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CT reconstruction algorithms affect histogram and texture analysis: evidence for liver parenchyma, focal solid liver
Su Joa Ahn1, Jung Hoon Kim2,3, Sang Min Lee4
1Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Republic of Korea.
Purpose:
To determine the effects of different reconstruction algorithms on histogram and texture features in different targets.
Materials And Methods:
Among 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.
Results:
Different 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 < 0.05). Meanwhile, different algorithms had a greater effect on focal liver lesions (six in HIR and nine in IMR on portal-phase, three in HIR, and eight in IMR on precontrast scans) than on liver parenchyma or cysts. The mean attenuation and standard deviation were not affected by the reconstruction algorithm (p > .05). Most parameters showed good or excellent intra- and interobserver agreement, with intraclass correlation coefficients ranging from 0.634 to 0.972.
Conclusions:
Different 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:
• Imaging heterogeneities influenced the quantification of image features. • Different reconstruction algorithms had a significant effect on histogram and texture features. • Solid liver lesions were more affected than liver parenchyma or cysts.
Insights
Different CT reconstruction algorithms significantly impact histogram and texture features, particularly in focal liver lesions compared to liver parenchyma or renal cysts.
Area of Science:
- Radiology
- Medical Imaging
- Image Analysis
Background:
- Image reconstruction algorithms are crucial for CT image quality.
- Understanding their impact on quantitative features is essential for accurate diagnosis.
- Focal liver lesions, liver parenchyma, and renal cysts present varying imaging characteristics.
Purpose of the Study:
- To evaluate the influence of different CT reconstruction algorithms on histogram and texture features.
- To compare these effects across normal liver parenchyma, focal liver lesions, and renal cysts.
Main Methods:
- CT images from 3620 patients were analyzed.
- Images were reconstructed using filtered back-projection (FBP), hybrid iterative reconstruction (HIR), and iterative model reconstruction (IMR).
- 11 histogram and texture features were extracted and analyzed.
Main Results:
- Reconstruction algorithms significantly affected histogram and texture features.
- Iterative model reconstruction (IMR) demonstrated a greater effect than hybrid iterative reconstruction (HIR).
- Focal liver lesions were more influenced by reconstruction algorithms than liver parenchyma or renal cysts.
Conclusions:
- CT reconstruction algorithms have a significant and differential impact on quantitative image features.
- The choice of reconstruction algorithm is critical when analyzing histogram and texture features, especially for focal liver lesions.
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