These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: Use of computer-assisted rescreening as an ancillary tool to subclassify AGUS cervical smears.
    Author: Chhieng DC, Elgert PA, Xiong Y, Cangiarella JF, Cohen JM.
    Journal: Diagn Cytopathol; 2000 Sep; 23(3):165-70. PubMed ID: 10945903.
    Abstract:
    A substantial percentage of women with a diagnosis of atypical glandular cells of undetermined significance (AGUS) on cervical smears harbor a significant squamous or glandular, preneoplastic or neoplastic lesion on subsequent follow-up. Attempts to subclassify AGUS smears by conventional methods have had mixed results. To determine whether subclassification of AGUS cervical smears using computer-assisted rescreening based on the neural network would improve correlation with subsequent histologic follow-up, 91 cervical smears, conventionally diagnosed as AGUS without concomitant squamous lesions, were subjected to analysis by a computer-assisted automated screening system. Computer-generated images were evaluated by a cytotechnologist without the knowledge of the histologic outcomes. Prior to manual review, each case was classified as either within normal limits, no review required; or abnormal, review required. Based on the degree of abnormality, the latter category was further subclassified into either low probability or high probability of abnormality. The results of the computer-assisted reclassification were then compared with the histologic follow-up of all patients. Thirty-three cases (38.8%) had a significant lesion on histologic follow-up. The lesions included 4 CIN I, 7 CIN II/III, 12 endocervical adenocarcinomas (ACA), and 10 endometrial ACA. Based on computer-generated images, 65% of the smears that were triaged as high probability of abnormality, 11.5% that were triaged as low probability of abnormality, and 10.5% that were triaged as within normal limits had a significant lesion on subsequent follow-up. We conclude that computer-assisted rescreening aids in the triage of AGUS smears and that computer-assisted rescreening based on the neural network or other algorithms may be a useful ancillary tool for subclassifying AGUS cervical smears.
    [Abstract] [Full Text] [Related] [New Search]