External Clinical Validation of Prone and Supine CT Colonography Registration

• Published in: Abdominal Imaging. Computational and Clinical Applications pp. 10 - 19
• Main Authors: Roth, Holger R., Boone, Darren J., Halligan, Steve, Hampshire, Thomas E., McClelland, Jamie R., Hu, Mingxing, Punwani, Shonit, Taylor, Stuart, Hawkes, David J.
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2012
• Series: Lecture Notes in Computer Science
• Subjects: CT colonography; image registration
• ISBN: 9783642336119; 3642336116
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-33612-6_2

This paper provides an external validation of a prone-supine registration algorithm for CT colonography (CTC). A validation sample of 49 patient cases with 66 polyps (6 to 30 mm) was selected from a publicly available, anonymized CTC archive. To enhance generalizability, no case was excluded due to poor preparation or inadequate distension. Corresponding prone and supine polyp coordinates were recorded and the endoluminal surfaces registered: a Markov Random Field technique was used to find feature matches between prone/supine acquisitions and following mapping of the endoluminal surface to a cylinder, dense surface correspondence was achieved via cylindrical non-rigid registration. The polyp registration error was determined and a subjective assessment of registration made for 2D slice-based and 3D endoluminal data display using a pre-specified scoring system. Results were compared to using “normalized distance along the colon centerline” (NDACC) which approximates to the method currently employed to match colonic positions using proprietary CT colonography interpretation software. Registration was possible in all 49 cases. Overall mean 3D polyp registration error was significantly smaller with 19.9 mm in comparison to 27.7 mm using NDACC (p=0.001). 82.7% of polyp matches were defined as “successful” in comparison to 37.1% using NDACC according to the pre-specified criteria. Similarly, using 2D visualization, 62.1% registrations were “successful” and only 22.7% using NDACC. Full surface-based prone-to-supine registration can successfully map the location of a polyp identified on one acquisition to the corresponding endoluminal surface in the opposing acquisition, greatly facilitating polyp matching and aiding interpretation. Our method compares favorably to using NDACC.