Stage Cervical Cancer Research Articles

Role of multi-parametric magnetic resonance imaging in preoperative staging of cervical carcinoma in females

BackgroundIn cervical cancer, accurate diagnosis of parametrial invasion (PMI) helps in determining the next step in management, either surgical resection or neoadjuvant therapy. Cervical cancer staging is still determined according to the clinical findings. But it is widely recognized that there are differences between clinical evaluation and the actual disease extent, particularly for PMI. In this prospective study, we investigate the relationship between clinical staging and magnetic resonance imaging (MRI) staging with post-management findings among patients with cervical cancer who underwent pre-treatment MRI, using fused T2-weighted image/diffusion-weighted imaging (T2/DWI).ResultsBased on examination under anesthesia (EUA), 80% of patients showed PMI, while fused T2/DWI was positive for PMI in 77.5% of patients. In all analyzed cases (40 females), MRI had sensitivity, specificity, and accuracy of 91%, 75%, and 87.5% compared to EUA. In the operated patients (24 females), MRI likewise had sensitivity, specificity, and accuracy of 81.3%, 87.5%, and 83%, respectively. In comparison with the postoperative results, the EUA showed higher sensitivity and accuracy than MRI (92.9% vs. 81.3%) and (83.3% vs. 79.2%), respectively, in the detection of PMI in operated cases. However, MRI was more specific in the PMI detection in cases with cervical cancer than EUA (75% vs. 70%).ConclusionMRI (with the aid of fused T2/DWI) improves the diagnostic performance for the PMI assessment in cases with cervical carcinoma. Therefore, MRI is helpful in choosing surgical candidates.

The economic burden of cervical cancer on women in Uganda: Findings from a cross-sectional study conducted at two public cervical cancer clinics.

There is limited research on how a cervical cancer diagnosis financially impacts women and their families in Uganda. This analysis aimed to describe the economic impact of cervical cancer treatment, including how it differs by socio-economic status (SES) in Uganda. We conducted a cross-sectional study from September 19, 2022 to January 17, 2023. Women were recruited from the Uganda Cancer Institute and Jinja Regional Referral Hospital, and were eligible if they were ≥ of 18 years and being treated for cervical cancer. Participants completed a survey that included questions about their out-of-pocket costs, unpaid labor, and family's economic situation. A wealth index was constructed to determine their SES. Descriptive statistics were reported. Of the 338 participants, 183 were from the lower SES. Women from the lower SES were significantly more likely to be older, have ≤ primary school education, and have a more advanced stage of cervical cancer. Over 90% of participants in both groups reported paying out-of-pocket for cervical cancer. Only 15 participants stopped treatment because they could not afford it. Women of a lower SES were significantly more likely to report borrowing money (higher SES n = 47, 30.5%; lower SES n = 84, 46.4%; p-value = 0.004) and selling possessions (higher SES n = 47, 30.5%; lower SES n = 90, 49.7%; p-value = 0.006) to pay for care. Both SES groups reported a decrease in the amount of time that they spent caring for their children since their cervical cancer diagnosis (higher SES n = 34, 31.2%; lower SES n = 36, 29.8%). Regardless of their SES, women in Uganda incur out-of-pocket costs related to their cervical cancer treatment. However, there are inequities as women from the lower SES groups were more likely to borrow funds to afford treatment. Alternative payment models and further economic support could help alleviate the financial burden of cervical cancer care in Uganda.

Application of 3.0 T multimodal MRI in FIGO staging of cervical cancer.

In malignant tumours of the female reproductive system, cervical cancer is second only to breast cancer, seriously threatening the health and safety of most women. To evaluate the clinical value of 3.0 T multimodal nuclear magnetic resonance imaging (MRI) in the International Federation of Gynecology and Obstetrics' (FIGO) staging of cervical cancer. The clinical data of 30 patients with pathologically diagnosed cervical cancer admitted to our hospital from January 2018 to August 2022 were analysed retrospectively. Before treatment, all patients were examined with conventional MRI, diffusion-weighted imaging and multi-directional contrast-enhanced imaging. The accuracy of multimodal MRI in the FIGO staging of cervical cancer (29/30, 96.7%) was significantly higher than the accuracy obtained in a control group (21/30, 70.0%), with a statistically significant difference (p= 0.013). In addition, there was good agreement between two observers applying multimodal imaging (kappa= 0.881) and moderate agreement between two observers in the control group (kappa= 0.538). Multimodal MRI can evaluate cervical cancer comprehensively and accurately to enable accurate FIGO staging, providing significant evidence for clinical operation planning and subsequent combined therapy.

Impact of Surgical Treatment on Quality of Life of Patients with Early-Stage Cervical Cancer: A Case Study of Two Referral Hospitals in Kenya

Objective: To determine the impact of surgical treatment on quality of life (QoL) of patients with early-stage cervical cancer at Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya, and Kenyatta National Hospital (KNH), Nairobi, Kenya. Methods: A cohort study conducted among 71 patients undergoing surgery for surgically amenable cervical cancer stage. Consecutive sampling of females was used to recruit participants. Participants were followed up for 3 months post-operatively. Descriptive statistics was used to describe the study participants. Bivariate analysis was used to assess the relationship between dependent and independent variables, and p value ≤0.05 was considered to be statistically significant. Results: Nearly two-thirds (63.5%) of the females had a parity of four or more, 69 (97.2%) did not have a family history of cervical cancer, and 57 (80.3%) were negative on HIV test. Most females (47.9%) had Stage IB2 cervical cancer, followed by those with Stage IB1, seen in 28 (39.4%) of the females enrolled. There were statistically significant differences in pain/discomfort (p=0.028) and anxiety/depression (p=0.028). Patients aged 20–35 years had a two-fold increased likelihood (adjusted odds ratio: 2.44; 95% confidence interval: 1.30–3.10; p=0.011) of reporting better QoL scores compared to older females. The lower the cervical cancer stage (Stage IA2), the higher the likelihood for improved QoL following surgical management of cervical cancer (adjusted odds ratio: 5.69; 95% confidence interval: 3.55–6.89; p=0.001). Conclusion: This study reports that being aged 20–35 years old and having a lower stage cervical cancer increased the likelihood of a good QoL outcome following surgical management of cervical cancer.

Impact of Surgical Treatment on Quality of Life of Patients with Early-Stage Cervical Cancer: A Case Study of Two Referral Hospitals in Kenya

Objective: To determine the impact of surgical treatment on quality of life (QoL) of patients with early-stage cervical cancer at Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya, and Kenyatta National Hospital (KNH), Nairobi, Kenya. Methods: A cohort study conducted among 71 patients undergoing surgery for surgically amenable cervical cancer stage. Consecutive sampling of females was used to recruit participants. Participants were followed up for 3 months post-operatively. Descriptive statistics was used to describe the study participants. Bivariate analysis was used to assess the relationship between dependent and independent variables, and p value ≤0.05 was considered to be statistically significant. Results: Nearly two-thirds (63.5%) of the females had a parity of four or more, 69 (97.2%) did not have a family history of cervical cancer, and 57 (80.3%) were negative on HIV test. Most females (47.9%) had Stage IB2 cervical cancer, followed by those with Stage IB1, seen in 28 (39.4%) of the females enrolled. There were statistically significant differences in pain/discomfort (p=0.028) and anxiety/depression (p=0.028). Patients aged 20–35 years had a two-fold increased likelihood (adjusted odds ratio: 2.44; 95% confidence interval: 1.30–3.10; p=0.011) of reporting better QoL scores compared to older females. The lower the cervical cancer stage (Stage IA2), the higher the likelihood for improved QoL following surgical management of cervical cancer (adjusted odds ratio: 5.69; 95% confidence interval: 3.55–6.89; p=0.001). Conclusion: This study reports that being aged 20–35 years old and having a lower stage cervical cancer increased the likelihood of a good QoL outcome following surgical management of cervical cancer.

Delays in Cervical Cancer Treatment Initiation for Patients Living With or Without HIV in Botswana: An Observational Cohort Analysis (2015-2019)

PURPOSEPresent delays in treatment initiation of chemoradiation or radiation alone for patients with advanced stage cervical cancer in Botswana. METHODSWomen with locally advanced cervical cancer (stages IB2-IVB) were prospectively enrolled in an observational cohort study in 2015-2019. We evaluated delays at 30, 60, 90, 120, 150, and 180 or greater days between the date of diagnosis and treatment initiation. Factors associated with overall survival (OS) were modeled with multivariable Cox proportional hazards regression (aHR). Associations between delays in cervical cancer treatment initiation were evaluated via univariable logistic regression. RESULTSAmong the 556 patients included (median age = 47.9 years), 386 (69.4%) were women living with HIV with a median CD4 count of 448.0 cells/μL (IQR, 283.0-647.5 cells/μL) at diagnosis. Most patients had stages II (38.1%) and III (34.5%) cervical cancer. Early-stage patients experienced longer delays in treatment initiation compared to late-stage patients (p=0.033). Early-stage patients with delays ≥90 days and pathology diagnosis between 2016-2019 (aHR 0.34, p<0.001) versus <90 days decreased the risk of mortality, while those with delays ≥90 days and pathology diagnosis before 2016 (aHR 5.67, p=0.022) versus <90 days increased the risk the mortality. Late-stage patients with delays ≥120 days and pathology diagnosis between 2018-2019 (aHR 1.98, p=0.025) versus <120 days increased the risk the mortality. Early-stage patients with pathology diagnosis between 2016-2019 (OR 2.32, p=0.043) versus before 2016 were more likely to experience delays ≥90 days and late-stage patients who traveled >100 km to the treatment facility (OR 2.83, p<0.001) versus <100 km were more likely to experience delays ≥120 days. CONCLUSIONSDelays in care are common in Botswana, particularly for those living farther from the treatment clinic and at advanced stages. This paper is among the first to show an association between treatment delays and worsened OS at advanced stages of cervical cancer, highlighting the need for interventions to help patients receive timely care in global settings.

Thermally Engineered Ferric Yolk‐Shells for Vaginal Secretion Based Cervical Cancer Screening

AbstractEngineering of materials is crucial for the advanced detection of bio‐molecules, particularly in laser desorption/ionization mass spectrometry (LDI‐MS). However, effective screening with enhanced LDI performance remains challenging due to the lack of engineered substrate materials. Herein, thermally engineered ferric yolk‐shells are designed for enhanced metabolic screening of cervical cancer (CC) using vaginal secretion. A facile thermal engineering strategy is developed to prepare amorphous ferric yolk‐shells with integrated properties. Notably, the amorphous mesoporous yolk‐shells offer signal amplification up to orders of magnitude in LDI‐MS for standard metabolites and diverse bio‐samples. High‐performance CC screening (including identification of human papillomavirus (HPV) infection, high‐grade squamous intraepithelial lesion (HSIL), and CC) is achieved, with the areas under the curve of 0.842–0.963. Finally, a metabolic panel for CC screening, covering the stages of HPV, HSIL, and CC, is established. This work elucidates the LDI‐MS mechanism for enhanced metabolic detection and highlights potential applications in cancer screening.

Expression of Inflammation Depending on the Stage of Cervical Cancer.

Background and Objectives: Cervical cancer (CC) remains a major public health problem, ranking as the fourth most common cause of cancer incidence and mortality in women globally. The development of CC is believed to be closely related to chronic inflammation. Thus, we aimed to evaluate the expression of systemic inflammation in patients with CC and to determine the threshold prognostic value of the systemic inflammation markers for CC and its advanced stage. Materials and Methods: 182 participants were recruited: 94 histology-proven patient with CC and 88 healthy women with NILM confirmed by liquid-based cytology test. The pre-treatment serum concentrations of cytokines, including IFN-β, IFN-γ, IL-1β, IL-2, IL-6, IL-10, IL-12p70, LCN2, TREM-1, and TNF-α, were determined for all study patients. Results: The odds ratio (OR) of having IL-6 concentration >17.4 pg/mL in the CC group compared to control patients was 11.4 (95% CI: 4.897-26.684); that of having TREM-1 concentration >355.6 pg/mL was 5.9 (95% CI: 2.257-15.767); and that of having LCN2 concentration >23,721.5 pg/mL was 3.4 (95% CI: 1.455-8.166). The odds ratio (OR) of having IL-6 concentration >28.7 pg/mL in advanced-stage CC (III-IV stage) compared to early-stage CC (I-II stage) was 2.921 (95% CI: 1.06-8.045), and that of having LCN2 concentration >25,640.0 pg/mL was 4.815 (95% CI: 1.78-13.026). Conclusions: The pre-treatment serum inflammation markers IL-6, TREM-1, and LCN2 at specified levels could be used as predictors of cervical cancer, and IL-6 and LCN2 as predictors of an increased chance of advanced-stage (III-IV stages) cervical cancer. Patients with cervical cancer had expressed systemic inflammation, and expression of inflammation elevated the chance of having CC and advanced-stage disease.

MRI Plain Scan: A Tool in the Management of Cervical Cancer during Pregnancy.

The purpose of this study was to assess the diagnostic value of magnetic resonance imaging (MRI) in staging and treatment of cervical cancer in pregnancy, and to evaluate the benefit of apparent diffusion coefficient (ADC) during neoadjuvant chemotherapy management. This was a retrospective cohort study. Patients were divided into two groups according to the stage of cervical cancer. The mean term of pregnancy at the time of the diagnosis was the early second trimester (range 10-27 weeks) and the median age was 33 years (range 26-40 years). The abdominal and pelvic MRI images and clinical data of these patients were reviewed. Tumor size, local tumor spread, and nodal involvement were evaluated using an MRI dataset. The treatment and follow-up imaging were analyzed as well, and the ADC was measured before and after the chemotherapy. 16 patients with histopathologically confirmed cervical cancer during pregnancy were retrospectively enrolled. 7 patients were diagnosed with local cervical cancer (FIGO stage IAI) and designated as early stage group, as the lesion was invisible on MRI. In this group, pregnancies were allowed to continue until cesarean delivery (CD) at 38-41 weeks. The other 9 patients presenting with local or extensive cervical cancer (FIGO stage IB2-IIA2) were designated as the advanced-stage group. The lesion could be measured and analyzed on MRI. They were treated with neoadjuvant chemotherapy in pregnancy. Among them, 6 patients underwent TP regimen (paclitaxel 135~175 mg/m2 plus cisplatin 70~75 mg/m2), while 3 patients received TC regimen (paclitaxel 135~175 mg/m2 plus carboplatin AUC=5). NACT was performed for 1 to 2 courses before surgery. ADC demonstrated significant differences before and after chemotherapy administered during pregnancy (1.06 ± 0.12 sec/mm2 vs. 1.34 ± 0.21 sec/mm2). MRI has been found to be helpful in staging cervical cancer in pregnancy. Patients with stage IA confirmed by MRI can choose conservative treatment and continue the pregnancy until term birth. MRI can dynamically monitor the efficacy of chemotherapy for patients with stage IB and above during pregnancy. ADC value can have a potential role in the evaluation of chemotherapy efficacy.

The Role of Imaging in Cervical Cancer Staging: ESGO/ESTRO/ESP Guidelines (Update 2023).

Following the European Society of Gynaecological Oncology (ESGO), the European Society for Radiotherapy and Oncology (ESTRO), and the European Society of Pathology (ESP) joint guidelines (2018) for the management of patients with cervical cancer, treatment decisions should be guided by modern imaging techniques. After five years (2023), an update of the ESGO-ESTRO-ESP recommendations was performed, further confirming this statement. Transvaginal/transrectal ultrasound (TRS/TVS) or pelvic magnetic resonance (MRI) enables tumor delineation and precise assessment of its local extent, including the evaluation of the depth of infiltration in the bladder- or rectal wall. Additionally, both techniques have very high specificity to confirm the presence of metastatic pelvic lymph nodes but fail to exclude them due to insufficient sensitivity to detect small-volume metastases, as in any other currently available imaging modality. In early-stage disease (T1a to T2a1, except T1b3) with negative lymph nodes on TVS/TRS or MRI, surgicopathological staging should be performed. In all other situations, contrast-enhanced computed tomography (CECT) or 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET-CT) is recommended to assess extrapelvic spread. This paper aims to review the evidence supporting the implementation of diagnostic imaging with a focus on ultrasound at primary diagnostic workup of cervical cancer.

Information needs factors affecting pain experience among patients with cervical cancer stages III and IV at the Kenyatta National Hospital: A descriptive phenomenology study

Background: Cervical cancer is the leading cause of cancer-related deaths among women in Kenya.Patients present late when the cure is unattainable and have an impaired quality of life (QoL). Pain is theworst and most common cause of impaired QoL. Poor control is due to a focus on the physical aspect ofpain only rather than the holistic approach that also considers the nonphysical factors, includingpsychological, social, spiritual, economic, and information needs aspects of pain. Information need isdefined as a state in which one perceives a gap between information and knowledge available to solve aproblem. There is inadequate information exchange between health care providers and cervical cancerpatients in Kenya, with such patients reporting that inadequate information prolonged their suffering asthey sought diagnosis and treatment. There have been recommendations that communication guidelinesbe developed, and communication training skills be developed in a culturally relevant way. Differences incultural and socioeconomic contexts may impede this goal.Objective: To explore information needs factors among patients with cervical cancer stages III and IV atthe Kenyatta National Hospital.Methods: Qualitative research using a descriptive phenomenological study involving fifteen in-depthinterviews and five focus group discussions was conducted.Results: This study revealed poor methods of breaking bad news, conflicts in the disclosure of bad newsto patients, inadequate information on the investigations and procedures needed, and doctors’unavailability to provide detailed information, especially those that require seeking money from relatives.Conclusion: Information needs remain a gap affecting pain experienced by cervical cancer patients.

Prediction models for lymph node metastasis in cervical cancer based on preoperative heart rate variability.

The occurrence of lymph node metastasis (LNM) is one of the critical factors in determining the staging, treatment and prognosis of cervical cancer (CC). Heart rate variability (HRV) is associated with LNM in patients with CC. The purpose of this study was to validate the feasibility of machine learning (ML) models constructed with preoperative HRV as a feature of CC patients in predicting CC LNM. A total of 292 patients with pathologically confirmed CC admitted to the Department of Gynecological Oncology of the First Affiliated Hospital of Bengbu Medical University from November 2020 to September 2023 were included in the study. The patient' preoperative 5-min electrocardiogram data were collected, and HRV time-domain, frequency-domain and non-linear analyses were subsequently performed, and six ML models were constructed based on 32 parameters. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Among the 6 ML models, the random forest (RF) model showed the best predictive performance, as specified by the following metrics on the test set: AUC (0.852), accuracy (0.744), sensitivity (0.783), and specificity (0.785). The RF model built with preoperative HRV parameters showed superior performance in CC LNM prediction, but multicenter studies with larger datasets are needed to validate our findings, and the physiopathological mechanisms between HRV and CC LNM need to be further explored.

Nodal staging score for adequacy of nodal staging in cervical cancer

BackgroundCervical cancer remains the fourth most common female malignancy with increasing newly cases around the world. It is of clinical value to precisely evaluate whether false negative nodal existed and develop a nodal staging model in cervical cancer. Materials and methodsClinical data of cervical cancer patients was retrieved from the Surveillance, Epidemiology, and End Results database. Probability of missing nodal disease and nodal staging score (NSS) was computed to assess the nodal status of each individual.Prognostic value of NSS was assessed. ResultsA total of 9056 individuals were in this study, with 5115 squamous cell carcinoma, 2791 adenocarcinoma, 512 adenosquamous carcinoma, and 638 other type individuals. A beta-binomial model was used to compute the probability of nodal disease in four histological types, respectively. False negative probability drastically decreased as more nodes examined. To reach 0.05 of false negative probability, it required at least 17 lymph nodes in squamous cell carcinoma patients,18 in adenocarcinoma, 12 in adenosquamous carcinoma patients and 14 in other types. To reach 0.95 of NSS, it took 10 lymph nodes in squamous cell carcinoma, 6 in adenocarcinoma, 10 in adenosquamous carcinoma and 7 in other types. Significant prognostic values of NSS quartiles subsets were found in all four histological sets. ConclusionNSS tool enables adequate nodal staging of cervical cancer with significant prognostic value. Exact number of lymph nodes required for surgery in cervical cancer is specified based on histologic type.

Diagnostic accuracy of MRI, CT, and [18F]FDG-PET-CT in detecting lymph node metastases in clinically early-stage cervical cancer — a nationwide Dutch cohort study

ObjectivesImaging is increasingly used to assess lymph node involvement in clinically early-stage cervical cancer. This retrospective study aimed to evaluate the diagnostic accuracy of MRI, CT, and [18F]FDG-PET-CT.MethodsWomen with International Federation of Gynaecology and Obstetrics (FIGO) 2009 stage IA2-IIA cervical cancer and pretreatment imaging between 2009 and 2017 were selected from the Netherlands Cancer Registry. Patient-based and region-based (i.e. pelvic and common iliac) nodal status was extracted from radiology reports. Pathology results were considered the reference standard for calculating accuracy indices. Multiple imputation was used for missing pathology to limit verification bias risk.ResultsNodal assessment was performed in 1676 patients with MRI, 926 with CT, and 379 with [18F]FDG-PET-CT, with suspicious nodes detected in 17%, 16%, and 48%, respectively. [18F]FDG-PET-CT was used to confirm MRI/CT results in 95% of patients. Pathology results were imputed for 30% of patients. [18F]FDG-PET-CT outperformed MRI and CT in detecting patient-based nodal metastases with sensitivities of 80%, 48%, and 40%, and AUCs of 0.814, 0.706, and 0.667, respectively, but not in specificity: 79%, 92%, and 92%. Region-based analyses showed similar indices in the pelvic region, but worse performance in the common iliac region with AUCs of 0.575, 0.554, and 0.517, respectively.Conclusions[18F]FDG-PET-CT outperformed MRI and CT in detecting nodal metastases, which may be related to its use as a verification modality. However, MRI and CT had the highest specificity. As MRI is generally performed routinely to assess local and regional spread of cervical cancer, [18F]FDG-PET-CT can be used to confirm suspicious nodes.Critical relevance statementAccurate assessment of the nodal status in clinically early-stage cervical cancer is essential for tumour staging, treatment decision making and prognosis.Key points• The accuracy of MRI, CT or [18F]FDG-PET-CT for nodal staging in early cervical cancer is a subject of discussion.• Overall, [18F]FDG-PET-CT outperformed MRI, followed by CT, when used as a verification modality.• Staging with MRI and the addition of [18F]FDG-PET-CT to verify high-risk cases seems to be a good approach.Graphical

Radiomics analysis based on multiparametric magnetic resonance imaging for differentiating early stage of cervical cancer.

To investigate the performance of multiparametric magnetic resonance imaging (MRI)-based radiomics models in differentiating early stage of cervical cancer (Stage I-IIa vs. IIb-IV). One hundred patients with cervical cancer who underwent preoperative MRI between June 2020 and March 2022 were retrospectively enrolled. Training (n = 70) and testing cohorts (n = 30) were assigned by stratified random sampling. The clinical and pathological features, including age, histological subtypes, tumor grades, and node status, were compared between the two cohorts by t-test or chi-square test. Radiomics features were extracted from each volume of interest (VOI) on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps. The data balance of the training cohort was resampled by synthesizing minority oversampling techniques. Subsequently, the adiomics signatures were constructed by the least absolute shrinkage and selection operator algorithm and minimum-redundancy maximum-relevance with 10-fold cross-validation. Logistic regression was applied to predict the cervical cancer stages (low [I-IIa]) and (high [IIb-IV] FIGO stages). The receiver operating characteristic curve (area under the curve [AUC]) and decision curve analysis were used to assess the performance of the radiomics model. The characteristics of age, histological subtypes, tumor grades, and node status were not significantly different between the low [I-IIa] and high [IIb-IV] FIGO stages (p > 0.05 for both the training and test cohorts). Three models based on T2WI, ADC maps, and the combined were developed based on six radiomics features from T2WI and three radiomics features from ADC maps, with AUCs of 0.855 (95% confidence interval [CI], 0.777-0.934) and 0.823 (95% CI, 0.727-0.919), 0.861 (95% CI, 0.785-0.936) and 0.81 (95% CI, 0.701-0.918), 0.934 (95% CI, 0.884-0.984) and 0.902 (95% CI, 0.832-0.972) in the training and test cohorts. The radiomics models combined T2W and ADC maps had good predictive performance in differentiating the early stage from locally advanced cervical cancer.

Prediction Models Applying Convolutional Neural Network based Deep Learning to Cervical Cancer Outcomes

Early identification of Cervical Cancer (CC) helps in reducing the death rate of CC patients. A Pap smear/Pap test, which is also a widely used method, is used to detect CC in its early stages. The automatic detection and categorization of Pap smear images is a difficult task. So, it is important to design and implement a high-efficiency with low-cost screening system. Therefore, this paper compares the efficiency of two deep learning-based cervical cancer screening strategies. The first technique taken for comparison is the Mutation based Atom Search Optimization (MASO) optimized DenseNet 121 architecture. The MASO technique is used to adjust hyperparameters such as learning rate value, batch sizes, and the number of neurons in the dense layer in the DenseNet 121 architecture. The second technique taken is the Sooty Tern optimized CNN-based Long Short-Term Memory (ST-CNN-LSTM) classifier to identify the different types of cervical cancer stages. The areas affected by the cancer are identified using Kernel-Weighted Fuzzy Local Information C-Means clustering (KWFLICM) model. This model removes the nucleus and cytoplasm from the background area of the cell. Normal, mild dysplastic, severe dysplastic, and carcinoma are among the CC classifications offered by these two classifiers. The efficiency of these classifiers is compared in two datasets (Hervel and SIPaKMeD) via different performance metrics such as specificity, precisions, F-score, accuracy, confusion matrix, sensitivity, and recall. The ST-CNN-LSTM offers improved performance in terms of accuracy (99.80%), sensitivity (98.83%), and specificity (99%) when compared to other classifiers.

Predicting cervical intraepithelial neoplasia and determining the follow-up period in high-risk human papillomavirus patients.

Despite strong efforts to promote human papillomavirus (HPV) vaccine and cervical cancer screening, cervical cancer remains a threat to women's reproductive health. Some high-risk HPV types play a crucial role in the progression of cervical cancer and precancerous lesions. Therefore, HPV screening has become an important means to prevent, diagnose, and triage cervical cancer. This study aims to leverage artificial intelligence to predict individual risks of cervical intraepithelial neoplasia (CIN) in women with high-risk HPV infection and to recommend the appropriate triage strategy and follow-up period according to the risk level. A total of 475 cases were collected in this study. The sources were from the Department of Gynecology and Obstetrics in a tertiary hospital, a case report on HPV from the PubMed website, and clinical data of cervical cancer patients from The Cancer Genome Atlas (TCGA) database. Through in-depth study of the interaction between high-risk HPV and its risk factors, the risk factor relationship diagram structure was constructed. A Classification of Lesion Stages (CLS) algorithm was designed to predict cervical lesion stages. The risk levels of patients were analyzed based on all risk factors, and follow-up periods were formulated for each risk level. Our proposed CLS algorithm predicted the probability of occurrence of CIN3-the precancerous lesion stage of cervical cancer. This prediction was based on patients' HPV-16 and -18 infection status, age, presence of persistent infection, and HPV type. Follow-up periods of 3-6 months, 6-12 months, and 3- to 5-year intervals were suggested for high-risk, medium-risk, and low-risk patients, respectively. A lesion prediction model was constructed to determine the probabilities of occurrence of CIN by analyzing individual data, such as patient lifestyle, physical assessments, and patient complaints, in order to identify high-risk patients. Furthermore, the potential implications of the calculated features were mined to devise prevention strategies.

T1 mapping as a quantitative imaging biomarker for diagnosing cervical cancer: a comparison with diffusion kurtosis imaging

BackgroundT1 mapping can potentially quantitatively assess the intrinsic properties of tumors. This study was conducted to explore the ability of T1 mapping in distinguishing cervical cancer type, grade, and stage and compare the diagnostic performance of T1 mapping with diffusion kurtosis imaging (DKI).MethodsOne hundred fifty-seven patients with pathologically confirmed cervical cancer were enrolled in this prospectively study. T1 mapping and DKI were performed. The native T1, difference between native and postcontrast T1 (T1diff), mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were calculated. Cervical squamous cell carcinoma (CSCC) and adenocarcinoma (CAC), low- and high-grade carcinomas, and early- and advanced-stage groups were compared using area under the receiver operating characteristic (AUROC) curves.ResultsThe native T1 and MK were higher, and the MD and ADC were lower for CSCC than for CAC (all p < 0.05). Compared with low-grade CSCC, high-grade CSCC had decreased T1diff, MD, ADC, and increased MK (p < 0.05). Compared with low-grade CAC, high-grade CAC had decreased T1diff and increased MK (p < 0.05). Native T1 was significantly higher in the advanced-stage group than in the early-stage group (p < 0.05). The AUROC curves of native T1, MK, ADC and MD were 0,772, 0.731, 0.715, and 0.627, respectively, for distinguishing CSCC from CAC. The AUROC values were 0.762 between high- and low-grade CSCC and 0.835 between high- and low-grade CAC, with T1diff and MK showing the best discriminative values, respectively. For distinguishing between advanced-stage and early-stage cervical cancer, only the AUROC of native T1 was statistically significant (AUROC = 0.651, p = 0.002).ConclusionsCompared with DKI-derived parameters, native T1 exhibits better efficacy for identifying cervical cancer subtype and stage, and T1diff exhibits comparable discriminative value for cervical cancer grade.

Cervical lymphoepithelioma-like carcinoma with deficient mismatch repair and loss of SMARCA4/BRG1: a case report and five related cases

BackgroundWe encountered a cervical lymphoepithelial carcinoma (LEC) possessing a predominantly solid architecture with deficient mismatch repair (dMMR) and loss of expression of the SWI/SNF (SWItch/Sucrose Non-Fermentable) chromatin remodeling complex subunit. This is the first case report of LEC with dMMR and loss of SWI/SNF complex subunit.Case presentationA 34-year-old woman presented at our hospital with menstrual irregularities and abnormal vaginal bleeding. Magnetic resonance imaging revealed an exophytic mass in the posterior uterine cervix. Biopsy specimens confirmed squamous cell carcinoma with a 2018 International Federation of Gynecology and Obstetrics (FIGO) uterine cervical cancer stage of IB2. In a subsequent conization specimen, the tumor appeared exophytic. Microscopically, the tumor cells formed a predominant solid architecture. Abundant lymphocytic infiltration was observed. The pathological diagnosis indicated human papillomavirus (HPV)-associated squamous cell carcinoma with LEC pattern and pT1b2. Immunohistochemically, high programmed death-ligand 1 (PD-L1) expression, dMMR, and loss of the switch/sucrose non-fermentable family-related, matrix-associated, actin-dependent regulator of chromatin subfamily member 4 (SMARCA4)/BRG1, an SWI/SNF complex subunit, were observed. The patient underwent a radical hysterectomy and is alive without disease one year and five months later. Our analysis of five additional LEC cases revealed a consistent association with high-risk HPV and elevated PD-L1 expression. In addition to the present case, another patient exhibited dMMR. The SWI/SNF complex was retained except in the present case. The prognosis was favorable in all cases.ConclusionsThis unique case of LEC with dMMR suggests a distinct clinical entity with potential immunotherapy implications. Analysis of the other five LEC cases revealed that LEC was immune hot, and immune checkpoint inhibitors may be effective. The two dMMR cases showed loss of MLH1 and PMS2 expressions, and prominently high tumor PD-L1 expression. In those cases, dMMR might have contributed to the morphological characteristics of LEC.

Utility of expression of 4-hydroxynonenal tested by immunohistochemistry for cervical cancer.

Cervical cancer (CC) is a leading cause of mortality in women around the world, with the highest incidence rate still being in developing countries. The most common aetiological factor is infection with high-risk human papilloma virus viral strains. Oxidative stress through generation of reactive oxygen species leads to lipid peroxidation and DNA damage. Studies show that reactive lipid electrophiles such as 4-hydroxynonenal (4-HNE) produced in the process play an important role in cancer signalling pathways and are a good biomarker for oxidative stress. We aim to investigate the prognostic role of 4-HNE as a biomarker for oxidative stress in patients in early and advanced stages of CC measured by immunohistochemistry. This is a retrospective study of 69 patients treated at our Department of Oncogynaecology. Paraffin embedded tumour tissues were immunohistochemically tested for the levels of expression of 4-HNE. The results for H-score, Allred score, and combined score were investigated for association with tumour size, lymph node status, andInternational Federation of Gynaecology and Obstetrics stage. 4-hydroxynonenal showed higher expression in more advanced stages of CC and in cases with involved lymph nodes. Tumour size was not associated with the levels of 4-HNE. To best of our knowledge, this is the first study to use immunohistochemistry to examine the expression of 4-HNE as a prognostic factor in CC. The 3 score systems showed similar results. The pattern of 4-HNE histological appearance is dependent on the histological origin of cancer and is not universal.