Automated centerline for computed tomography colonography.

RATIONALE AND OBJECTIVES

A novel method to compute the centerline of the human colon obtained from computed tomography colonography is proposed. Two applications of this method are demonstrated: to compute local colonic distension (caliber), and to match polyps on supine and prone images.

MATERIALS AND METHODS

The centerline algorithm involves multiple steps including simplification of the colonic surface by decimation; thinning of the decimated colon to create a preliminary centerline; selection of equally spaced points on the preliminary centerline; grouping neighboring points; and mapping them back to rings in the original colon. This method was tested on 20 human computed tomography colonography datasets (supine and prone examinations of 10 patients) and on a computer-generated colon phantom.

RESULTS

Visual inspection of the colons and their centerlines showed the centerline to be accurate. For the colon phantom, the average error was only 1 mm. For 11 polyps visualized in both the supine and prone positions and found by computer-aided detection, the normalized distance along the centerline to each polyp was not significantly different on the supine and prone views (r = 0.999; P < .001).

CONCLUSION

This method produces an accurate colon centerline that may be useful for flight path planning, matching detections on the supine and prone views, and computing local colonic distension.