Image quality and radiation dose reduction in chest CT in pulmonary infection

2020 
To evaluate the effect of dose reduction with iterative reconstruction (IR) on image quality of chest CT scan comparing two protocols. Fifty-nine patients were enrolled. The two CT protocols were applied using Iterative Reconstruction (ASIR™) 40% but different noise indexes, recording dose-length product (DLP) and volume computed tomography dose index (CTDIvol). The subjective IQ was rated based on the distinction of anatomic details using a 4-point Likert scale based on the European Guidelines on Quality Criteria for CT. For each patient, two single CTs, at enrollment (group 1) and at follow-up after lowering the dose (group 2), were evaluated by two radiologists evaluating, for each examination, five different lung regions (central zone—CZ; peripheral zone—PZ; sub-pleural region—SPR; centrilobular region—CLR; and apical zone—AZ). An inter-observer agreement was expressed by weighted Cohen’s kappa statistics (k) and intra-individual differences of subjective image analysis through visual grading characteristic (VGC) analysis. An average 50.4% reduction in CTDIvol and 51.5% reduction in DLP delivered were observed using the dose-reduced protocol. An agreement between observers evaluating group 1 CTs was perfect (100%) and moderate to good in group 2 examinations (k-Cohen ranging from 0.56 for PZ and AZ to 0.70 for SPR). In the VGC analysis, image quality ratings were significantly better for group 1 than group 2 scans for all regions (AUCVGC ranging from 0.56 for CZ to 0.62). However, disagreement was limited to a score 4 (excellent)-to-score 3 (good) IQ transition; apart from a single case in PZ, both the observers scored the IQ at follow-up as 2 (sufficient) starting from a score 4 (excellent). Dose reduction achieved in the follow-up CT scans, although a lower IQ still allows a good diagnostic confidence.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    37
    References
    4
    Citations
    NaN
    KQI
    []