Investigator
University Of Pittsburgh
Assessment of the efficacy and accuracy of cervical cytology screening with the Hologic Genius Digital Diagnostics System
Abstract Background Medical technologies powered by artificial intelligence are quickly transforming into practical solutions by rapidly leveraging massive amounts of data processed via deep learning algorithms. There is a necessity to validate these innovative tools when integrated into clinical practice. Methods This study evaluated the performance of the Hologic Genius Digital Diagnostics System (HGDDS) with a cohort of 890 previously reviewed and diagnosed ThinPrep Papanicolaou (Pap) tests with the intent to deploy this system for routine clinical use. The study included all diagnostic categories of The Bethesda System, with follow‐up tissue sampling performed within 6 months of abnormal Pap test results to serve as the ground truth. Results The HGDDS demonstrated excellent performance in detecting significant Pap test findings, with close to 100% sensitivity (98.2%–100%) for cases classified as atypical squamous cells of undetermined significance and above within a 95% confidence interval and a high negative predictive value (92.4%–100%). Conclusions The HGDDS streamlined workflow, reduced manual workload, and functioned as a stand‐alone system.
Analysis of the sensitivity of high‐grade squamous intraepithelial lesion Pap diagnosis and interobserver variability with the Hologic Genius Digital Diagnostics System
AbstractBackgroundArtificial intelligence (AI)–based systems are transforming cytopathology practice. The aim of this study was to evaluate the sensitivity of high‐grade squamous intraepithelial lesion (HSIL) Papanicolaou (Pap) diagnosis assisted by the Hologic Genius Digital Diagnostics System (GDDS).MethodsA validation study was performed with 890 ThinPrep Pap tests with the GDDS independently. From this set, a subset of 183 cases originally interpreted as HSIL confirmed histologically were included in this study. The sensitivity for detecting HSIL by three cytopathologists was calculated.ResultsMost HSIL cases were classified as atypical glandular cell/atypical squamous cell–high grade not excluded (AGC/ASC‐H) and above by all cytopathologists. Of these cases, 11.5% were classified as low‐grade squamous intraepithelial lesion (LSIL) by pathologist A (P‐A), 6% by pathologist B (P‐B), and 5.5% by pathologist C (P‐C); 3.8%, 2.7%, and 1.6% of these cases were classified as atypical squamous cell of unknown significance (ASC‐US) by P‐A, P‐B, and P‐C, respectively. The sensitivity for detection of cervical intraepithelial neoplasia 2 and above (CIN2+) lesions was 100% if ASC‐US and above (ASC‐US+) abnormalities were counted among all three pathologists. The sensitivity for detection of CIN2+ lesions was 84.7%, 91.3%, and 92.9% by P‐A, P‐B, and P‐C, respectively, for ASC‐H and above abnormalities. The Kendall W coefficient was 0.722, which indicated strong agreement between all pathologists.ConclusionsNew‐generation AI‐assisted Pap test screening systems such as the GDDS have the potential to transform cytology practice. In this study, the GDDS aided in interpreting HSIL in ThinPrep Pap tests, with good sensitivity and agreement between the pathologists who interacted with this system.
Diagnostic performance of the hologic genius digital diagnostics system for low-grade squamous intraepithelial lesion (LSIL) ThinPrep papanicolaou tests
Advancements in digital imaging technology for Papanicolaou test slides, combined with artificial intelligence are driving the development and adoption of innovative computer-assisted screening methods for cervical cancer within the cytology community. Our study aimed to assess the performance of the Hologic Genius Digital Diagnostic System (HGDDS) in the interpretation of low-grade squamous intraepithelial lesions (LSIL) in ThinPrep Papanicolaou slides. As part of a validation study performed with 890 ThinPrep Papanicolaou slides using the HGDDS, a subset of 146 LSIL cases were included in this study. Performance characteristics for the detection of cervical intraepithelial neoplasia (CIN) and interobserver variability among 3 cytopathologists were assessed. On evaluation of the consensus results of the 3 cytopathologists, of the 146 LSIL Papanicolaou cases, 60.3% were interpreted as LSIL with the HGDDS. The remainder were interpreted as ASCUS (26%), ASC-H (10.3%), HSIL (2.7%), and NILM (0.7%). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for detecting CIN1+ lesions in the ASCUS + category with the HGDDS were 100%, 25%, 97.9%, and 100%, respectively. The sensitivity, specificity, PPV, and NPV for the detection of CIN1+ lesions in the LSIL + category with the HGDDS were 74.7%, 75%, 99.1%, and 7.7%, respectively. Kendall's W coefficient was 0.792, indicating strong agreement among participating pathologists. Our study demonstrated that ThinPrep Papanicolaou tests with LSIL could be interpreted with strong agreement among pathologists and with good performance indicators when utilizing the HGDDS.
Volunteering at CerviCusco in Peru
Improving the Pap test with artificial intelligence
The cytology community should be excited about the emergence of artificial intelligence–based solutions and embrace these promising technologies. However, there is also a need to determine how best to adopt these tools into routine practice and to monitor their long‐term usefulness.
The evolution of cervical cancer screening
There are few medical success stories in history as significant as the reduction in cervical cancer incidence. Through the collaborative efforts of dedicated scientific pioneers, the past century has witnessed remarkable advancement that began with the detection of exfoliated cancer cells through cytologic examination to widespread implementation of cervical cancer screening programs to the discovery of the link between cervical cancer and human papillomavirus (HPV). Current screening methods apply HPV-based testing, and artificial intelligence-based screening systems utilizing digitalized cytology images are being used in a continuous effort to optimize the accuracy and efficiency of the Papanicolaou test. This review summarizes the major milestones in cervical cancer screening history to emphasize its evolution as the World Health Organization aims for the global elimination of cervical cancer.
