| | Evaluation of required saline volume in dynamic contrast-enhanced computed tomography using saline flush techniqueReceived 30 June 2008; accepted 29 September 2008. Abstract The present study was performed to find the required volume of physiological saline for flushing that will allow the most efficient use of contrast medium during the early phase of dynamic CT. We calculated contrast medium aortic arrival time (AT), time to peak aortic enhancement (TPAE) and the elapsed time to TPAE from AT (rise time) from the TECs of pharmacokinetic analysis and clinical study. The rise time determined in the clinical study was 6.2 s, which was shorter than that in the simulation study. In the present study, an appropriate volume for saline flush was estimated to be about 18ml. 1. Introduction  Since the introduction of helical computed tomography (CT), the technique of dynamic CT imaging has been widely discussed [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]. Moreover, since the introduction of multidetector-row CT (MDCT), most recent studies have used a dual-head injector, which allows injection of physiological saline immediately after infusion of contrast medium (physiological saline flush technique). This technique enables efficient use of the contrast medium remaining in both the injector tube and the venous segment including the infused vein and subclavian vein, which together are referred to as “dead space.” The effectiveness of this technique has been demonstrated in many studies. However, the saline volumes used in these studies varied widely from 20 to 50ml. Furthermore, to our knowledge, there have been only a few studies regarding the volume of physiological saline used in saline flush technique [15], [16], [17], [18], [19], [20], [21]. Irie et al. compared five different volumes of physiological saline for flushing (0, 6, 12, 25, and 50ml) in terms of the time to peak aortic enhancement (TPAE) and reported that the resulting values were similar among volumes of 12ml or higher. In their physiological saline flush technique, TPAE prolonged by 6s and 12ml of contrast medium was saved [22]. A limitation of their study was that the start of image acquisition was fixed to 30s after infusion of contrast medium. In this method, a number of factors potentially influence the quality of the resulting images. One of these may be the subject’s cardiac function, which is associated with variation of the contrast medium arrival time (AT). Differences in AT can produce variable patterns of the time–enhancement curve (TEC), and eventually lead to variation of the TPAE. Such inconsistent results may make TPAE analyses unreliable. In our previous investigation, we found wide variance of AT among subjects, ranging from 9 to 22s. We also found that the time from the AT to peak aortic enhancement (rise time) was correlated with the duration of contrast medium injection and was independent of the individual ATs [23]. Based on these findings, we attempted to remove intersubject variability by defining the time from starting contrast injection to starting image acquisition as a fixed time point after AT in the present study. We then estimated the volume of dead space by analyzing the TECs, which were generated by applying the principles of pharmacokinetics, and the clinical data obtained from the subjects who did not undergo the physiological saline flush technique. The aim of this study was to investigate the adequate volume of physiological saline for saline flush technique that allows more efficient use of contrast medium during the early phase of the upper abdominal dynamic CT. 2. Materials and methods 2.1. Simulation study 2.1.1. Simulation of TEC in pharmacokinetic analysis We developed the simulation software program using a pharmacokinetic model on simulation of aortic TECs. A linear physiological model was developed based on the assumption that blood flow rate is controlled, to assess changes in contrast medium concentration in the aorta using the following compartments: the dead space, pulmonary circulation system, aorta, and systemic circulation system (Fig. 1). We then derived mass-balance equations based on the tissue distribution of contrast medium, from which changes in the contrast concentration in each compartment were calculated as time factors. Subsequently, we calculated the contrast material concentration in each compartment using the sixth-order Runge–Kutta method. The software was developed in C++Builder (Borland K.K., Tokyo, Japan). The following mass-balance equations were used: Here, kP represents the tissue/blood distribution coefficient and was equal to 1 ( kP= 1) because contrast media do not penetrate into tissues and are evenly distributed between the blood and extracellular fluid. In addition, as we intended to investigate initial changes in contrast medium concentration, the values of CLtot (total body clearance) were ignored. We made the assumption that 100% of the dose of contrast material administered via a peripheral vein reaches directly into the dead space. Based on this assumption, we simulated a closed circuit that circulates from the pulmonary compartment, distributes into the aorta, and reaches the pulmonary compartment again through the systemic circulation. The contrast medium concentration was expressed as C (C0, infused contrast medium; CD, dead space; CP, pulmonary circulation system; CA, aorta; CS, systemic circulation). The corresponding compartment volume (blood volume) was expressed as V (VD, dead space; VP, pulmonary circulation system; VA, aorta; and VS, systemic circulation). The volume flow between two successive compartments (blood flow volume) was expressed as Q (QD, dead space; QP, pulmonary circulation system; QA, aorta; QS, systemic circulation; Q0, infused contrast material; QD=blood leaving the dead space; QP=QA=QS, cardiac output). Circulating blood volume, a physiological parameter included in the data analysis, was calculated using Ogawa’s equation [24]. Cardiac output was calculated using the following formulas with a cardiac index of 2.8l/(minm2) [25], which were chosen for the mean age of the subjects (i.e., 65 years). Height was expressed as H [cm] and weight was expressed as W [kg]. The circulating blood volumes (l) for men and women are as follows: The cardiac output is determined with the following equation: We assumed a blood volume distribution of 16% in the pulmonary circulation, 2% in the aorta, and 82% in the systemic circulation. With regard to cardiac output, we made the assumption that 100% of the blood volume is distributed to all of the compartments. We showed the validity of the aortic TEC obtained by the computer-based physiological model of contrast medium enhancement and agreement with clinical data in our previously published report [14]. 2.1.2. Analysis of TEC in the simulation study We simulated changes in aortic TEC with the volume of dead space by assessing an imaginary male patient 158.8cm in height and body weight 55.3kg with an iodine concentration of 300mgI/ml, contrast medium volume of 92ml, and injection rate of 3.1ml/s. The simulated blood volume was 3872ml and the simulated cardiac output was 4347ml/min. We calculated the aortic TEC every 5ml from 0 to 30ml of the dead space volume (0, 5, 10, 15, 20, 25, and 30ml). We then calculated the AT, TPAE, enhancement rate, and rise time. AT was the time from injection until the enhancement unit (enhancement attenuation value (in Hounsfield units: HU) – plain attenuation value) first exceeded 5HU. Enhancement rate was the slope of the linear equation of EU range from 5HU to the average trigger threshold in a clinical study (shown in HU/s). Rise time was the elapsed time from AT to TPAE (Fig. 2). Transformation into attenuation values was based on the correlation between the iodine concentration and the attenuation value observed with the CT scanner (i.e., 1.0mgI/ml=25.22HU). 2.2. Clinical study 2.2.1. Patient population This study was performed within the routine clinical standards of our hospital. Our institutional review board approved the retrospective review of patient images. A total of 45 patients for whom upper abdominal dynamic contrast-enhanced CT was clinically indicated and which patients qualified for contrast injection under the pre-specified injection conditions via a right arm vein were selected from June 2006 to April 2007. The subjects consisted of 27 men and 18 women with a mean age±standard deviation (S.D.) of 64.8±11.7 years (range, 31–84), mean height±S.D. of 158.8±11.3cm (range, 132.0–187.0cm), mean body weight±S.D. of 55.3±9.6kg (range, 34.0–73.0kg), and mean body mass index (BMI)±S.D. of 21.8±2.3 (range, 18.1–28.4). For these 45 patients, the clinical diagnoses were chronic hepatitis (n=9), liver cirrhosis (n=5), hepatocellular carcinoma (n=17), metastasis liver cancer (n=4), benign hepatic tumor (n=5), and pancreatic tumor (n=5). 2.2.2. CT scan protocol All the patients were scanned with a 16-detector CT scanner (SOMATOM Sensation16; Siemens Healthcare, Erlangen, Germany) with the following settings: rotation time, 0.5s; beam collimation, 16mm×1.5mm, section thickness and intersection gap, 7.0mm; helical pitch, 1.2 (first phase), 0.75 (second and third phases); scan field of view, 50cm; X-ray tube voltage, 120kV; X-ray tube current, effective mA 230. Images were reconstructed in a display field of view of 30–38cm, depending on the patient’s physique. Helical studies were always started at the top of the upper abdomen in a cephalocaudal direction, and unenhanced and three-phase contrast-enhanced helical scans of the upper abdomen were obtained. The patients were instructed to hold their breath at the tidal inspiration level during scanning. Three-phase contrast-enhanced CT scanning of the upper abdomen was performed during the early arterial phase, late arterial phase, and equilibrium phase. An automatic bolus tracking system (CARE Bolus; Siemens Healthcare) was used to time the start of early arterial phase scanning after injection of contrast agent. The CT number was monitored by one radiological technologist at the bifurcation of the celiac artery level; the region of interest (ROI) cursor (about 1.0cm2) was placed in the abdominal aorta. Real-time, low-dose (120kV, 25mA) serial monitoring studies began 8s after the start of contrast injection. The trigger threshold level was set at an increase of 100HU over the aortic baseline CT number. The first phase was started at 9s after the trigger, the second phase was started 6s after scanning of the first phase was completed, and the third phase was started 120s after contrast injection (Fig. 3). The first and second phase scans were performed during one breath hold. 2.2.3. Contrast infusion protocols Iodine contents of 300, 350, and 370mgI/ml of nonionic contrast medium were injected at the adjusted dose of 500mgI/kg body weight (499.5±3.7mgI/kg) over 30s. A total of 26 patients with body weight <58kg received an iodine concentration of 300mgI/ml (Iopamiron 300 Syringe; Nihon Schering, Osaka, Japan, Omnipaque 300 Syringe; Daiichi Pharmaceutical, Tokyo, Japan), 14 patients with body weight of 58–67kg received an iodine concentration of 350mgI/ml (Iomeron 350 Syringe; Eisai, Tokyo, Japan), and five patients with body weight >67kg received an iodine concentration of 370mgI/ml (Iopamiron 370 Syringe; Nihon Schering). The mean dose administered was 85.0±9.9ml (range, 57–97ml) and the mean injection rate was 2.8±0.3ml/s (range, 2.0–3.2ml/s). For contrast injection, we used a power injector (Autoenhance A-250; Nemoto Kyorindo, Tokyo, Japan) and a 21-gauge catheter inserted into the right antecubital vein. 2.2.4. Analysis of TEC in the clinical study We set an ROI of about 1cm2 in the abdominal aorta and measured attenuation values in all CT images. Then, the AT, enhancement rate, and trigger threshold were calculated based on the monitoring data. We calculated the mean TEC from the clinical data obtained in the 45 patients as follows: 1.For each patient, the time axis was shifted so that the AT always corresponded to time 0. 2.The mean CT values within 1-s intervals were calculated for each patient. 3.Individual time points after the AT were grouped into clusters and the corresponding CT values observed were averaged for each of the time points. 4.The averaged CT values were plotted using the time points as a parameter. 5.The averaged CT values were obtained with curve-fitting by the least squares method to estimate TEC. We also used a quadratic function approximation. We calculated both the enhancement rate and the rise time from the TEC based on the clinical data of the 45 patients. Curve-fitting, calculation based on an approximation with a quadratic function and statistics were performed using Ekuseru-Toukei 2006 (Social Survey Research Information Co. Ltd., Tokyo, Japan). 3. Results 3.1. Phantom study 3.1.1. Changes in aortic TEC at different dead space volumes The TECs simulated with different dead space volumes are presented in Fig. 4. All of the AT values calculated from the simulation data were 1.2±0.3s (range, 1.0–1.5s). The enhancement rates were also consistent at 25.6±0.6HU/s (range, 24.5–26.3HU/s). The TPEAs with assumed dead space volumes of 0, 5, 10, 15, 20, 25, and 30ml were 30.0, 28.0, 27.0, 25.5, 23.5, 22.5, and 21.0s, respectively. The relationship between the rise times determined by the TECs and the corresponding dead space volumes are presented in Fig. 5. The rise time was shorter with increasing dead space volume (r=−0.99). References [1]. [1]Bae KT, Heiken JP, Brink JA. Aortic and hepatic contrast medium enhancement at CT. Part I. Prediction with a computer model. Radiology. 1998;207:647–655. MEDLINE [2]. [2]Bae KT, Heiken JP, Brink JA. Aortic and hepatic contrast medium enhancement at CT. Part II. Effect of reduced cardiac output in a porcine model. Radiology. 1998;207:657–662. MEDLINE [3]. [3]Bae KT, Heiken JP, Brink JA. Aortic and hepatic peak enhancement at CT: effect of contrast medium injection rate—pharmacokinetic analysis and experimental porcine model. Radiology. 1998;206:455–464. MEDLINE [4]. [4]Kim S, Kim JH, Han JK, Lee KH, Min BG. Prediction of optimal injection protocol for tumor detection in contrast-enhanced dynamic hepatic CT using simulation of lesion-to-liver contrast difference. Comput Med Imaging Graph. 2000;24:317–327. Abstract | Full Text |
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[24]. [24]Ogawa R, Fujita T, Fukuda Y. Blood volume studies in healthy Japanese adults. Respir Circ. 1970;18:833–838. [25]. [25]Guyton AC, Hall JE. Textbook of medical physiology, 9th edition. Philadelphia: Saunders; 1999 [Japanese edition—Tokyo: Igaku-Shoin]. Isao Yamaguchi was born in Fukuoka, Japan, in 1964. He received the MS degree from the Kanazawa University Graduate School, Japan, in 2006. He is currently a PhD candidate student of Division of Health Sciences, Kanazawa University Graduate School of Medicine Science. Since 2003, he has been with the Radiological Center, University of Fukui Hospital, Japan, where he is Chief Radiological Technologist. His research interests focus on Multi-detector row Computed Tomography and Contrast enhancement. Eiji Kidoya was born in Fukui, Japan, in 1962. Since 1984, he has been with the Radiological Center, University of Fukui Hospital, Japan, where he is Radiological Technologist. His research interests are Clinical study on Computed Tomography. Masayuki Suzuki was born in Ishikawa, Japan, in 1950. He received the MD degree from the Kanazawa University School of Medicine, Japan, in 1975 and a PhD in 1983. His research interests focus on Diagnostic neuroradiology using MR imaging and Study of the variations in chest CT examinations using Multi-detector CT. Since 1997, he has been with the Division of Health Sciences, Kanazawa University Graduate School of Medicine Science, Japan, where he is Professor. Hirohiko Kimura was born in Fukui, Japan, in 1956. He received the MD degree from the Fukui Medical University, Japan, in 1987 and a PhD in 1992. Since 2007, he has been with the Department of Radiology, Facility of Medical Sciences, University of Fukui, Japan, where he is Professor. His research interests focus on Diagnostic neuroradiology using MR imaging. a Radiological Center, University of Fukui Hospital, 23-3, Matsuokashimoaizuki, eiheiji-cho, Yoshida-gun, Fukui 910-1193, Japan b Division of Health Sciences, Kanazawa University Graduate School of Medicine Science, 5-11-80 Kodatsuno, Kanazawa, Ishikawa 920-0942, Japan c Department of Radiology, Facility of Medical Sciences, University of Fukui, 23-3, Matsuokashimoaizuki, eiheiji-cho, Yoshida-gun, Fukui 910-1193, Japan  Corresponding author at: Radiological Center, University of Fukui Hospital, 23-3, Matsuokashimoaizuki, eiheiji-cho, Yoshida-gun, Fukui 910-1193, Japan. Tel.: +81 776 61 3111; fax: +81 776 61 8154.
PII: S0895-6111(08)00099-2 doi:10.1016/j.compmedimag.2008.09.005 © 2008 Elsevier Ltd. All rights reserved. | |
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