Evaluation of BMI‐based tube voltage selection in CT colonography: A prospective comparison of low kV versus routine 120 kV protocol

Journal of Applied Clinical Medical Physics(2023)

引用 1|浏览4
暂无评分
摘要
To explore the value of individualized kVp selection based on the patient's body mass index (BMI, kg/m2 ) in CT colonography (CTC).Seventy-eight patients underwent two CTC scans: conventional 120 kVp in supine position (Group A) with 30% Adaptive statistical iteration algorithm (ASIR-V) and BMI-based lower kV p in prone position (Group B): tube voltage was suggested by an experienced investigator according to the patient's body mass index (BMI; calculated as weight divided by height squared; kg/m (2)).70 kV for BMI < 23 kg/m2 (Group B1, n = 27), 80 kV for 23 ≤ BMI ≤ 25 kg/m2 (Group B2, n = 21) and 100 kV for BMI > 25 kg/m2 (Group B3, n = 30). Group A, corresponding to the BMI value in Group B, was divided into A1, A2, and A3 subgroups for analysis. Groups B used ASIR-V of different weights (30%-90% ASIR-V). The Hounsfield Unit (HU) and SD values of the muscles and the intestinal cavity air were measured, and the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) of images were calculated. Imaging quality was evaluated by two reviewers and statistically compared.The 120 kV scans were preferred more than 50% of the time. All images had excellent quality with good consistency between reviewers (Kappa > 0.75, p < 0.05). The radiation dose was reduced in groups B1, B2 and B3 by 63.62%, 44.63%, and 32.14%, respectively, compared with group A (p < 0.05). The SNR and CNR values between group A1/A2/A3 and B1/B2/B3 + 60%ASIR-V were not statistically significant (p < 0.05). There was no statistically significant difference between the subjective scores of group B combined with 60%ASIR-V and group A (p > 0.05).BMI-based individualized kV CTC imaging significantly reduces overall radiation dose while providing an equal image quality with the conventional 120 kV.
更多
查看译文
关键词
selection colonography,tube,voltage,bmi‐based
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要