Sherman M E, Mango L J, Kelly D, Paull G, Ludin V, Copeland C, Solomon D, Schiffman M H
Johns Hopkins Medical Institutions, Baltimore, Maryland.
Mod Pathol. 1994 Jun;7(5):578-81.
One hundred fourteen cervical smears obtained from 18 women developing biopsy-proven high-grade squamous intraepithelial lesions and two with invasive squamous carcinomas were analyzed by two pathologists using the PAPNET neural network-based automated screening system (PAPNET Analyses A and B). The smears were originally reported as negative and had been previously rescreened and reclassified according to The Bethesda System. Using the PAPNET video displays of 128 potentially abnormal cellular images per smear, each reviewer (PAPNET A and B) determined whether a smear required conventional rescreening. Results of the PAPNET triage were compared with the reclassification diagnoses of the smears by conventional microscopy. PAPNET Analysis A selected eight (14%) smears reclassified as negative, 25 (69%) as atypical squamous cells of undetermined significance, and 15 (71%) as squamous intraepithelial lesions (SIL) for rescreening. In PAPNET Analysis A, two (10%) SILs were not selected for rescreening, and four (19%) were considered unsatisfactory for analysis. PAPNET Analysis B selected 21 (37%) smears reclassified as negative, 25 (69%) as atypical squamous cells of undetermined significance, and 18 (86%) as SIL for review. In PAPNET Analysis B, two (10%) SILs were missed, and one (5%) smear was unsatisfactory for analysis. Each PAPNET analysis selected smears for rescreening in 19 (95%) of 20 patients and detected SILs in 10 patients that were missed in the original screening. Using PAPNET, SILs would have been detected a median of 56 months (PAPNET A) and 62 months (PAPNET B) before their actual discovery. These preliminary data suggest that PAPNET may help detect SILs missed in routine cytologic screening.(ABSTRACT TRUNCATED AT 250 WORDS)
两名病理学家使用基于PAPNET神经网络的自动筛查系统（PAPNET分析A和B），对从18例经活检证实为高级别鳞状上皮内病变的女性以及2例浸润性鳞状细胞癌患者获取的114份宫颈涂片进行了分析。这些涂片最初报告为阴性，并且之前已根据贝塞斯达系统进行了重新筛查和重新分类。利用每份涂片128张潜在异常细胞图像的PAPNET视频显示，每位审阅者（PAPNET A和B）确定一份涂片是否需要进行传统的重新筛查。将PAPNET分类结果与通过传统显微镜对涂片进行的重新分类诊断进行比较。PAPNET分析A选择了8份（14%）重新分类为阴性的涂片、25份（69%）意义不明确的非典型鳞状细胞涂片以及15份（71%）鳞状上皮内病变（SIL）涂片进行重新筛查。在PAPNET分析A中，有2份（10%）SIL未被选作重新筛查，4份（19%）被认为分析不满意。PAPNET分析B选择了21份（37%）重新分类为阴性的涂片、25份（69%）意义不明确的非典型鳞状细胞涂片以及18份（86%）SIL涂片进行复查。在PAPNET分析B中，有2份（10%）SIL被漏检，1份（5%）涂片分析不满意。每项PAPNET分析在20例患者中的19例（95%）中选择了涂片进行重新筛查，并在10例患者中检测到了最初筛查中漏检的SIL。使用PAPNET，SIL在实际发现前的中位时间为56个月（PAPNET A）和62个月（PAPNET B）。这些初步数据表明，PAPNET可能有助于检测常规细胞学筛查中漏检的SIL。（摘要截短于250字）
