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Ultra fractal transfer between computers7/30/2023 ![]() As “Fractals are an attractive framework to try and resolve a variety of problems involving the assessment of structural complexity and irregularity” 11, fractal-based analysis has been increasingly used to investigate the vascular system in physiological as well as pathological states 5.Īs microvascularity has been shown as an alternative feature for differentiating astrocytic cancers of different grades 3, 14, 15, 16, 17, we explored a computer-assisted and fractal-based approach to objectively quantify the histological microvascular pattern configuration to establish a method that can be translated into clinical practice to appropriately describe and categorize gliomas.Ī factor analysis on the whole set of variables with varimax rotation ( Figure 4a) further demonstrated the structure of variation, with the first axis associated with an increase in mvFD, loc bcD and loc A% and the second axis associated with an increase in MVs/mm 2, loc A%, mvFD and MIB, respectively (in decreasing order of relevance). The last point cannot prescind from the other two points, because no method can be translated into clinical application without validation and standardization of the methodology.įractal geometry 8 has been accepted as a valid approach in the field of quantitative microscopy and histopathology 9, 10, 11, 12, 13. An index of the microvascularity should be: a) capable of quantitatively describing what the human eye visually observes and describes under the microscope in qualitative terms or by a semi-quantitative score b) objective, i.e., not affected by intra- and/or inter-observer variability and c) clinically meaningful, i.e., having potential prognostic and/or predictive value. ![]() Computer-assisted image analysis can improve the analyses of histological entities by generating continuous variables that can be used for statistical comparisons. Morphometrics is an integrative tool to study the microvasculature of brain tumors. Therefore, additional criteria and appropriate tools are required in tumor grading. The inter-observer variability and the erroneous perception of the tumor histology can results in a patient being over- or under-treated 7. However, the assignment of a glioma to a specific grade can be challenging, particularly in grade II versus grade III gliomas, according to the World Health Organization (WHO) classification system 6. Notwithstanding the existence of advanced genetic, biochemical, radiologic and nuclear imaging tools, the gold standard for typing and grading brain tumors is the evaluation of histological specimens performed by the neuropathologist. The histopathological diagnosis and grading of brain tumors have important implications in designing improved therapeutic strategies. However, there are no still available methods that have been validated for routine use in clinical practice 5. introduced the idea to quantify the neoplastic microvasculature in histological specimens in 1972 1, several investigators have studied the microvascular spatial pattern as a biomarker to predict the patient prognosis and response to anti-angiogenic drugs 2, 3, 4. The qualitative evaluation currently performed by the neuropathologist can be combined with the computer-assisted quantitative analysis of the microvascularity to improve the diagnosis and optimize the treatment of patients with brain cancer. ![]() The fractal parameters are reliable quantitative indicators of the neoplastic microvasculature, making them potential surrogate biomarkers. The computer-aided quantitative analysis also showed that grade III gliomas are generally more vascularized than grade II gliomas. The statistical analysis showed that the fractal-based indexes are the most discriminant parameters to describe the microvessels. A computer-aided and fractal-based analysis was used to describe the microvessels and to quantify their geometrical complexity in histological specimens collected from 17 patients. ![]() We propose and examine a computer-aided and fractal-based image analysis technique to quantify the microvascularity in histological specimens of WHO grade II and III gliomas. Fractal analysis is widely applied to investigate the vascular system in physiological as well as pathological states. ![]()
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