The Optimal Body Size Index with Which to Determine Iodine Dose for Hepatic Dynamic CT: A Prospective Multicenter Study

Awai, Kazuo; Kanematsu, Masayuki; Kim, Tonsok; Ichikawa, Tomoaki; Nakamura, Yuko; Nakamoto, Atsushi; Yoshioka, Kunihiro; Mochizuki, Takashi; Matsunaga, Naofumi; Yamashita, Yasuyuki

doi:10.1148/radiol.2015142941

Cited by 74 publications

(64 citation statements)

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“…According to Bae ( 10 ), the blood volume and CO directly affect the enhancement of vessels, by contrast media while other patient characteristics have an indirect effect and manifest a complex relationship. Others ( 18 19 ) have suggested that enhancement is increased in elderly patients. However, most earlier studies did not perform multivariate regression analysis or did not include the CO as an independent factor in their multivariate linear regression analysis.…”

Section: Discussionmentioning

confidence: 99%

Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography

et al. 2018

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ObjectiveTo evaluate the effect of patient characteristics on popliteal aortic contrast enhancement at lower extremity CT angiography (LE-CTA) scanning.Materials and MethodsPrior informed consent to participate was obtained from all 158 patients. All were examined using a routine protocol; the scanning parameters were tube voltage 100 kVp, tube current 100 mA to 770 mA (noise index 12), 0.5-second rotation, 1.25-mm detector row width, 0.516 beam pitch, and 41.2-mm table movement, and the contrast material was 85.0 mL. Cardiac output (CO) was measured with a portable electrical velocimeter within 5 minutes of starting the CT scan. To evaluate the effects of age, sex, body size, CO, and scan delay on the CT number of popliteal artery, the researchers used multivariate regression analysis.ResultsA significant positive correlation was seen between the CT number of the popliteal artery and the patient age (r = 0.39, p < 0.01). A significant inverse correlation was observed between the CT number of the popliteal artery and the height (r = −0.48), total body weight (r = −0.52), body mass index (r = −0.33), body surface area (BSA) (r = −0.56), lean body weight (r = −0.56), and CO (r = −0.35) (p < 0.001 for all). There was no significant correlation between the enhancement and the scan delay (r = 0.06, p = 0.47). The BSA, CO, and age had significant effects on the CT number (standardized regression: BSA −0.42, CO −0.22, age 0.15; p < 0.05, respectively).ConclusionThe BSA, CO, and age are significantly correlated with the CT number of the popliteal artery on LE-CTA.

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Section: Discussionmentioning

confidence: 99%

Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography

et al. 2018

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“…[ 21 , 23 – 25 ] Consequently, various body size indices such as the LBW and the BSA have been introduced to determine the optimal contrast agent dose for cardiac CT- and hepatic dynamic CT studies and for CTA. [ 26 – 29 ] Awai et al [ 28 ] suggested that the LBW exhibited the strongest correlation with aortic and hepatic enhancement and Yanaga et al [ 29 ] reported that an LBW-tailored dose yielded more consistent aortic enhancement with reduced interpatient variability than the CTA protocol that delivered a BW-tailored dose. According to Bae et al, [ 26 ] a contrast dose based on the BSA was useful for obtaining consistent contrast enhancement on cardiac CT angiographs.…”

Section: Discussionmentioning

confidence: 99%

Relationships between patient characteristics and contrast agent dose for successful computed tomography venography with a body-weight-tailored contrast protocol

Iyama

Nakaura²,

Kidoh³

et al. 2018

Medicine

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The aim of this study was to evaluate the effect of patient characteristics on the contrast agent dosage that is required to reach effective enhancement of the inferior vena cava (IVC) on computed tomography venographs (CTV).This retrospective study included 50 patients who underwent CTV at 80 kVp. The contrast injection protocol (iodine 600 mg/kg) was tailored to their body weight. We calculated the required contrast agent volume (CAVmean-IVC) to reach the mean enhancement of IVC. We performed univariate and multivariate linear regression analyses between the sex, age, body weight (BW), lean body weight (LBW), body surface area (BSA), height (HT), estimated glomerular filtration rate (eGFR), and CAVmean-IVC.The univariate linear regression analysis show that HT, BW, LBW, and BSA were significantly correlated with CAVmean-IVC (P < .01 for all). The CAVmean-IVC was significantly higher for males than females (P < .01). Multivariate regression analysis showed that BW, LBW, and BSA had a statistically significant effect on CAVmean-IVC. There was no significant correlation of age, HT, or eGFR with CAVmean-IVC.BW, LBW, and BSA each had an independent significant effect on CAVmean-IVC. The conventional BW-tailored contrast injection protocol might be insufficient for CTV.

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“…As in earlier studies, factors with an effect on contrast enhancement, i.e., the patient's age, sex, TBW, and height, were recorded ( 17 18 ). We acquired their age and sex from their electronic health records.…”

Section: Methodsmentioning

confidence: 99%

Development and Validation of Generalized Linear Regression Models to Predict Vessel Enhancement on Coronary CT Angiography

et al. 2018

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ObjectiveWe evaluated the effect of various patient characteristics and time-density curve (TDC)-factors on the test bolus-affected vessel enhancement on coronary computed tomography angiography (CCTA). We also assessed the value of generalized linear regression models (GLMs) for predicting enhancement on CCTA.Materials and MethodsWe performed univariate and multivariate regression analysis to evaluate the effect of patient characteristics and to compare contrast enhancement per gram of iodine on test bolus (ΔHUTEST) and CCTA (ΔHUCCTA). We developed GLMs to predict ΔHUCCTA. GLMs including independent variables were validated with 6-fold cross-validation using the correlation coefficient and Bland–Altman analysis.ResultsIn multivariate analysis, only total body weight (TBW) and ΔHUTEST maintained their independent predictive value (p < 0.001). In validation analysis, the highest correlation coefficient between ΔHUCCTA and the prediction values was seen in the GLM (r = 0.75), followed by TDC (r = 0.69) and TBW (r = 0.62). The lowest Bland–Altman limit of agreement was observed with GLM-3 (mean difference, −0.0 ± 5.1 Hounsfield units/grams of iodine [HU/gI]; 95% confidence interval [CI], −10.1, 10.1), followed by ΔHUCCTA (−0.0 ± 5.9 HU/gI; 95% CI, −11.9, 11.9) and TBW (1.1 ± 6.2 HU/gI; 95% CI, −11.2, 13.4).ConclusionWe demonstrated that the patient's TBW and ΔHUTEST significantly affected contrast enhancement on CCTA images and that the combined use of clinical information and test bolus results is useful for predicting aortic enhancement.

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The Optimal Body Size Index with Which to Determine Iodine Dose for Hepatic Dynamic CT: A Prospective Multicenter Study

Abstract: Among body size parameters, LBW exhibited the strongest correlation with aortic and hepatic enhancement, especially in women.

Cited by 74 publications

References 40 publications

Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography

Effect of Patient Characteristics on Vessel Enhancement at Lower Extremity CT Angiography

Relationships between patient characteristics and contrast agent dose for successful computed tomography venography with a body-weight-tailored contrast protocol

Development and Validation of Generalized Linear Regression Models to Predict Vessel Enhancement on Coronary CT Angiography

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