Bernier M, Bergemer A M, Got C, Marsan C
Service d'Anatomie et de Cytologie Pathologiques, Hôpital A. Paré, Université Paris VI, Boulogne.
Arch Anat Cytol Pathol. 1998;46(3):184-7.
There have been several reports regarding the accuracy of the PAPNET system applied to the screening for cancerous and precancerous lesions. Based on neuronal networks, this computerized tool was initially trained to select atypical cells. It has been approved in the USA for the re-screening of cervical smears for quality assurance. However, its particular behaviour has not been frequently studied when the system is designed to detect frequent infectious organisms. We report the results of re-screening of 42 inflammatory cervico-uterine smears by the PAPNET system. The computerized images were reviewed by two different pathologists, with complete agreement between the two observers in 39 cases. Infectious organisms were detected in only 66% of cases. Trichomonas, mycoses and Gardnerella were diagnosed in 63%, 56% and 87% of cases respectively. No herpetic lesions were identified. The low accuracy of the PAPNET system in the diagnosis of infectious cervico-uterine smears should be taken into account if this system is developed as an exclusive pre-screening method.
已有多篇关于PAPNET系统应用于癌性和癌前病变筛查准确性的报道。基于神经网络,这个计算机化工具最初被训练用于筛选非典型细胞。它在美国已被批准用于宫颈涂片的再次筛查以确保质量。然而,当该系统旨在检测常见感染性生物体时,其特定行为尚未得到充分研究。我们报告了PAPNET系统对42份炎性宫颈涂片进行再次筛查的结果。两位不同的病理学家对计算机化图像进行了评估,两位观察者在39例中完全一致。仅在66%的病例中检测到感染性生物体。滴虫、霉菌和加德纳菌分别在63%、56%和87%的病例中被诊断出来。未发现疱疹性病变。如果将该系统开发为唯一的预筛查方法,则应考虑PAPNET系统在诊断感染性宫颈涂片方面的低准确性。