Effect of Model-Based Iterative Reconstruction on CT Number Measurements Within Small (10-29 mm) Low-Attenuation Renal Masses.

Journal: AJR. American Journal Of Roentgenology
Published:
Abstract

Objective: The purpose of this study was to assess the effect of model-based iterative reconstruction (MBIR) on CT number measurements within small (10-29 mm) low-attenuation renal masses.

Methods: One hundred 10- to 29-mm exophytic or endophytic low-attenuation renal lesions imaged with CT (unenhanced and nephrographic [100 seconds] phases, 120 kVp, variable mA, 2.5-mm slice thickness) were identified in 100 patients. The raw CT source data were prospectively reconstructed twice: once using Veo MBIR and once using a blend of 30% adaptive statistical iterative reconstruction (ASiR) and filtered back projection (FBP). Lesions were chosen to form four equal-sized (n = 25) groups stratified by lesion size (10-19 or 20-29 mm) and growth pattern (endophytic or exophytic). Attenuation (in HU) was measured using identical ROIs and compared with two-tailed t tests. The effects of patient diameter and lesion anatomy on attenuation discrepancies of 5 HU or more were assessed using binary logistic regression.

Results: Mean MBIR attenuation was not significantly different than mean 30% ASiR/FBP attenuation in the overall study population (unenhanced phase, 17 ± 13 vs 17 ± 13 HU, p = 0.74; nephrographic phase, 31 ± 27 vs 30 ± 26 HU, p = 0.89) or in any subgroup (p = 0.63-0.95). Only lesion size predicted discrepancies of 5 HU or more (p = 0.008; odds ratio, 1.20 [95% CI, 1.05-1.34] per 1 mm decrease) (p = 0.19-0.98 for the other variables). Seven lesions had enhancement of 20 HU or more with only one reconstruction method (MBIR = 4; 30% ASiR = 3).

Conclusions: Veo MBIR has no significant or consistent effect on attenuation measurements within small (10-29 mm) low-attenuation renal masses and is therefore unlikely to change clinically accepted attenuation thresholds for renal mass characterization.

Authors
Kimberly Shampain, Matthew Davenport, Richard Cohan, Mitchell Goodsitt, James Ellis, Joel Platt

Similar Publications