CT reconstruction algorithms affect histogram and texture analysis: evidence for liver parenchyma, focal solid liver lesions, and renal cysts

摘要

PurposeTo determine the effects of different reconstruction algorithms on histogram and texture features in different targets.Materials and methodsAmong 3620 patients, 480 had normal liver parenchyma, 494 had focal solid liver lesions (metastases=259; hepatocellular carcinoma=99; hemangioma=78; abscess=32; and cholangiocarcinoma=26), and 488 had renal cysts. CT images were reconstructed with filtered back-projection (FBP), hybrid iterative reconstruction (HIR), and iterative model reconstruction (IMR) algorithms. Computerized histogram and texture analyses were performed by extracting 11 features.ResultsDifferent reconstruction algorithms had distinct, significant effects. IMR had a greater effect than HIR. For instance, IMR had a significant effect on five features of liver parenchyma, nine features of focal liver lesions, and four features of renal cysts on portal-phase scans and four, eight, and four features, respectively, on precontrast scans (p .05). Most parameters showed good or excellent intra- and interobserver agreement, with intraclass correlation coefficients ranging from 0.634 to 0.972.ConclusionsDifferent reconstruction algorithms affect histogram and texture features. Reconstruction algorithms showed stronger effects in focal liver lesions than in liver parenchyma or renal cysts.Key Points center dot Imaging heterogeneities influenced the quantification of image features.center dot Different reconstruction algorithms had a significant effect on histogram and texture features.center dot Solid liver lesions were more affected than liver parenchyma or cysts.