Personalized administration of contrast medium with high delivery rate in low tube voltage coronary computed tomography angiography.
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2019
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Abstract
High delivery rate is an important factor in optimizing contrast medium administration in coronary computed tomography angiography (CCTA). A personalized contrast volume calculation algorithm incorporating high iodine delivery rate (IDR) can reduce total iodine dose (TID) and produce optimal vessel contrast enhancement (VCE) in low tube voltage CCTA. In this study, we developed and validated an algorithm for calculating the volume of contrast medium delivered at a high rate for patients undergoing retrospectively ECG-gated CCTA with low tube voltage protocol.The algorithm for an IDR of 2.22 gI·s was developed based on the relationship between VCE and contrast volume in 141 patients; test bolus parameters and characteristics in 75 patients; and, tube voltage in a phantom study. The algorithm was retrospectively tested in 45 patients who underwent retrospectively ECG-gated CCTA with a 100 kVp protocol. Image quality, TID and radiation dose exposure were compared with those produced using the 120 kVp and routine contrast protocols.Age, sex, body surface area (BSA) and peak contrast enhancement (PCE) were significant predictors for VCE (P<0.05). A strong linear correlation was observed between VCE and contrast volume (r=0.97, P<0.05). The 100-to-120 kVp contrast enhancement conversion factor (E) was calculated at 0.81. Optimal VCE (250 to 450 HU) and diagnostic image quality were obtained with significant reductions in TID (32.1%) and radiation dose (38.5%) when using 100 kVp and personalized contrast volume calculation algorithm compared with 120 kVp and routine contrast protocols (P<0.05).The proposed algorithm could significantly reduce TID and radiation exposure while maintaining optimal VCE and image quality in CCTA with 100 kVp protocol.
| Reference Key |
tan2019personalizedquantitative
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| Authors | Tan, Sock Keow;Ng, Kwan Hoong;Yeong, Chai Hong;Raja Aman, Raja Rizal Azman;Mohamed Sani, Fadhli;Abdul Aziz, Yang Faridah;Sun, Zhonghua; |
| Journal | Quantitative imaging in medicine and surgery |
| Year | 2019 |
| DOI |
10.21037/qims.2019.03.13
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