肾动脉多普勒超声诊断研究
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摘要
目的
本研究的目的是对前期研究初步建立的肾动脉狭窄(RAS)血流频谱自动分类器进行进一步对比研究。
资料与方法
在2011年8月-2013年4月对40例肾动脉狭窄患者80条肾动脉同时进行彩色多普勒超声(CDS)和血管造影(DSA)或CT血管造影(CTA)的连续性检查,测量肾动脉收缩期峰值流速(renal peak systolic velocity,RPSV)、肾动脉与腹主动脉峰值流速比值(RAR)和肾动脉与叶间动脉峰值流速比值(RIR)和叶间动脉的加速时间(AT)、加速度(AC)、阻力指数(RI),同时采集并存储叶间动脉的血流频谱,首先对频谱进行信号曲线提取、曲线归一化处理和曲线平滑处理,然后从曲线中提取有效周期进行分析,用建立的支持向量机(SVM)分类器进行分类诊断,并使用ROC曲线(receiver operating characteristic curves,ROC curves)分析确定肾动脉PSV、RAR、RIR和叶间动脉的AT、AC、RI的最佳诊断阈值,计算这些不同指标的敏感度、特异度、阳性预测值、阴性预测值和准确率。对SVM分类器和最佳诊断指标的诊断结果行诊断一致性分析。
结果
1.在肾动脉造影或CTA显示的80条肾动脉主干中,37条为70%以上狭窄,其余为正常或69%以下狭窄。ROC曲线分析结果显示AT和AC是最佳诊断指标,二者对70%以上RAS的诊断敏感度分别为97.3%和94.6%、特异度分别为93%和95.3%、准确率均为95%,RPSV、RAR、RIR、AT、AC、RI的最佳阈值依次分别为277cm/s、2.75、9.3、0.074s、165cm/s2、0.59。
2.SVM分类器对于70%以上肾动脉狭窄的诊断敏感度、特异度、准确率分别为94.6%、93%和93.8%。
3.AC与AT、AC与SVM、AT与SVM的诊断一致性均很好,Kappa值分别为0.95、0.88、0.83。
结论
研究表明采用RBF核函数,选取曲线一阶矩M1、二阶矩M2、峰值H、波动面积占比R、收缩期二次拟合参数a这五维特征作为分类特征建立的SVM分类器能够客观有效地对肾动脉狭窄的血流频谱进行分类诊断,其诊断效率和最佳诊断指标AT、AC接近。SVM分类器的开发是在计算机辅助诊断肾动脉狭窄领域内有意义的探索,这将会促进多普勒超声诊断肾动脉狭窄技术向基层医院的推广。
目的
本研究的目的是探讨受检者体位、呼吸因素对肾动脉血流参数的影响,为肾动脉多普勒超声检查的规范化提供依据。
资料与方法
征集60例性别匹配的健康志愿者,分别在平卧位和侧卧位状态下对双侧肾动脉主干和叶间动脉在平静呼吸吸气末和呼气末时相进行多普勒超声检测,测量肾动脉主干的收缩期峰值流速(PSV)、舒张期末流速(EDV)、阻力指数(RI)和叶间动脉的收缩期峰值流速(PSV)、抒张期末流速(EDV)、阻力指数(RI)、加速时间(AT)、加速度(AC),并记录校正θ角。肾动脉主干血流参数的检测部位为主干的起始段,在肾脏的上、中、下部分别获取叶间动脉血流频谱,并测量相关参数,取其平均值。对肾动脉血流参数在不同体位下及不同呼吸时相的测值进行对比研究和统计学分析,同时对左右侧肾脏间的肾动脉血流参数进行对比分析。
结果
1.肾动脉主干的PSV和RI在平卧位与侧卧位之间差异具有统计学意义(p<0.001),其检测时的θ角之间差异也具有统计学意义(p<0.001)；肾动脉主干的EDV和叶间动脉的PSV、EDV、RI、AC、AT在平卧位与侧卧位之间的差异均无统计学意义。
2.在平卧位状态下,左右侧肾动脉主干的PSV、EDV、RI和叶间动脉的PSV、EDV、RI、AC、AT之间差异无统计学意义；在侧卧位状态下,左右侧肾动脉主干PSV之间差异有统计学意义(p=0.012),其检测时的θ角之间差异也有统计学意义(p<0.001)；在侧卧位状态下,左右肾动脉主干的EDV、RI和叶间动脉的PSV、EDV、RI、AC、AT之间差异无统计学意义。
3.在平静呼吸过程中,肾脏的位置主要在上下向出现了轻度移动,而肾动脉走行未见明显的变化；在平卧位和侧卧位状态下,肾动脉主干的PSV、EDV、RI和叶间动脉的PSV、EDV、RI、AT、AC在吸气末时相与呼气末时相测值之间的差异无统计学意义。
结论
1.肾动脉主干的PSV和RI在平卧位和侧卧位之间差异有统计学意义,这说明体位对肾动脉主干的血流参数测值有影响,在肾动脉超声检查时应考虑这一影响因素；而体位对肾内叶间动脉的血流参数测值无明显影响。
2.侧卧位时左右侧肾动脉主干PSV之间差异具有统计学意义,主干的其它血流参数和叶间动脉的血流参数在左右侧之间差异无统计学意义。
3.本研究结果显示肾动脉多普勒血流参数在平静呼吸的吸气末时相和呼气末时相测值之间差异无统计学意义,提示在平静呼吸状态下肾动脉多普勒超声检测时可以不用考虑呼吸因素的影响。
Objection
The aim of this study was to certify the accuracy of SVM classfier of renal artery stenosis spectrum.
Materials and Methods
From August2011to April2013,40patients with80renal arteries were detected by color Doppler sonography(CDS) and were referred to renal digital-subtraction angiography(DSA) or computed tomography angiography(CTA) afterwards. Six Doppler parameters, including renal peak systolic velocity(RPSV), renal-aortic ratio(RAR), renal-interlobar ratio(RIR), acceleration time(AT),acceleration(AC), resistance index(RI) were measured. At the same time the blood flow signal curve of interlobar artery was collected and stored. Then80spectrums of renal artery were used to testify the validation of support vector machines(S VM) classifier, and statistical analysis to determine the best threshold of the six parameters for predicting RAS was performed with receiver operating characteristic(ROC) curves. The sensitivity, specificity, negative predicting value, positive predicting value and accuracy of different parameters were calculated. The agreement between SVM classifier and the best parameters was measured using Kappa statistics.
Results
1. In the80main renal arteries demonstrated by renal arteriography, there were37cases(diameter reduction>70%),43cases (diameter reduction<70%or normal). ROC analysis showed that the AT and AC were the best parameters with the accuracy of95%, the sensitivity and specificity of AT were97.3%and93%respectively, that of AC were94.6%and95.3%respectively. The best cutoff values for the6parameters (RPSV, RAR, RIR, AT, AC, RI) were277cm/s,2.75,9.3,0.074s,165cm/s2,0.59respectively.
2. Using RBF kernel, SVM classifier with five-dimensional features (curve first moment, second moment, peak H, fluctuations in the area of accounting for R, systolic quadratic fit parameters) as classification feature could effectively classify spectrum of RAS with94.6%sensitivity,93.0%specificity and93.8%accuracy.
3. The agreement between AC and AT, AC and SVM, AT and SVM were good, their Kappa were0.95,0.88,0.83respectively.
Conclusions
For the detection of RAS (diameter reduction>70%), AT and AC are the best indicators in the six parameters. SVM classifier can effectively classify spectrum of renal artery and its diagnostic efficiency is close to the best indicators(AT and AC). The development of SVM classifier is a meaningful exploration in computer-aided diagnosis of RAS, which will help to promote the use of Doppler ultrasound for detecting RAS in the primiary hospitals.
Objective
The aim of this study was to evaluate the influence of posture and normal respiration on the renal artery blood flow parameters and provide the evidence for standardization of renal artery Doppler ultrasound.
Materials and Methods
Sex-matched healthy young people of60cases, respectively, in the supine and lateral position, both main renal artery and interlobar artery were dectected by Doppler ultrasound. During end of inspiration breath-holding and end of expiration breath-holding, peak systolic velocity(PSV), end-diastolic velocity(EDV), resistance index(RI) of bilateral main renal artery and PSV, EDV, RI, acceleration time(AT), acceleration(AC) of bilateral interlobar artery were measured and the parameters were analyzed. Doppler spectra of main renal artery were obtained at the origin of artery and Doppler spectra of interlobar artery were obtained at the upper, middle, and lower pole interlobar arteries. The renal artery blood flow parameters were also analyzed between both sides.
Results
1. PSV and RI of main renal artery between supine position and lateral position had statistically significant difference(p<0.001) and θ angle between supine position and lateral position also had statistically significant difference(p<0.001). EDV of main renal artery and PSV, EDV, RI, AC, AT of interlobar artery between supine position and lateral position had no significant difference.
2. PSV, EDV, RI of main renal artery and PSV, EDV, RI, AC, AT of interlobar artery between left and right side had no statistically significant difference in supine position. In lateral position, PSV of main renal artery and their θ angle between right and left side had statistically significant difference(PSV:p=0.012,0:p<0.001), while the other parameters between two sides had no statistically significant differences.
3. During the normal respiration, the positon of kidney changed slightly in vertical direction, but the renal artery had no obvious change. PSV, EDV, RI of bilateral main renal artery and PSV, EDV, RI, AT, AC of bilateral interlobar artery measured during end of inspiration breath-holding and end of expiration breath-holding had no significant difference.
Conclusions
1. PSV and RI of main renal artery between supine and lateral position had statistically significant difference. This showed that the postural factors affected the renal artery blood flow parameters and it should be considered when we checking renal artery with ultrasound. But it had no effect on the renal interlobar artery blood flow parameters.
2. Except PSV of main renal artery in lateral position, the other parameters of main renal artery and interlobar artery between right and left side had no statistically significant differences.
3. The renal artery blood flow parameters had no significant difference between different breathing phases in normal respiration. This results suggests that the effect of breathing in normal respiration could be neglected in Doppler measurement of the renal artery.
本研究的目的是对前期研究初步建立的肾动脉狭窄(RAS)血流频谱自动分类器进行进一步对比研究。
资料与方法
在2011年8月-2013年4月对40例肾动脉狭窄患者80条肾动脉同时进行彩色多普勒超声(CDS)和血管造影(DSA)或CT血管造影(CTA)的连续性检查,测量肾动脉收缩期峰值流速(renal peak systolic velocity,RPSV)、肾动脉与腹主动脉峰值流速比值(RAR)和肾动脉与叶间动脉峰值流速比值(RIR)和叶间动脉的加速时间(AT)、加速度(AC)、阻力指数(RI),同时采集并存储叶间动脉的血流频谱,首先对频谱进行信号曲线提取、曲线归一化处理和曲线平滑处理,然后从曲线中提取有效周期进行分析,用建立的支持向量机(SVM)分类器进行分类诊断,并使用ROC曲线(receiver operating characteristic curves,ROC curves)分析确定肾动脉PSV、RAR、RIR和叶间动脉的AT、AC、RI的最佳诊断阈值,计算这些不同指标的敏感度、特异度、阳性预测值、阴性预测值和准确率。对SVM分类器和最佳诊断指标的诊断结果行诊断一致性分析。
结果
1.在肾动脉造影或CTA显示的80条肾动脉主干中,37条为70%以上狭窄,其余为正常或69%以下狭窄。ROC曲线分析结果显示AT和AC是最佳诊断指标,二者对70%以上RAS的诊断敏感度分别为97.3%和94.6%、特异度分别为93%和95.3%、准确率均为95%,RPSV、RAR、RIR、AT、AC、RI的最佳阈值依次分别为277cm/s、2.75、9.3、0.074s、165cm/s2、0.59。
2.SVM分类器对于70%以上肾动脉狭窄的诊断敏感度、特异度、准确率分别为94.6%、93%和93.8%。
3.AC与AT、AC与SVM、AT与SVM的诊断一致性均很好,Kappa值分别为0.95、0.88、0.83。
结论
研究表明采用RBF核函数,选取曲线一阶矩M1、二阶矩M2、峰值H、波动面积占比R、收缩期二次拟合参数a这五维特征作为分类特征建立的SVM分类器能够客观有效地对肾动脉狭窄的血流频谱进行分类诊断,其诊断效率和最佳诊断指标AT、AC接近。SVM分类器的开发是在计算机辅助诊断肾动脉狭窄领域内有意义的探索,这将会促进多普勒超声诊断肾动脉狭窄技术向基层医院的推广。
目的
本研究的目的是探讨受检者体位、呼吸因素对肾动脉血流参数的影响,为肾动脉多普勒超声检查的规范化提供依据。
资料与方法
征集60例性别匹配的健康志愿者,分别在平卧位和侧卧位状态下对双侧肾动脉主干和叶间动脉在平静呼吸吸气末和呼气末时相进行多普勒超声检测,测量肾动脉主干的收缩期峰值流速(PSV)、舒张期末流速(EDV)、阻力指数(RI)和叶间动脉的收缩期峰值流速(PSV)、抒张期末流速(EDV)、阻力指数(RI)、加速时间(AT)、加速度(AC),并记录校正θ角。肾动脉主干血流参数的检测部位为主干的起始段,在肾脏的上、中、下部分别获取叶间动脉血流频谱,并测量相关参数,取其平均值。对肾动脉血流参数在不同体位下及不同呼吸时相的测值进行对比研究和统计学分析,同时对左右侧肾脏间的肾动脉血流参数进行对比分析。
结果
1.肾动脉主干的PSV和RI在平卧位与侧卧位之间差异具有统计学意义(p<0.001),其检测时的θ角之间差异也具有统计学意义(p<0.001)；肾动脉主干的EDV和叶间动脉的PSV、EDV、RI、AC、AT在平卧位与侧卧位之间的差异均无统计学意义。
2.在平卧位状态下,左右侧肾动脉主干的PSV、EDV、RI和叶间动脉的PSV、EDV、RI、AC、AT之间差异无统计学意义；在侧卧位状态下,左右侧肾动脉主干PSV之间差异有统计学意义(p=0.012),其检测时的θ角之间差异也有统计学意义(p<0.001)；在侧卧位状态下,左右肾动脉主干的EDV、RI和叶间动脉的PSV、EDV、RI、AC、AT之间差异无统计学意义。
3.在平静呼吸过程中,肾脏的位置主要在上下向出现了轻度移动,而肾动脉走行未见明显的变化；在平卧位和侧卧位状态下,肾动脉主干的PSV、EDV、RI和叶间动脉的PSV、EDV、RI、AT、AC在吸气末时相与呼气末时相测值之间的差异无统计学意义。
结论
1.肾动脉主干的PSV和RI在平卧位和侧卧位之间差异有统计学意义,这说明体位对肾动脉主干的血流参数测值有影响,在肾动脉超声检查时应考虑这一影响因素；而体位对肾内叶间动脉的血流参数测值无明显影响。
2.侧卧位时左右侧肾动脉主干PSV之间差异具有统计学意义,主干的其它血流参数和叶间动脉的血流参数在左右侧之间差异无统计学意义。
3.本研究结果显示肾动脉多普勒血流参数在平静呼吸的吸气末时相和呼气末时相测值之间差异无统计学意义,提示在平静呼吸状态下肾动脉多普勒超声检测时可以不用考虑呼吸因素的影响。
Objection
The aim of this study was to certify the accuracy of SVM classfier of renal artery stenosis spectrum.
Materials and Methods
From August2011to April2013,40patients with80renal arteries were detected by color Doppler sonography(CDS) and were referred to renal digital-subtraction angiography(DSA) or computed tomography angiography(CTA) afterwards. Six Doppler parameters, including renal peak systolic velocity(RPSV), renal-aortic ratio(RAR), renal-interlobar ratio(RIR), acceleration time(AT),acceleration(AC), resistance index(RI) were measured. At the same time the blood flow signal curve of interlobar artery was collected and stored. Then80spectrums of renal artery were used to testify the validation of support vector machines(S VM) classifier, and statistical analysis to determine the best threshold of the six parameters for predicting RAS was performed with receiver operating characteristic(ROC) curves. The sensitivity, specificity, negative predicting value, positive predicting value and accuracy of different parameters were calculated. The agreement between SVM classifier and the best parameters was measured using Kappa statistics.
Results
1. In the80main renal arteries demonstrated by renal arteriography, there were37cases(diameter reduction>70%),43cases (diameter reduction<70%or normal). ROC analysis showed that the AT and AC were the best parameters with the accuracy of95%, the sensitivity and specificity of AT were97.3%and93%respectively, that of AC were94.6%and95.3%respectively. The best cutoff values for the6parameters (RPSV, RAR, RIR, AT, AC, RI) were277cm/s,2.75,9.3,0.074s,165cm/s2,0.59respectively.
2. Using RBF kernel, SVM classifier with five-dimensional features (curve first moment, second moment, peak H, fluctuations in the area of accounting for R, systolic quadratic fit parameters) as classification feature could effectively classify spectrum of RAS with94.6%sensitivity,93.0%specificity and93.8%accuracy.
3. The agreement between AC and AT, AC and SVM, AT and SVM were good, their Kappa were0.95,0.88,0.83respectively.
Conclusions
For the detection of RAS (diameter reduction>70%), AT and AC are the best indicators in the six parameters. SVM classifier can effectively classify spectrum of renal artery and its diagnostic efficiency is close to the best indicators(AT and AC). The development of SVM classifier is a meaningful exploration in computer-aided diagnosis of RAS, which will help to promote the use of Doppler ultrasound for detecting RAS in the primiary hospitals.
Objective
The aim of this study was to evaluate the influence of posture and normal respiration on the renal artery blood flow parameters and provide the evidence for standardization of renal artery Doppler ultrasound.
Materials and Methods
Sex-matched healthy young people of60cases, respectively, in the supine and lateral position, both main renal artery and interlobar artery were dectected by Doppler ultrasound. During end of inspiration breath-holding and end of expiration breath-holding, peak systolic velocity(PSV), end-diastolic velocity(EDV), resistance index(RI) of bilateral main renal artery and PSV, EDV, RI, acceleration time(AT), acceleration(AC) of bilateral interlobar artery were measured and the parameters were analyzed. Doppler spectra of main renal artery were obtained at the origin of artery and Doppler spectra of interlobar artery were obtained at the upper, middle, and lower pole interlobar arteries. The renal artery blood flow parameters were also analyzed between both sides.
Results
1. PSV and RI of main renal artery between supine position and lateral position had statistically significant difference(p<0.001) and θ angle between supine position and lateral position also had statistically significant difference(p<0.001). EDV of main renal artery and PSV, EDV, RI, AC, AT of interlobar artery between supine position and lateral position had no significant difference.
2. PSV, EDV, RI of main renal artery and PSV, EDV, RI, AC, AT of interlobar artery between left and right side had no statistically significant difference in supine position. In lateral position, PSV of main renal artery and their θ angle between right and left side had statistically significant difference(PSV:p=0.012,0:p<0.001), while the other parameters between two sides had no statistically significant differences.
3. During the normal respiration, the positon of kidney changed slightly in vertical direction, but the renal artery had no obvious change. PSV, EDV, RI of bilateral main renal artery and PSV, EDV, RI, AT, AC of bilateral interlobar artery measured during end of inspiration breath-holding and end of expiration breath-holding had no significant difference.
Conclusions
1. PSV and RI of main renal artery between supine and lateral position had statistically significant difference. This showed that the postural factors affected the renal artery blood flow parameters and it should be considered when we checking renal artery with ultrasound. But it had no effect on the renal interlobar artery blood flow parameters.
2. Except PSV of main renal artery in lateral position, the other parameters of main renal artery and interlobar artery between right and left side had no statistically significant differences.
3. The renal artery blood flow parameters had no significant difference between different breathing phases in normal respiration. This results suggests that the effect of breathing in normal respiration could be neglected in Doppler measurement of the renal artery.
引文
[1]Simon G. What is critical renal artery stenosis? Implications for treatment. Am J Hypertens 2000;13(11):1189-93.
[2]Mehta AN, Fenves A. Current opinions in renovascular hypertension. Proc(Bayl Unit Med Cent) 2010;23(3):246-9.
[3]Hansen KJ, Edwards MS, Craven TE, et al. Prevalence of renovascular disease in the elderly:a population-based study. J Vase Surg 2002;36(3):443-51.
[4]de Mast Q, Beutler JJ. The prevalence of atherosclerotic renal artery stenosis in risk groups:a systematic literature review. J Hypertens 2009;27(7):1333-40.
[5]Richard AF, Friedrich KP, Erik WY, et al. Incidence trends and mortality in end-stage renal disease attributed to renovascular disease in the United States. Am J Kid Dis,2001; 37(6):1184-90.
[6]van Ampting Jacobine MA, Penne EL, Beek FJA. Prevalence of atherosclerotic renal artery stenosis in patients starting dialysis. Nephrol Dia Transplant, 2003;18(6):1147-51.
[7]Kalra PA, Guo H, Kausz AT, et al. Atherosclerotic renovascular disease in United States patients aged 67 years or older:risk factors, revascularization, and prognosis. Kidney Int,2005; 68(1):293-301.
[8]Wright JR, Shurrab AE, Cooper A, et al. Left ventricular morphology and function in patients with atherosclerotic renovascular disease. J Am Soc Nephrol,2005; 16(9):2746-53.
[9]Greene ER, Venters MD, Avashi PS, et al. Noninvasive characterization of renal artery blood flow. Kidney Int,1981;20(4):523-9.
[10]Spyridopoulos TN, Kaziani K, Balanika AP, et al. Ultrasound as a first line screening tool for the detection of Renal Artery Stenosis:a comprehensive review. Medic Ultrason,2010;12(3):228-32.
[11]de Oliveira SIRS, Widman A, Molnar LJ, et al. Color Doppler ultrasound:a new index improves the diagnosis of renal artery stenosis. Ultrasound Med Biol,2000, 26(1):41-47.
[12]Li JC, Ji ZG, Cai S, et al. Evaluation of severe transplant renal artery stenosis with Doppler sonography. J Clinical Ultrasound,2005,33(6):261-9.
[13]Li JC, Wang L, Jiang YX, et al. Evaluation of renal artery stenosis with velocity parameters of Doppler sonography. J Ultrasound Med,2006; 25(6):735-42.
[14]Chain S, Luciardi H, Feldman G, et al. Diagnostic role of new Doppler index in assessment of renal artery stenosis. Cardiovascular Ultrasound,2006,25;4:4
[15]秦卫,王芳,王梅,等.彩色多普勒超声在动脉粥样硬化性肾动脉狭窄诊断中的应用.中华超声影像学杂志,2005,14(7)：508-11.
[16]Ripolles T, Aliaga R, Morote V, et al. Utility of intrarenal Doppler ultrasound in the diagnosis of renal artery stenosis. European J Radiology,2001,40(1):54-7.
[17]李建初.小慢波频谱诊断肾动脉狭窄的现状和进展(述评).中华医学超声杂志,2007,4(6)：321-4.
[18]孙哲,黎庶,徐惠绵.数字化乳腺X线计算机辅助诊断系统临床应用价值的初步探讨.中华医学杂志,2005,85(24)：1692-5.
[19]Matsumoto S, Ohno Y, Yamagata H, et al. Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings. Radiat Med,2008; 26(9):562-9
[20]Willems JL, Abreu-Lima C, Arnaud P, et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med, 1991,325(25):1803-4.
[21]Oweis R, Hijazi L. A computer-aided ECG diagnostic tool. Computer Methods and Programs in Biomedicine,2006,81(3):279-84.
[22]张羽,汪源源,王威琪,余建国.超声多普勒血流信号的小波特征提取及分类.生物医学工程学杂志,2002,19(2)：244-6.
[23]张榆锋,郭振宇,周屹,施心陵.基于小波变换与基于短时傅立叶变换的模拟颈动脉超声多普勒信号的时频分布比较研究.中国生物医学工程学报,2005,24(1)：107-9.
[24]Serge Belongie, Jitendra Malik, Jan Puzicha. Shape matching and object recognition using shape contexts. IEEE TRANS.PAMI,2002,24:4.
[25]陈竹修.基于傅里叶变换的形状上下文描述方法.计算机应用与软件,2007,24(6)：140-4.
[1]SpyRIdopoulos TN, Kaziani K, Balanika AP, et al. Ultrasound as a first line screening tool for the detection of Renal Artery Stenosis:a comprehensive review. Medic Ultra Son,2010;12(3):228-32.
[2]Li JC, Ji ZG, Cai S, et al. Evaluation of severe transplant renal artery stenosis with Doppler sonography. J Clinical Ultrasound,2005,33(6):261-9.
[3]Li JC, Jiang YX, et al. Evaluation of renal artery stenosis with hemodynamic parameters of Doppler sonography. J Vascul Surg,2008;48(2):323-8.
[4]王杰,杨萌等.鲁棒的超声多普勒肾动脉血流信号提取方法[J].计算机科学.2010；37(2)：274-6.
[5]Comaniciu D,Meer P.Mean shift:A robust approach toward feature space analysis[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence.2002;24(5):603-19.
[6]Chih-Chung Chang,Chih-Jen Lin. LIBSVM--A library for support vector machines[EB/OL]. http://www. csie.ntu.edu.tw/-cjlin/libSVM/.
[7]李炳成,沈俊.曲线矩不变性的研究.电子科学学刊.1992；14(3)：262-70.
[8]孙哲,黎庶,徐惠绵.数字化乳腺X线计算机辅助诊断系统临床应用价值的初步探讨.中华医学杂志,2005；85(24)：1692-5.
[9]Matsumoto S, Ohno Y, Yamagata H, et al. Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings. Radiat Med,2008;26(9):562-9.
[10]Willems JL, Abreu-Lima C, Arnaud P, et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med, 1991;325(25):1803-4.
[11]Oweis R, Hijazi L. A computer-aided ECG diagnostic tool. Computer Methods and Programs in Biomedicine,2006; 81(3):279-84.
[12]张羽,汪源源,王威琪,余建国.超声多普勒血流信号的小波特征提取及分类.生物医学工程学杂志,2002；19(2)：244-6.
[13]张榆锋,郭振宇,周屹,施心陵.基于小波变换与基于短时傅立叶变换的模拟颈动 脉超声多普勒信号的时频分布比较研究.中国生物医学工程学报.2005；24：107-9.
[14]Serge Belongie, Jitendra Malik, Jan Puzicha. Shape matching and object recognition using shape contexts. IEEE TRANS.PAMI.2002;24:4.
[15]陈竹修.基于傅里叶变换的形状上下文描述方法.计算机应用与软件,2007；24(6)：140-4.
[16]刘慧婷,张曼,程家兴.基于多项式拟合算法的EMD端点问题的处理.计算机工程与应用,2004；40(16)：84-6.
[17]C Cortes,V Vapnik. Support-Vector networks. Machin learning.1995;20:273-297.
[18]Vapnik V.The Nature of Statistical Learning Theory.张学工译.统计学习理论的本质,北京：清华大学出版社,2000：100-101.
[19]Riling G, FlandRIn P. On the influence of sampling on the empirical mode decomposition[C]//Proc 2006 IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP 2006),Toulouse,France,2006;3:444-7.
[20]邓拥军,王伟,钱成春,等.EMD方法及Hilbert变换中边界问题的处理.科学通报,2001；46(3)：257-63.
[21]邓乃扬,田英杰.数据挖掘中的新方法--支持向量机.北京：科学出版社.2004：164-208.
[22]Hsu C W.A practical guide to support vector classification [EB/OL].[2012-12-01]. http://www.csie.ntu.edu.tw/～cjlin/papers/guide/guide.pdf.
[23]Kliewer MA,Tupler RH,Carroll BA,et al. Renal artery stenosis:analysis of Doppler waveform parameters and tardus-parvus pattern. Radiology,1993,189(3):779-87.
[24]Handa N, Fukunaga R, Etani H, et al. Efficacy of echo-Doppler examination for the evaluation of renovascular disease. Ultrasound Med Biol,1988,14(1):1-5.
[25]Stavros AT, Parker SH, Yakes WF, et al. Segmental stenosis of the renal artery: pattern recognition of tardus and parvus abnormalities with duplex sonography. Radiology,1992,184(2):487-92.
[26]Patriquin HB,Lafortune M,Je'quier JC,et al. Stenosis of the renal artery:assessment of slowed systole in the downstream circulation with Doppler sonography. Radiology,1992,184(2):479-85.
[27]Ripolles T, Aliaga R, Morote V,et al.Utility of interenal Doppler ultrasound in the diagnosis of renal artery stenosis. Eur J Radiol,2001,40(1):54-63
[28]李建初,姜玉新,蔡胜,等.流速指标对肾动脉狭窄的诊断价值.中华超声影像学杂志,2004,12(13)：902-6.
[29]李建初.小慢波频谱诊断肾动脉狭窄的现状和进展.中华医学超声杂志(电子版),2007,4(6)：321-4.
[1]Zubarev AV. Ultrasound of renal vessels. Eur Radiol,2001;11(10):1902-15.
[2]李建初.肾动脉狭窄的超声规范化检测与结果分析.中华医学超声杂志(电子版),2010；7(1)：5-9
[3]马少平,祝伟宏,吴志坚,等.超声点追踪及连续切面法观察不同体位下肾脏活动度的价值.中外医学研究,2012；10(20)：50-1.
[4]Lin ZY, Dai CY, Chang WY, et al. Influence of posture change on intrarenal arterial resistive index measurement. Abdomen Imaging,2002;27(6):626-8.
[5]Hayashi N, Someya N, EndoMY,Miura A and Fukuba Y. Vasoconstriction and blood flow responses in visceral arteries to mental task in humans. Exp. Physiol, 2006; 91(1):215-20.
[6]Iwao T, Toyonaga A, Shigemori H, Oho K, Sumino M, Sato M and Tanikawa K. Echo-Doppler measurements of portal vein and superior mesenteric artery blood flow in humans:inter-and intra-observer short-term reproducibility. J. Gastroenterol. Hepatol,1996; 11(1):40-6.
[7]Momen A, Leuenberger U A, Ray C A, Cha S, Handly B and Sinoway L I. Renal vascular response to static handgrip:role of muscle mechanoreflex. Am. J. Physiol. Heart Circ. Physiol,2003; 285(3):H1247-53.
[8]Mary TD, Christopher Z, Charles T. Three-dimensional analysis of renal artery bending motion during respiration. J Endovasc Ther,2005;12(3):380-6.
[9]Nami S, Masako E, Yoshiyuki F, Naoyuki H. The limited effect of breathing frequency on blood velocity measurements in renal and superior mesenteric arteries. Physiological Measurement,2007;28(11):1369-74.
[10]柏树令.系统解剖学(7年制用).第1版.北京：人民卫生出版社,2001：161-2.
[11]王怀经.局部解剖学(7年制用).北京：人民卫生出版社,2002：177.
[12]张岐山,郭应禄,燕山,等.泌尿系超声诊断治疗学.科学技术文献出版社,2001：37.
[13]张小平,李兴国.肾筋膜及肾周间隙的解剖学研究进展.局解手术学杂志,2004；13(2)：122-3.
[14]袁小旭,司徒杰.仰、俯卧位下肾结肠位置变化与相对位移的影响.解剖学研究,2009；27(5)：551-4.
[15]Renan Liflacker. Atlas of vascular anatomy. Lippincott Williams & Wilkins,Inc, U.S.A,1997:278.
[16]Esther SH, Susan W, Christopher T, et al. Positionally dependent renal artery restenosis.Circulation,2009;120(8):714-5.
[17]Takano R, Ando Y, Taniguchi N, et al. Power Doppler sonography of the kidney: effect of Valsalva's maneuver. J Clin Ultrasound,2001;29(7):384-8.
[18]Richards WO, Scovill W, Shin B, et al. Acute renal failure associated with increased intra-abdominal pressure. Ann Surg,1983; 197(2):183.
[19]Navar LG, Carmines PK, Paul RV. Renal circulation. In:Massry S, Glassock R, editors. Textbook of nephrology.2nd ed. Baltimore:Williams & Wilkins; 1989. p 43.
[20]王咏梅,张炽敏,李嘉,等.肾内动脉血流阻力指数在慢性肾病诊治中的意义.中国超声医学杂志,2007,23(4)：290-292.
[21]Knapp R, Plotzeneder A, Frauscher F, et al. Variability of Doppler parameters in the healthy kidney:an anatomic-physiologic correlation. J Ultrasound Med, 1995;14(6):427-9.
[22]Bude RO, Rubin JM. Relationship between the resistive index and vascular compliance and resistance. Radiology,1999;211(2):411-7.
[23]Tublin ME, Tessler FN, Murphy ME:Correlation between renal vascular resistance, pulse pressure, and the resistive index in isolated perfused rabbit kidneys. Radiology, 1999;213(1):258-64.
[24]Derchi LE et al. Mild renal dysfunction and renal vascular resistance in primary hypertension. Am J Hypertens,2005,18(7):966-971.
[25]Seiler S, Colbus S, Lucisano G,et al. Ultrasound renal resistive index is not an organ-specific predictor of allograft outcome. Nephrol Dial Transplant, 2012,27(8):3315-20.
[26]Radermacher J, Mengel M, Ellis S,et al. The renal arterial resistance index and renal allograft survival. N Engl J Med,2003,349(2):115-24.
[27]Kawai T, Kamide K, Onishi M, et al. Usefulness of the resistive index in renal Doppler ultrasonography as an indicator of vascular damage in patients with risks of atherosclerosis. Nephrol Dial Transplant,2011,26(10):3256-62.
[28]Milovanceva-Popovska M, Dzikova S. Doppler ultrasonography:A tool for nephrologists-single centre experience. Prilozi,2008;29(1):107-128.
[29]Keogan MT, Kliewer MA, Hertzberg BS, et al. Renal resistive indexes:variability in Doppler US measurement in a healthy population. Radiology,1996;199(1): 165-9.
[30]Yildirim H, Gungor S, Cihangiroglu MM, et al. Doppler studies in normal kidneys of preterm and term neonates:Changes in relation to gestational age and birth weight. J Ultrasound Med,2005;24(5):623-7.
[31]Ansarin K, Bavil AS, Ghabili K, et al. Are Doppler ultrasonography parameters symmetric between the right and left kidney? Int J Gen Med,2010;16(3):371-3.
[32]Kliewer MA, Hertzberg BS, Keogan MT, et al. Early systole in the healthy kidney: Variability of Doppler US waveform parameters. Radiology,1997;205(1):109-13.
[33]Atmaram S, Pai Panandiker, Shelly Sharma, et al. Novel assessment of renal motion in children as measured via four-dimensional computed tomography. Int. J. Radiation Oncology Biol. Phys,2012;82(5):1771-6.
[34]Moore JE Jr., Ku DN. Pulsatile velocity measurements in a model of the human abdominal aorta under simulated exercise and postprandial conditions. J Biomech Eng,1994;116(1):107-11.
[35]Taremi M, Ringash J, Dawson LA. Upper abdominal malignancies:Intensity-modulated radiation therapy. Front Radiat Ther Oncol,2007;40:272-88.
[36]Murtz P, Pauleit D, Traber F, et al. Pulse triggering for improved diffusion-weighted MR imaging of the abdomen. Rofo,2000;172(7):587-90.
[37]Faries PL, Agarwal G, Lookstein R, et al. Use of cine magnetic resonance angiography in quantifying aneurysm pulsatility associated with endoleak. J Vase Surg,2003;38(4):652-6.
[38]Suramo I, Paivansalo M, Myllyla V. Cranio-caudal movements of the liver, pancreas and kidneys in respiration. Acta Radiol Diag,1984;25(2):129-31.
[39]Davies SC, Hill AL, Holmes RB, et al. Ultrasound quantification of respiratory organ motion in the upper abdomen. Br J Radiol,1994;67(803):1096-102.
[40]Aruga T, Itami J, Aruga M, et al. Target volume definition for upper abdominal irradiation using CT scans obtained during inhale and exhale phases. Int J Radiat Oncol Biol Phys,2000; 48(2):465-9.
[41]Schwartz LH, Richaud J, Buffat L, et al. Kidney mobility during respiration. Radiother Oncol,1994;32(1):84-6.
[42]Moerland MA, van den Bergh ACM, Bhagwandien R, et al. The influence of respiration induced motion of the kidney on the accuracy of radiotherapy treatment planning, a magnetic resonance imaging study. Radiother Oncol,1994; 30(2):150-4.
[43]van Srnsen de Koste JR, Senan R, Kleynen CE, et al. Renal mobility during uncoached quiet respiration:an analysis of 4DCT scans. Int J Radiat Oncol Biol Phys,2006;64(3):799-803.
[44]习勉,刘孟忠,李巧巧,等.基于4DCT的腹部器官呼吸运动分析.癌症,2009；28(9)：989-93.
[45]Vasbinder GB, Maki JH, Nijenhuis RJ, et al. Motion of the distal renal artery during three-dimensional contrast-enhanced breath-hold MRA. J Magn Reson Imaging,2002;16(6):685-96.
[2]Mehta AN, Fenves A. Current opinions in renovascular hypertension. Proc(Bayl Unit Med Cent) 2010;23(3):246-9.
[3]Hansen KJ, Edwards MS, Craven TE, et al. Prevalence of renovascular disease in the elderly:a population-based study. J Vase Surg 2002;36(3):443-51.
[4]de Mast Q, Beutler JJ. The prevalence of atherosclerotic renal artery stenosis in risk groups:a systematic literature review. J Hypertens 2009;27(7):1333-40.
[5]Richard AF, Friedrich KP, Erik WY, et al. Incidence trends and mortality in end-stage renal disease attributed to renovascular disease in the United States. Am J Kid Dis,2001; 37(6):1184-90.
[6]van Ampting Jacobine MA, Penne EL, Beek FJA. Prevalence of atherosclerotic renal artery stenosis in patients starting dialysis. Nephrol Dia Transplant, 2003;18(6):1147-51.
[7]Kalra PA, Guo H, Kausz AT, et al. Atherosclerotic renovascular disease in United States patients aged 67 years or older:risk factors, revascularization, and prognosis. Kidney Int,2005; 68(1):293-301.
[8]Wright JR, Shurrab AE, Cooper A, et al. Left ventricular morphology and function in patients with atherosclerotic renovascular disease. J Am Soc Nephrol,2005; 16(9):2746-53.
[9]Greene ER, Venters MD, Avashi PS, et al. Noninvasive characterization of renal artery blood flow. Kidney Int,1981;20(4):523-9.
[10]Spyridopoulos TN, Kaziani K, Balanika AP, et al. Ultrasound as a first line screening tool for the detection of Renal Artery Stenosis:a comprehensive review. Medic Ultrason,2010;12(3):228-32.
[11]de Oliveira SIRS, Widman A, Molnar LJ, et al. Color Doppler ultrasound:a new index improves the diagnosis of renal artery stenosis. Ultrasound Med Biol,2000, 26(1):41-47.
[12]Li JC, Ji ZG, Cai S, et al. Evaluation of severe transplant renal artery stenosis with Doppler sonography. J Clinical Ultrasound,2005,33(6):261-9.
[13]Li JC, Wang L, Jiang YX, et al. Evaluation of renal artery stenosis with velocity parameters of Doppler sonography. J Ultrasound Med,2006; 25(6):735-42.
[14]Chain S, Luciardi H, Feldman G, et al. Diagnostic role of new Doppler index in assessment of renal artery stenosis. Cardiovascular Ultrasound,2006,25;4:4
[15]秦卫,王芳,王梅,等.彩色多普勒超声在动脉粥样硬化性肾动脉狭窄诊断中的应用.中华超声影像学杂志,2005,14(7)：508-11.
[16]Ripolles T, Aliaga R, Morote V, et al. Utility of intrarenal Doppler ultrasound in the diagnosis of renal artery stenosis. European J Radiology,2001,40(1):54-7.
[17]李建初.小慢波频谱诊断肾动脉狭窄的现状和进展(述评).中华医学超声杂志,2007,4(6)：321-4.
[18]孙哲,黎庶,徐惠绵.数字化乳腺X线计算机辅助诊断系统临床应用价值的初步探讨.中华医学杂志,2005,85(24)：1692-5.
[19]Matsumoto S, Ohno Y, Yamagata H, et al. Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings. Radiat Med,2008; 26(9):562-9
[20]Willems JL, Abreu-Lima C, Arnaud P, et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med, 1991,325(25):1803-4.
[21]Oweis R, Hijazi L. A computer-aided ECG diagnostic tool. Computer Methods and Programs in Biomedicine,2006,81(3):279-84.
[22]张羽,汪源源,王威琪,余建国.超声多普勒血流信号的小波特征提取及分类.生物医学工程学杂志,2002,19(2)：244-6.
[23]张榆锋,郭振宇,周屹,施心陵.基于小波变换与基于短时傅立叶变换的模拟颈动脉超声多普勒信号的时频分布比较研究.中国生物医学工程学报,2005,24(1)：107-9.
[24]Serge Belongie, Jitendra Malik, Jan Puzicha. Shape matching and object recognition using shape contexts. IEEE TRANS.PAMI,2002,24:4.
[25]陈竹修.基于傅里叶变换的形状上下文描述方法.计算机应用与软件,2007,24(6)：140-4.
[1]SpyRIdopoulos TN, Kaziani K, Balanika AP, et al. Ultrasound as a first line screening tool for the detection of Renal Artery Stenosis:a comprehensive review. Medic Ultra Son,2010;12(3):228-32.
[2]Li JC, Ji ZG, Cai S, et al. Evaluation of severe transplant renal artery stenosis with Doppler sonography. J Clinical Ultrasound,2005,33(6):261-9.
[3]Li JC, Jiang YX, et al. Evaluation of renal artery stenosis with hemodynamic parameters of Doppler sonography. J Vascul Surg,2008;48(2):323-8.
[4]王杰,杨萌等.鲁棒的超声多普勒肾动脉血流信号提取方法[J].计算机科学.2010；37(2)：274-6.
[5]Comaniciu D,Meer P.Mean shift:A robust approach toward feature space analysis[J]. IEEE Transaction on Pattern Analysis and Machine Intelligence.2002;24(5):603-19.
[6]Chih-Chung Chang,Chih-Jen Lin. LIBSVM--A library for support vector machines[EB/OL]. http://www. csie.ntu.edu.tw/-cjlin/libSVM/.
[7]李炳成,沈俊.曲线矩不变性的研究.电子科学学刊.1992；14(3)：262-70.
[8]孙哲,黎庶,徐惠绵.数字化乳腺X线计算机辅助诊断系统临床应用价值的初步探讨.中华医学杂志,2005；85(24)：1692-5.
[9]Matsumoto S, Ohno Y, Yamagata H, et al. Computer-aided detection of lung nodules on multidetector row computed tomography using three-dimensional analysis of nodule candidates and their surroundings. Radiat Med,2008;26(9):562-9.
[10]Willems JL, Abreu-Lima C, Arnaud P, et al. The diagnostic performance of computer programs for the interpretation of electrocardiograms. N Engl J Med, 1991;325(25):1803-4.
[11]Oweis R, Hijazi L. A computer-aided ECG diagnostic tool. Computer Methods and Programs in Biomedicine,2006; 81(3):279-84.
[12]张羽,汪源源,王威琪,余建国.超声多普勒血流信号的小波特征提取及分类.生物医学工程学杂志,2002；19(2)：244-6.
[13]张榆锋,郭振宇,周屹,施心陵.基于小波变换与基于短时傅立叶变换的模拟颈动 脉超声多普勒信号的时频分布比较研究.中国生物医学工程学报.2005；24：107-9.
[14]Serge Belongie, Jitendra Malik, Jan Puzicha. Shape matching and object recognition using shape contexts. IEEE TRANS.PAMI.2002;24:4.
[15]陈竹修.基于傅里叶变换的形状上下文描述方法.计算机应用与软件,2007；24(6)：140-4.
[16]刘慧婷,张曼,程家兴.基于多项式拟合算法的EMD端点问题的处理.计算机工程与应用,2004；40(16)：84-6.
[17]C Cortes,V Vapnik. Support-Vector networks. Machin learning.1995;20:273-297.
[18]Vapnik V.The Nature of Statistical Learning Theory.张学工译.统计学习理论的本质,北京：清华大学出版社,2000：100-101.
[19]Riling G, FlandRIn P. On the influence of sampling on the empirical mode decomposition[C]//Proc 2006 IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP 2006),Toulouse,France,2006;3:444-7.
[20]邓拥军,王伟,钱成春,等.EMD方法及Hilbert变换中边界问题的处理.科学通报,2001；46(3)：257-63.
[21]邓乃扬,田英杰.数据挖掘中的新方法--支持向量机.北京：科学出版社.2004：164-208.
[22]Hsu C W.A practical guide to support vector classification [EB/OL].[2012-12-01]. http://www.csie.ntu.edu.tw/～cjlin/papers/guide/guide.pdf.
[23]Kliewer MA,Tupler RH,Carroll BA,et al. Renal artery stenosis:analysis of Doppler waveform parameters and tardus-parvus pattern. Radiology,1993,189(3):779-87.
[24]Handa N, Fukunaga R, Etani H, et al. Efficacy of echo-Doppler examination for the evaluation of renovascular disease. Ultrasound Med Biol,1988,14(1):1-5.
[25]Stavros AT, Parker SH, Yakes WF, et al. Segmental stenosis of the renal artery: pattern recognition of tardus and parvus abnormalities with duplex sonography. Radiology,1992,184(2):487-92.
[26]Patriquin HB,Lafortune M,Je'quier JC,et al. Stenosis of the renal artery:assessment of slowed systole in the downstream circulation with Doppler sonography. Radiology,1992,184(2):479-85.
[27]Ripolles T, Aliaga R, Morote V,et al.Utility of interenal Doppler ultrasound in the diagnosis of renal artery stenosis. Eur J Radiol,2001,40(1):54-63
[28]李建初,姜玉新,蔡胜,等.流速指标对肾动脉狭窄的诊断价值.中华超声影像学杂志,2004,12(13)：902-6.
[29]李建初.小慢波频谱诊断肾动脉狭窄的现状和进展.中华医学超声杂志(电子版),2007,4(6)：321-4.
[1]Zubarev AV. Ultrasound of renal vessels. Eur Radiol,2001;11(10):1902-15.
[2]李建初.肾动脉狭窄的超声规范化检测与结果分析.中华医学超声杂志(电子版),2010；7(1)：5-9
[3]马少平,祝伟宏,吴志坚,等.超声点追踪及连续切面法观察不同体位下肾脏活动度的价值.中外医学研究,2012；10(20)：50-1.
[4]Lin ZY, Dai CY, Chang WY, et al. Influence of posture change on intrarenal arterial resistive index measurement. Abdomen Imaging,2002;27(6):626-8.
[5]Hayashi N, Someya N, EndoMY,Miura A and Fukuba Y. Vasoconstriction and blood flow responses in visceral arteries to mental task in humans. Exp. Physiol, 2006; 91(1):215-20.
[6]Iwao T, Toyonaga A, Shigemori H, Oho K, Sumino M, Sato M and Tanikawa K. Echo-Doppler measurements of portal vein and superior mesenteric artery blood flow in humans:inter-and intra-observer short-term reproducibility. J. Gastroenterol. Hepatol,1996; 11(1):40-6.
[7]Momen A, Leuenberger U A, Ray C A, Cha S, Handly B and Sinoway L I. Renal vascular response to static handgrip:role of muscle mechanoreflex. Am. J. Physiol. Heart Circ. Physiol,2003; 285(3):H1247-53.
[8]Mary TD, Christopher Z, Charles T. Three-dimensional analysis of renal artery bending motion during respiration. J Endovasc Ther,2005;12(3):380-6.
[9]Nami S, Masako E, Yoshiyuki F, Naoyuki H. The limited effect of breathing frequency on blood velocity measurements in renal and superior mesenteric arteries. Physiological Measurement,2007;28(11):1369-74.
[10]柏树令.系统解剖学(7年制用).第1版.北京：人民卫生出版社,2001：161-2.
[11]王怀经.局部解剖学(7年制用).北京：人民卫生出版社,2002：177.
[12]张岐山,郭应禄,燕山,等.泌尿系超声诊断治疗学.科学技术文献出版社,2001：37.
[13]张小平,李兴国.肾筋膜及肾周间隙的解剖学研究进展.局解手术学杂志,2004；13(2)：122-3.
[14]袁小旭,司徒杰.仰、俯卧位下肾结肠位置变化与相对位移的影响.解剖学研究,2009；27(5)：551-4.
[15]Renan Liflacker. Atlas of vascular anatomy. Lippincott Williams & Wilkins,Inc, U.S.A,1997:278.
[16]Esther SH, Susan W, Christopher T, et al. Positionally dependent renal artery restenosis.Circulation,2009;120(8):714-5.
[17]Takano R, Ando Y, Taniguchi N, et al. Power Doppler sonography of the kidney: effect of Valsalva's maneuver. J Clin Ultrasound,2001;29(7):384-8.
[18]Richards WO, Scovill W, Shin B, et al. Acute renal failure associated with increased intra-abdominal pressure. Ann Surg,1983; 197(2):183.
[19]Navar LG, Carmines PK, Paul RV. Renal circulation. In:Massry S, Glassock R, editors. Textbook of nephrology.2nd ed. Baltimore:Williams & Wilkins; 1989. p 43.
[20]王咏梅,张炽敏,李嘉,等.肾内动脉血流阻力指数在慢性肾病诊治中的意义.中国超声医学杂志,2007,23(4)：290-292.
[21]Knapp R, Plotzeneder A, Frauscher F, et al. Variability of Doppler parameters in the healthy kidney:an anatomic-physiologic correlation. J Ultrasound Med, 1995;14(6):427-9.
[22]Bude RO, Rubin JM. Relationship between the resistive index and vascular compliance and resistance. Radiology,1999;211(2):411-7.
[23]Tublin ME, Tessler FN, Murphy ME:Correlation between renal vascular resistance, pulse pressure, and the resistive index in isolated perfused rabbit kidneys. Radiology, 1999;213(1):258-64.
[24]Derchi LE et al. Mild renal dysfunction and renal vascular resistance in primary hypertension. Am J Hypertens,2005,18(7):966-971.
[25]Seiler S, Colbus S, Lucisano G,et al. Ultrasound renal resistive index is not an organ-specific predictor of allograft outcome. Nephrol Dial Transplant, 2012,27(8):3315-20.
[26]Radermacher J, Mengel M, Ellis S,et al. The renal arterial resistance index and renal allograft survival. N Engl J Med,2003,349(2):115-24.
[27]Kawai T, Kamide K, Onishi M, et al. Usefulness of the resistive index in renal Doppler ultrasonography as an indicator of vascular damage in patients with risks of atherosclerosis. Nephrol Dial Transplant,2011,26(10):3256-62.
[28]Milovanceva-Popovska M, Dzikova S. Doppler ultrasonography:A tool for nephrologists-single centre experience. Prilozi,2008;29(1):107-128.
[29]Keogan MT, Kliewer MA, Hertzberg BS, et al. Renal resistive indexes:variability in Doppler US measurement in a healthy population. Radiology,1996;199(1): 165-9.
[30]Yildirim H, Gungor S, Cihangiroglu MM, et al. Doppler studies in normal kidneys of preterm and term neonates:Changes in relation to gestational age and birth weight. J Ultrasound Med,2005;24(5):623-7.
[31]Ansarin K, Bavil AS, Ghabili K, et al. Are Doppler ultrasonography parameters symmetric between the right and left kidney? Int J Gen Med,2010;16(3):371-3.
[32]Kliewer MA, Hertzberg BS, Keogan MT, et al. Early systole in the healthy kidney: Variability of Doppler US waveform parameters. Radiology,1997;205(1):109-13.
[33]Atmaram S, Pai Panandiker, Shelly Sharma, et al. Novel assessment of renal motion in children as measured via four-dimensional computed tomography. Int. J. Radiation Oncology Biol. Phys,2012;82(5):1771-6.
[34]Moore JE Jr., Ku DN. Pulsatile velocity measurements in a model of the human abdominal aorta under simulated exercise and postprandial conditions. J Biomech Eng,1994;116(1):107-11.
[35]Taremi M, Ringash J, Dawson LA. Upper abdominal malignancies:Intensity-modulated radiation therapy. Front Radiat Ther Oncol,2007;40:272-88.
[36]Murtz P, Pauleit D, Traber F, et al. Pulse triggering for improved diffusion-weighted MR imaging of the abdomen. Rofo,2000;172(7):587-90.
[37]Faries PL, Agarwal G, Lookstein R, et al. Use of cine magnetic resonance angiography in quantifying aneurysm pulsatility associated with endoleak. J Vase Surg,2003;38(4):652-6.
[38]Suramo I, Paivansalo M, Myllyla V. Cranio-caudal movements of the liver, pancreas and kidneys in respiration. Acta Radiol Diag,1984;25(2):129-31.
[39]Davies SC, Hill AL, Holmes RB, et al. Ultrasound quantification of respiratory organ motion in the upper abdomen. Br J Radiol,1994;67(803):1096-102.
[40]Aruga T, Itami J, Aruga M, et al. Target volume definition for upper abdominal irradiation using CT scans obtained during inhale and exhale phases. Int J Radiat Oncol Biol Phys,2000; 48(2):465-9.
[41]Schwartz LH, Richaud J, Buffat L, et al. Kidney mobility during respiration. Radiother Oncol,1994;32(1):84-6.
[42]Moerland MA, van den Bergh ACM, Bhagwandien R, et al. The influence of respiration induced motion of the kidney on the accuracy of radiotherapy treatment planning, a magnetic resonance imaging study. Radiother Oncol,1994; 30(2):150-4.
[43]van Srnsen de Koste JR, Senan R, Kleynen CE, et al. Renal mobility during uncoached quiet respiration:an analysis of 4DCT scans. Int J Radiat Oncol Biol Phys,2006;64(3):799-803.
[44]习勉,刘孟忠,李巧巧,等.基于4DCT的腹部器官呼吸运动分析.癌症,2009；28(9)：989-93.
[45]Vasbinder GB, Maki JH, Nijenhuis RJ, et al. Motion of the distal renal artery during three-dimensional contrast-enhanced breath-hold MRA. J Magn Reson Imaging,2002;16(6):685-96.