Orringer Daniel A, Pandian Balaji, Niknafs Yashar S, Hollon Todd C, Boyle Julianne, Lewis Spencer, Garrard Mia, Hervey-Jumper Shawn L, Garton Hugh J L, Maher Cormac O, Heth Jason A, Sagher Oren, Wilkinson D Andrew, Snuderl Matija, Venneti Sriram, Ramkissoon Shakti H, McFadden Kathryn A, Fisher-Hubbard Amanda, Lieberman Andrew P, Johnson Timothy D, Xie X Sunney, Trautman Jay K, Freudiger Christian W, Camelo-Piragua Sandra
Department of Neurosurgery, University of Michigan Medical School, Ann Arbor, MI 48109, USA.
Department of Pathology, New York University, New York, NY 10016, USA.
Nat Biomed Eng. 2017;1. doi: 10.1038/s41551-016-0027. Epub 2017 Feb 6.
Conventional methods for intraoperative histopathologic diagnosis are labour- and time-intensive, and may delay decision-making during brain-tumour surgery. Stimulated Raman scattering (SRS) microscopy, a label-free optical process, has been shown to rapidly detect brain-tumour infiltration in fresh, unprocessed human tissues. Here, we demonstrate the first application of SRS microscopy in the operating room by using a portable fibre-laser-based microscope and unprocessed specimens from 101 neurosurgical patients. We also introduce an image-processing method - stimulated Raman histology (SRH) - which leverages SRS images to create virtual haematoxylin-and-eosin-stained slides, revealing essential diagnostic features. In a simulation of intraoperative pathologic consultation in 30 patients, we found a remarkable concordance of SRH and conventional histology for predicting diagnosis (Cohen's kappa, κ > 0.89), with accuracy exceeding 92%. We also built and validated a multilayer perceptron based on quantified SRH image attributes that predicts brain-tumour subtype with 90% accuracy. Our findings provide insight into how SRH can now be used to improve the surgical care of brain tumour patients.
术中组织病理学诊断的传统方法既耗费人力又耗时,可能会延误脑肿瘤手术期间的决策。受激拉曼散射(SRS)显微镜检查是一种无需标记的光学方法,已被证明能够快速检测新鲜、未处理的人体组织中的脑肿瘤浸润情况。在此,我们通过使用便携式光纤激光显微镜和来自101名神经外科患者的未处理标本,展示了SRS显微镜检查在手术室中的首次应用。我们还引入了一种图像处理方法——受激拉曼组织学(SRH),该方法利用SRS图像创建虚拟苏木精-伊红染色切片,揭示重要的诊断特征。在对30名患者进行的术中病理会诊模拟中,我们发现SRH与传统组织学在预测诊断方面具有显著的一致性(科恩kappa系数,κ>0.89),准确率超过92%。我们还基于量化的SRH图像属性构建并验证了一个多层感知器,其预测脑肿瘤亚型的准确率为90%。我们的研究结果为了解如何利用SRH改善脑肿瘤患者的手术治疗提供了思路。