General Surgery, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
J Investig Med. 2020 Jan;68(1):60-67. doi: 10.1136/jim-2019-000997. Epub 2019 Jul 19.
Use of endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) cytology to detect pancreatic cancer is limited, with a high false negative rate mainly due to the relatively fewer number of completely cancerous cells. To improve the accuracy of EUS-FNA cytological diagnosis, we evaluated a novel optical system-spatial-domain low-coherence quantitative phase microscopy (SL-QPM)-to analyze nanoscale nuclear architecture on original cytology samples, especially those diagnosed as indeterminate for malignancy, with the goal of maintaining high specificity and reducing false positive rate. We performed SL-QPM on original cytology samples obtained by EUS-FNA from 40 patients with suspicious pancreatic solid lesions (27 adenocarcinomas, 5 neuroendocrine tumor, 8 chronic pancreatitis), including 13 cases that were cytologically indeterminate. Each diagnosis had been confirmed by follow-up surgical pathology. The SL-QPM-derived nanoscale nuclear architectural parameters distinguished pancreatic cancer from cytologically indeterminate cells. A logistic regression model using nuclear entropy and SD increased the sensitivity of cytology in identifying pancreatic cancer from 72% to 94% while maintaining 100% specificity. The SL-QPM-derived nanoscale nuclear architecture properties show great promise in improving the cytological diagnosis of EUS-FNA for pancreatic cancer and could be used when traditional cytopathology does not get an accurate diagnosis, and can be easily translated into a traditional clinical device.
使用内镜超声引导下细针抽吸（EUS-FNA）细胞学检查来检测胰腺癌是有限的，其假阴性率较高，主要是因为完全癌变的细胞相对较少。为了提高 EUS-FNA 细胞学诊断的准确性，我们评估了一种新型光学系统——空域低相干定量相显微镜（SL-QPM）——来分析原始细胞学样本上的纳米级核结构，特别是那些诊断为恶性程度不确定的样本，目标是保持高特异性和降低假阳性率。我们对 40 名可疑胰腺实体病变患者（27 例腺癌，5 例神经内分泌肿瘤，8 例慢性胰腺炎）通过 EUS-FNA 获得的原始细胞学样本进行了 SL-QPM 分析，其中包括 13 例细胞学不确定的病例。每个诊断都通过后续手术病理得到了证实。SL-QPM 衍生的纳米级核结构参数可区分胰腺癌与细胞学不确定的细胞。使用核熵和 SD 的逻辑回归模型提高了细胞学识别胰腺癌的敏感性，从 72%提高到 94%，同时保持了 100%的特异性。SL-QPM 衍生的纳米级核结构特性有望改善 EUS-FNA 对胰腺癌的细胞学诊断，可用于传统细胞病理学无法获得准确诊断的情况，并且易于转化为传统的临床设备。
