Diagnostic value of the 2011 International Federation for Cervical Pathology and Colposcopy Terminology in predicting cervical lesions

Clinical Benefit of a Conservative Treatment for High-Risk Human Papillomavirus Lesions in Patients with HIV

Infection with human immunodeficiency virus (HIV) shows a higher risk of infection by human papillomavirus (HPV). We aim to provide evidence about the effect of a Coriolus versicolor-based vaginal gel (Papilocare®) for treating HPV in women with HIV. Women ≥25 years coinfected by endocervical HPV and with low-grade abnormal cervicovaginal cytology were treated for 6 months with Papilocare in this observational, prospective, noncontrolled pilot study. Cytology, colposcopy, biopsy, hybrid capture test, and 5-point Likert scale were assessed to evaluate cervical lesions repair, HPV clearance, and changes in cervical reepithelization, respectively, at 6 months. Fifteen patients (25-54 years) were included. Overall HPV clearance and cytological normalization rates were 73.3% and 80.0%, respectively, and 55.6% of the abnormal colposcopies were normalized. Reepithelialization index improved in 66.7% of cases. Papilocare may be effective for managing endocervical HPV infection in patients living with HIV.

Evaluation of Onco E6 point of care rapid diagnostic test for human papilloma virus in Bahir Dar, Amhara Regional State, Ethiopia

INTRODUCTION

Cervical cancer is a malignant tumor arising from the cells of the uterine cervix. The oncogenic human papillomavirus (HPV) infection is the main causative agent of cervical cancer. Effective HPV screening program can lead to a significant reduction in the morbidity and mortality associated with this cancer.

OBJECTIVE

The aim of the study was to evaluate the diagnostic performance of OncoE6™ cervical test kit for cervical precancer and cancer in Amhara Regional State, northwest Ethiopia.

METHODS

An institute-based cross-sectional study was conducted at Felege Hiwot Compressive Specialized Hospital which is found in Bahir Dar, Amhara Regional state. A total of 297 samples were collected. A sterile, disposable speculum was inserted, without lubricant, and two swabs were taken using the "Tipped Polyester" (Dacron) swab provided with the Onco E6™ kit. Swabs taken were tested for onco E6 proteins testing as per the manufacturer's protocol and pap smear for cytology test. A punch of biopsy was also taken for histopathological diagnosis. Data for all samples were collected using pre-prepared excel database for onco E6 test, pap cytology and punch histopathology. All the data were coded and entered into Epi-info and transported to SPSS version 26.0 software package for analysis.

RESULTS

Out of 56 (18.86%) participants who tested positive on the histo-pathological diagnosis, Onco E6 was positive in 32 (57.14%), negative in 24 (42.85%). Of 241 participants who tested negative on the histo-pathological diagnosis, Onco E6 was positive in 5 (2.07%) and negative in 236 (97.9%). OncoE6™ cervical test kit had a sensitivity of 57.14% (95% CI: 43.22%-70.29%) and specificity of 98% (95% CI: 95.23%-99.32%) with positive predictive value of 86.6% (95% CI: 71.36%-95.53%), negative predictive value of 90.76% (95% CI: 86.49%-93.93%), and accuracy of 90.18% (95% CI: 86.21%-93.31%).

CONCLUSION

The HPV 16/18 OncoE6™ Cervical test kit test had sub-optimum sensitivity and high specificity for detection of cervical precancer and cancer cases. The sensitivity of the kit could be increased by incorporating other more prevalent genotypes like genotype 52, 58, 31 and 35. The HPV16/18-E6 test could be used either as primary screening tool or in conjunction with other diagnostic methods.

The Distribution of Cervical Transformation Zone and Its Impact on Colposcopic Diagnosis: A Multicenter Study in China

OBJECTIVE

The value of the transformation zone (TZ) is often overlooked in clinical settings. This study aims to assess TZ distribution, associated factors, and its impact on colposcopic diagnosis.

METHODS

χ 2 tests were used to analyze demographics, clinical history, and tissue samples to examine the differences in TZ distribution. Factors affecting the TZ were explored using logistic regression, and diagnostic indicators were calculated.

RESULTS

A total of 5,302 individual datasets were finally included. TZ1, TZ2, and TZ3 accounted for 31.6%, 38.5%, and 30.0%, respectively. Age is the most important factor that influences the location of the TZ. The proportion of TZ3 steadily increased with age, comprising over 55% in women over 50. The colposcopic diagnostic performance shows that high-grade squamous intraepithelial lesion or worse (HSIL+) sensitivity of TZ3 (58.1%, 95% confidence interval [CI] = 52.9-63.4) is significantly lower than that of TZ1 (69.8%, 95% CI = 65.5-74.1) and TZ2 (73.2%, 95% CI = 69.7-76.8). The HSIL+ specificity of TZ3 (96.3, 95% CI = 95.3-97.4) was higher than that of TZ1 (96.3, 95% CI = 95.2-97.3) and TZ2 (92.5, 95% CI = 91.1-93.9). The HSIL+ positive predictive value (81.3%, 95% CI = 76.4-86.2) and negative predictive value (89.3%, 95% CI = 87.6-90.9) for TZ3 are high, with no significant differences when compared with TZ1 and TZ2.

CONCLUSIONS

Age predominantly influences TZ location, with TZ3 being most frequently found in women over 50. While TZ3 poses a higher risk of missed diagnosis during colposcopy, it remains clinically valuable in identifying diseased and nondiseased status. Increasing colposcopists' awareness of TZ importance is needed in clinical practice.

Evaluation of the diagnostic performance of colposcopy in the detection of cervical high-grade squamous intraepithelial lesions among women with transformation zone type 3

BACKGROUND

Inaccurate colposcopy diagnosis may lead to inappropriate management and increase the incidence of cervical cancer. This study aimed to evaluate the diagnostic accuracy of colposcopy in the detection of histologic cervical intraepithelial neoplasia grade 2 or worse (CIN2+) in women with transformation zone type 3 (TZ3).

METHODS

Records from 764 patients with TZ3 who underwent colposcopy-directed biopsy and/or endocervical curettage in Putuo Hospital China between February 2020 and March 2023 were retrospectively collected. Colposcopy was carried out based on 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC) and Colposcopy nomenclature. The diagnostic performance of colposcopy for identifying CIN2 + was evaluated compared with biopsies. The Kappa and McNemar tests were used to perform statistical analyses.

RESULTS

Among the study population, 11.0% had pathologic CIN2+. The relative sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of colposcopy for histologic CIN2 + were 51.2%, 96.5%, 64.2% and 94.1%, respectively. The senior colposcopists (80.6%) had a higher colposcopic accuracy to diagnose histologic CIN2 + than junior colposcopists (68.6%). In subgroup analyses, age group ≥ 60 years (70.3%) showed lowest diagnostic accuracy when compared with age groups of < 45 years (84.4%) and 45-59 years (74.9%).

CONCLUSION

Our findings suggest an increased risk of diagnostic inaccuracy of colposcopy in identifying CIN2 + in those ≥ 60 years of age with TZ3, and the accuracy of colposcopy is required to be further improved.

Development and validation of artificial intelligence-based analysis software to support screening system of cervical intraepithelial neoplasia

Cervical cancer, the fourth most common cancer among women worldwide, often proves fatal and stems from precursor lesions caused by high-risk human papillomavirus (HR-HPV) infection. Accurate and early diagnosis is crucial for effective treatment. Current screening methods, such as the Pap test, liquid-based cytology (LBC), visual inspection with acetic acid (VIA), and HPV DNA testing, have limitations, requiring confirmation through colposcopy. This study introduces CerviCARE AI, an artificial intelligence (AI) analysis software, to address colposcopy challenges. It automatically analyzes Tele-cervicography images, distinguishing between low-grade and high-grade lesions. In a multicenter retrospective study, CerviCARE AI achieved a remarkable sensitivity of 98% for high-risk groups (P2, P3, HSIL or higher, CIN2 or higher) and a specificity of 95.5%. These findings underscore CerviCARE AI's potential as a valuable diagnostic tool for highly accurate identification of cervical precancerous lesions. While further prospective research is needed to validate its clinical utility, this AI system holds promise for improving cervical cancer screening and lessening the burden of this deadly disease.

Role of DNA ploidy in diagnosis and prognosis of high-grade cervical intraepithelial neoplasia: A prospective cohort study

OBJECTIVE

To compare the sensitivity and specificity of DNA ploidy with cytology, human papillomavirus (HPV) testing and colposcopy in diagnosis of high-grade cervical intraepithelial neoplasia (CIN) and to assess the role of aneuploidy in cervical lesions with the worst prognosis. A prospective observational cohort study was conducted on 254 women with altered colpocytology.

METHODS

Colposcopy, biopsy, DNA-ICM and HPV examinations were applied to cervical cytological and histological samples. Participants were evaluated every 6 months and divided into two groups: 'Harm' and 'No-harm'. Logistic regression and multivariate COX model were used to identify independent risk factors for diagnosis and prognosis of high-grade CIN, and ROC curve to assess the sensitivity and specificity of methods.

RESULTS

Variables 'age greater than or equal to 30 years', 'lesion size greater than 20%', 'aneuploidy' and 'HPV 16' were associated with diagnosis of high-grade CIN and 'aneuploidy' and 'women living with HIV', with a worse prognosis. Agreement for colposcopy was good, with a sensitivity of 79.3% and specificity of 94.4%; DNA-ICM and cytology were moderate, with sensitivity of 74.6% and 72.3% and specificity of 85.3% and 76.1%, respectively. High-risk HPV and HPV 16 tests were weak, with sensitivity of 75.0% and 43.75% and specificity of 50.0% and 88.64%, respectively.

CONCLUSIONS

In relation to high-grade CIN diagnosis, DNA-ICM presented similar sensitivity and specificity to cytology and high-risk HPV test when associated with HPV 16. Regarding prognosis, this research certifies that aneuploidy is considered a predictor of more severe cervical injury.

Pivotal Clinical Study to Evaluate the Efficacy and Safety of Assistive Artificial Intelligence-Based Software for Cervical Cancer Diagnosis

Colposcopy is the gold standard diagnostic tool for identifying cervical lesions. However, the accuracy of colposcopies depends on the proficiency of the colposcopist. Machine learning algorithms using an artificial intelligence (AI) system can quickly process large amounts of data and have been successfully applied in several clinical situations. This study evaluated the feasibility of an AI system as an assistive tool for diagnosing high-grade cervical intraepithelial neoplasia lesions compared to the human interpretation of cervical images. This two-centered, crossover, double-blind, randomized controlled trial included 886 randomly selected images. Four colposcopists (two proficient and two inexperienced) independently evaluated cervical images, once with and the other time without the aid of the Cerviray AI^® system (AIDOT, Seoul, Republic of Korea). The AI aid demonstrated improved areas under the curve on the localization receiver-operating characteristic curve compared with the colposcopy impressions of colposcopists (difference 0.12, 95% confidence interval, 0.10-0.14, p < 0.001). Sensitivity and specificity also improved when using the AI system (89.18% vs. 71.33%; p < 0.001, 96.68% vs. 92.16%; p < 0.001, respectively). Additionally, the classification accuracy rate improved with the aid of AI (86.40% vs. 75.45%; p < 0.001). Overall, the AI system could be used as an assistive diagnostic tool for both proficient and inexperienced colposcopists in cervical cancer screenings to estimate the impression and location of pathologic lesions. Further utilization of this system could help inexperienced colposcopists confirm where to perform a biopsy to diagnose high-grade lesions.

Colposcopy Accuracy and Diagnostic Performance: A Quality Control and Quality Assurance Survey in Italian Tertiary-Level Teaching and Academic Institutions-The Italian Society of Colposcopy and Cervico-Vaginal Pathology (SICPCV)

Quality Control (QC) and Quality Assurance (QA) principles are essential for effective cervical cancer prevention. Being a crucial diagnostic step, colposcopy's sensitivity and specificity improvements are strongly advocated worldwide since inter- and intra-observer differences are the main limiting factors. The objective of the present study was the evaluation of colposcopy accuracy through the results of a QC/QA assessment from a survey in Italian tertiary-level academic and teaching hospitals. A web-based, user-friendly platform based on 100 colposcopic digital images was forwarded to colposcopists with different levels of experience. Seventy-three participants were asked to identify colposcopic patterns, provide personal impressions, and indicate the correct clinical practice. The data were correlated with a panel of experts' evaluation and with the clinical/pathological data of the cases. Overall sensitivity and specificity with the threshold of CIN2+ accounted for 73.7% and 87.7%, respectively, with minor differences between senior and junior candidates. Identification and interpretation of colposcopic patterns showed full agreement with the experts' panel, ranging from 50% to 82%, in some instances with better results from junior colposcopists. Colposcopic impressions correlated with a 20% underestimation of CIN2+ lesions, with no differences linked to level of experience. Our results demonstrate the good diagnostic performance of colposcopy and the need for improving accuracy through QC assessments and adhesion to standard requirements and recommendations.

Artificial intelligence in colposcopic examination: A promising tool to assist junior colposcopists

Introduction

Well-trained colposcopists are in huge shortage worldwide, especially in low-resource areas. Here, we aimed to evaluate the Colposcopic Artificial Intelligence Auxiliary Diagnostic System (CAIADS) to detect abnormalities based on digital colposcopy images, especially focusing on its role in assisting junior colposcopist to correctly identify the lesion areas where biopsy should be performed.

Materials and methods

This is a hospital-based retrospective study, which recruited the women who visited colposcopy clinics between September 2021 to January 2022. A total of 366 of 1,146 women with complete medical information recorded by a senior colposcopist and valid histology results were included. Anonymized colposcopy images were reviewed by CAIADS and a junior colposcopist separately, and the junior colposcopist reviewed the colposcopy images with CAIADS results (named CAIADS-Junior). The diagnostic accuracy and biopsy efficiency of CAIADS and CAIADS-Junior were assessed in detecting cervical intraepithelial neoplasia grade 2 or worse (CIN2+), CIN3+, and cancer in comparison with the senior and junior colposcipists. The factors influencing the accuracy of CAIADS were explored.

Results

For CIN2 + and CIN3 + detection, CAIADS showed a sensitivity at ~80%, which was not significantly lower than the sensitivity achieved by the senior colposcopist (for CIN2 +: 80.6 vs. 91.3%, p = 0.061 and for CIN3 +: 80.0 vs. 90.0%, p = 0.189). The sensitivity of the junior colposcopist was increased significantly with the assistance of CAIADS (for CIN2 +: 95.1 vs. 79.6%, p = 0.002 and for CIN3 +: 97.1 vs. 85.7%, p = 0.039) and was comparable to those of the senior colposcopists (for CIN2 +: 95.1 vs. 91.3%, p = 0.388 and for CIN3 +: 97.1 vs. 90.0%, p = 0.125). In detecting cervical cancer, CAIADS achieved the highest sensitivity at 100%. For all endpoints, CAIADS showed the highest specificity (55-64%) and positive predictive values compared to both senior and junior colposcopists. When CIN grades became higher, the average biopsy numbers decreased for the subspecialists and CAIADS required a minimum number of biopsies to detect per case (2.2-2.6 cut-points). Meanwhile, the biopsy sensitivity of the junior colposcopist was the lowest, but the CAIADS-assisted junior colposcopist achieved a higher biopsy sensitivity.

Conclusion

Colposcopic Artificial Intelligence Auxiliary Diagnostic System could assist junior colposcopists to improve diagnostic accuracy and biopsy efficiency, which might be a promising solution to improve the quality of cervical cancer screening in low-resource settings.

[Revision of the French colposcopic terminology]

OBJECTIVES

To revise the 1983 colposcopic terminology form the French Society of Colposcopy and cervicovaginal pathology (SFCPCV).

METHODS

All the three following steps of colposcopic examination were considered for the description of various colposcopic features: inspection without coloration, followed by the application of acetic acid and iodine staining. This revised terminology now includes the different possible colposcopic aspects of the normal cervix, including the ectropion and the normal transformation zone. It also includes colposcopic appearance of abnormal glandular cervical epithelium and of vaginal epithelium. The revised nomenclature was reviewed by all the board of the SFCPCV and was finally approved during the 45^th annual conference of the SFCPCV.

RESULTS

Abnormal transformation zone grade (TAG) 1a and 1b have been brought together under the sole TAG1 designation. TAG2a and TAG2b now correspond to TAG2, whereas TAG2c corresponds to TAG3. Colposcopic report should mention the interpretability of the colposcopic examination, with the precise type of the squamocolumnar junction (1, 2 or 3), the colposcopic impression, the size of any TAG and finally mention whether one or multiple biopsies were taken and their precise location. Colposcopic impression must give priority to the most pejorative colposcopic aspect which takes precedence over others.

CONCLUSION

When performing colposcopy, one should keep in mind that this examination only relies on the interpretation of various colposcopic signs and images with this not guaranteeing for diagnosis. Only histological analysis of a possible guided cervical biopsy provides for a precise diagnosis.

Colposcopic accuracy in diagnosing squamous intraepithelial lesions: a systematic review and meta-analysis of the International Federation of Cervical Pathology and Colposcopy 2011 terminology

BACKGROUND

Colposcopy is an important tool in diagnosing cervical cancer, and the International Federation of Cervical Pathology and Colposcopy (IFCPC) issued the latest version of the guidelines in 2011. This study aims to systematically assess the accuracy of colposcopy in predicting low-grade squamous intraepithelial lesions or worse (LSIL+) / high-grade squamous intraepithelial lesions or worse (HSIL+) under the 2011 IFCPC terminology.

METHODS

We performed a systematic review and meta-analysis, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched for studies about the performance of colposcopy in diagnosing cervical intraepithelial neoplasia under the new IFCPC colposcopy terminology from PubMed, Embase, Web of Science and the Cochrane database. Data were independently extracted by two authors and an overall diagnostic performance index was calculated under two colposcopic thresholds.

RESULTS

Totally, fifteen articles with 22,764 participants in compliance with the criteria were included in meta-analysis. When colposcopy was used to detect LSIL+, the combined sensitivity and specificity were 0.92 (95% CI 0.88-0.95) and 0.51 (0.43-0.59), respectively. When colposcopy was used to detect HSIL+, the combined sensitivity and specificity were 0.68 (0.58-0.76) and 0.93 (0.88-0.96), respectively.

CONCLUSION

In accordance with the 2011 IFCPC terminology, the accuracy of colposcopy has improved in terms of both sensitivity and specificity. Colposcopy is now more sensitive with LSIL+ taken as the cut-off value and is more specific to HSIL+. These findings suggest we are avoiding under- or overdiagnosis both of which impact on patients' well-being.

Application of EfficientNet-B0 and GRU-based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions

BACKGROUND

Colposcopy is indispensable for the diagnosis of cervical lesions. However, its diagnosis accuracy for high-grade squamous intraepithelial lesion (HSIL) is at about 50%, and the accuracy is largely dependent on the skill and experience of colposcopists. The advancement in computational power made it possible for the application of artificial intelligence (AI) to clinical problems. Here, we explored the feasibility and accuracy of the application of AI on precancerous and cancerous cervical colposcopic image recognition and classification.

METHODS

The images were collected from 6002 colposcopy examinations of normal control, low-grade squamous intraepithelial lesion (LSIL), and HSIL. For each patient, the original, Schiller test, and acetic-acid images were all collected. We built a new neural network classification model based on the hybrid algorithm. EfficientNet-b0 was used as the backbone network for the image feature extraction, and GRU(Gate Recurrent Unit)was applied for feature fusion of the three modes examinations (original, acetic acid, and Schiller test).

RESULTS

The connected network classifier achieved an accuracy of 90.61% in distinguishing HSIL from normal and LSIL. Furthermore, the model was applied to "Trichotomy", which reached an accuracy of 91.18% in distinguishing the HSIL, LSIL and normal control at the same time.

CONCLUSION

Our results revealed that as shown by the high accuracy of AI in the classification of colposcopic images, AI exhibited great potential to be an effective tool for the accurate diagnosis of cervical disease and for early therapeutic intervention in cervical precancer.

Evaluating the Feasibility of Machine-Learning-Based Predictive Models for Precancerous Cervical Lesions in Patients Referred for Colposcopy

Background: Colposcopy plays an essential role in cervical cancer control, but its performance remains unsatisfactory. This study evaluates the feasibility of machine learning (ML) models for predicting high-grade squamous intraepithelial lesions or worse (HSIL+) in patients referred for colposcopy by combining colposcopic findings with demographic and screening results. Methods: In total, 7485 patients who underwent colposcopy examination in seven hospitals in mainland China were used to train, internally validate, and externally validate six commonly used ML models, including logistic regression, decision tree, naïve bayes, support vector machine, random forest, and extreme gradient boosting. Nine variables, including age, gravidity, parity, menopause status, cytological results, high-risk human papillomavirus (HR-HPV) infection type, HR-HPV multi-infection, transformation zone (TZ) type, and colposcopic impression, were used for model construction. Results: Colposcopic impression, HR-HPV results, and cytology results were the top three variables that determined model performance among all included variables. In the internal validation set, six ML models that integrated demographics, screening results, and colposcopic impression showed significant improvements in the area under the curve (AUC) (0.067 to 0.099) and sensitivity (11.55% to 14.88%) compared with colposcopists. Greater increases in AUC (0.087 to 0.119) and sensitivity (17.17% to 22.08%) were observed in the six models with the external validation set. Conclusions: By incorporating demographics, screening results, and colposcopic impressions, ML improved the AUC and sensitivity for detecting HSIL+ in patients referred for colposcopy. Such models could transform the subjective experience into objective judgments to help clinicians make decisions at the time of colposcopy examinations.

Association of Swede Score and 2011 IFCPC Nomenclature in Women with Abnormal Cytology

OBJECTIVE

 To assess the association between two colposcopic indices, the Swede score and the 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC) Nomenclature as well as to determine the efficacy of the Swede score with cutoffs of 7 and 8.

METHODS

 In the present cross-sectional pilot study, 34 women who had at least 1 colposcopy-directed biopsy due to abnormal cytology were enrolled. The colposcopic findings were scored by both the Swede score and the 2011 IFCPC Nomenclature and were compared with each other. The Kappa coefficient and the McNemar test were used. Accuracy, sensitivity, specificity, and positive and negative predictive values (NPV and PPV, respectively) were calculated, as well as the effectiveness with cutoffs of 7 and 8 in identifying cervical intraepithelial neoplasm (CIN) 2+ when using the Swede score.

RESULTS

 The correlation between the 2 colposcopic indices was 79.41%. The Kappa coefficient and the McNemar p-value were 0.55 and 0.37, respectively. The IFCPC Nomenclature had sensitivity, specificity, accuracy, PPV, and NPV of 85.71, 55.00, 67.64, 57.14, and 84.61%, respectively. The Swede score had sensitivity, specificity, accuracy, PPV, and NPV of 100, 63.15, 79.41, 68.18, and 100%, respectively. A Swede score cutoff of 7 for CIN 2+ detection had a specificity of 94.73%, while with a cutoff of 8 it increased to 100%. The sensitivity for both values was 60%. The PPV and NPV for cutoffs of 7 and 8 were 90 and 75 and 100 and 76%, respectively.

CONCLUSION

 Although both colposcopic indices have good reproducibility, the Swede score showed greater accuracy, sensitivity, and specificity in identifying CIN 2 + , especially when using a cutoff of 8.

Diagnosis of Cervical Cancer and Pre-Cancerous Lesions by Artificial Intelligence: A Systematic Review

OBJECTIVE

The likelihood of timely treatment for cervical cancer increases with timely detection of abnormal cervical cells. Automated methods of detecting abnormal cervical cells were established because manual identification requires skilled pathologists and is time consuming and prone to error. The purpose of this systematic review is to evaluate the diagnostic performance of artificial intelligence (AI) technologies for the prediction, screening, and diagnosis of cervical cancer and pre-cancerous lesions.

MATERIALS AND METHODS

Comprehensive searches were performed on three databases: Medline, Web of Science Core Collection (Indexes = SCI-EXPANDED, SSCI, A & HCI Timespan) and Scopus to find papers published until July 2022. Articles that applied any AI technique for the prediction, screening, and diagnosis of cervical cancer were included in the review. No time restriction was applied. Articles were searched, screened, incorporated, and analyzed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines.

RESULTS

The primary search yielded 2538 articles. After screening and evaluation of eligibility, 117 studies were incorporated in the review. AI techniques were found to play a significant role in screening systems for pre-cancerous and cancerous cervical lesions. The accuracy of the algorithms in predicting cervical cancer varied from 70% to 100%. AI techniques make a distinction between cancerous and normal Pap smears with 80-100% accuracy. AI is expected to serve as a practical tool for doctors in making accurate clinical diagnoses. The reported sensitivity and specificity of AI in colposcopy for the detection of CIN2+ were 71.9-98.22% and 51.8-96.2%, respectively.

CONCLUSION

The present review highlights the acceptable performance of AI systems in the prediction, screening, or detection of cervical cancer and pre-cancerous lesions, especially when faced with a paucity of specialized centers or medical resources. In combination with human evaluation, AI could serve as a helpful tool in the interpretation of cervical smears or images.

Improving colposcopic accuracy for cervical precancer detection: a retrospective multicenter study in China

Background

Colposcopy alone can result in misidentification of high-grade squamous intraepithelial or worse lesions (HSIL +), especially for women with Type 3 transformation zone (TZ) lesions, where colposcopic assessment is particularly imprecise. This study aimed to improve HSIL + case identification by supplementing referral screening results to colposcopic findings.

Methods

This is an observational multicenter study of 2,417 women, referred to colposcopy after receiving cervical cancer screening results. Logistic regression analysis was conducted under uni- and multivariate models to identify factors which could be used to improve HSIL + case identification. Histological diagnosis was established as the gold standard and is used to assess accuracy, sensitivity, and specificity, as well as to incrementally improve colposcopy.

Results

Multivariate analysis highlighted age, TZ types, referral screening, and colposcopists’ skills as independent factors. Across this sample population, diagnostic accuracies for detecting HSIL + increased from 72.9% (95%CI 71.1–74.7%) for colposcopy alone to 82.1% (95%CI 80.6–83.6%) after supplementing colposcopy with screening results. A significant increase in colposcopic accuracy was observed across all subgroups. Although, the highest increase was observed in women with a TZ3 lesion, and for those diagnosed by junior colposcopists.

Conclusion

It appears possible to supplement colposcopic examinations with screening results to improve HSIL + detection, especially for women with TZ3 lesions. It may also be possible to improve junior colposcopists’ diagnoses although, further psychological research is necessary. We need to understand how levels of uncertainty influence diagnostic decisions and what the concept of “experience” actually is and what it means for colposcopic practice.

Role of Artificial Intelligence Interpretation of Colposcopic Images in Cervical Cancer Screening

The accuracy of colposcopic diagnosis depends on the skill and proficiency of physicians. This study evaluated the feasibility of interpreting colposcopic images with the assistance of artificial intelligence (AI) for the diagnosis of high-grade cervical intraepithelial lesions. This study included female patients who underwent colposcopy-guided biopsy in 2020 at two institutions in the Republic of Korea. Two experienced colposcopists reviewed all images separately. The Cerviray AI® system (AIDOT, Seoul, Korea) was used to interpret the cervical images. AI demonstrated improved sensitivity with comparable specificity and positive predictive value when compared with the colposcopic impressions of each clinician. The areas under the curve were greater with combined impressions (both AI and that of the two colposcopists) of high-grade lesions, when compared with the individual impressions of each colposcopist. This study highlights the feasibility of the application of an AI system in cervical cancer screening. AI interpretation can be utilized as an assisting tool in combination with human colposcopic evaluation of exocervix.

Visual appearance of the uterine cervix differs on the basis of HPV type status in high-grade squamous intraepithelial lesion: the results of a reliable method

Background

This study aimed to evaluate the differences in cervical appearance among different human papillomavirus (HPV) genotypes in patients with high-grade squamous intraepithelial lesions (HSILs).

Methods

A total of 239 histopathological HSIL patients were included and divided into eight groups on the basis of HPV genotype in this prospective study. We present a reliable imaging method that provides reproducible, sensitive and unbiased assessments of cervical appearance characteristics. Colorimetric and morphometric data of colposcopic patterns after the application of acetic acid and iodine were acquired using ImageJ software and the surrounding normal regions were used as controls.

Results

The differences in red, green, blue and mean greyscale values in acetowhite epithelium obtained from ImageJ were not significant between the HPV16 and HPV18 groups (P < 0.05). The differences in red, green, and mean greyscale values in iodine staining were significant between the HPV18 and the other groups (P < 0.05). The frequency of the occurrence of the coarse mosaic patterns was significantly different among groups (P < 0.05), reducing in sequence were the HPV16, HPV-negative, HPV18, HPV31/33 and HPV52/58 groups. For the lesion area of HSILs, the HPV-negative group was the largest. The sensitivity of colposcopic impression varied among HPV genotypes (P < 0.01), being lowest in the HPV52 group.

Conclusions

Although being nonspecific, iodine negativity should be concerned in HPV18-positive lesions which is closely related to glandular epithelium. Vascular patterns in HPV52/58-positive HSIL are quite occult and tend to be missed by colposcopists. HPV-negative lesions are prone to be large and present typical vascular patterns despite being rare.

Assessing colposcopic accuracy for high-grade squamous intraepithelial lesion detection: a retrospective, cohort study

Background

Inappropriate management of high-grade squamous intraepithelial lesions (HSIL) may be the result of an inaccurate colposcopic diagnosis. The aim of this study was to assess colposcopic performance in identifying HSIL+ cases and to analyze the associated clinical factors.

Methods

Records from 1130 patients admitted to Shenzhen Maternal and Child Healthcare Hospital from 12th January, 2018 up until 30th December, 2018 were retrospectively collected, and included demographics, cytological results, HPV status, transformation zone type, number of cervical biopsy sites, colposcopists’ competencies, colposcopic impressions, as well as histopathological results. Colposcopy was carried out using 2011 colposcopic terminology from the International Federation of Cervical Pathology and Colposcopy. Logistic regression modelling was implemented for uni- and multivariate analyses. A forward stepwise approach was adopted in order to identify variables associated with colposcopic accuracy. Histopathologic results were taken as the comparative gold standard.

Results

Data from 1130 patient records were collated and analyzed. Colposcopy was 69.7% accurate in identifying HSIL+ cases. Positive predictive value, negative predictive value, sensitivity and specificity of detecting HSIL or more (HSIL+) were 35.53%, 64.47%, 42.35% and 77.60%, respectively. Multivariate analysis highlighted the number of biopsies, cytology, and transformation zone type as independent factors. Age and HPV subtype did not appear to statistically correlate with high-grade lesion/carcinoma.

Conclusion

Evidence presented here suggests that colposcopy is only 69.7% accurate at diagnosing HSIL. Even though not all HSIL will progress into cancer it is considered pre-cancerous and therefore early identification will save lives. The number of biopsies, cytology and transformation zone type appear to be predictors of misdiagnosis and therefore should be considered during clinical consultations and by way of further research.

Clinical application of the 2011 IFCPC colposcope terminology

BACKGROUND

Colposcopy offers an accurate way to the diagnose of cervical precancerous lesions. However, the diagnostic accuracy of colposcopy is unsatisfied. This study was to evaluate colposcopic accuracy according to the 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC) terminology.

METHODS

A retrospective cohort study was performed in 1,838 patients who underwent colposcopy in Shandong Qianfoshan Hospital, Cheeloo College of Medicine, Shandong University from October 2013 to April 2018. Using conization or cervical biopsy pathology as the gold standard, the agreement between colposcopic diagnosis and pathologic diagnosis was calculated, and correlations between variables were analyzed.

RESULTS

As an authoritative and widely used terminology for colposcopy diagnosis, the 2011 IFCPC terminology has certain clinical practicality and diagnostic accuracy. However, some signs such as mosaic, punctation, sharp border, inner border sign and ridge sign had high specificity but unsatisfactory sensitivity, which limited the diagnostic value. Therefore, we discussed the Lugol's staining, a very common sign in colposcopy, and analyzed the diagnostic significance of bright yellow staining in low-grade squamous intraepithelial lesion (LSIL) and mustard yellow staining in high-grade squamous intraepithelial lesion (HSIL). The results showed that mustard yellow may be a valuable indicator in the diagnosis of HSIL.

CONCLUSION

The 2011 IFCPC colposcope terminology has standardized interpretations of the colposcopic findings and improved the accuracy of colposcopy diagnosis. The aceto-white epithelium still has important diagnostic value; however, the value of a few signs is needed to be discussed and new signs are expected to be discovered. Although the significance of Lugol's staining was diminishing, mustard yellow might be a valuable indicator for the diagnosis of HSIL.

Analysis of the agreement between colposcopic impression and histopathological diagnosis of cervical biopsy in a single tertiary center of Chengdu

PURPOSE

The aim of this retrospective study was to analyze the agreement between colposcopic impression and histopathological diagnosis of cervical biopsy.

METHODS

The medical records of patients underwent a colposcopy-guided cervical biopsy at Chengdu Women's and Children's Central Hospital between January 2017 and January 2019 were collected, including age, menopausal status, cervical cytology and human papillomavirus (HPV) test results, type of transformation zone, colposcopic diagnosis and histopathological outcomes of cervical biopsy. Colposcopy was carried out using 2011 colposcopic terminology of International Federation for Cervical Pathology and Colposcopy (IFCPC). Related variables were analyzed.

RESULTS

A total of 495 patients were collected in this study. The perfect agreement between colposcopic impression and histopathological diagnosis was 46.9%, and the strength of agreement with kappa value was 0.283 (P < 0.001), and the agreement within 1 grade was 93.5%. Positive predictive value (PPV), negative predictive value (NPV), sensitivity, specificity, false-positive rate and false-negative rate of detecting HSIL or more (HSIL +) were 93.1%, 57.8%, 80.9%, 93.9%, 6.1% and 45.3%, respectively. Colposcopic diagnosis more often underestimated (43.2%) [especially in HSIL (59.3%) and carcinoma (70.7%) patients] than overestimated (9.9%) in cervical lesions. The results of cytology, HPV status, patients' age and different experiences of practitioners were the factors for under-diagnosis of HSIL + by colposcopy.

CONCLUSION

Colposcopy is an excellent tool to estimate cervical high-grade lesion but is imprecise. Many factors can bias the diagnosis of colposcopy, especially the known results of cervical cytology and HPV. Precise diagnosis of cervical lesion should rely on the colposcopy-directed biopsy.

Factors Correlated with the Accuracy of Colposcopy-Directed Biopsy: A Systematic Review and Meta-Analysis

PURPOSE/AIM OF THE STUDY

Colposcopy-directed cervical biopsy has played a major role in diagnosing cervical lesions. The precision of colposcopy-guided biopsy has been questioned. We analyzed several factors that may be correlated with the accuracy of biopsy.

METHODS

PubMed, EMBASE were searched from January 1, 1998 to March 1, 2020. Odds ratio with 95% confidence intervals (CIs) were calculated.

SELECTION CRITERIA

Included studies evaluated factors correlated with the accuracy of biopsy and patients' final diagnosis was established by histological examination of the specimen obtained by conization, loop electrosurgical excision procedure (LEEP), or colpohysterectomy.

RESULTS

A total of 10 studies were selected for the systematic review and meta-analysis. The pooled analysis indicated that the diagnostic inaccuracies of colposcopy-directed cervical biopsy were magnified in women who were 50 years of age or older. Postmenopausal status and transformation zone 3 type were also associated with the diagnostic inaccuracies of colposcopy-directed biopsy. High-grade squamous intraepithelial lesions had better concordance rates than low-grade squamous intraepithelial lesions. The number of vaginal deliveries, number of biopsies, and HPV type were associated with biopsy underdiagnosis and biopsy overestimation.

CONCLUSIONS

This meta-analysis found that the correlation between the histological findings at biopsy and after surgical treatment was influenced by women's age, menopausal status, and the transformation zone type. The diagnostic efficacy was also better for high-grade squamous intraepithelial lesions than for low-grade squamous intraepithelial lesions. Further large-scale randomized clinical trials are required to analyze the factors correlated with biopsy underdiagnosis and biopsy overestimation.

Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies

BACKGROUND

Colposcopy diagnosis and directed biopsy are the key components in cervical cancer screening programs. However, their performance is limited by the requirement for experienced colposcopists. This study aimed to develop and validate a Colposcopic Artificial Intelligence Auxiliary Diagnostic System (CAIADS) for grading colposcopic impressions and guiding biopsies.

METHODS

Anonymized digital records of 19,435 patients were obtained from six hospitals across China. These records included colposcopic images, clinical information, and pathological results (gold standard). The data were randomly assigned (7:1:2) to a training and a tuning set for developing CAIADS and to a validation set for evaluating performance.

RESULTS

The agreement between CAIADS-graded colposcopic impressions and pathology findings was higher than that of colposcopies interpreted by colposcopists (82.2% versus 65.9%, kappa 0.750 versus 0.516, p < 0.001). For detecting pathological high-grade squamous intraepithelial lesion or worse (HSIL+), CAIADS showed higher sensitivity than the use of colposcopies interpreted by colposcopists at either biopsy threshold (low-grade or worse 90.5%, 95% CI 88.9-91.4% versus 83.5%, 81.5-85.3%; high-grade or worse 71.9%, 69.5-74.2% versus 60.4%, 57.9-62.9%; all p < 0.001), whereas the specificities were similar (low-grade or worse 51.8%, 49.8-53.8% versus 52.0%, 50.0-54.1%; high-grade or worse 93.9%, 92.9-94.9% versus 94.9%, 93.9-95.7%; all p > 0.05). The CAIADS also demonstrated a superior ability in predicting biopsy sites, with a median mean-intersection-over-union (mIoU) of 0.758.

CONCLUSIONS

The CAIADS has potential in assisting beginners and for improving the diagnostic quality of colposcopy and biopsy in the detection of cervical precancer/cancer.

Factors predicting the spontaneous regression of cervical high-grade squamous intraepithelial lesions (HSIL/CIN2)

PURPOSE

To determine clinical, pathological and virological factors predicting the spontaneous regression of HSIL/CIN2.

METHODS

This retrospective study included 73 patients with HSIL/CIN2 diagnosed by biopsy between 2012 and 2016 and followed-up without treatment in the department of gynecology at Bordeaux University Hospital. All biopsies sampled inside or outside our department were reviewed and immunolabelled for p16 and Ki67. The response rate was the regression or the disappearance of HSIL/CIN2 as defined by the regression or the disappearance of initial colposcopic findings, cytological and/or histological results.

RESULTS

The diagnosis of CIN2 was confirmed in 63 of 70 biopsies available for review. The Cohen's kappa coefficient was κ = 90%, indicating almost perfect inter-observer agreement. The lesion spontaneously regressed or disappeared in 36 of 60 patients (60%) with confirmed CIN2 during a median follow-up of 20 months (range 6-55). Baseline factors influencing the response rate were colposcopic findings (69% with minor change vs 31% with major change, p = 0.033), cytological results (72% with ASCUS/LSIL vs 28% with ASC-H/HSIL, p = 0.018), and HPV genotyping (71% with HPV not 16 vs 42% with HPV-16, p = 0.027). The other factors (age, smoking, surface area of the lesion, p16 and Ki67 expressions) did not significantly influence the outcome.

CONCLUSION

Colposcopic findings, cytological results, and HPV genotyping were baseline factors predicting spontaneous regression of HSIL/CIN2.

The relationship of human papillomavirus infection with endocervical glandular involvement on cone specimens in women with cervical intraepithelial neoplasia

OBJECTIVE

The aim of study was to evaluate the association of endocervical gland involvement (EGI) on histological samples with high risk (HR) human papillomavirus (HPV) infection and with the persistence/recurrence rate of cervical intraepithelial neoplasia (CIN) after treatment.

METHODS

A total of 1301 subjects who had conization procedures after cervical punch biopsies (533 persistent CIN1, 768 CIN2+ including 20 microinvasive cervical cancer) were enrolled in the study. HPV genotypes were identified using the INNO-LiPA HPV genotyping assay on cervical scraping. Logistic regression and Cox regression analyses were used to evaluate the association of EGI on the persistence/recurrence rate of CIN after treatment.

RESULTS

The rate of EGI on final histology was 46.3% (602/1301). HPV 16 was the only HR-HPV significantly associated with increasing rates of EGI (231/602 as compared to 211/699, p = 0.002). EGI was also associated with an excess of multiple HR-HPV infections (237/602 as compared with 225/699, p = 0.006). After correction for confounders, the odds ratio of EGI among women infected by HPV 16 was 1.41 (95% CI = 1.12-178). CIN2+ lesions were diagnosed in 40.5% (283/699) of EGI negative subjects and 86.7% (522/602, p < 0.001 compared to negative subjects) of EGI positive subjects.After a median of 25 months of follow-up (IQR = 15-47) of 1090 treated women, the persistence of HPV 16 during follow-up was 38.1% (93/217, p = 0.03 compared to EGI negative) among EGI positive and 32% (58/181) among controls. After corrections for potential confounders, the odds ratio of CIN2+ persistence and or recurrence was higher among EGI positive (OR = 2.35, 95% CI = 1.16-4.77) than negative controls.

CONCLUSION

EGI on histological samples is associated with increased rates of HPV 16, multiple high risk-HPV infections and CIN2+ lesions. EGI positive subjects also had an increased CIN recurrence/persistence after treatment compared to controls.

Evaluation of the accuracy of colposcopy in detecting high-grade squamous intraepithelial lesion and cervical cancer

PURPOSE

The primary aim of this study was to evaluate the diagnostic accuracy of colposcopy in identifying high-grade squamous intraepithelial lesion or worse (HSIL+) and the characteristic performance of colposcopic images with various severity levels of cervical lesions.

METHODS

The medical records from 1828 women who underwent colposcopy at Affiliated Hospital of Tongji University from February 2016 to March 2019 were reviewed. Human papilloma virus (HPV) GenoArray test kit (HybriBio Ltd) and Thinprep cytologic test (TCT, Hologic, USA) were used to perform HPV genotyping and cytology. All colposcopic images were collected from the standard-of-care colposcope (Leisegang 3ML LED) and evaluated based on the 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC) Colposcopy Standards. The linear by linear association, Pearson χ² test, χ² test, Kappa test, McNemar test and risk test were used to perform statistical analyses.

RESULTS

The consistency between colposcopy and biopsy pathology was 59.35% with the moderate strength of kappa coefficient of 0.464. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of colposcopy and cytology for HSIL+ were 56.29%, 93.82%, 77.47%, 85.04% and 37.13%, 98.49%, 90.29%, 80.58%, respectively. The colposcopic features of HSIL+ were as follows: (1) thick or bulgy acetowhite epithelium with sharp border; (2) completely nonstained of Lugol's iodine; (3) type III/IV/V of gland openings; (4) punctation or atypical vessels.

CONCLUSION

The data and findings herein provide the resource for evaluating the diagnostic value of colposcopy, and suggested that the accuracy of colposcopy is required to be further improved.

Application of 2011 International Federation for Cervical Pathology and Colposcopy Terminology on the Detection of Vaginal Intraepithelial Neoplasia

Purpose

To evaluate the colposcopic accuracy of the detection of vaginal intraepithelial neoplasia (VaIN) according to the colposcopic terminology for the vagina from the 2011 International Federation of Cervical Pathology and Colposcopy (IFCPC).

Methods

A total of 467 women who were suspected of having VaIN and underwent colposcopy at Obstetrics and Gynecology Hospital of Fudan University from January to December 2018 were included in this retrospective cohort study. The 2011 IFCPC revised terminology for the vagina was applied, and the agreement between colposcopic diagnosis and vaginal biopsy pathology was analysed.

Results

Agreement between colposcopy and pathology was 69.16% (kappa=0.437, p<0.001), with 23.34% overestimated and 7.49% underestimated diagnosis for colposcopy. The agreement was the lowest (35.71%) in the high-grade VaIN group, which was significantly different from that of other lesion grade groups (p<0.01). Among grade 1 findings, thin acetowhite epithelium was the most frequent (80.51%). Grade 2 findings and vascular patterns were rare. The positive predictive values of the micropapillary pattern were 55.98% for low-grade VaIN and 5.98% for high-grade VaIN. The specificity of iodine negativity was 10.92% for low-grade VaIN and 8.30% for high-grade VaIN. There were significant differences in the maximum size of single lesions and in the number of lesions among different grade lesion groups.

Conclusion

The agreement between colposcopy findings utilizing the 2011 IFCPC terminology and vaginal pathology is moderate, and more definite findings for high-grade VaIN may be needed. The micropapillary pattern can be considered an alternative low-grade finding, while iodine staining is nonspecific for all lesions. Scattered and spotty lesions suggest low-grade VaIN, while large single lesions suggest high-grade VaIN.

The challenges of colposcopy for cervical cancer screening in LMICs and solutions by artificial intelligence

BACKGROUND

The World Health Organization (WHO) called for global action towards the elimination of cervical cancer. One of the main strategies is to screen 70% of women at the age between 35 and 45 years and 90% of women managed appropriately by 2030. So far, approximately 85% of cervical cancers occur in low- and middle-income countries (LMICs). The colposcopy-guided biopsy is crucial for detecting cervical intraepithelial neoplasia (CIN) and becomes the main bottleneck limiting screening performance. Unprecedented advances in artificial intelligence (AI) enable the synergy of deep learning and digital colposcopy, which offers opportunities for automatic image-based diagnosis. To this end, we discuss the main challenges of traditional colposcopy and the solutions applying AI-guided digital colposcopy as an auxiliary diagnostic tool in low- and middle- income countries (LMICs).

MAIN BODY

Existing challenges for the application of colposcopy in LMICs include strong dependence on the subjective experience of operators, substantial inter- and intra-operator variabilities, shortage of experienced colposcopists, consummate colposcopy training courses, and uniform diagnostic standard and strict quality control that are hard to be followed by colposcopists with limited diagnostic ability, resulting in discrepant reporting and documentation of colposcopy impressions. Organized colposcopy training courses should be viewed as an effective way to enhance the diagnostic ability of colposcopists, but implementing these courses in practice may not always be feasible to improve the overall diagnostic performance in a short period of time. Fortunately, AI has the potential to address colposcopic bottleneck, which could assist colposcopists in colposcopy imaging judgment, detection of underlying CINs, and guidance of biopsy sites. The automated workflow of colposcopy examination could create a novel cervical cancer screening model, reduce potentially false negatives and false positives, and improve the accuracy of colposcopy diagnosis and cervical biopsy.

CONCLUSION

We believe that a practical and accurate AI-guided digital colposcopy has the potential to strengthen the diagnostic ability in guiding cervical biopsy, thereby improves cervical cancer screening performance in LMICs and accelerates the process of global cervical cancer elimination eventually.

A standardized simulation training program to type 1 loop electrosurgical excision of the transformation zone: a prospective observational study

PURPOSE

To evaluate a simulation-based standardized training program for type 1 loop electrosurgical excision procedure (LEEP) under direct colposcopic vision in postgraduate teaching.

METHODS

Seventeen participants (five experienced and 12 novice surgeons) performed 170 simulated cervical excisional procedures. Each participant performed 10 type 1 (cone length between 8 and 10 mm) excisional procedures under direct colposcopic vision on a low-fidelity simulator. Length of specimen was measured after each excision allowing the surgeons a subsequent resection to ensure a cone length of more than 8 mm. Main outcome measures were cone length, specimen fragmentation, and a self-developed score (LEEP score), which allowed the simultaneous evaluation of both measured parameters.

RESULTS

The precision of the excision showed statistically significant improvement in the novice group during the training procedures after five procedures [LEEP score 1.61 (SD 1.34) vs. 0.46 (SD 0.58); p = 0.023], while experts showed consistently high performance. Inexperienced surgeons performed more frequently cuts that were too deep than experienced surgeons (33/120, 27.5% vs. 4/50, 8%; p = 0.003).

CONCLUSIONS

Low-fidelity simulation training seems to be an effective method for learning the accurate cone length for a type 1 excision for novice surgeons. As excessive excisions are related with high risk for premature delivery in subsequent pregnancies, in our opinion, LEEP should be practiced in simulation training, especially before performing in woman of reproductive age.

Office Cervicoscopy versus Stationary Colposcopy in Suspicious Cervix: A Randomized Controlled Trial

Study Objective:

The objective of the study was to estimate the diagnostic accuracy and doctor satisfaction of small caliber office cervicoscopy versus stationary colposcopy in diagnosis of ectocervical as well as endocervical lesions in women clinically presented with suspicious cervix.

Patients and Methods:

Eligible 112 cases with clinically suspicious cervix were randomized into Group A (56 cases) and Group B (56 cases) who were subjected to small caliber office cervicoscopy and stationary colposcopy, respectively. The outcome was the diagnostic accuracy and safety of both tools for detection of ectocervical and endocervical cervical lesions.

Results:

There was no statistically significant difference between both groups regarding parity, previous abortion, age at marriage, duration of marriage, and age at menarche and menopause. On unaided naked eye examination of the cervix (UNEE), there were no statistically significant differences between both groups. Diagnostic indices were similar in both groups apart from the finding that office cervicoscopy was more sensitive for detection of endocervical abnormalities. Doctors were significantly more satisfied with stationary colposcopy than office cervicoscopy.

Conclusions:

Office cervicoscopy is a good complementary tool added to stationary colposcopy for detection of cervical lesions in cases with suspicious cervix as an example of high-risk group for cervical cancer. Due to its small caliber, cervicoscopy offers a better evaluation of the endocervical canal, especially in cases of Type 2 and 3 transformation zone with a possibility of examination of the endometrial cavity.