Role of colposcopy in the management of women with abnormal cytology

Detecting and localizing cervical lesions in colposcopic images with deep semantic feature mining

Objective

This study aims to investigate the feasibility of employing artificial intelligence models for the detection and localization of cervical lesions by leveraging deep semantic features extracted from colposcopic images.

Methods

The study employed a segmentation-based deep learning architecture, utilizing a deep decoding network to integrate prior features and establish a semantic segmentation model capable of distinguishing normal and pathological changes. A two-stage decision model is proposed for deep semantic feature mining, which combines image segmentation and classification to categorize pathological changes present in the dataset. Furthermore, transfer learning was employed to create a feature extractor tailored to colposcopic imagery. Multi-scale data were bolstered by an attention mechanism to facilitate precise segmentation of lesion areas. The segmentation results were then coherently mapped back onto the original images, ensuring an integrated visualization of the findings.

Results

Experimental findings demonstrated that compared to algorithms solely based on image segmentation or classification, the proposed approach exhibited superior accuracy in distinguishing between normal and lesioned colposcopic images. Furthermore, it successfully implemented a fully automated pixel-based cervical lesion segmentation model, accurately delineating regions of suspicious lesions. The model achieved high sensitivity (96.38%), specificity (95.84%), precision (97.56%), and f1 score (96.96%), respectively. Notably, it accurately estimated lesion areas, providing valuable guidance to assisting physicians in lesion classification and localization judgment.

Conclusion

The proposed approach demonstrates promising capabilities in identifying normal and cervical lesions, particularly excelling in lesion area segmentation. Its accuracy in guiding biopsy site selection and subsequent localization treatment is satisfactory, offering valuable support to healthcare professionals in disease assessment and management.

Evaluation of follow-up colposcopy procedures after abnormal cervical screening result across a statewide study in Mississippi

PURPOSE

Cervical screening is used to detect and treat precancers to prevent invasive cancers. However, successful prevention also requires adequate follow-up and treatment of individuals with abnormal screening results. The aim was to investigate demographics, clinical characteristics, and follow-up status for individuals needing colposcopy after an abnormal screening result.

METHODS

The STRIDES (Studying Risk to Improve DisparitiES) cohort comprises individuals undergoing cervical cancer screening and management at a Mississippi Health Department or University of Mississippi clinic. Follow-up status, demographics, and clinical data were assessed from electronic health records and, if necessary, patient navigation on individuals identified as needing a colposcopy after an abnormal screening.

RESULTS

Of the 1,458 individuals requiring colposcopy, 43.0% had the procedure within 4 months, 16.4% had a delayed procedure, and 39.5% had no documented colposcopy follow-up, with significant predictors of follow-up identified as age and cytology diagnosis. Individuals 30 + were more likely to have follow up with a colposcopy compared to individuals < 30 years (49% and 38.7%, respectively; p < .001). Individuals with cytology diagnoses of LSIL (52.9%), ASC-H (51.4%), and HSIL (62.3%) had higher percentages of adherence to follow-up guidelines (p < .001). In total, we found that 78% of individuals had some type of follow-up, including a repeat screening visit.

CONCLUSION

Despite high cervical cancer screening rates among Mississippians, a substantial proportion did not have adequate next-step intervention. However, it is encouraging that highest risk individuals were more likely to have a colposcopy. Regardless, continuing to understand the underlying causes for incomplete follow-up is crucial for timely secondary targeted interventions to reduce cervical cancer burden, promote awareness, and improve health outcomes.

Cervical Cancer: Precursors and Prevention

Cervical cancer, caused due to oncogenic types of human papillomavirus (HPV), is a leading preventable cause of cancer morbidity and mortality globally. Chronic, persistent HPV infection-induced cervical precursor lesions, if left undetected and untreated, can progress to invasive cancer. Cervical cancer screening approaches have evolved from cytology (Papanicolaou test) to highly sensitive HPV-based molecular methods and personalized, risk-stratified, management guidelines. Innovations like self-collection of samples to increase screening access, innovative triage methods to optimize management of screen positives, and scalable and efficacious precancer treatment approaches will be key to further enhance the utility of prevention interventions.

Enhancing Cervical Cancer Screening: Review of p16/Ki-67 Dual Staining as a Promising Triage Strategy

Cervical cancer, primarily caused by high-risk human papillomavirus (HR-HPV) types 16 and 18, is a major global health concern. Persistent HR-HPV infection can progress from reversible precancerous lesions to invasive cervical cancer, which is driven by the oncogenic activity of human papillomavirus (HPV) genes, particularly E6 and E7. Traditional screening methods, including cytology and HPV testing, have limited sensitivity and specificity. This review explores the application of p16/Ki-67 dual-staining cytology for cervical cancer screening. This advanced immunocytochemical method allows for simultaneously detecting p16 and Ki-67 proteins within cervical epithelial cells, offering a more specific approach for triaging HPV-positive women. Dual staining and traditional methods are compared, demonstrating their high sensitivity and negative predictive value but low specificity. The increased sensitivity of dual staining results in higher detection rates of CIN2+ lesions, which is crucial for preventing cervical cancer progression. However, its low specificity may lead to increased false-positive results and unnecessary biopsies. The implications of integrating dual staining into contemporary screening strategies, particularly considering the evolving landscape of HPV vaccination and changes in HPV genotype prevalence, are also discussed. New guidelines and further research are necessary to elucidate the long-term effects of integrating dual staining into screening protocols.

Diagnostic value of high-risk HPV E6/E7 mRNA in patients with ASCUS

OBJECTIVE

To investigate the infection status of high-risk human papillomavirus (HR-HPV) E6/E7 mRNA in patients with a cytological diagnosis of "atypical squamous cells of undetermined significance" (ASCUS) and to analyze the pathogenic rate of different high-risk HPV subtypes combined with biopsy pathological results to provide a more accurate basis for managing ASCUS patients.

METHODS

A total of 1387 patients with ASCUS and HPV E6/E7 mRNA positivity who were referred for colposcopy were retrospectively analyzed. They were divided into HPV16+, 18/45 + and other HR-HPV + groups premenopausal and postmenopausal groups. The pathological results of the biopsy were divided into the LSIL- group (including normal and low-grade squamous intraepithelial lesions) and the HSIL + group (including high-grade squamous intraepithelial lesions and higher lesions). SPSS was used for the analysis.

RESULTS

The age group 31-40 years had the highest level of HPV16+, and HPV18/45 + was the highest in the 41-50 years group. The detection rates of HSIL + in the HPV16+, HPV18/45+, HPV 16/18/45 + and Other HR-HPV + groups were 48.4%, 18.8%, 43.9% and 15.0%, respectively. The infection rates of HPV16/18/45 in postmenopausal and premenopausal women were 42.4% and 34.3%, respectively. In the HPV18/45 group, the incidence of HSIL + was 30.0% in postmenopausal women and 15.0% in premenopausal women (P < 0.01). In the HPV 16 + and Other HR-HPV + groups, the incidence of HSIL + in postmenopausal patients was not significantly different from that in premenopausal patients. The incidence of cervical cancer in postmenopausal patients is significantly higher than that in premenopausal patients.

CONCLUSIONS

Colposcopy referral or further biopsy is recommended for all ASCUS patients with HPV16/18/45E6/E7 mRNA positivity and postmenopausal patients with HR-HPVE6/E7 mRNA positivity. For premenopausal ASCUS patients with other HR-HPV E6/E7 mRNA positivity, colposcopy should be performed if possible, depending on the specific situation, to achieve early detection and diagnosis.

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.