The clinical recognition of abnormal vascular tortuosity, or excessive bending, twisting, and winding, is important to the diagnosis of many diseases. Automated detection and quantitation of abnormal vascular tortuosity from three-dimensional (3-D) medical image data would, therefore, be of value. However, previous research has centered primarily upon two-dimensional (2-D) analysis of the special subset of vessels whose paths are normally close to straight. This report provides the first 3-D tortuosity analysis of clusters of vessels within the normally tortuous intracerebral circulation. We define three different clinical patterns of abnormal tortuosity. We extend into 3-D two tortuosity metrics previously reported as useful in analyzing 2-D images and describe a new metric that incorporates counts of minima of total curvature. We extract vessels from MRA data, map corresponding anatomical regions between sets of normal patients and patients with known pathology, and evaluate the three tortuosity metrics for ability to detect each type of abnormality within the region of interest. We conclude that the new tortuosity metric appears to be the most effective in detecting several types of abnormalities. However, one of the other metrics, based on a sum of curvature magnitudes, may be more effective in recognizing tightly coiled, "corkscrew" vessels associated with malignant tumors.

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Blood vessel morphology (vessel radius, branching pattern, and tortuosity) is altered by a multitude of diseases. Although murine models of human pathology are important to the investigation of many diseases, there are few publications that address quantitative measurements of murine vascular morphology. This report outlines methods of imaging mice in vivo using magnetic resonance angiograms obtained on a clinical 3T unit, of defining mouse vasculature from these images, and of quantifying measures of vessel shape. We provide examples of both healthy and diseased vasculature and illustrate how the approach can be used to assess pathology both visually and quantitatively. The method is amenable to the assessment of many diseases in both human beings and mice.