A novel automated screening and interpretation process for cervical cytology using the internet transmission of low-resolution images: a feasibility study.

Background: Transmission over the Internet of low-resolution images acquired by automated screening of cervical cytology specimens has the potential to provide remote interpretation and, hence, centralization of a cytology workforce.
Methods: Liquid-based cervical cytology slides were scanned using the FocalPoint(R) System. Ten black-and-white images that had the greatest probability of containing abnormality were acquired from each of 32 reference slides (16 negative samples, 3 samples of atypical squamous cells of uncertain significance, 5 samples of low-grade squamous intraepithelial lesions [LSIL], 5 samples of high-grade squamous intraepithelial lesions [HSIL], 1 adenocarcinoma in situ sample, and 2 carcinoma samples) and were transmitted as e-mail attachments in JPEG format to remote reading stations. The slides were interpreted independently by two pathologists and were assigned to either of two groups: 1) suspicious for >or=HSIL or 2) <or=LSIL. The interpretations were compared with the reference diagnoses. The specimens were then randomized, and the image sets were redistributed to the pathologists for another round of interpretation and scoring.
Results: The initial and subsequent trials yielded similar results. Pooling the interpretations of the two pathologists, the concordance rate between reference and assigned diagnostic groups for each of the two trials was 84%, the false-positive rate was 8.3%, and the false-negative rate was 37.5%. Review of the discrepant slides revealed subtle cellular changes that may be utilized to reduce errors and, with training, to optimize sensitivity and specificity.
Conclusions: This procedure showed promise for allowing remote interpretation of device-selected images. The procedure may represent an effective way to centralize cervical cytology services and to allow the provision of services to previously unscreened populations that lack an effective cytology infrastructure.
(Copyright (c) 2005 American Cancer Society.)