Department of Biomaterials, Bioengineering Institute, New York University College of Dentsitry, New York, NY, USA.
Department of Oral and Maxillofacial Pathology, Radiology & Medicine, New York University College of Dentistry, New York, NY, USA.
J Dent Res. 2021 May;100(5):479-486. doi: 10.1177/0022034520973162. Epub 2020 Nov 12.
Oral cavity cancer has a low 5-y survival rate, but outcomes improve when the disease is detected early. Cytology is a less invasive method to assess oral potentially malignant disorders relative to the gold-standard scalpel biopsy and histopathology. In this report, we aimed to determine the utility of cytological signatures, including nuclear F-actin cell phenotypes, for classifying the entire spectrum of oral epithelial dysplasia and oral squamous cell carcinoma. We enrolled subjects with oral potentially malignant disorders, subjects with previously diagnosed malignant lesions, and healthy volunteers without lesions and obtained brush cytology specimens and matched scalpel biopsies from 486 subjects. Histopathological assessment of the scalpel biopsy specimens classified lesions into 6 categories. Brush cytology specimens were analyzed by machine learning classifiers trained to identify relevant cytological features. Multimodal diagnostic models were developed using cytology results, lesion characteristics, and risk factors. Squamous cells with nuclear F-actin staining were associated with early disease (i.e., lower proportions in benign lesions than in more severe lesions), whereas small round parabasal-like cells and leukocytes were associated with late disease (i.e., higher proportions in severe dysplasia and carcinoma than in less severe lesions). Lesions with the impression of oral lichen planus were unlikely to be either dysplastic or malignant. Cytological features substantially improved upon lesion appearance and risk factors in predicting squamous cell carcinoma. Diagnostic models accurately discriminated early and late disease with AUCs (95% CI) of 0.82 (0.77 to 0.87) and 0.93 (0.88 to 0.97), respectively. The cytological features identified here have the potential to improve screening and surveillance of the entire spectrum of oral potentially malignant disorders in multiple care settings.
口腔癌的 5 年生存率较低,但如果疾病早期得到检测,预后会有所改善。细胞学检查是一种相对金标准的手术刀活检和组织病理学检查而言,侵袭性更小的评估口腔潜在恶性疾病的方法。在本报告中,我们旨在确定细胞学特征(包括核 F-肌动蛋白细胞表型)在分类整个口腔上皮异型增生和口腔鳞状细胞癌谱中的效用。我们纳入了患有口腔潜在恶性疾病的受试者、患有先前诊断的恶性病变的受试者以及无病变的健康志愿者,并从 486 名受试者中获得了毛刷细胞学标本和匹配的手术刀活检标本。对手术刀活检标本的组织病理学评估将病变分为 6 类。使用机器学习分类器对毛刷细胞学标本进行分析,以识别相关的细胞学特征。使用细胞学结果、病变特征和危险因素开发了多模态诊断模型。核 F-肌动蛋白染色的鳞状细胞与早期疾病相关(即良性病变中比例低于更严重的病变),而小圆基底样细胞和白细胞与晚期疾病相关(即严重异型增生和癌中比例高于较轻的病变)。具有口腔扁平苔藓印象的病变不太可能是异型增生或恶性的。细胞学特征在预测鳞状细胞癌方面大大优于病变外观和危险因素。诊断模型以 AUC(95%CI)分别为 0.82(0.77 至 0.87)和 0.93(0.88 至 0.97)准确地区分了早期和晚期疾病。这里确定的细胞学特征有可能在多种护理环境中改善整个口腔潜在恶性疾病谱的筛查和监测。