Detailed quantitative assessment of colonic morphology at CT colonography using novel software: a feasibility and reproducibility study.

The aim of this study was to evaluate feasibility and reproducibility of quantitative assessment of colonic morphology on CT colonography (CTC). CTC datasets from 60 patients with optimal colonic distension were assessed using prototype software. Metrics potentially associated with poor endoscopic performance were calculated for the total colon and each segment including: length, volume, tortuosity (number of high curvature points <90°), and compactness (volume of box containing centerline divided by centerline length). Sigmoid apex height relative to the lumbosacral junction was also measured. Datasets were quantified twice each, and intra-reader reliability was evaluated using concordance correlation coefficient and Bland-Altman plot. Complete quantitative datasets including the five proposed metrics were generated from 58 of 60 (97 %) CTC examinations. The sigmoid and transverse segments were the longest (55.9 and 51.4 cm), had the largest volumes (0.410 and 0.609 L), and were the most tortuous (3.39 and 2.75 high curvature points) and least compact (3347 and 3595 mm2), noting high inter-patient variability for all metrics. Mean height of the sigmoid apex was 6.7 cm, also with high inter-patient variability (SD 6.8 cm). Intra-reader reliability was high for total and segmental lengths and sigmoid apex height (CCC = 0.9991) with excellent repeatability coefficient (CR = 3.0-3.3). There was low percent variance of metrics dependent upon length (median 5 %). Detailed automated quantitative assessment of colonic morphology on routine CTC datasets is feasible and reproducible, requiring minimal reader interaction.

Colon unfolding via skeletal subspace deformation.

We present an efficient method to digitally straighten a colon volume using mesh skinning, a technique well known in computer graphics to deform a polygonal mesh attached to a skeleton hierarchy. In our case, the colon centerline is used as the skeleton structure and the polyhedral model of the lumen as the skin that is to be deformed as the centerline is straightened. Once the colon has been straightened, we use standard rendering techniques to compute the virtual dissection. Our approach is significantly more efficient than previously proposed techniques.

Computed tomographic colonography: automated tool for polyp measurement delivering on patient risk stratification.

OBJECTIVE: We evaluated an automated polyp size measurement tool in computed tomographic colonography for its accuracy and value for patient risk stratification. METHODS: A simulation program generated a raw data phantom with sessile and pedunculated polyps of known sizes using 120 to 140 kV and 50, 40, 20, 15, and 10 mAs. All polyps were measured by clicking on the polyp surface. Comparison of the calculated size with the known polyp sizes allowed calculation of reproducibility and accuracy. For patients with proven polyps, we also compared automated measurements with manual and endoscopic measurements to evaluate the effect on patient risk stratification. RESULTS: The automated measurement tool allowed accurate measurements. In the patient study, assignment to the correct size group was not significantly different from the radiologist's results. However, it slightly improved patient risk stratification by reducing both failed and unnecessary colonoscopy referral. CONCLUSIONS: An automated tool for polyp measurement in patients facilitates patient risk stratification.

Comparative performance of two polyp detection systems on CT colonography.

OBJECTIVE: The purpose of our study was to evaluate two current automatic polyp detection systems to determine their sensitivity and false-positive rate in patients who have undergone CT colonography and subsequent endoscopy. MATERIALS AND METHODS: We evaluated two polyp detection systems--Polyp Enhanced Viewing (PEV) and the Summers computer-aided detection (CAD) system (National Institutes of Health [NIH]) using a unique cohort of CT colonography examinations: 31 examinations with true-positive lesions identified by radiologists and 34 examinations with false-positive lesions incorrectly identified by radiologists. All patients had reference-standard colonoscopy within 7 days of CT. Candidate lesions were compared with the endoscopic reference standard and prospective radiologist interpretation. The sensitivity and false-positive rates were calculated for each system. RESULTS: The NIH system had a higher sensitivity than the PEV tool for polyps > or = 1 cm (22/23, 96%; 78-99%, 95% CI vs 14/23, 61%; 38-81%, 95% CI; p = 0.008, respectively). There was no significant difference in the detection of medium-sized polyps 6-9 mm in size (8/13 vs 6/13, p = 0.68, respectively). The PEV tool had an average of 1.18 false-positive detections per patient, whereas the NIH tool had an average of 5.20 false-positive detections per patient, with the PEV tool having significantly fewer false-positive detections in both patient groups (p < 0.001). CONCLUSION: One polyp detection system tended to operate with a higher sensitivity, whereas the other tended to operate with a lower false-positive rate. Prospective trials using polyp detection systems as a primary or secondary means of CT colonography interpretation appear warranted.

Automated polyp measurement with CT colonography: preliminary observations in a phantom colon model.

OBJECTIVE: The purpose of this study was to evaluate the accuracy and precision of polyp measurements obtained with an automated tool in a colon phantom containing polyps of multiple sizes, morphologic types, and locations. MATERIALS AND METHODS: A colon phantom was scanned at 12, 25, 50, and 100 mA with standard CT colonographic acquisition parameters. Four reviewers using manual 2D methods and an automated polyp measurement tool measured 24 polyps of varying sizes and morphologic types, some at a haustral fold tip and some not at a fold tip. The accuracy (difference from true value) of manual and automated methods was compared across polyp sizes, morphologic types, locations, and doses. Precision (closeness of different measures) was compared for intraobserver and interobserver measurements. RESULTS: The accuracy of automated polyp measurement was dependent on morphologic type (p < or = 0.02), size (for three of four reviewers, p < or = 0.05), and location of polyps with respect to haustral folds (two of four reviewers, p < or = 0.01). For two of four reviewers, automated measures were less accurate for 5-mm polyps, flat polyps, and polyps at the tips of folds (p < or = 0.04). Intraobserver precision was high, two automated measurements being within 0.1 mm of each other 82-93% of the time. Interobserver precision values for automated measures were more similar 85% of the time (82/96; p < 0.001). CONCLUSION: Accuracy of automated polyp measurements depends on polyp size, morphologic type, and location. When using an automated tool, radiologists should visually inspect automated polyp measurements, particularly for small and flat polyps and those located on folds, because manual measurements may be more accurate in this setting. Automated polyp measurements are more precise than manual measurements.