Knowledge-based iterative model reconstruction (IMR) algorithm in ultralow-dose CT for evaluation of XXXX : evaluation of radiation dose reduction, image quality, and diagnostic performance.

@entity1 @entity28 @entity30220 @entity2073 @entity1791
PURPOSE: To evaluate the efficacy of a knowledge-based iterative model reconstruction (IMR) algorithm for reducing image noise in ultralow-dose (ULD) CT for @entity1791 . MATERIALS AND METHODS: A total of 103 @entity1 diagnosed with urinary stones (n = 276) were enrolled. Regular dose (RD) scans (120 kV and 150 mAs, maximal tube current in dose modulation) were reconstructed using filtered back-projection ( @entity30220 , RD- @entity30220 ), and ULD scans (100 kV and 20 mAs, fixed tube current) were reconstructed with @entity30220 (ULD- @entity30220 ), statistical iterative reconstruction (IR; ULD-iDose), and a knowledge-based IMR algorithm (ULD-IMR). Prospective interpretations of the two scans were performed with respect to radiation dose, objective image noise, and subjective assessment. The subjective assessment was also evaluated with regard to each @entity1 's body mass index (BMI, < 25 or >=  25 kg/m(2)). Using RD CT (RD- @entity30220 ) as the reference standard, two reviewers assessed the diagnostic performance and inter-observer agreement for ULD-IMR. RESULT: The average effective doses with RD CT and ULD CT were 8.31 and 0.68 @entity2073 , respectively, and the average radiation dose reduction rate was 91.82% (p < 0.01). The lowest objective image noise was observed with ULD-IMR (p < 0.01). Subjective assessment in ULD-IMR was comparable to that of RD- @entity30220 , although RD- @entity30220 remained statistically superior. For BMI, there was a statistically significant difference in subjective image quality between the normal (4.7    0.54) and overweight or @entity28 groups (4.2    0.5) (p < 0.05). The ULD-IMR showed a greater than 75% concordant rate in overall stones and 100% in ureter stones larger than 3 mm. However, for stones <3 mm, neither reviewer had a good detection rate (45.5% and 56.9% for the general and genitourinary radiologist, respectively). Inter-observer agreement was almost perfect (k = 0.82). CONCLUSION: Despite a significant radiation dose reduction, ULD-IMR images were comparable in image quality and noise to RD- @entity30220 images. Furthermore, the diagnostic performance of the ULD non-enhanced CT protocol was comparable to that of the RD scan for diagnosing urinary stones larger than 3 mm.
