Paper
20 March 2014 Grading vascularity from histopathological images based on traveling salesman distance and vessel size
M. Khalid Khan Niazi, Jessica Hemminger, Habibe Kurt, Gerard Lozanski, Metin Gurcan
Author Affiliations +
Abstract
Vascularity represents an important element of tissue/tumor microenvironment and is implicated in tumor growth, metastatic potential and resistence to therapy. Small blood vessels can be visualized using immunohistochemical stains specific to vascular cells. However, currently used manual methods to assess vascular density are poorly reproducible and are at best semi quantitative. Computer based quantitative and objective methods to measure microvessel density are urgently needed to better understand and clinically utilize microvascular density information. We propose a new method to quantify vascularity from images of bone marrow biopsies stained for CD34 vascular lining cells protein as a model. The method starts by automatically segmenting the blood vessels by methods of maxlink thresholding and minimum graph cuts. The segmentation is followed by morphological post-processing to reduce blast and small spurious objects from the bone marrow images. To classify the images into one of the four grades, we extracted 20 features from the segmented blood vessel images. These features include first four moments of the distribution of the area of blood vessels, first four moments of the distribution of 1) the edge weights in the minimum spanning tree of the blood vessels, 2) the shortest distance between blood vessels, 3) the homogeneity of the shortest distance (absolute difference in distance between consecutive blood vessels along the shortest path) between blood vessels and 5) blood vessel orientation. The method was tested on 26 bone marrow biopsy images stained with CD34 IHC stain, which were evaluated by three pathologists. The pathologists took part in this study by quantifying blood vessel density using gestalt assessment in hematopoietic bone marrow portions of bone marrow core biopsies images. To determine the intra-reader variability, each image was graded twice by each pathologist with two-week interval in between their readings. For each image, the ground truth (grade) was acquired through consensus among the three pathologists at the end of the study. A ranking of the features reveals that the fourth moment of the distribution of the area of blood vessels along with the first moment of the distribution of the shortest distance between blood vessels can correctly grade 68.2% of the bone marrow biopsies, while the intra- and inter-reader variability among the pathologists are 66.9% and 40.0%, respectively.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Khalid Khan Niazi, Jessica Hemminger, Habibe Kurt, Gerard Lozanski, and Metin Gurcan "Grading vascularity from histopathological images based on traveling salesman distance and vessel size", Proc. SPIE 9041, Medical Imaging 2014: Digital Pathology, 90410C (20 March 2014); https://doi.org/10.1117/12.2043808
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KEYWORDS
Blood vessels

Image segmentation

Bone

Biopsy

Tumors

RGB color model

Databases

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