Automatic vessel segmentation and quantification of the rat aortic ring assay of angiogenesis

• Published in: Laboratory investigation Vol. 73; no. 5; p. 734
• Main Authors: Nissanov, J, Tuman, R W, Gruver, L M, Fortunato, J M
• Format: Journal Article
• Language: English
• Published: United States 01-11-1995
• Subjects: Animals; Aorta; Culture Techniques; Hydrocortisone - pharmacology; Image Processing, Computer-Assisted - instrumentation; Image Processing, Computer-Assisted - methods; Male; Neovascularization, Pathologic; Neovascularization, Physiologic - drug effects; Rats; Rats, Sprague-Dawley; Sensitivity and Specificity
• ISSN: 0023-6837

Pharmacologic control of angiogenesis is a promising new approach to the treatment of a variety of pathologic conditions including cancer. The recently developed in vitro rat aortic ring model provides a simple, reproducible assay for discovering angiogenic agonists and antagonists. However, quantification of results in this assay is time consuming, tedious, and subjective, because it involves visual inspection of images and manually counting the newly formed microvessels extending from the cultured aortic ring. This report describes an automated image analysis-based procedure for quantification of this assay that overcomes these difficulties.
The designed image processing algorithm segments the vessels from gray scale images. A high-pass filter is used, and the results are separated into nonvascular and vessel compartments based on object size and shape. Quantification relies on identification of vessels intersecting a closed transect set a fixed distance from the aortic ring. The number and the total area of these vessels are determined. The entire operation has been automated and packaged in an application called Vessels.
The correlation between computer-determined vessel area/vessel number and visual microvessel count is high (r2 = 0.91 and r2 = 0.86, respectively).
Vessels offers high-speed, fully automatic batch processing including production of a hard copy for documentation. The application runs on the Apple family of computers. On a Quadra 800, the application can process approximately 30 images/hour, which is approximately 2.5 times faster than manual quantification of this assay.