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The assessment of an endocervical component in cervicovaginal smears with the PAPNET system

机译：用PAPNET系统评估宫颈阴道涂片中的宫颈内膜成分

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The use of neural network systems is on the rise. Among these systems is PAPNET which was recently approved by the FDA to re-evaluate negative cervicovaginal smears previously diagnosed by manual evaluation. The neural network of this system is used to locate representative samples for review and triage by cytotechnologists. The Bethesda System (TBS), requires the presence of an endocervical component (ECC) for smear adequacy, consisting of either endocervical cells and/or squamous metaplastic cells. The purpose of this study is to evaluate the reliability of this system in selecting and displaying an endocervical component. In addition, the evaluation of this study will provide an endorsement to previous findings regarding the efficiency of the PAPNET system. This study consisted of 158 cervicovaginal smears from patients with cytologic diagnoses of ASCUS by light microscopy triaged with the PAPNET system for detection of an endocervical component. The racial distribution of this group was as follows: Afro-American (132 cs.), Caucasian (26 cs.). The patients' age ranged from 14 years to 64 years, with a mean of 26 years (n=26.1). Colposcopic biopsy diagnoses confirmed 32 as negative, 100 as low-grade squamous lesions, 26 as high-grade squamous lesions, and none with invasive carcinomas. Cases evaluated by the PAPNET system revealed that an endocervical component was on at least one of the two review screens. The results were as follows: no component-4 cases (2.53%), endocervical cells only-1 case (0.63%), metaplastic cells only-66 cases (41.77%), both metaplastic and endocervical cells-87 cases (55.06%). At least one of the necessary components required for specimen adequacy was found in 97% of the cases reviewed with the PAPNET system. This could be vital in reassuring smear adequacy and prove useful as part of an efficient quality assurance program in cytopathology.
机译：神经网络系统的使用正在增加。在这些系统中，有PAPNET，最近已被FDA批准，可以重新评估以前通过手动评估诊断出的阴性宫颈阴道涂片。该系统的神经网络用于定位代表性样品，以供细胞技术人员检查和分类。贝塞斯达系统（TBS）要求存在宫颈内膜成分（ECC），以实现涂片充分性，该成分由宫颈内膜细胞和/或鳞状化生细胞组成。本研究的目的是评估该系统在选择和展示宫颈内膜成分中的可靠性。此外，对本研究的评估将支持以前有关PAPNET系统效率的发现。这项研究由158例经细胞学诊断为ASCUS的宫颈阴道涂片组成，该涂片采用PAPNET系统分光光镜检查，用于检测宫颈内膜成分。这一组人的种族分布如下：美国黑人（132 cs。），高加索人（26 cs。）。患者年龄从14岁到64岁不等，平均26岁（n = 26.1）。阴道镜活检诊断证实32例为阴性，100例为低级别鳞状病变，26例为高级别鳞状病变，无浸润癌。通过PAPNET系统评估的病例显示，宫颈内膜成分在两个复查屏幕中的至少一个上。结果如下：无成分4例（2.53％），仅宫颈内膜细胞1例（0.63％），仅化生细胞-66例（41.77％），化生和宫颈内细胞均87例（55.06％） 。在PAPNET系统审查的97％的病例中，至少发现了满足样品充分性的必要成分之一。这对于确保涂片充分性至关重要，并被证明是细胞病理学有效质量保证计划的一部分。

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