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Publication Detail
CT colonography: external clinical validation of an algorithm for computer-assisted prone and supine registration.
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Evaluation Study
  • Authors:
    Boone DJ, Halligan S, Roth HR, Hampshire TE, Helbren E, Slabaugh GG, McQuillan J, McClelland JR, Hu M, Punwani S, Taylor SA, Hawkes DJ
  • Publication date:
    09/2013
  • Pagination:
    752, 760
  • Journal:
    Radiology
  • Volume:
    268
  • Issue:
    3
  • Status:
    Published
  • Country:
    United States
  • PII:
    radiol.13122083
  • Language:
    eng
  • Keywords:
    Algorithms, Anatomic Landmarks, Colonic Polyps, Colonography, Computed Tomographic, Humans, Patient Positioning, Prevalence, Prone Position, Radiographic Image Enhancement, Subtraction Technique, Supine Position, United States
Abstract
PURPOSE: To perform external validation of a computer-assisted registration algorithm for prone and supine computed tomographic (CT) colonography and to compare the results with those of an existing centerline method. MATERIALS AND METHODS: All contributing centers had institutional review board approval; participants provided informed consent. A validation sample of CT colonographic examinations of 51 patients with 68 polyps (6-55 mm) was selected from a publicly available, HIPAA compliant, anonymized archive. No patients were excluded because of poor preparation or inadequate distension. Corresponding prone and supine polyp coordinates were recorded, and endoluminal surfaces were registered automatically by using a computer algorithm. Two observers independently scored three-dimensional endoluminal polyp registration success. Results were compared with those obtained by using the normalized distance along the colonic centerline (NDACC) method. Pairwise Wilcoxon signed rank tests were used to compare gross registration error and McNemar tests were used to compare polyp conspicuity. RESULTS: Registration was possible in all 51 patients, and 136 paired polyp coordinates were generated (68 polyps) to test the algorithm. Overall mean three-dimensional polyp registration error (mean ± standard deviation, 19.9 mm ± 20.4) was significantly less than that for the NDACC method (mean, 27.4 mm ± 15.1; P = .001). Accuracy was unaffected by colonic segment (P = .76) or luminal collapse (P = .066). During endoluminal review by two observers (272 matching tasks, 68 polyps, prone to supine and supine to prone coordinates), 223 (82%) polyp matches were visible (120° field of view) compared with just 129 (47%) when the NDACC method was used (P < .001). By using multiplanar visualization, 48 (70%) polyps were visible after scrolling ± 15 mm in any multiplanar axis compared with 16 (24%) for NDACC (P < .001). CONCLUSION: Computer-assisted registration is more accurate than the NDACC method for mapping the endoluminal surface and matching the location of polyps in corresponding prone and supine CT colonographic acquisitions.
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