| 颜冰清,杨明,刘治超,等.自动管电压调制技术联合Clear Infinity算法在冠状动脉CT血管成像中的应用研究[J].中华放射医学与防护杂志,2026,46(5):464-470.Yan Bingqing,Yang Ming,Liu Zhichao,et al.Application of Auto-kV combined with clear infinity algorithm in coronary CT angiography[J].Chin J Radiol Med Prot,2026,46(5):464-470 |
| 自动管电压调制技术联合Clear Infinity算法在冠状动脉CT血管成像中的应用研究 |
| Application of Auto-kV combined with clear infinity algorithm in coronary CT angiography |
| 投稿时间：2025-10-27 |
| DOI：10.3760/cma.j.cn112271-20251027-00377 |
| 中文关键词: 冠状动脉CT血管成像 自动管电压调制技术 Clear Infinity算法 图像质量 辐射剂量 |
| 英文关键词:Coronary CT angiography Auto tube voltage modulation technology Clear Infinity algorithm Image quality Radiation dose |
| 基金项目:北京医学奖励基金会资助项目(YXJL-2024-0350-0096) |
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| 摘要点击次数: 2034 |
| 全文下载次数: 17 |
| 中文摘要: |
| 目的 探讨自动管电压调制技术(Auto-kV)联合基于深度学习的Clear Infinity (CI)算法在冠状动脉CT血管成像(CCTA)中降低辐射剂量与对比剂用量,同时提高图像质量的可行性。方法 前瞻性纳入华中科技大学同济医学院附属协和医院拟行CCTA检查的患者120例,按随机数表法分为A组(n=60)与B组(n=60):A组采用固定100 kV扫描,对比剂用量统一为45 ml;B组采用Auto-kV扫描,并根据不同的管电压给予不同的对比剂用量及流速。记录两组容积CT剂量指数(CTDIvol)、剂量长度乘积(DLP)、有效剂量(E)。A组图像采用50%权重的Clear View (CV)迭代算法重建,B组分别采用50%权重CV算法(B1组)及30%、50%、70%权重CI算法(B2、B3、B4组)重建。测量主动脉根部、冠状动脉各分支及胸壁脂肪的CT值与噪声(SD),并计算图像信噪比(SNR)及对比噪声比(CNR)。主观评分采用4分制。结果 B组的CTDIvol、DLP、E均显著低于A组(t=-3.21、-3.78、-3.78,P<0.05),对比剂用量较A组减少。在采用相同重建算法(CV 50%)的条件下,B1组冠状动脉CT值及SD显著高于A组,而两组的SNR、CNR及主观评分差异无统计学意义(P>0.05)。与B1组相比,B2~B4组各冠状动脉节段的CT值显著升高(t=-30.65~-9.54,P<0.05),噪声显著降低(t=11.26~26.42,P<0.05),SNR和CNR显著升高(t=-20.32~-14.56、-20.89~-14.60,P<0.05),且上述指标随CI权重增加呈阶梯式变化(CT值、SNR、CNR递增,SD递减)。所有重建图像(B1~B4)均满足诊断要求(主观评分≥2分),其中B2与B3组主观评分高于B1组(Z=-3.68~-3.32,P<0.05)与B4组(Z=2.97~3.32,P<0.05),B1组和B4组主观评分差异无统计学意义(P>0.05)。结论 Auto-kV联合Clear Infinity算法可以在降低CCTA检查辐射剂量与对比剂用量的同时提升图像质量,其中30%~50%中低权重CI重建在主观评分上表现最佳,推荐作为CCTA临床常规重建方案。 |
| 英文摘要: |
| 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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