Summation and axial slab reformation of thin-section abdominal CT: How much are they different from primary reconstruction of a raw projection data?

Summation and axial slab reformation (ASR) of thin-section CT dataset are increasingly used to increase productivity against data explosion and to increase the image quality. We hypothesized that the summation or ASR can substitute primary reconstruction (PR) directly from a raw projection data. PR datasets (5-mm section thickness, 20% overlap) were reconstructed in 150 abdominal studies. Summation and ASR datasets of the same image positions and nominal section thickness were calculated from thin-section reconstruction images (2-mm section thickness, 50% overlap). Median root-mean-square error between PR and summation (9.55: 95% CI: 9.51, 9.59) was significantly greater than that between PR and ASR (7.12: 95% CI: 7.08, 7.17) (p < 0.0001). Three radiologists independently analyzed 2,000 pairs of PR and test images (PR [as control], summation, or ASR) to determine if summation or ASR is distinguished from PR. Multireader-multicase ROC analysis showed that Az value was 0.597 (95% CI: 0.552, 0.642) for the discrimination between PR and summation, and 0.574 (95% CI: 0.529, 0.619) for the discrimination between PR and ASR. The difference between these two Az values were not significant (p = 0.41). Radiologists can distinguish between the PR image and the summation or ASR image in abdominal studies, although this discrimination performance is slightly better than would be expected from random guessing. Image fidelity of ASR is higher than that of summation, if PR is regarded as the reference standard.