Assessment of structural similarity in CT using filtered backprojection and iterative reconstruction: a phantom study with 3D printed lung vessels.

OBJECTIVE: To compare the performance of three generations of CT reconstruction techniques using structural similarity (SSIM) as a measure of image quality for CT scans of a chest phantom with 3D printed lung vessels.
METHODS: CT images of the chest phantom were acquired at seven dose levels by changing the tube current while other acquisition parameters were kept constant. Three CT reconstruction techniques were applied on each acquisition. The first technique was filtered backprojection (FBP), the second technique was FBP with iterative filtering (adaptive iteration dose reduction in 3 dimensions (AIDR 3D)) and the third technique was model-based iterative reconstruction (Forward projected model-based Iterative Reconstruction SoluTion (FIRST)). Image quality of the CT data was quantified in terms of SSIM. The SSIM index was used for image quality comparison between the dose levels and different reconstruction techniques. The SSIM index gives a value between 0 and 1, with 0 as the lowest image quality and 1 as an excellent image quality.
RESULTS: The lowest SSIM index was observed for FBP at all dose levels. The reconstruction technique with the highest SSIM depends on the dose level. For tube currents higher than 80 mA, AIDR 3D showed the highest SSIM index, and for tube currents lower or equal to 80 mA FIRST showed the highest SSIM index.
CONCLUSION: SSIM index is a robust quantity and is correlated to the image quality as perceived by the humans. Advanced CT reconstruction techniques provide better image quality in all conditions compared to FBP. Advances in knowledge: SSIM is a robust measure to compare CT image quality for advanced reconstruction techniques relative to a reference. The 3D print technology is an useful method for the development of dedicated phantoms for CT image quality evaluation.