Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Department of Surgery, Amsterdam, The Netherlands.
Antoni van Leeuwenhoek Hospital, The Netherlands Cancer Institute, Department of Pathology, Amsterda, The Netherlands.
J Biomed Opt. 2019 Jan;24(1):1-9. doi: 10.1117/1.JBO.24.1.016002.
In the last decades, laparoscopic surgery has become the gold standard in patients with colorectal cancer. To overcome the drawback of reduced tactile feedback, real-time tissue classification could be of great benefit. In this ex vivo study, hyperspectral imaging (HSI) was used to distinguish tumor tissue from healthy surrounding tissue. A sample of fat, healthy colorectal wall, and tumor tissue was collected per patient and imaged using two hyperspectral cameras, covering the wavelength range from 400 to 1700 nm. The data were randomly divided into a training (75%) and test (25%) set. After feature reduction, a quadratic classifier and support vector machine were used to distinguish the three tissue types. Tissue samples of 32 patients were imaged using both hyperspectral cameras. The accuracy to distinguish the three tissue types using both hyperspectral cameras was 0.88 (STD = 0.13) on the test dataset. When the accuracy was determined per patient, a mean accuracy of 0.93 (STD = 0.12) was obtained on the test dataset. This study shows the potential of using HSI in colorectal cancer surgery for fast tissue classification, which could improve clinical outcome. Future research should be focused on imaging entire colon/rectum specimen and the translation of the technique to an intraoperative setting.
在过去的几十年中，腹腔镜手术已成为治疗结直肠癌的金标准。为了克服触觉反馈减弱的缺点，实时组织分类可能会带来很大的好处。在这项离体研究中，高光谱成像（HSI）被用于区分肿瘤组织和健康的周围组织。每位患者采集一块脂肪、健康的结直肠壁和肿瘤组织样本，并使用两台高光谱相机进行成像，覆盖波长范围从 400 到 1700nm。数据随机分为训练集（75%）和测试集（25%）。在进行特征降维后，使用二次分类器和支持向量机来区分三种组织类型。使用两台高光谱相机对 32 名患者的组织样本进行了成像。在测试数据集上，使用两台高光谱相机区分三种组织类型的准确率为 0.88（STD = 0.13）。当按患者确定准确率时，在测试数据集上的平均准确率为 0.93（STD = 0.12）。这项研究表明，高光谱成像在结直肠癌手术中具有快速组织分类的潜力，这可能会改善临床结果。未来的研究应集中在对整个结肠/直肠标本进行成像以及将该技术转化为术中设置上。
