Two- versus three-dimensional colon evaluation with recently developed virtual dissection software for CT colonography.
This retrospective study was institutional review board approved; the requirement for informed patient consent was waived. The purpose of this study was to retrospectively compare a two-dimensional (2D) data interpretation technique with a three-dimensional (3D) colon dissection technique in terms of interpretation time and sensitivity for colonic polyp detection, with colonoscopy as the reference standard. Ninety-six patients (56 men, 40 women; mean age, 54.8 years) underwent colonoscopy and multidetector computed tomographic (CT) colonography on the same day. Two radiologists independently analyzed the data on a per-polyp and per-patient basis. The sensitivity of both approaches was compared by using the McNemar test. The time required to interpret CT colonographic data with each technique was also assessed. Compared with the conventional 2D colonic polyp detection method, primary 3D interpretation with use of virtual dissection software for CT colonography revealed comparable per-polyp (77% and 69% for two readers) and per-patient (77% and 73% for two readers) sensitivities and comparable per-patient specificity (99% and 89% for two readers) for the detection of polyps 6 mm in diameter or larger and involved a shorter interpretation time.
Kim
Se Hyung
SH
Department of Radiology and Institute of Radiation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, 28 Yongon-dong, Chongno-gu, Seoul 110-744, Korea.
Lee
Jeong Min
JM
Eun
Hyo Won
HW
Lee
Min Woo
MW
Han
Joon Koo
JK
Lee
Jae Young
JY
Choi
Byung Ihn
BI
D000328:Adult; D000368:Aged; D003111:Colonic Polyps / Q000000981:diagnostic imaging*; D023881:Colonography, Computed Tomographic; D003113:Colonoscopy; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008875:Middle Aged; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012189:Retrospective Studies; D012984:Software; D018709:Statistics, Nonparametric