Purpose: To assess how ASIR (adaptive statistical iterative reconstruction) contributes to dose reduction and affects image quality of non-contrast cranial computed tomography (cCT).
Materials and methods: Non-contrast emergency CT scans of the head acquired in 177 patients were evaluated. The scans were acquired and processed using four different protocols: Group A (control): 120 kV, FBP (filtered back projection) n = 71; group B1: 120 kV, scan and reconstruction performed with 20 % ASIR (blending of 20 % ASIR and 80 % FBP), n = 86; group B2: raw data from group B1 reconstructed using a blending of 40 % ASIR and 60 % FBP, n = 74; group C1: 120 kV, scan and reconstruction performed with 30 % ASIR, n = 20; group C2: raw data from group C1 reconstructed using a blending of 50 % ASIR and 50 % FBP, n = 20. The effective dose was calculated. Image quality was assessed quantitatively and qualitatively.
Results: Compared to group A, groups B1/2 and C1/2 showed a significantly reduced effective dose of 40.4 % and 73.3 % (p < 0.0001), respectively. Group B1 and group C1/2 also showed significantly reduced quantitative and qualitative image quality parameters. In group B2, quantitative measures were comparable to group A, and qualitative scores were lower compared to group A but higher compared to group B1. Diagnostic confidence grading showed groups B1/2 to be adequate for everyday clinical practice. Group C2 was considered acceptable for follow-up imaging of severe acute events such as bleeding or subacute stroke.
Conclusion: Use of ASIR makes it possible to reduce radiation significantly while maintaining adequate image quality in non-contrast head CT, which may be particularly useful for younger patients in an emergency setting and in follow-up.
Key points: ASIR may reduce radiation significantly while maintaining adequate image quality. cCT protocol with 20 % ASIR and 40 %ASIR/60 %FBP blending is adequate for everyday clinical use. cCT protocol with 30 % ASIR and 50 %ASIR/50 %FBP blending is adequate for follow-up imaging
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