External clinical validation of prone and supine CT colonography registration

Authors:
Holger R. Roth;Darren J. Boone;Steve Halligan;Thomas E. Hampshire;Jamie R. McClelland;Mingxing Hu;Shonit Punwani;Stuart Taylor;David J. Hawkes
Affiliations:
Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Imaging, Department of Specialist Radiology, University College Hospital, London, UK;Centre for Medical Imaging, Department of Specialist Radiology, University College Hospital, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Image Computing, University College London, London, UK;Centre for Medical Imaging, Department of Specialist Radiology, University College Hospital, London, UK;Centre for Medical Imaging, Department of Specialist Radiology, University College Hospital, London, UK;Centre for Medical Image Computing, University College London, London, UK
Venue:
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
Year:
2012

Citing 4
Cited 0

Discrete Surface Ricci Flow

IEEE Transactions on Visualization and Computer Graphics
Fast free-form deformation using graphics processing units

Computer Methods and Programs in Biomedicine
Supine and Prone Colon Registration Using Quasi-Conformal Mapping

IEEE Transactions on Visualization and Computer Graphics
Automatic prone to supine haustral fold matching in CT colonography using a Markov random field model

MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.