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Comparative Evaluation of Total and Algorithmic MTFs in Four Iterative Reconstruction CT Systems

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H Jin

H Jin*, J Kim, Seoul National University, Seoul

SU-E-CAMPUS-I-1 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: MTF of iterative reconstruction (IR) CT is known to be contrast dependent, which is of critical importance for predicting signal response of lesions with different contrast. Previous studies attempting to characterize the contrast dependant MTF of IR CT were carried out using multi contrast phantoms, which is of limited effect in revealing the range of MTF change between extremely high and low contrast objects. This study presents a novel technique for assessing the range of MTF changes and compares the measurement results in four IR CT.
Methods: An AAPM phantom was scanned with 4 different CT systems (Discovery 750, GE, Somatom Definition, Siemens, Ingenuity, Philips, and Aquillion One, Toshiba) at same dose level (12.5mGy), and was reconstructed using FBP and IR techniques (ASIR and VEO in GE, Safire in Siemens, iDose4 in Philips, and AIDR in Toshiba). Total MTF was measured using a small bead in the phantom to characterize frequency response for high contrast objects. In addition, the algorithmic MTF was derived from noise power spectrum (NPS) using uniform background images in order to evaluate the frequency response for very low contrast objects.
Results: The algorithmic MTF₅₀ of FBP showed higher responses up to 16.5% than total MTF₅₀ in all 4 CT systems, which reflected the decoupling of focal spot blurring effect. The algorithmic MTF₅₀ of IR recons was lower that total MTF₅₀ in 2 vendors(GE, Siemens) showing up to 48% reduction of MTF₅₀ in VEO, whereas IR recons from the other 2 vendors showed no marked reduction of algorithmic MTF₅₀.
Conclusion: Our study revealed the degrading trends of MTF for low contrast objects in some IR technique. This characteristic needs to be considered in interpreting signal patterns of low contrast lesions in IR CT.

Funding Support, Disclosures, and Conflict of Interest: The research was supported by the Converging Research Center Program through the Ministry of Education, Science and Technology (2012K001498).

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