三种扩散成像技术在乳腺良恶性病变鉴别诊断中的对比研究
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摘要
目的探讨扩散加权成像(DWI)、体素内不相干运动(IVIM)和扩散峰度成像(DKI)各参数对乳腺良恶性病变的诊断价值。方法回顾性分析经病理证实的51例乳腺病变患者,共58个病灶,其中良性病灶22个,恶性病灶36个。所有患者均采集T_1WI、短时间反转恢复(STIR)、动态增强磁共振成像(DCE-MRI)、DWI、IVIM和DKI序列,通过图像后处理工作站测量表观扩散系数(ADC)、慢速表观扩散系数(slow ADC)、快速表观扩散系数(fast ADC)和平均扩散峰度(MK)。采用独立样本t检验比较良恶性病变各参数值差异,采用配对t检验比较ADC与slow ADC值差异。应用受试者工作特征曲线(ROC)及曲线下面积(AUC)计算各参数诊断乳腺良恶性病变阈值、敏感度及特异度,多参数联合诊断效能采用Logistic回归分析。观察者间一致性分析采用组内相关系数(ICC)。结果乳腺良性病变与恶性病变的ADC、slow ADC和MK值均有统计学差异(P<0.001),ADC与slow ADC值差异无统计学意义。当ADC、slow ADC、fast ADC和MK诊断阈值设为1.123×10~(-3)mm~2/s、0.893×10~(-3)mm~2/s、4.911×10~(-3)mm~2/s和0.920时,敏感度和特异度依次分别为80.510%和77.272%、86.120%和77.272%、75.000%和68.181%、80.510%和86.363%。联合slow ADC和MK值诊断效能最大(AUC=0.902,敏感度88.889%,特异度90.909%)。fast ADC值ICC为0.67,一致性中等,ADC、slow ADC和MK值观察者间一致性良好(ICC>0.90)。结论采用DWI、IVIM和DKI获得的相关参数有助于乳腺良恶性病变鉴别诊断,联合slow ADC和MK的诊断效能最高。
Objective To contrast the diagnostic value of various parameters of diffusion-weighted imaging(DWI) 、intravoxel incoherent motion(IVIM) imaging and diffusion kurtosis imaging(DKI) in benign and malignant breast lesions.Methods A study performed in 51 patients with pathologically confirmed lesions were analyzed retrospectively by two researchers.The study included 58 lesions with 22 benign lesions and 36 malignant lesions.All patients underwent T_1WI、STIR、DCE-MRI、DWI、IVIM and DKI sequences.All parameters were measured at a post-processing workstation,including apparent diffusion coefficient(ADC) 、slow apparent diffusion coefficient(slow ADC) 、fast apparent diffusion coefficient(fast ADC) and mean diffusion kurtosis(MK).Independent sample Student's t test was used to compare the ADC、slow ADC、fast ADC and MK value differences between benign and malignant lesions,and the ADC and slow ADC value difference was compared by paired t test.The sensitivity,specificity and best thresholds of these parameters for differential diagnosing of malignant and benign lesions were calculated by ROC and AUC.The Logistic regression was used for multiparameter joint diagnosis.The ICC was used for inter-observer agreement analysis.Results There were statistically significant differences in ADC、slow ADC and MK values of benign and malignant lesions(P<0.001),and no significant difference between ADC and slow ADC values.When ADC,slow ADC,fast ADC and MK diagnostic thresholds were set to Using the 1.123 × 10~(-3)mm~2/s、0.893 × 10~(-3)mm~2/s、4.911 × 10~(-3)mm~2/s and 0.920 as the respective thresholds of ADC、slow ADC、fast ADC and MK,the corresponding sensitivity and specificity of these parameters were(80.510%,77.272%) 、(86.120%,77.272%) 、(75.000%,68.181%) and(80.510%,86.363 %) respectively.Combined slow ADC and MK values were the most effective(AUC=0.902,sensitivity 88.889% and specificity 90.909%).There were excellent inter-observer agreement in ADC、slow ADC and MK values(ICC>0.90).For fast ADC value,the inter-obserer agreement was relatively good with an ICC of 0.67.Conclusion The parameters of DWI、IVIM and DKI are helpful in differential diagnosis of benign and malignant breast lesions,with the highest diagnostic efficacy of combined slow ADC and MK.
Objective To contrast the diagnostic value of various parameters of diffusion-weighted imaging(DWI) 、intravoxel incoherent motion(IVIM) imaging and diffusion kurtosis imaging(DKI) in benign and malignant breast lesions.Methods A study performed in 51 patients with pathologically confirmed lesions were analyzed retrospectively by two researchers.The study included 58 lesions with 22 benign lesions and 36 malignant lesions.All patients underwent T_1WI、STIR、DCE-MRI、DWI、IVIM and DKI sequences.All parameters were measured at a post-processing workstation,including apparent diffusion coefficient(ADC) 、slow apparent diffusion coefficient(slow ADC) 、fast apparent diffusion coefficient(fast ADC) and mean diffusion kurtosis(MK).Independent sample Student's t test was used to compare the ADC、slow ADC、fast ADC and MK value differences between benign and malignant lesions,and the ADC and slow ADC value difference was compared by paired t test.The sensitivity,specificity and best thresholds of these parameters for differential diagnosing of malignant and benign lesions were calculated by ROC and AUC.The Logistic regression was used for multiparameter joint diagnosis.The ICC was used for inter-observer agreement analysis.Results There were statistically significant differences in ADC、slow ADC and MK values of benign and malignant lesions(P<0.001),and no significant difference between ADC and slow ADC values.When ADC,slow ADC,fast ADC and MK diagnostic thresholds were set to Using the 1.123 × 10~(-3)mm~2/s、0.893 × 10~(-3)mm~2/s、4.911 × 10~(-3)mm~2/s and 0.920 as the respective thresholds of ADC、slow ADC、fast ADC and MK,the corresponding sensitivity and specificity of these parameters were(80.510%,77.272%) 、(86.120%,77.272%) 、(75.000%,68.181%) and(80.510%,86.363 %) respectively.Combined slow ADC and MK values were the most effective(AUC=0.902,sensitivity 88.889% and specificity 90.909%).There were excellent inter-observer agreement in ADC、slow ADC and MK values(ICC>0.90).For fast ADC value,the inter-obserer agreement was relatively good with an ICC of 0.67.Conclusion The parameters of DWI、IVIM and DKI are helpful in differential diagnosis of benign and malignant breast lesions,with the highest diagnostic efficacy of combined slow ADC and MK.
引文
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2 Heller SL,Moy L,Lavianlivi S,et al.Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast-enhanced MRI[J].J Magn Reson Imaging,2013,37:138-145.
3 Soares F,Janela F,Pereira M,et al.3D Lacunarity in Multifractal A-nalysis of Breast Tumor Lesions in Dynamic Contrast-Enhanced Magnetic Resonance Imaging[J].IEEE Trans Image Process,2013,22:4422-4435.
4王高燕,杨光钊,董海波,等.基于体素内不相干运动DWI在乳腺良恶性病变鉴别中的价值[J].临床放射学杂志,2016,35:348-352.
5王莹莹,张焱,程敬亮,等.单指数及DKI模型在乳腺良恶性病变鉴别诊断中的价值[J].临床放射学杂志,2017,36:193-197.
6高欣,周丽娟,徐孝秋,等.扩散峰度成像对乳腺良、恶性病变的鉴别诊断价值[J].中华放射学杂志,2017,51:583-587.
7 Le Bihan D,Breton E,Lallemand D,et al.MR imaging of intravoxel incoherent motions:application to diffusion and perfusion in neurologic disorders[J].Radiology,1986,161:401-407.
8 Partridge SC,De Martini WB,Kurland BF,et al.Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value[J].AJR,2009,193:1716-1722.
9 Sigmund EE,Cho GY,Kim S,et al.Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer[J].Magn Reson Med,2011,65:1437-1447.
10 Bokacheva L,Kaplan JB,Giri DD,et al.Intravoxel incoherent motion diffusion-weighted MRI at 3.0T differentiates malignant breast lesions from benign lesions and breast parenchyma[J].J Magnreson Imaging,2014,40:813-823.
11 Liu C,Liang C,Liu Z,et al.Intravoxel incoherent motion(IVIM)in evaluation of breast lesions:Comparison with conventional DWI[J].Eur J Radiol,2013,82:e782-e789.
12 Nilsen LB,Fangberget A,Geier O,et al.Quantitative analysis of diffusion-weighted magnetic resonance imaging in malignant breast lesions using different b value combinations[J].Eur Radiol,2013,23:1027-1033.
13 Jensen JH,Helpern JA,Ramani A,et al.Diffusional kurtosis imaging:the quantification of non-gaussian water diffusion by means of magnetic resonance imaging[J].Magn Reson Med,2005,53:1432-1440.
14 Sun K,Chen X,Chai W,et al.Breast cancer:diffusion kurtosis MRimaging-diagnostic accuracy and correlation with clinical-pathologic factors[J].Radiology,2015,277:46-55.
15 Nogueira L,Brando S,Matos E,et al.Application of the diffusion kurtosis model for the study of breast lesions[J].Eur Radiol,2014,24:1197-1203.
16 Wu D,Li G,Zhang J,et al.Characterization of breast tumors using diffusion kurtosis imaging(DKI)[J].PLo S One,2014,9:e113240.
17 Aribal E,Asadov R,Ramazan A,et al.Multiparametric breast MRIwith 3T:effectivity of combination of contrast enhanced MRI,DWIand 1H single voxel spectroscopy in differentiation of Breast tumors[J].Eur J Radiol,2016,85:979-986.
18 Shrout PE,Measurement reliability and agreement in psychiarty[J].Stat Methods Med Res,1998,7:301-317.
2 Heller SL,Moy L,Lavianlivi S,et al.Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast-enhanced MRI[J].J Magn Reson Imaging,2013,37:138-145.
3 Soares F,Janela F,Pereira M,et al.3D Lacunarity in Multifractal A-nalysis of Breast Tumor Lesions in Dynamic Contrast-Enhanced Magnetic Resonance Imaging[J].IEEE Trans Image Process,2013,22:4422-4435.
4王高燕,杨光钊,董海波,等.基于体素内不相干运动DWI在乳腺良恶性病变鉴别中的价值[J].临床放射学杂志,2016,35:348-352.
5王莹莹,张焱,程敬亮,等.单指数及DKI模型在乳腺良恶性病变鉴别诊断中的价值[J].临床放射学杂志,2017,36:193-197.
6高欣,周丽娟,徐孝秋,等.扩散峰度成像对乳腺良、恶性病变的鉴别诊断价值[J].中华放射学杂志,2017,51:583-587.
7 Le Bihan D,Breton E,Lallemand D,et al.MR imaging of intravoxel incoherent motions:application to diffusion and perfusion in neurologic disorders[J].Radiology,1986,161:401-407.
8 Partridge SC,De Martini WB,Kurland BF,et al.Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value[J].AJR,2009,193:1716-1722.
9 Sigmund EE,Cho GY,Kim S,et al.Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer[J].Magn Reson Med,2011,65:1437-1447.
10 Bokacheva L,Kaplan JB,Giri DD,et al.Intravoxel incoherent motion diffusion-weighted MRI at 3.0T differentiates malignant breast lesions from benign lesions and breast parenchyma[J].J Magnreson Imaging,2014,40:813-823.
11 Liu C,Liang C,Liu Z,et al.Intravoxel incoherent motion(IVIM)in evaluation of breast lesions:Comparison with conventional DWI[J].Eur J Radiol,2013,82:e782-e789.
12 Nilsen LB,Fangberget A,Geier O,et al.Quantitative analysis of diffusion-weighted magnetic resonance imaging in malignant breast lesions using different b value combinations[J].Eur Radiol,2013,23:1027-1033.
13 Jensen JH,Helpern JA,Ramani A,et al.Diffusional kurtosis imaging:the quantification of non-gaussian water diffusion by means of magnetic resonance imaging[J].Magn Reson Med,2005,53:1432-1440.
14 Sun K,Chen X,Chai W,et al.Breast cancer:diffusion kurtosis MRimaging-diagnostic accuracy and correlation with clinical-pathologic factors[J].Radiology,2015,277:46-55.
15 Nogueira L,Brando S,Matos E,et al.Application of the diffusion kurtosis model for the study of breast lesions[J].Eur Radiol,2014,24:1197-1203.
16 Wu D,Li G,Zhang J,et al.Characterization of breast tumors using diffusion kurtosis imaging(DKI)[J].PLo S One,2014,9:e113240.
17 Aribal E,Asadov R,Ramazan A,et al.Multiparametric breast MRIwith 3T:effectivity of combination of contrast enhanced MRI,DWIand 1H single voxel spectroscopy in differentiation of Breast tumors[J].Eur J Radiol,2016,85:979-986.
18 Shrout PE,Measurement reliability and agreement in psychiarty[J].Stat Methods Med Res,1998,7:301-317.
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