Desenvolvimento e validação de um método para análise morfométrica e fractal da rede vascular peritumoral em modelos experimentais de câncer - Jamacaru, Francisco Vagnaldo Fechine (2018)
Tumor growth is dependent on the induction of angiogenesis, a complex pathophysiological process that can be modified by the action of drugs. Thus, the development of methods that appropriately quantify tumor angiogenesis, both in human tumors and in experimental cancer models, is imperative for the evaluation of the therapeutic efficacy of antiangiogenic drugs. Therefore, the objective of this study was to develop and validate a computational system for morphometric and fractal analysis of the peritumoral vasculature in a murine model of subcutaneous heterotopic implant of neoplastic cells. For this, a computer program was developed consisting of five modules that characterize different stages of images processing: selection of the region of interest, preprocessing, segmentation, post-processing and quantification. The system automatically identifies and segments the vascular network and quantifies the architectural pattern of the peritumoral vasculature, in a fast and objective fashion, by determining the fractal dimension and the following morphometric descriptors: vascular area, vascular area density, vascular perimeter, total vascular length, number of blood vessels, number of end points, number of bifurcations, number of nodes, number of branches, vascular density and vascular thickness. The validation process of the proposed computational system (automatic method) involved the evaluation of validity and reliability. Thus, there were used digital images of the vascular network of the tumor surrounding areas, obtained, in a standardized fashion and without applying means of contrasting the vessels, of a model of subcutaneous heterotopic implant of Walker's 256 carcinossarcoma cells on the back of rats. The evaluation of the validity of the automatic method included the comparison of automatic recognition of blood vessels performed by the software on 25 subimages with the manual recognition performed by two raters (gold-standard) and then determining the sensitivity, specificity and the kappa coefficient . It also involved the quantification of agreement between manual and automatic methods in the measurement of morphometric descriptors. Furthemore, it included the comparison of the performance of the proposed system with that of a comparator software in relation to the determination of the fractal dimension in 30 images. To assess reliability, two examiners used the automatic method for analyzing 30 images at two moments. The intra-rater, inter-raters and between methods agreement was assessed by calculating intraclass correlation coefficient. The sensitivity of the automatic method was 84.64%, while its specificity was 96.72%. The agreement between manual and automatic recognition of blood vessels was classified as almost perfect, according to kappa statistics. It was classified as good to excellent the agreement between the measurements of the morphometric descriptors performed by manual and automatic methods. The agreement between the proposed system and the comparator software in relation to fractal dimension measurements was excellent. Inter-raters agreement was quantified as good at moment 1 and as moderate to good at moment 2. Intra-rater agreement was assessed as good for examiner 1 and as moderate to good for examiner 2. Therefore, such results demonstrate that the proposed computational system constitutes an accurate and reproducible method for morphometric and fractal analysis of the peritumoral vascular network.