Application of a New Deep Learning Image Reconstruction (DLIR) Algorithm in Pediatric Orbital horizontal level Ultra-Low Dose CT scan: A Pilot Study Based on Image Quality

Purpose: To evaluate the performance of a new deep learning image reconstruction (DLIR) algorithm in pediatric orbital ultra-low-dose CT by sinus CT for improving image quality and reducing radiation dose. Methods: A retrospective analysis of 50 children who underwent paranasal sinus or orbital CT examination at our hospital was performed. ultra-low-dose CT of the nasal sinus was used to simulate orbital scanning as the experimental group and compared with the control group of general-low dose orbital CT. Two groups scanning used 100 kVp tube voltage, automatic tube current (SmartmA, 60-250 mA), slice thickness 1.25 mm, interslice spacing 1.25 mm, and pitch 0.992:1 with rotation time 1.00 s. The experimental group configured a Noise Index of 22 and a pre-ASiR-V weight of 70%, while the control group set a Noise Index of 8 and a pre-ASiR-V weight of 30%. The radiation dose, image noise (SD), signal-to-noise ratio (SNR), contrast noise ratio (CNR), and subjective scores of both groups were compared. The CT dose index (CTDI) and dose-length product (DLP) values were documented, and the effective dose (ED) was subsequently calculated. The results indicated that the experimental group experienced reductions of 83.92% in DLP and 83.17% in ED compared to the control group.Compared between DL-H (the optimal set of DLIR) and ASiR-V 70% (the control group), the image noise was reduced by 41.6% (4.17±0.86 HU vs. 7.14±1.19 HU), and the CNR was improved by 39.3% (26.60±5.61 vs. 16.14±2.48). In the qualitative image assessment, DL-H obtained the highest score. Conclusion: Combined with the comparison results of quantitative and qualitative image assessment, DL-H under the ultra-low-dose scan was significantly better than ASiR-V 70% under the general-low dose scan, and ASiR-V 70% was better than DL-M and DL-L. We can infer that the use of DL-H may be able to save a significant amount of radiation dose while achieving the current image quality.