Department of Otolaryngology-Head and Neck Surgery, Mount Sinai School of Medicine, New York, NY, USA.
Ann Surg Oncol. 2012 Oct;19(11):3534-9. doi: 10.1245/s10434-012-2351-1. Epub 2012 Apr 11.
The efficacy of ablative surgery for head and neck squamous cell carcinoma (HNSCC) depends critically on obtaining negative margins. Although intraoperative "frozen section" analysis of margins is a valuable adjunct, it is expensive, time-consuming, and highly dependent on pathologist expertise. Optical imaging has potential to improve the accuracy of margins by identifying cancerous tissue in real time. Our goal was to determine the accuracy and inter-rater reliability of head and neck cancer specialists using high-resolution microendoscopic (HRME) images to discriminate between cancerous and benign mucosa.
Thirty-eight patients diagnosed with head and neck squamous cell carcinoma (HNSCC) were enrolled in this single-center study. HRME was used to image each specimen after application of proflavine, with concurrent standard histopathologic analysis. Images were evaluated for quality control, and a training set containing representative images of benign and neoplastic tissue was assembled. After viewing training images, seven head and neck cancer specialists with no previous HRME experience reviewed 36 test images and were asked to classify each.
The mean accuracy of all reviewers in correctly diagnosing neoplastic mucosa was 97% (95% confidence interval (CI), 94-99%). The mean sensitivity and specificity were 98% (97-100%) and 92% (87-98%), respectively. The Fleiss kappa statistic for inter-rater reliability was 0.84 (0.77-0.91).
Medical professionals can be quickly trained to use HRME to discriminate between benign and neoplastic mucosa in the head and neck. With further development, the HRME shows promise as a method of real-time margin determination at the point of care.
头颈部鳞状细胞癌(HNSCC)消融手术的疗效在很大程度上取决于获得阴性切缘。虽然术中“冰冻切片”分析切缘是一种有价值的辅助手段,但它昂贵、耗时且高度依赖病理学家的专业知识。光学成像有可能通过实时识别癌组织来提高切缘的准确性。我们的目标是确定使用高分辨率微内窥镜(HRME)图像区分癌性和良性黏膜的头颈部癌症专家的准确性和组内可靠性。
本单中心研究纳入了 38 例诊断为头颈部鳞状细胞癌(HNSCC)的患者。在应用普罗凡后,使用 HRME 对每个标本进行成像,并同时进行标准组织病理学分析。对图像进行质量控制评估,并组装包含良性和肿瘤组织代表性图像的培训集。在查看培训图像后,7 名没有 HRME 经验的头颈部癌症专家查看了 36 张测试图像,并被要求对每张图像进行分类。
所有评审员正确诊断癌性黏膜的平均准确率为 97%(95%置信区间(CI),94-99%)。平均敏感度和特异性分别为 98%(97-100%)和 92%(87-98%)。组内可靠性的 Fleiss kappa 统计量为 0.84(0.77-0.91)。
医疗专业人员可以通过快速培训,使用 HRME 区分头颈部的良性和癌性黏膜。随着进一步的发展,HRME 有望成为一种在护理点实时确定切缘的方法。