Surgery, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland.
Eur J Surg Oncol. 2019 Feb;45(2):141-146. doi: 10.1016/j.ejso.2018.09.005. Epub 2018 Oct 15.
Breast cancer is the most frequent cancer in women worldwide. The primary treatment is breast-conserving surgery or mastectomy with an adequate clearance margin. Diathermy blade is used extensively in breast-conserving surgery. Surgical smoke produced as a side product has cancer-specific molecular features. Differential mobility spectrometry (DMS) is a rapid and affordable technology for analysis of complex gas mixtures. In our study we examined surgical smoke from malignant and benign breast tissue created with a diathermy blade using DMS.
Punch biopsies of 4 mm diameter from breast cancer surgical specimens were taken during gross dissection of fresh surgical specimen and placed in a well plate. The measurement system is a custom-built device called automatic tissue analysis system (ATAS) based on a DMS sensor. Each specimen was incised with a diathermy blade and the surgical smoke was analyzed.
We examined 106 carcinoma samples from 21 malignant breast tumors. Benign samples (n = 198) included macroscopically normal mammary gland (n = 82), adipose tissue (n = 88) and vascular tissue (n = 28). The classification accuracy when comparing malignant samples to all benign samples was 87%. The sensitivity was 80% and the specificity was 90%. The classification accuracy of carcinomas to ductal and lobular was 94%, 47%, respectively.
Benign and malignant breast tissue can be identified with ATAS. These results lay foundation for intraoperative margin assessment with DMS from surgical smoke.
乳腺癌是全球女性最常见的癌症。主要治疗方法是保乳手术或乳房切除术,并保证有足够的清除边缘。热刀广泛应用于保乳手术中。作为副产品产生的手术烟雾具有特定的癌症分子特征。差分迁移率谱(DMS)是一种快速且经济实惠的分析复杂气体混合物的技术。在我们的研究中,我们使用 DMS 检查了热刀切除的良性和恶性乳腺组织产生的手术烟雾。
在新鲜手术标本的大体解剖过程中,从乳腺癌手术标本上切取 4mm 直径的穿刺活检,并将其放置在培养皿中。测量系统是一种称为自动组织分析系统(ATAS)的定制设备,基于 DMS 传感器。每个标本均用热刀切开,并对手术烟雾进行分析。
我们检查了 21 个恶性乳腺肿瘤中的 106 个癌样本。良性样本(n=198)包括宏观正常的乳腺(n=82)、脂肪组织(n=88)和血管组织(n=28)。将恶性样本与所有良性样本进行比较时的分类准确率为 87%。敏感性为 80%,特异性为 90%。将癌样本分类为导管和小叶的准确率分别为 94%和 47%。
ATAS 可识别良性和恶性乳腺组织。这些结果为 DMS 从手术烟雾中进行术中边缘评估奠定了基础。