Remmerbach Torsten W, Meyer-Ebrecht Dietrich, Aach Til, Würflinger Thomas, Bell Andre A, Schneider Timna E, Nietzke Nadja, Frerich Bernhard, Böcking Alfred
Department of Oral, Maxillofacial, and Plastic Surgery, University of Leipzig, Leipzig, Germany.
Cancer. 2009 Jun 25;117(3):228-35. doi: 10.1002/cncy.20028.
This report describes what to the authors' knowledge is the first clinical application of semiautomated multimodal cell analysis (MMCA), a novel technique for the early detection of cancer for cases with a limited number of suspicious cells. In this clinical study, MMCA was applied to oral cancer diagnostics on brush biopsies. The MMCA approach was based on the sequential application of multiple stainings of identical, slide-based cells and repeated relocalizations and measurements of their diagnostic features, resulting in multiparametric features of individual cells. Data integration of the variously stained cells increased diagnostic accuracy. The implementation of MMCA also enabled fully automatic, adaptive image preprocessing, including registration of multimodal images and segmentation of cell nuclei.
In a preliminary clinical trial, 47 slides from brush biopsies of suspicious oral lesions were analyzed. The final histologic diagnoses included 20 squamous cell carcinomas, 7 hyperkeratotic leukoplakias, and 20 lichen planus mucosae.
The stepwise application of 2 additional approaches (morphology, DNA content, argyrophilic nucleolar organizer region counts) increased the specificity of conventional cytologic diagnosis from 92.6% to 100%. This feasibility study provided a proof of concept, demonstrating efficiency, robustness, and diagnostic accuracy on slide-based cytologic specimens.
The authors concluded that MMCA may become a sensitive and highly specific, objective, and reproducible adjuvant diagnostic tool for the identification of neoplastic changes in oral smears that contain only a few abnormal cells.
据作者所知，本报告描述了半自动多模态细胞分析（MMCA）的首次临床应用，MMCA是一种用于早期检测癌细胞数量有限病例的新技术。在这项临床研究中，MMCA应用于刷检活检的口腔癌诊断。MMCA方法基于对同一玻片上的细胞进行多次染色，并重复重新定位和测量其诊断特征，从而得到单个细胞的多参数特征。对不同染色细胞的数据整合提高了诊断准确性。MMCA的实施还实现了全自动、自适应图像预处理，包括多模态图像配准和细胞核分割。
在一项初步临床试验中，对47例可疑口腔病变刷检活检的玻片进行了分析。最终组织学诊断包括20例鳞状细胞癌、7例角化过度性白斑和20例黏膜扁平苔藓。
逐步应用另外两种方法（形态学、DNA含量、嗜银核仁组织区计数）使传统细胞学诊断的特异性从92.6%提高到100%。这项可行性研究提供了概念验证，证明了在基于玻片的细胞学标本上的效率、稳健性和诊断准确性。
作者得出结论，MMCA可能成为一种敏感、高度特异、客观且可重复应用的辅助诊断工具，用于识别仅含有少数异常细胞的口腔涂片的肿瘤性变化。
