparison experiments show that the edge extension module is able to improve the model performance by at most 3.4% regarding pixel-level IoU and 9.0% regarding lesion-level IoU. As for the final result, our method is able to achieve a pixel-level IoU of 77.0%, a precision of 86.0%, and a lesion-level recall of 86.2% while having a response time of 82 ms per frame. Experiments show that our method is able to display the full microscopic view with accurately labeled HM hydrops lesions following the movement of slides in real-time. CONCLUSIONS: To the best of our knowledge, this is the first method to utilize deep neural networks in HM lesion recognition. This method provides a robust and accurate solution with powerful feature extraction and segmentation capabilities for auxiliary diagnosis of HM.

Nomograms for predicting overall survival and cancer-specific survival in patients with invasive micropapillary carcinoma: Based on the SEER database.

BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer that lacks a prognostic prediction model. Its treatment and prognostic factors remain controversial. Our study aimed to develop nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in IMPC patients. METHODS: A total of 2149 patients confirmed to have IMPC between 2003 and 2018 were selected from the Surveillance, Epidemiology and End Results (SEER) database. They were divided into training and validation cohorts. Univariate and multivariate Cox regression analyses were used to identify significant independent prognostic factors. The nomograms were used to predict 3- and 5-year OS and CSS. The training and validation cohorts were used to verify the nomograms internally and externally. The predictive capability of the nomograms was evaluated by the consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) curve. RESULTS: In the study, 2149 IMPC patients were randomized to a training group (n = 1611) and a validation group (n = 538). Age, T stage, N stage, ER, radiotherapy, and surgery were identified as independent prognostic factors for OS and CSS. These variables were selected to construct nomograms for IMPC. The C-index (0.768 for OS and 0.811 for CSS) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomograms. Additionally, DCA showed that the nomograms had higher clinical value than traditional TNM tumor staging. CONCLUSIONS: The models can accurately predict the prognosis of IMPC patients and can aid in providing individualized treatment for patients.

Study on the application of optical coherence microscopy in Hirschsprung's disease.

To explore the clinical application value of optical coherence microscopy (OCM) in Hirschsprung's disease. 109 HSCR patients were recuited in a Chinese hospital from January 2018 to July 2021. All the recruited patients underwent barium enema angiography preoperatively and the resected diseased intestinal tubes were evaluated intraoperatively. The OCM and the histopathological examination were performed successively on the surgical specimens, and the OCM images were compared with the relevant tissue sections to characterize different lesions. 10 non-HSCR fetal colorectal tissues at the same period were retained for OCM, the characteristics of which with and without HSCR under OCM imaging were analyzed. In the OCM images of in vitro tissue, it can be clearly observed that the scattering degree of HSCR narrow segment mucosal is high, glands and crypt structures are reduced or even atrophy, and the scattering degree of submucosal and intermuscular is low; In the dilated segment, the low scattering and high scattering are complex, and the muscle layer is obviously hypertrophy and structural disorder. Compared with the pathological findings, the OCM sensitivity, Kappa value, and AUC area reached 92.66%, 0.63, and 0.91, respectively. OCM can quickly and clearly display the structure of all layers of colorectal tissue, which is highly consistent with the corresponding histopathological examination results and has high sensitivity. which will provide a more reliable basis for OCM diagnosis of early HSCR, targeted biopsy and location of operative treatment, and has a certain potential for clinical application.

Survival nomogram for endometrial cancer with lung metastasis: A SEER database analysis.

Purpose: The lung is the most common distant metastatic organ in patients with endometrial cancer (EC) but is rarely reported. This study examines the association between clinical characteristics and overall survival (OS) in EC with lung metastasis. Methods: Patients with EC who had accompanying lung metastasis were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2017. Univariate and multivariate Cox regression were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) and assess OS outcomes related to EC with lung metastasis. A Cox proportional hazards nomogram model for OS was constructed and validated. The calibration plot, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the discriminative ability and clinical benefit of the novel nomogram. Kaplan-Meier curves and scatter diagram analysis were used to investigate the risk stratifications of the nomogram. Results: Overall, 1542 EC patients with lung metastasis between 2010 and 2017 were included and randomly divided into training and validation cohorts. A nomogram model was constructed using the clinical characteristics of tumor grade, histological type, surgery, adjuvant chemotherapy, adjuvant radiation, brain metastasis and liver metastasis. The concordance indexes (C-indexes) were 0.750 (95% CI, 0.732-0.767) and 0.743 (95% CI, 0.719-0.767) for the training cohort and validation cohort, respectively. Calibration plots and DCA showed good clinical applicability of the nomogram. The areas under the curves (AUCs) were 0.803 and 0.766 for 1-year and 3-year OS, respectively, indicating that the nomogram model had a stable discriminative ability. An online calculator of our nomogram is available on the internet at https://endometrialcancer.shinyapps.io/DynNomapp/. Additionally, patients in the high-risk group had a significantly worse OS than those in the low-risk group. Conclusion: An easy-to-use, highly accurate nomogram was developed for predicting the prognosis of EC patients with lung metastasis.

Multi-center clinical study using optical coherence tomography for evaluation of cervical lesions in-vivo.

In this prospective study of an in-vivo cervical examination using optical coherence tomography (OCT), we evaluated the diagnostic value of non-invasive and real-time OCT in cervical precancerous lesions and cancer diagnosis, and determined the characteristics of OCT images. 733 patients from 5 Chinese hospitals were inspected with OCT and colposcopy-directed biopsy. The OCT images were compared with the histological sections to find out the characteristics of various categories of lesions. The OCT images were also interpreted by 3 investigators to make a 2-class classification, and the results were compared against the pathological results. Various structures of the cervical tissue were clearly observed in OCT images, which matched well with the corresponding histological sections. The OCT diagnosis results delivered a sensitivity of 87.0% (95% confidence interval, CI 82.2-90.7%), a specificity of 84.1% (95% CI 80.3-87.2%), and an overall accuracy of 85.1%. Both good consistency of OCT images and histological images and satisfactory diagnosis results were provided by OCT. Due to its features of non-invasion, real-time, and accuracy, OCT is valuable for the in-vivo evaluation of cervical lesions and has the potential to be one of the routine cervical diagnosis methods.

Computer-Aided Diagnosis in Histopathological Images of the Endometrium Using a Convolutional Neural Network and Attention Mechanisms.

Uterine cancer (also known as endometrial cancer) can seriously affect the female reproductive system, and histopathological image analysis is the gold standard for diagnosing endometrial cancer. Due to the limited ability to model the complicated relationships between histopathological images and their interpretations, existing computer-aided diagnosis (CAD) approaches using traditional machine learning algorithms often failed to achieve satisfying results. In this study, we develop a CAD approach based on a convolutional neural network (CNN) and attention mechanisms, called HIENet. In the ten-fold cross-validation on ∼3,300 hematoxylin and eosin (H&E) image patches from ∼500 endometrial specimens, HIENet achieved a 76.91 ± 1.17% (mean ± s. d.) accuracy for four classes of endometrial tissue, i.e., normal endometrium, endometrial polyp, endometrial hyperplasia, and endometrial adenocarcinoma. Also, HIENet obtained an area-under-the-curve (AUC) of 0.9579 ± 0.0103 with an 81.04 ± 3.87% sensitivity and 94.78 ± 0.87% specificity in a binary classification task that detected endometrioid adenocarcinoma. Besides, in the external validation on 200 H&E image patches from 50 randomly-selected female patients, HIENet achieved an 84.50% accuracy in the four-class classification task, as well as an AUC of 0.9829 with a 77.97% (95% confidence interval, CI, 65.27%∼87.71%) sensitivity and 100% (95% CI, 97.42%∼100.00%) specificity. The proposed CAD method outperformed three human experts and five CNN-based classifiers regarding overall classification performance. It was also able to provide pathologists better interpretability of diagnoses by highlighting the histopathological correlations of local pixel-level image features to morphological characteristics of endometrial tissue.

Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue.

OBJECTIVE: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge for clinical adoption, however, is the steep learning curve clinicians need to overcome to interpret OCM images. Developing an intelligent technique for computer-aided diagnosis (CADx) to accurately interpret OCM images will facilitate clinical adoption of the technology and improve patient care. METHODS: 497 high-resolution three-dimensional (3-D) OCM volumes (600 cross-sectional images each) were collected from 159 ex vivo specimens of 92 female patients. OCM image features were extracted using a convolutional neural network (CNN) model, concatenated with patient information [e.g., age and human papillomavirus (HPV) results], and classified using a support vector machine classifier. Ten-fold cross-validations were utilized to test the performance of the CADx method in a five-class classification task and a binary classification task. RESULTS: An 88.3 ± 4.9% classification accuracy was achieved for five fine-grained classes of cervical tissue, namely normal, ectropion, low-grade and high-grade squamous intraepithelial lesions (LSIL and HSIL), and cancer. In the binary classification task [low-risk (normal, ectropion, and LSIL) versus high-risk (HSIL and cancer)], the CADx method achieved an area-under-the-curve value of 0.959 with an 86.7 ± 11.4% sensitivity and 93.5 ± 3.8% specificity. CONCLUSION: The proposed deep-learning-based CADx method outperformed four human experts. It was also able to identify morphological characteristics in OCM images that were consistent with histopathological interpretations. SIGNIFICANCE: Label-free OCM imaging, combined with deep-learning-based CADx methods, holds a great promise to be used in clinical settings for the effective screening and diagnosis of cervical diseases.

Wnt/ß-catenin signaling pathway in severe preeclampsia.

This study aims to elucidate the mechanisms of Wnt/ß-catenin signaling pathway in the development of preeclampsia (PE). The mRNA levels of Wnt1, ß-catenin, c-myc and cyclinD1 were determined by real-time PCR in the placentas. Moreover, the expression levels of Wnt1, ß-catenin, Dickkopf-1 (DKK1) and glycogen synthase kinase 3ß (GSK-3ß) proteins were detected by Western blot. Immunohistochemistry was used in placental tissue microarray to localize the expression of Wnt1, ß-catenin, DKK1 proteins in the placentas of two groups. Compared with the control placentas, the mRNA levels of Wnt1, ß-catenin, c-myc and cyclinD1 were decreased in the severe preeclamptic placentas. The Western blot results showed that the expression levels of Wnt1, ß-catenin, and GSK-3ß proteins were significantly elevated in the control group, while the expression level of DKK1 was significantly decreased. In addition, the staining intensity of Wnt1, ß-catenin were weaker in the placentas of the severe PE group while the staining intensity of DKK1 was significantly stronger in the placentas of the severe PE group. Wnt/ß-catenin signaling pathway may play a significant role in the pathogenesis of PE by regulating the invasion and proliferation of trophoblast.