| Yan Bingqing,Yang Ming,Liu Zhichao,et al.Application of Auto-kV combined with clear infinity algorithm in coronary CT angiography[J].Chinese Journal of Radiological Medicine and Protection,2026,46(5):464-470 |
| Application of Auto-kV combined with clear infinity algorithm in coronary CT angiography |
| Received:October 27, 2025 |
| DOI：10.3760/cma.j.cn112271-20251027-00377 |
| KeyWords:Coronary CT angiography Auto tube voltage modulation technology Clear Infinity algorithm Image quality Radiation dose |
| FundProject:北京医学奖励基金会资助项目(YXJL-2024-0350-0096) |
| Author Name | Affiliation | E-mail | | Yan Bingqing | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Yang Ming | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Liu Zhichao | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Zhou Min | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Nie Zhuang | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Zhao Jie | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | | | Lei Ziqiao | Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China | leiziqiaowhxh@163.com |
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| Abstract:: |
| Objective To investigate the feasibility of automatic tube voltage modulation (Auto-kV) combined with the deep learning-based Clear Infinity (CI) algorithm for reducing radiation dose and contrast medium volume while improving image quality in coronary CT angiography (CCTA). Methods A total of 120 patients scheduled for CCTA were prospectively enrolled and assigned to two groups randomly: Group A (n=60) underwent fixed 100 kV scanning with a uniform contrast volume of 45 ml, Group B (n=60) underwent Auto-kV scanning, with contrast volume and flow rate adjusted according to the selected tube voltage. Radiation dose parameters[volume CT dose index (CTDIvol), dose-length product (DLP), effective dose (E)] were recorded for both groups. Images in Group A were reconstructed using 50%-weighted Clear View (CV) iterative algorithm. Images in Group B were reconstructed using 50%-weighted CV (Subgroup B1) and CI with 30%, 50%, and 70% blending weights (Subgroups B2, B3, B4) CT attenuation and image noise (standard deviation, SD) were measured in the aortic root, coronary artery segments, and chest wall fat. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. Subjective image quality was scored using a 4-point scale. Results Group B demonstrated significantly lower CTDIvol, DLP, and E compared to Group A (t=-3.21, -3.78, -3.78,P<0.05), with a concomitant reduction in contrast medium volume. When reconstructed with the same algorithm (CV50%), subgroup B1 exhibited significantly higher coronary artery CT values and noise (SD) than Group A, while no significant intergroup differences were observed in SNR, CNR, or subjective image quality scores (P>0.05). Relative to B1, the B2-B4 subgroups showed significantly increased CT attenuation across all coronary segments (t=-30.65 to -9.54, P<0.05), significantly lower noise (t=11.26-26.42,P<0.05), and consequently, significantly higher SNR and CNR (t=-20.32 to -14.56, -20.89 to -14.60, P<0.05). These objective image quality parameters displayed a graded response to increasing CI blending weight: CT value, SNR, and CNR increased progressively, whereas noise (SD) decreased in a stepwise manner. All reconstructions (B1-B4) yielded diagnostically acceptable image quality(subjective score≥2). Subgroups B2 and B3 received the highest subjective scores, which were significantly superior to those of both B1 (Z=-3.68 to -3.32, P<0.05)and B4 (Z=2.97 to 3.32, P<0.05). No statistically significant difference was found between the subjective scores of B1 and B4 (P>0.05). Conclusions Auto-kV combined with the CI algorithm can reduce radiation dose and contrast medium volume while improving image quality in CCTA. CI reconstruction with moderate blending weights (30%-50%) yielded the best subjective image quality and is recommended as the routine clinical reconstruction protocol. |
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