Feasibility of automated matching of supine and prone CT-colonography examinations.

Matching of prone and supine positions in CT colonography may improve accuracy of polyp detection. The purpose of this study was to investigate the feasibility of automatic prone-supine matching in CT-colonography using proven polyps as fixed points of reference. The method is based on similarities in the direction of centre-lines and allows for compression and extraction of the centre-lines in both positions. To illustrate the impact of the match error of the new method in practice, the visibility of the matched polyps in a primary three-dimensional unfolded cube setting was determined as well. The method was compared with a method that relies on the normalized distance along the centre-line (NDAC method). The median absolute match error was 14 mm (range 0-59 mm, average 20 mm) either proximal or distal from the actual polyp in prone position. In the observer study, 70% (26/37) of the polyps were directly visible in prone view. The overall difference in median absolute match error between both methods was small (2 mm), although half way along the centre-line there were polyps with substantial differences in match error (larger with NDAC). We concluded that automated prone-supine matching of CT-colonography studies is feasible and has a low match error. The difference with the NDAC method was small and not significant, although half way along the centre-line some differences were seen.

Aspects of computer-aided detection (CAD) and volumetry of pulmonary nodules using multislice CT.

With the superb spatial resolution of modern multislice CT scanners and their ability to complete a thoracic scan within one breath-hold, software algorithms for computer-aided detection (CAD) of pulmonary nodules are now reaching high sensitivity levels at moderate false positive rates. A number of pilot studies have shown that CAD modules can successfully find overlooked pulmonary nodules and serve as a powerful tool for diagnostic quality assurance. Equally important are tools for fast and accurate three-dimensional volume measurement of detected nodules. These allow monitoring of nodule growth between follow-up examinations for differential diagnosis and response to oncological therapy. Owing to decreasing partial volume effect, nodule volumetry is more accurate with high resolution CT data. Several studies have shown the feasibility and robustness of automated matching of corresponding nodule pairs between follow-up examinations. Fast and automated growth rate monitoring with only few reader interactions also adds to diagnostic quality assurance.

Segmentation and size measurement of polyps in CT colonography.

Virtual colonoscopy is a relatively new method for the detection of colonic polyps. Their size, which is measured from reformatted CT images, mainly determines diagnosis. We present an automatic method for measuring the polyp size. The method is based on a robust segmentation method that grows a surface patch over the entire polyp surface starting from a seed. Projection of the patch points along the polyp axis yields a 2D point set to which we fit an ellipse. The long axis of the ellipse denotes the size of the polyp. We evaluate our method by comparing the automated size measurement with those of two radiologists using scans of a colon phantom. We give data for inter-observer and intra-observer variability of radiologists and our method as well as the accuracy and precision.