The aim of this study is to develop a novel technique for improving the intraoperative margin assessment of glioblastoma by examining the total extrinsic extracellular matrix（ECM） with eosin staining using fluoresce...The aim of this study is to develop a novel technique for improving the intraoperative margin assessment of glioblastoma by examining the total extrinsic extracellular matrix（ECM） with eosin staining using fluorescence lifetime imaging microscopy（FLIM） and scale-invariant feature transform（SIFT） descriptor analysis. Pseudocolor FLIM images obviously exhibit ECM distributions, changes in sequential sections, and different regions of interest. Meanwhile, SIFT descriptors are first utilized for the discrimination of glioblastoma margins by matching similar ECM regions and extracting keypoint orientations from FLIM images obtained from a series of continuous slices. The findings indicate that FLIM imaging with SIFT analysis of the total ECM is a promising method for improving intraoperative diagnosis of frozen and surgically excised brain specimen sections.展开更多
基金supported by the National Basic Research Program of China(No.2015CB352005)the National Natural Science Foundation of China(Nos.61525503,61378091,and 61620106016)+2 种基金the Guangdong Natural Science Foundation Innovation Team(No.2014A030312008)the Hong Kong,Macao and Taiwan cooperation innovation platform&major projects of international cooperation in Colleges and the Universities in Guangdong Province(No.2015KGJHZ002)the Shenzhen Basic Research Project(Nos.JCYJ20150930104948169,JCYJ2016032814 4746940,and GJHZ20160226202139185)
文摘The aim of this study is to develop a novel technique for improving the intraoperative margin assessment of glioblastoma by examining the total extrinsic extracellular matrix（ECM） with eosin staining using fluorescence lifetime imaging microscopy（FLIM） and scale-invariant feature transform（SIFT） descriptor analysis. Pseudocolor FLIM images obviously exhibit ECM distributions, changes in sequential sections, and different regions of interest. Meanwhile, SIFT descriptors are first utilized for the discrimination of glioblastoma margins by matching similar ECM regions and extracting keypoint orientations from FLIM images obtained from a series of continuous slices. The findings indicate that FLIM imaging with SIFT analysis of the total ECM is a promising method for improving intraoperative diagnosis of frozen and surgically excised brain specimen sections.
