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基于神经网络技术(PAPNET检测系统)的宫颈涂片假阴性率显著降低。

Significant reduction in the rate of false-negative cervical smears with neural network-based technology (PAPNET Testing System).

作者信息

Koss L G, Sherman M E, Cohen M B, Anes A R, Darragh T M, Lemos L B, McClellan B J, Rosenthal D L, Keyhani-Rofagha S, Schreiber K, Valente P T

机构信息

Department of Pathology, Montefiore Medical Center and the Albert Einstein College of Medicine, Bronx, NY 10467, USA.

出版信息

Hum Pathol. 1997 Oct;28(10):1196-203. doi: 10.1016/s0046-8177(97)90258-6.

Abstract

False-negative cervical Pap smears may lead to disability or death from carcinoma of the uterine cervix. New computer technology has led to the development of an interactive, neural network-based vision instrument to increase the accuracy of cervical smear screening. The instrument belongs to a new class of medical devices designed to provide computer-aided diagnosis (CADx). To test the instrument's performance, 487 archival negative smears (index smears) from 228 women with biopsy-documented high-grade precancerous lesions or invasive cervical carcinoma (index women) were retrieved from the files of 10 participating laboratories that were using federally mandated quality assurance procedures. Samples of sequential negative smears (total 9,666) were retrieved as controls. The instrument was used to identify evidence of missed cytological abnormalities, including atypical squamous or glandular cells of undetermined significance (ASCUS, AGUS), low-grade or high-grade squamous intraepithelial lesions (LSIL, HSIL) and carcinoma. Using the instrument, 98 false-negative index smears were identified in 72 of the 228 index women (31.6%, 95% confidence interval [CI]: 25% to 38%). Disregarding the debatable categories of ASCUS or AGUS, there were 44 women whose false-negative smears disclosed squamous intraepithelial lesions (SIL) or carcinoma (19.3%; 95% CI: 14.2% to 24.4%). Unexpectedly, SILs were also identified in 127 of 9,666 control negative smears (1.3%; 95% CI: 1.1% to 1.5%). Compared with historical performance data from several participating laboratories, the instrument increased the detection rate of SILs in control smears by 25% and increased the yield of quality control rescreening 5.1 times (P < 0.0001). These data provide evidence that conventional screening and quality control rescreening of cervical smears fail to identify a substantial number of abnormalities. A significant improvement in performance of screening of cervical smears could be achieved with the use of the instrument described in this report.

摘要

子宫颈巴氏涂片假阴性可能导致子宫颈癌致残或死亡。新的计算机技术促使开发出一种基于神经网络的交互式视觉仪器,以提高子宫颈涂片筛查的准确性。该仪器属于旨在提供计算机辅助诊断(CADx)的新型医疗设备。为测试该仪器的性能,从10个采用联邦规定质量保证程序的参与实验室档案中,检索出228名活检证实患有高级别癌前病变或浸润性子宫颈癌的女性(索引女性)的487份存档阴性涂片(索引涂片)。检索出连续阴性涂片样本(共9666份)作为对照。该仪器用于识别漏诊的细胞学异常证据,包括意义不明确的非典型鳞状或腺细胞(ASCUS、AGUS)、低级别或高级别鳞状上皮内病变(LSIL、HSIL)及癌。使用该仪器,在228名索引女性中的72名(31.6%,95%置信区间[CI]:25%至38%)中识别出98份假阴性索引涂片。不考虑有争议的ASCUS或AGUS类别,有44名女性的假阴性涂片显示有鳞状上皮内病变(SIL)或癌(19.3%;95%CI:14.2%至24.4%)。出乎意料的是,在9666份对照阴性涂片中的127份(1.3%;95%CI:1.1%至1.5%)中也识别出SIL。与几个参与实验室的历史性能数据相比,该仪器使对照涂片中SIL的检出率提高了25%,并使质量控制复查的产量提高了5.1倍(P<0.0001)。这些数据证明,子宫颈涂片的传统筛查和质量控制复查未能识别出大量异常情况。使用本报告所述仪器可显著提高子宫颈涂片筛查的性能。

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