What can the radiologist teach CAD: lessons from CT colonoscopy

CT colonography with computer-aided detection: recognizing the causes of false-positive reader results

Computed tomography (CT) colonography is a screening modality used to detect colonic polyps before they progress to colorectal cancer. Computer-aided detection (CAD) is designed to decrease errors of detection by finding and displaying polyp candidates for evaluation by the reader. CT colonography CAD false-positive results are common and have numerous causes. The relative frequency of CAD false-positive results and their effect on reader performance on the basis of a 19-reader, 100-case trial shows that the vast majority of CAD false-positive results were dismissed by readers. Many CAD false-positive results are easily disregarded, including those that result from coarse mucosa, reconstruction, peristalsis, motion, streak artifacts, diverticulum, rectal tubes, and lipomas. CAD false-positive results caused by haustral folds, extracolonic candidates, diminutive lesions (<6 mm), anal papillae, internal hemorrhoids, varices, extrinsic compression, and flexural pseudotumors are almost always recognized and disregarded. The ileocecal valve and tagged stool are common sources of CAD false-positive results associated with reader false-positive results. Nondismissable CAD soft-tissue polyp candidates larger than 6 mm are another common cause of reader false-positive results that may lead to further evaluation with follow-up CT colonography or optical colonoscopy. Strategies for correctly evaluating CAD polyp candidates are important to avoid pitfalls from common sources of CAD false-positive results.

CAD-associated reader error in CT colonography

RATIONALE AND OBJECTIVES

Computed tomographic colonographic interpretation with computer-aided detection (CAD) may be superior to unaided viewing, although polyp characteristics may influence accuracy. Reader error due to polyp characteristics was evaluated in a multiple-case, multiple-reader trial of computed tomographic colonography with CAD.

MATERIALS AND METHODS

Two experts retrospectively reviewed 52 positive cases (74 polyps) and categorized them as hard, moderate, or easy to detect. Each case was evaluated without and with CAD. Features that may influence a reader's ability to detect a polyp or to accept or reject a CAD mark were tabulated. The association between polyp characteristics and detection rates in the trial was assessed. The difference in detection rates (CAD vs unassisted) was calculated, and regression analysis was performed.

RESULTS

Of 64 polyps found by CAD, experts categorized 20 as hard, 28 as moderate, and 16 as easy to detect. Reader characterization errors predominated (47.3%) over other errors. Factors associated with lower detection rates included small size, flat morphology, and resemblance to a thickened fold. CAD was superior for polyps resembling lipomas compared to those that did not resemble lipomas (average increase in detection rate with CAD, 12.8% vs 5.5%; P < .05).

CONCLUSIONS

Polyp characteristic may impair computed tomographic colonographic interpretation augmented by CAD. Readers can avoid errors of measurement by evaluating diminutive polyp candidates with sample measurements. Caution should be taken when evaluating focally thick folds and when using visual impression to dismiss a polyp candidate as a lipoma when it is submerged in densely tagged fluid.