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“双低”扫描方案联合人工智能迭代重建算法用于肥胖患者腹部CT增强扫描的可行性研究

Feasibility study of "double-low" scanning protocol combined with artificial intelligence iterative reconstruction algorithm for abdominal computed tomography enhancement in patients with obesity.

作者信息

Ji Mei-Tong, Wang Ren-Ren, Wang Qi, Li Han-Shuo, Zhao Yong-Xia

机构信息

Department of Radiology, Affiliated Hospital of Hebei University, Baoding City, Hebei Province, 071000, China.

出版信息

BMC Med Imaging. 2025 Jul 9;25(1):276. doi: 10.1186/s12880-025-01808-9.

DOI:10.1186/s12880-025-01808-9
PMID:40634847
Abstract

OBJECTIVE

To evaluate the efficacy of the "double-low" scanning protocol combined with the artificial intelligence iterative reconstruction (AIIR) algorithm for abdominal computed tomography (CT) enhancement in obese patients and to identify the optimal AIIR algorithm level.

METHODS

Patients with a body mass index ≥ 30.00 kg/m who underwent abdominal CT enhancement were randomly assigned to groups A or B. Group A underwent conventional protocol with the Karl 3D iterative reconstruction algorithm at levels 3-5. Group B underwent the "double-low" protocol with AIIR algorithm at levels 1-5. Radiation dose, total iodine intake, along with subjective and objective image quality were recorded. The optimal reconstruction levels for arterial-phase and portal-venous-phase images were identified. Comparisons were made in terms of radiation dose, iodine intake, and image quality.

RESULTS

Overall, 150 patients with obesity were collected, and each group consisted of 75 cases. Karl 3D level 5 was the optimal algorithm level for group A, while AIIR level 4 was the optimal algorithm level for group B. AIIR level 4 images in group B exhibited significantly superior subjective and objective image quality than those in Karl 3D level 5 images in group A (P < 0.001). Group B showed reductions in mean CT dose index values, dose-length product, size-specific dose estimate based on water-equivalent diameter, and total iodine intake, compared with group A (P < 0.001).

CONCLUSION

The "double-low" scanning protocol combined with the AIIR algorithm significantly reduces radiation dose and iodine intake during abdominal CT enhancement in obese patients. AIIR level 4 is the optimal reconstruction level for arterial-phase and portal-venous-phase in this patient population.

摘要

目的

评估“双低”扫描方案联合人工智能迭代重建(AIIR)算法用于肥胖患者腹部计算机断层扫描(CT)增强的效果,并确定最佳的AIIR算法水平。

方法

将体重指数≥30.00 kg/m²且接受腹部CT增强检查的患者随机分为A组或B组。A组采用常规方案,使用卡尔3D迭代重建算法,重建水平为3至5级。B组采用“双低”方案,使用AIIR算法,重建水平为1至5级。记录辐射剂量、总碘摄入量以及主观和客观图像质量。确定动脉期和门静脉期图像的最佳重建水平。比较两组在辐射剂量、碘摄入量和图像质量方面的差异。

结果

总共收集了150例肥胖患者,每组75例。卡尔3D的5级是A组的最佳算法水平,而AIIR的4级是B组的最佳算法水平。B组的AIIR 4级图像在主观和客观图像质量上均显著优于A组的卡尔3D 5级图像(P < 0.001)。与A组相比,B组的平均CT剂量指数值、剂量长度乘积、基于水等效直径的特定尺寸剂量估计值和总碘摄入量均有所降低(P < 0.001)。

结论

“双低”扫描方案联合AIIR算法可显著降低肥胖患者腹部CT增强检查期间的辐射剂量和碘摄入量。AIIR 4级是该患者群体动脉期和门静脉期的最佳重建水平。

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