Objective: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma(HCC) treated with radiofrequency ablation(RFA) using histogram analysis of apparent diffusion coefficients(AD...Objective: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma(HCC) treated with radiofrequency ablation(RFA) using histogram analysis of apparent diffusion coefficients(ADC).Methods: Breath-hold diffusion weighted imaging(DWI) was performed in 64 patients(33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging(MRI)and follow-up computed tomography(CT) or MRI. The ADC values(ADC_(10), ADC_(30_, ADC_(median) and ADC_(max))were obtained from the histogram's 10 th, 30 th, 50 th and 100 th percentiles. The ratios of ADC_(10), ADC_(30_,ADCmedian and ADCmax to the mean non-lesion area-ADC(RADC_(10), RADC_(30_, RADC_(median), and RADC_(max)) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test.Results: The ADC_(30_, ADCmedian, ADCmax, RADC_(30_, RADC_(median), and RADC_(max) were significantly larger in the progressive group than in the stable group(P<0.05). The median progression-free survival(PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months,respectively. Univariate analysis indicated that RADC_(10), RADC_(30_, and RADC_(median) were significantly correlated with the PFS [hazard ratio(HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADCmedian was the only independent predictor of tumor progression(P=0.04). And the cutoff value of RADC_(median) was 0.71.Conclusions: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.展开更多
BACKGROUND For periampullary adenocarcinoma,the histological subtype is a better prognostic predictor than the site of tumor origin.Intestinal-type periampullary adenocarcinoma(IPAC)is reported to have a better progno...BACKGROUND For periampullary adenocarcinoma,the histological subtype is a better prognostic predictor than the site of tumor origin.Intestinal-type periampullary adenocarcinoma(IPAC)is reported to have a better prognosis than the pancreatobiliary-type periampullary adenocarcinoma(PPAC).However,the classification of histological subtypes is difficult to determine before surgery.Apparent diffusion coefficient(ADC)histogram analysis is a noninvasive,nonenhanced method with high reproducibility that could help differentiate the two subtypes.AIM To investigate whether volumetric ADC histogram analysis is helpful for distinguishing IPAC from PPAC.METHODS Between January 2015 and October 2018,476 consecutive patients who were suspected of having a periampullary tumor and underwent magnetic resonance imaging(MRI)were reviewed in this retrospective study.Only patients who underwent MRI at 3.0 T with different diffusion-weighted images(b-values=800 and 1000 s/mm^2)and who were confirmed with a periampullary adenocarcinoma were further analyzed.Then,the mean,5th,10th,25th,50th,75th,90th,and 95th percentiles of ADC values and ADCmin,ADCmax,kurtosis,skewness,and entropy were obtained from the volumetric histogram analysis.Comparisons were made by an independent Student's t-test or Mann-Whitney U test.Multiple-class receiver operating characteristic curve analysis was performed to determine and compare the diagnostic value of each significant parameter.RESULTS In total,40 patients with histopathologically confirmed IPAC(n=17)or PPAC(n=23)were enrolled.The mean,5th,25th,50th,75th,90th,and 95th percentiles and ADCmax derived from ADC1000 were significantly lower in the PPAC group than in the IPAC group(P<0.05).However,values derived from ADC800 showed no significant difference between the two groups.The 75th percentile of ADC1000 values achieved the highest area under the curve(AUC)for differentiating IPAC from PPAC(AUC=0.781;sensitivity,91%;specificity,59%;cut-off value,1.50×10^-3 mm^2/s).CONCLUSION Volumetric ADC histogram an展开更多
目的探究基于肿瘤整体体积的表观扩散系数(apparent diffusion coefficient,ADC)直方图分析在直肠癌组织学分级中的临床作用。材料与方法回顾性分析121例直肠癌患者资料,所有患者术前均行3.0 T MRI检查。采用FireVoxel软件勾画兴趣区并...目的探究基于肿瘤整体体积的表观扩散系数(apparent diffusion coefficient,ADC)直方图分析在直肠癌组织学分级中的临床作用。材料与方法回顾性分析121例直肠癌患者资料,所有患者术前均行3.0 T MRI检查。采用FireVoxel软件勾画兴趣区并进行直方图分析,通过方差分析比较直肠癌不同组织学分级的直方图参数[ADC最小值(ADC_(min))、ADC最大值(ADC_(max))、ADC平均值(ADC_(mean))、第5、10、25、50、75、90、95百分位数值域、偏度、峰度]。Spearman相关检验分析组织学分级与直方图参数之间的相关性。用logistic回归找出最优组合模型。并利用受试者工作特征(receiver operating characteristic,ROC)曲线分析直方图参数对于直肠癌分化程度的诊断能力。结果直方图参数ADC_(mean)、第75、90百分位、偏度和峰度在高、中和低分化的直肠癌之间有显著性差异(P<0.05)。直肠癌分化程度与上述直方图参数之间存在相关性(r=0.548、0.568、0.563、-0.555,-0.760,P<0.05)。在ADC直方图参数中,峰度在区分低分化直肠癌和高分化/中分化直肠癌时达到了最高ROC曲线下面积(area under the curve,AUC)值,为0.918,最佳截止值为2.045。ADC_(mean)、第75、90百分位、偏度和峰度的组合产生了最高的AUC,为0.928。结论基于全病灶ADC直方图分析可用于预测直肠癌的组织学分级,并且ADC_(mean)、第75、90百分位、偏度和峰度组合可能是区分低、中高分化直肠癌的最佳选择。展开更多
基金supported by CAMS Innovation Fund for Medical Sciences (CIFMS) (No. 2016-I2M-1-001)PUMC Youth Fund (No. 2017320010)Beijing Hope Run Fund of Cancer Foundation of China (No. LC2016B15)
文摘Objective: The aim of this study was to predict tumor progression in patients with hepatocellular carcinoma(HCC) treated with radiofrequency ablation(RFA) using histogram analysis of apparent diffusion coefficients(ADC).Methods: Breath-hold diffusion weighted imaging(DWI) was performed in 64 patients(33 progressive and 31 stable) with biopsy-proven HCC prior to RFA. All patients had pre-treatment magnetic resonance imaging(MRI)and follow-up computed tomography(CT) or MRI. The ADC values(ADC_(10), ADC_(30_, ADC_(median) and ADC_(max))were obtained from the histogram's 10 th, 30 th, 50 th and 100 th percentiles. The ratios of ADC_(10), ADC_(30_,ADCmedian and ADCmax to the mean non-lesion area-ADC(RADC_(10), RADC_(30_, RADC_(median), and RADC_(max)) were calculated. The two patient groups were compared. Key predictive factors for survival were determined using the univariate and multivariate analysis of the Cox model. The Kaplan-Meier survival analysis was performed, and pairs of survival curves based on the key factors were compared using the log-rank test.Results: The ADC_(30_, ADCmedian, ADCmax, RADC_(30_, RADC_(median), and RADC_(max) were significantly larger in the progressive group than in the stable group(P<0.05). The median progression-free survival(PFS) was 22.9 months for all patients. The mean PFS for the stable and progressive groups were 47.7±1.3 and 9.8±1.3 months,respectively. Univariate analysis indicated that RADC_(10), RADC_(30_, and RADC_(median) were significantly correlated with the PFS [hazard ratio(HR)=31.02, 43.84, and 44.29, respectively, P<0.05 for all]. Multivariate analysis showed that RADCmedian was the only independent predictor of tumor progression(P=0.04). And the cutoff value of RADC_(median) was 0.71.Conclusions: Pre-RFA ADC histogram analysis might serve as a useful biomarker for predicting tumor progression and survival in patients with HCC treated with RFA.
基金Supported by the National Natural Science Foundation of China,No.81701657,No.81571642,No.81801695,and No.81771801the Fundamental Research Funds for the Central Universities,No.2017KFYXJJ126
文摘BACKGROUND For periampullary adenocarcinoma,the histological subtype is a better prognostic predictor than the site of tumor origin.Intestinal-type periampullary adenocarcinoma(IPAC)is reported to have a better prognosis than the pancreatobiliary-type periampullary adenocarcinoma(PPAC).However,the classification of histological subtypes is difficult to determine before surgery.Apparent diffusion coefficient(ADC)histogram analysis is a noninvasive,nonenhanced method with high reproducibility that could help differentiate the two subtypes.AIM To investigate whether volumetric ADC histogram analysis is helpful for distinguishing IPAC from PPAC.METHODS Between January 2015 and October 2018,476 consecutive patients who were suspected of having a periampullary tumor and underwent magnetic resonance imaging(MRI)were reviewed in this retrospective study.Only patients who underwent MRI at 3.0 T with different diffusion-weighted images(b-values=800 and 1000 s/mm^2)and who were confirmed with a periampullary adenocarcinoma were further analyzed.Then,the mean,5th,10th,25th,50th,75th,90th,and 95th percentiles of ADC values and ADCmin,ADCmax,kurtosis,skewness,and entropy were obtained from the volumetric histogram analysis.Comparisons were made by an independent Student's t-test or Mann-Whitney U test.Multiple-class receiver operating characteristic curve analysis was performed to determine and compare the diagnostic value of each significant parameter.RESULTS In total,40 patients with histopathologically confirmed IPAC(n=17)or PPAC(n=23)were enrolled.The mean,5th,25th,50th,75th,90th,and 95th percentiles and ADCmax derived from ADC1000 were significantly lower in the PPAC group than in the IPAC group(P<0.05).However,values derived from ADC800 showed no significant difference between the two groups.The 75th percentile of ADC1000 values achieved the highest area under the curve(AUC)for differentiating IPAC from PPAC(AUC=0.781;sensitivity,91%;specificity,59%;cut-off value,1.50×10^-3 mm^2/s).CONCLUSION Volumetric ADC histogram an
文摘目的探究基于肿瘤整体体积的表观扩散系数(apparent diffusion coefficient,ADC)直方图分析在直肠癌组织学分级中的临床作用。材料与方法回顾性分析121例直肠癌患者资料,所有患者术前均行3.0 T MRI检查。采用FireVoxel软件勾画兴趣区并进行直方图分析,通过方差分析比较直肠癌不同组织学分级的直方图参数[ADC最小值(ADC_(min))、ADC最大值(ADC_(max))、ADC平均值(ADC_(mean))、第5、10、25、50、75、90、95百分位数值域、偏度、峰度]。Spearman相关检验分析组织学分级与直方图参数之间的相关性。用logistic回归找出最优组合模型。并利用受试者工作特征(receiver operating characteristic,ROC)曲线分析直方图参数对于直肠癌分化程度的诊断能力。结果直方图参数ADC_(mean)、第75、90百分位、偏度和峰度在高、中和低分化的直肠癌之间有显著性差异(P<0.05)。直肠癌分化程度与上述直方图参数之间存在相关性(r=0.548、0.568、0.563、-0.555,-0.760,P<0.05)。在ADC直方图参数中,峰度在区分低分化直肠癌和高分化/中分化直肠癌时达到了最高ROC曲线下面积(area under the curve,AUC)值,为0.918,最佳截止值为2.045。ADC_(mean)、第75、90百分位、偏度和峰度的组合产生了最高的AUC,为0.928。结论基于全病灶ADC直方图分析可用于预测直肠癌的组织学分级,并且ADC_(mean)、第75、90百分位、偏度和峰度组合可能是区分低、中高分化直肠癌的最佳选择。
