Computer-aided detection (CAD) using 360 degree virtual dissection: can CAD in a first reviewer paradigm be a reliable substitute for primary 2D or 3D search?
OBJECTIVE
The purpose of this study was to evaluate the feasibility of a new computer-aided detection (CAD) software program as a first reviewer for detecting colorectal polyps when applied to 360 degrees virtual dissection image display.


METHODS
Forty-one consecutive patients who underwent imaging without oral contrast material for stool tagging from a teaching file database constituted the patient population for this feasibility study. Using CT colonography equipped with CAD software, reviewers evaluated each possible polyp detected by the software using virtual dissection images combined with axial and 3D endoluminal views and compared the results with optical colonoscopy, the reference standard. Two experienced radiologists blinded to the reference standard findings interpreted the CAD detections to be true or false. The false detections were reviewed and categorized.


RESULTS
Sensitivities for polyps that were 6-9 mm were 78.3% (18/23) and 91.3% (21/23) for reviewers 1 and 2, respectively. For polyps > or = 1 cm, sensitivities were 94.9% (37/39) and 97.4% (38/39) for reviewers 1 and 2, respectively. Per-patient sensitivities for polyps > or = 6 and > or = 10 mm were 94.4% (34/36) and 95.1% (39/41) for reviewer 1 and 97.2% (35/36) and 97.6% (40/41) for reviewer 2, respectively. The average number of false detections per acquisition was 4.28. The average interpretation times were 4 minutes 26 seconds and 5 minutes 38 seconds for reviewers 1 and 2, respectively.


CONCLUSIONS
Colorectal polyp detection using CT colonography equipped with CAD and virtual dissection as a first reviewer is feasible. Detection rates are similar to colonoscopy. Interobserver variability is low and interpretation times are short. False-positive detections per patient are few in number.
Johnson
Kristina T
KT
Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA.
Fletcher
Joel G
JG
Johnson
C Daniel
CD
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D023881:Colonography, Computed Tomographic / Q000379:methods*; D015179:Colorectal Neoplasms / Q000000981:diagnostic imaging*; D004210:Dissection / Q000379:methods; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012984:Software