Researchers test AI algorithm for cervical cancer screening

The team says their findings serve as an important example for introducing digital pathology and deep learning into clinical practice, and their approach could substantially improve cervical cancer screening.

Jeff Rowe | Jul 17, 2020 12:00 am

A recent study by the National Cancer Institute (NCI) has demonstrated the improved effectiveness of an AI algorithm in screening for cervical cancer over the current standard Pap cytology.

The algorithm was developed and the study conducted by investigators at the NCI, part of the National Institutes of Health, in collaboration with researchers from several other institutions. The study’s goal was to determine if a fully automated dual-stain test could match or exceed the performance of the manual approach.  According to NIH, the new approach uses AI to automate dual-stain evaluation and has clear implications for clinical care.

“We’re excited to show we have a fully automated approach to cervical cancer screening as a follow-up to a positive HPV (human papillomavirus) test that outperformed the standard method in our study,” said Nicolas Wentzensen, M.D., Ph.D., of NCI’s Division of Cancer Epidemiology and Genetics, who led the study. “Based on our results, it could increase the efficiency of cervical cancer screening by finding more precancers and reducing false positives, which has the potential to eliminate a substantial number of unnecessary procedures among HPV-positive women.”

The study included 4,253 women aged 18 years or older who were referred to colposcopy at the University of Oklahoma Health Sciences Center between 2009 and 2011.

“Automated evaluation of DS slides dramatically increases the efficiency of cervical cancer screening by substantially reducing unnecessary colposcopies compared with current standards and similarly achieves excellent performance in a simulated fully vaccinated population. Thus, CYTOREADER exceeds human diagnostic accuracy and serves as an example of AI achieving improvements beyond the automation of a human standard,” researchers said in the study, the results of which were published in the Journal of the National Cancer Institute.

Currently, explained NIH, women with positive HPV tests may have additional HPV tests or Pap cytology tests to assess the need for colposcopy, biopsy, or treatment. “Pap cytology, in which specially trained laboratory professionals (cytotechnologists) analyze stained slides to look for abnormal cells, is used to find precancers before they progress to cancer. But these approaches are not ideal. For example, Pap cytology tests are time consuming, not very sensitive, and prone to false-positive findings.”

The researchers found that the AI-based dual-stain test had a lower rate of positive tests than both Pap cytology and manual dual-stain, with better sensitivity (the ability to correctly identify precancers) and substantially higher specificity (the ability to correctly identify those without precancers) than Pap cytology.

NIH added that because the manual dual-stain test has only recently received FDA approval for screening of women who have HPV-positive test results, its use is just getting started. Additional regulatory approval will be needed to allow for screening of HPV-positive women with a fully automated dual-stain test.