WE-D-18A-03: BEST IN PHYSICS (IMAGING) – Statistical Model Based Iterative Reconstruction (MBIR) in Clinical CT Systems: Experimental Assessment of Z- and Axial Spatial Resolution




The purpose of this work was to experimentally assess the unique spatial resolution characteristics of statistical model based iterative reconstruction (MBIR) along both axial and z directions and to examine the impact of spatial resolution on the task-based diagnostic detection performance.


An anthropomorphic chest phantom was repeatedly scanned 100 times using a clinical CT scanner at four dose levels (25%, 50%, 75%, 100%). Both FBP and MBIR (Veo™) were used for reconstruction. Nine objects with contrasts ranging from 13 to 1710 HU were used to assess spatial resolution. The axial and z resolutions were quantified locally in the image domain by point spread functions (PSF) and slice sensitivity profiles (SSP) respectively. The tradeoff between local image noise and resolution and their joint impact on the channelized Hotelling observer (CHO) detectabilities (d ') was investigated.


The axial resolution of MBIR improved monotonically with increasing dose and contrast level (FWHM_PSF=2.0 mm at 13 HU/25% dose and was 0.8 mm 1710 HU/100% dose). In comparison, axial resolution of FBP was independent of dose and contrast (FWHM_PSF=1.2 mm). The z resolution of MBIR demonstrated similar contrast dependence but only negligible dose dependence. The spatial resolution of MBIR and FBP became equivalent at some transitional contrast levels (280 HU for 25% dose and 90 HU for 100% dose), above which MBIR demonstrated superior resolution than FBP (and vice versa). Spatial resolution and noise assessed at the same location demonstrated a strong tradeoff in MBIR, and CHO detectability index d' was improved by MBIR for all contrast and dose levels.


MBIR produces images with unique spatial resolution characteristics and introduces new challenges to its clinical use and evaluation. One potential solution, as suggested by this work, is to perform rigorous spatial resolution and noise measurements at different dose levels for each specific task.

K. Li, J. Garrett, Y. Ge: Nothing to disclose; G.-H. Chen: Research funded, General Electric Company Research funded, Siemens AG Research funded, Varian Medical Systems, Research funded, Hologic, Inc.