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.
Department of Radiology, The Hospital of the University of Pennsylvania, One Silverstein, 3400 Spruce Street, Philadelphia, PA, 19104, USA. cnweber49@gmail.com.
Charles N
CN
Weber
Department of Radiology, The Hospital of the University of Pennsylvania, One Silverstein, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
Anna S
AS
Lev-Toaff
Department of Radiology, The Hospital of the University of Pennsylvania, One Silverstein, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
Marc S
MS
Levine
Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, USA.
Sandra
S
Sudarsky
Siemens Healthcare GmbH, Forchheim, Germany.
Lutz
L
Guendel
Medical Imaging Technologies, Siemens Healthcare, Princeton, NJ, USA.
Bernhard
B
Geiger
Department of Radiology, The Hospital of the University of Pennsylvania, One Silverstein, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
Hanna M
HM
Zafar
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003106:Colon / Q000033:anatomy & histology*; D023881:Colonography, Computed Tomographic; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012984:Software
CT colonography; Colonic morphology; Feasibility and reproducibility; Quantitative assessment