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Relating noise to image quality indicators in CT examinations with tube current modulation
Justin B Solomon1, Xiang Li, Ehsan Samei
1Carl E. Ravin Advanced Imaging Laboratories and Clinical Imaging Physics Group, Department of Radiology, Medical Physics Graduate Program, Duke University Medical Center, Hock Plaza, 2424 Erwin Rd, Ste 302, Durham, NC 27705, USA. justin.solomon@duke.edu
Objective:
Modern CT systems use surrogates of noise-noise index (NI) and quality reference effective tube current-time product (Q)-to infer the quality of images acquired using tube current modulation. This study aimed to determine the relationship between actual noise and these surrogates for two CT scanners from two different manufacturers.
Materials And Methods:
Two phantoms (adult and 1-year-old child) were imaged on two CT scanners (64 and 128 MDCT) using a clinical range of NI (6-22) and Q (30-300 mA). Each scan was performed twice, and noise was measured in the mediastinum, lung, and abdomen using an image subtraction technique. The effect on noise from changing other imaging parameters, such as beam collimation, pitch, peak kilovoltage, slice thickness, FOV, reconstruction kernel or algorithm, and patient age category (adult or pediatric), was investigated.
Results:
On the 64-MDCT scanner, noise increased linearly along with NI, with the slope affected by changing the anatomy of interest, peak kilovoltage, reconstruction algorithm, and convolution kernel. The noise-NI relationship was independent of phantom size, slice thickness, pitch, FOV, and beam width. On the 128-MDCT scanner, noise decreased nonlinearly along with increasing Q, slice thickness, and peak tube voltage. The noise-Q relationship also depended on anatomy of interest, phantom size, age selection, and reconstruction algorithm but was independent of pitch, FOV, and detector configuration.
Conclusion:
We established how noise changes with changing image quality indicators across a clinically relevant range of imaging parameters. This work can aid in optimizing protocols by targeting specific noise levels for different types of CT examinations.
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