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乳腺病变的磁共振诊断策略研究及新辅助化疗的疗效评估

Diagnostic Strategy of Breast Lesion on MRI and Evaluation of Tumor Response to Neoadjuvant Chemotherapy

【作者】 张静

【导师】 蔡幼铨; 安宁豫;

【作者基本信息】 中国人民解放军军医进修学院 , 影像医学与核医学, 2009, 博士

【摘要】 第一部分1.5T磁共振乳腺扩散加权成像b值的优化目的:通过分析水模、正常乳腺腺体、乳腺良性及恶性病变的表观扩散系数(Apparent diffusion coefficient,ADC)及图像信噪比(Signal-to-noise ratio,SNR)随b值的变化规律,探讨1.5T磁共振乳腺扩散加权成像(Diffusionweighted imaging,DWI)合理的b值取值范围。材料与方法:对32例经病理证实的乳腺病变(恶性18例,良性14例)及对侧正常腺体进行乳腺MR检查,采用横轴位的平面回波-扩散加权成像序列(EPI-DWI);TR=8400ms,TE=93.8ms,层厚=4mm,激励次数(NEX)=2,视野(FOV)=30×30cm,矩阵=128×128,ASSET=2,b值分别采0,50,100,200,400,600,800,1000,1200,1400,1600,1800,2000,2200,2400,2600s/mm2。采用GE公司标准水模进行相同序列扫描,测量不同b值下水模、正常乳腺腺体、乳腺良性及恶性病变的平均ADC值和图像SNR。采用Pearson相关分析法分析图像SNR、ADC值随不同b值的变化规律;采用t检验比较相同b值下正常乳腺腺体、乳腺良性及恶性病变的平均ADC值;分析乳腺良恶性病变ADC值差异随不同b值的变化规律。结果:水模及正常乳腺DWI图像SNR均随b值的增加逐渐下降,二者呈负相关。当b值取值范围<1400 s/mm2时,水模的ADC值基本保持不变,正常乳腺腺体、乳腺良、恶性病变的ADC值均随着b值的增加下降;相同b值下,恶性病变的平均ADC值显著低于良性病变及正常腺体,当b值取800~1000s/mm2时,恶性病变与良性病变和正常腺体之间的ADC值差异最低大;当b值>1400s/mm2,差异逐渐减小。结论:当b值取值800~1000s/mm2时,既能取得良好的图像质量,又能有效地鉴别乳腺良、恶性病变,是1.5T MR乳腺DWI最合理的b值取值范围。第二部分磁共振扩散加权成像在乳腺肿块性病变和非肿块性病变中应用价值的对比研究目的:对比乳腺良、恶性病变的表观弥散系数(apparent diffusioncoefficient,ADC),探讨DWI在乳腺肿块性病变和非肿块性病变中的诊断价值。材料与方法:搜集术前行乳腺MR检查并经穿刺或手术病理证实的236例乳腺病变,以对侧正常乳腺腺体作为正常对照,采用横轴位的平面回波-扩散加权成像序列(EPI-DWI),TR=8400ms,TE=93.8ms,层厚=4mm,激励次数(NEX)=2:视野(FOV)=30×30cm,矩阵=128×128,ASSET=2,b值=0和1000s/mm2;参考动态增强图像准确定位,测量病变区和对侧正常乳腺腺体的ADC值,应用t检验比较良、恶性病变及正常腺体ADC值的差异,采用接收者工作特征曲线(receiver operating characteristic curve,ROC)确定良恶性病变的ADC界值;根据BI-RADS MRI将乳腺病变按照形态学表现分为肿块性病变和非肿块性病变两组,比较ADC值在肿块和非肿块性病变中定性诊断的效能。结果:236例乳腺病变中恶性155例,平均ADC值为1.08±0.32×10-3mm2/s,良性81例,平均ADC值为1.48±0.35×10-3mm2/s,选取对侧正常腺体221个感兴趣区(ROI)为正常对照,其平均ADC值为1.95±0.3×10-3mm2/s,恶性病变ADC值明显低于良性病变及正常腺体,差异有统计学意义(P<0.01);根据ROC曲线确定ADC界值为1.25×10-3mm2/s,诊断敏感性和特异性分别为78.2%和77.5%。肿块性病变中恶性105例,平均ADC值为1.04±0.3×10-3mm2/s,良性56例,平均ADC值为1.47±0.33×10-3mm2/s,ADC界值为1.15×10-3mm2/s,其敏感性和特异性分别为79.8%和81.8%。75例非肿块性病变中恶性50例,平均ADC值为1.18±0.34×10-3mm2/s,良性25例,平均ADC值为1.51±0.4×10-3mm2/s,ADC界值为1.35×10-3mm2/s,其敏感性和特异性分别为78%和72%。在恶性病例中,导管内癌的ADC值(1.34±0.44×10-3mm2/s)高于浸润性导管癌(1.01±0.22×10-3mm2/s);在浸润性导管癌中,表现为肿块性病变的ADC值(0.98±0.2×10-3mm2/s)明显低于非肿块性病变(1.09±0.25×10-3mm2/s)。结论:乳腺恶性病变的ADC值低于良性病变,根据ADC界值可以鉴别良、恶性,诊断敏感性和特异性高;对肿块性病变和非肿块性病变应采用不同的ADC界值,可以提高诊断的准确性;DWI对肿块性病变的诊断效能优于非肿块性病变。不同病理类型的乳腺病变ADC值不同。第三部分磁共振动态增强扫描结合扩散加权成像诊断乳腺癌的策略研究目的:分析乳腺良、恶性病变的形态学表现、血流动力学表现,结合ADC值,采用单变量和多变量分析,挖掘有意义的恶性MR征象,制定乳腺癌的诊断策略,探讨动态增强MR(dynamic contrast-enhanced MR imaging,DCE-MRI)结合DWI对乳腺病变的诊断和鉴别诊断价值。材料和方法:223名患者术前行乳腺MR检查并经穿刺或手术病理证实乳腺良、恶性病灶236个。扫描序列包括平面回波-扩散加权成像(EPI-DWI),脂肪抑制快速自旋回波T2WI(FSE-T2WI),自旋回波T1WI(SE-T1WI);动态增强扫描采用VIBRANT序列,注射造影剂前及注射后0min、1min、2min、3min、4min、5min、6min各扫描一次。由放射科医生采用双盲法阅片,根据乳腺MR影像报告及数据系统(BI-RADS MRI),将病变按照不同形态学表现分为肿块和非肿块性病变两组,分析形态学表现(形状、边缘、分布特征、内部增强特征)、血流动力学表现(时间-信号强度曲线类型、最大增强率、达峰时间、早期增强率),并结合ADC值,应用SPSS15.0软件进行单变量及多变量分析,挖掘有意义恶性征象,建立回归模型,计算其敏感性、特异性、准确性、阳性预测值和阴性预测值。结果:236例乳腺病变中恶性155例,良性81例,按照病变形态学表现类型分为肿块性病变159例,其中恶性103例,良性56例;非肿块性病变75例,其中恶性50例,良性25例;2例无法明确分组。对于肿块性病变,病变边缘、毛刺征、内部增强特征、TIC曲线类型、ADC值及1min增强率在良恶性病变中有统计学差异;边缘不光滑、有毛刺、内部增强不均匀、廓清型曲线、ADC值<1.15×10-3mm2/s、1min增强率>105%为恶性征象。对于非肿块性病变,病变的TIC曲线类型、ADC值和1min增强率在良恶性病变中有统计学差异;廓清型TIC曲线、ADC值<1.35×10-3mm2/s和1min增强率>75%为恶性征象。肿块性病变诊断模型的敏感性、特异性、阳性预测值、阴性预测值和诊断准确性分别为85.3%、84.6%、91.6%、74.6%和85.1%;非肿块性病变诊断模型的敏感性、特异性、阳性预测值、阴性预测值和诊断准确性分别为82%、83.3%、91.1%、69%和82.4%。结论:DCE-MRI结合DWI诊断乳腺癌的敏感性和特异性高,有重要临床应用价值。对于肿块和非肿块性病变应当采取不同的诊断策略。第四部分磁共振扩散加权成像在乳腺癌新辅助化疗疗效评估中的应用价值研究目的:对比乳腺癌新辅助化疗前、后不同疗程ADC值的变化及其在化疗有效组和无效组间的差异,探讨DWI在乳腺癌新辅助化疗疗效评估中的应用价值。材料和方法:搜集36例经穿刺病理证实的乳腺癌患者,在新辅助化疗前、化疗后不同疗程末行DWI和DEC-MRI检查,以最终手术病理为金标准分为有效组和无效组,应用t检验比较化疗前、后不同疗程肿瘤ADC值,及其在化疗有效组和无效组的差异,于化疗前、后测量对侧正常乳腺腺体ADC值作为对照。结果:36例乳腺癌根据手术病理分为有效组和无效组,24例有效病灶治疗前平均ADC值为0.98±0.18×10-3mm2/s,12例无效病灶治疗前肿瘤平均ADC值为0.95±0.15×10-3mm2/s,两者无统计学差异((t=0.694,P=0.411)。化疗有效组肿瘤的ADC值较化疗前明显升高,化疗前肿瘤ADC值与化疗2~8个疗程后比较有统计学差异,化疗1个疗程后肿瘤ADC值较化疗前增高,但未达到显著水平。化疗无效组化疗前、后肿瘤ADC值无统计学差异;在化疗有效组,化疗前正常乳腺腺体平均ADC值为1.98±0.30×10-3mm2/s,化疗4个疗程后正常乳腺腺体平均ADC值为1.96±0.28×10-3mm2/s,差异无统计学意义。结论:化疗有效组乳腺癌ADC值较化疗前升高,而无效组化疗前后肿瘤ADC值无差异,根据ADC值可以早期预测乳腺癌新辅助化疗疗效。

【Abstract】 Title:The optimized b value of Breast Diffusion Weighted MRIPurpose:To optimize the b value of breast Diffusion-weighted MRI(DW-M RI) at 1.5T by comparing the apparent diffusion coefficient(ADC) of disease-free contralateral breast tissue and benign and malignant lesions and the signal-to-noise ratio(SNR) of images using different b value in the same patient.Materials and Methods:32 women with confirmed malignant(18) and benign (14)lesions were examined using EPI-DWI with different b values at 1.5T MR scanner.DW images were acquired in the transverse plane covering both breasts, TR/TE=8400ms/93.8ms,FOV=30cm;NEX=2,matrix=128×128;slice thickness=4mm,b= 0,50,100,200,400,600,800,1000,1200,1400,1600,1800, 2000,2200,2400,2600 s/mm2 respectively,The ADCs of the phantom and the disease-free contralateral breast tissues and benign and malignant lesions were calculated from the ADC map.SNR was calculated on DW images.The relation between SNR of images and the b value were analyzed.One-way analysis of variance was applied to compare the ADCs of malignant lesions with benign lesions and disease-free contralateral breast tissues.The difference in ADCs was compared between different b value.Results:The SNR of DWI dropped as b value increasing which responsible for the poor image quality,and there was an inverse correlation between SNR and b value.The ADCs of phantom stayed invariable when b value was in the range of 0~1400 s/mm2,while the ADCs of normal breast tissue dropped gradually as b value increasing,which may be explained by the effect of perfusion in breast tissue.Significant difference was observed in ADCs between malignant and benign lesions using the same b value.The difference was magnified when b value was set in the range of 800~1000s/mm2,while it become smaller in the condition of b value>1400 s/mm2.Conclusion:For good image quality and valid differentiation between malignant and benign lesion,the optimized b value of DWI is in the range of 800~1000s/mm2.PartⅡDiffusion-weighted MR Imaging of breast mass and non-mass lesionPurpose:To evaluate Diffusion-weighted MR Imaging of breast mass and non-mass lesion in lesion characterization by comparing ADCs of malignanty with benignancy.Materials and Methods:236 pathology-confirmed breast lesions(155 malignanty,81 benignancy) and 221 disease-free contralateral breast tissues were examined using EPI-DWI(b values=0,1000 s/mm2);TR/TE=8400ms/93.8ms; FOV=30×30cm;matrix=128×128;ASSET=2,slice thickness=4mm.DCE-MR imaging was also performed for accurate location of the lesion using VIBRANT sequence.The mean ADC values of malignant and benign lesions and the disease-flee contralateral breast tissues were calculated from the ADC map for each patient.One-way analysis of variance was applied to compare the mean ADCs of malignant lesions with benign lesions and disease-flee contralateral breast tissues.The threshold ADC value for malignant lesion was determined using a receiver operating characteristic(ROC) curve analysis.Each lesion was classified into two major types:mass and non-mass lesion.The diagnostic performance of DWI was compared in breast mass and non-mass lesions.Results:155 malignant and 81 benign lesions were confirmed in 236 lesions. The mean ADCs of malignant lesions(1.08±0.32×10-3mm2/s) were statistically lower than that of benign lesions(1.48±0.35×10-3mm2/s) and normal tissues (1.95±0.30×10-3mm2/s).The sensitivity and specificity of the ADCs for malignant lesions with a threshold of less than 1.25×10-3mm2/s was 78.2%and 77.5% respectively.105 malignant and 56 benign lesions were included in 161 mass lesions.The mean ADCs of malignant lesions(1.04±0.3×10-3mm2/s) were statistically lower than that of benign lesions(1.47±0.33×10-3mm2/s).The sensitivity and specificity of the ADCs for malignant lesions with a threshold of less than 1.15×10-3mm2/s was 79.8%and 81.8%respectively.50 malignant and 25 benign lesions were included in 75 non-mass lesions.The mean ADCs of malignant lesions(1.18±0.34×10-3mm2/s) were statistically lower than that of benign lesions(1.51±0.4×10-3mm2/s).The sensitivity and specificity of the ADCs for malignant lesions with a threshold of less than 1.35×10-3mm2/s was 78%and 72%respectively.The means ADCs of DCIS is higher than that of IDC.In IDC, the mean ADC value of mass lesion(0.98±0.20×10-3mm2/s) is lower than that of non-mass lesion(1.09±0.25×10-3mm2/s).Conclusion:The ADCs would be an effective parameter in distinguishing between malignant and benign breast lesions.The diagnostic performance of DWI is better for mass lesion compared to non-mass lesions.The cut-off value for ADCs is different between mass and non-mass lesions.The ADCs varied with the histophathologic features.PartⅢDiagnostic strategy of Breast Lesion using combination of dynamic contrast-enhanced and diffusion-weighted imagingPurpose:To evaluate the diagnostic accuracy of a combination of dynamic contrast-enhanced MR imaging(DCE-MRI) and diffusion-weighted MR imaging (DWI) in characterization of breast lesion and to find the strongest discriminators between malignancy and benignancy.Materials and Methods:223 patients with 236 pathology-confirmed breast lesions were examined using EPI-DWI,FSE-T2WI,SE-T1WI,DCE-MR imaging were performed using VIBRANT sequence.The breast MR images were reviewed by two radioligists experienced in breast MR imaging.Based on the American College of Radiology Breaast Imaging Reporting and Date System MR imaging criteria(BI-RADS MRI),each lesion was classified into two major types:mass and non-mass lesion.MR images was analyzed include tumor shape,margin, internal enhancement characteristics,distribution,and time-signal intensity curves (TIC),maximam enhancement ratio,early enhancement ratio and so on.The ADCs of lesions were calculated on ADC maps.Univariate and multivariate analysis of MR imaging data were performed to find the strongest discriminators and the Logestic regression model was established to predict the probabilities for malignancy.The sensitivity,specificity,accuracy,positive predictive value,and negative predictive value were calculated respectively. Results:155 malignant and 81 benign lesions were confirmed in 236 lesions include 159 mass lesions and 75 non-mass lesions.Irregular and spiculated margin,heterogeneous internal enhancement,washout TIC pattern,and the ADC value<1.15×10-3mm2/s and the early enhancement ratio>105%were the strongest indicators of malignancy for mass lesion.Washout TIC pattern and the ADC value<1.35×10-3mm2/s and the early enhancement ratio>75%were the strongest indicators of malignancy for non-mass lesion.The sensitivity,specificity, accuracy,positive predictive value,and negative predictive value for mass lesion were 85.3%,84.6%,91.6%,74.6%and 85.1%respectively.The sensitivity, specificity,accuracy,positive predictive value,and negative predictive value for non-mass lesion were 82%,83.3%,91.1%,69%and 82.4%,respectively.Conclusion:The combination of DCE-MRI and DWI could produce high diagnostic accuracy in distinguishing malignant from benign breast lesions.The diagnostic strategy is different for mass and non-mass lesions.PartⅣEvaluation by diffusion-weighted imaging of tumor response to neoadjuvant chemotherapyPurpose:To evaluate diffusion-weighted imaging(DWI) in assessing tumor response to neoadjuvant chemotherapy.Materials and Methods:36 patients with confirmed malignancy were examined using DWI before and after 1st~8th cycles of neoadjuvant chemotherapy(NACT).Tumors were classified into 2 groups:responder and non-responder according to pathologic evaluations.The changes in ADCs were analyzed between responder and non-responder before and after each cycle of NACT.The contralateral normal breast tissures were also investigated as controls.Results:24 responders and 12 non-responders were included in 36 tumors. No statistical difference was found between the mean ADCs of responder(0.98±0.18×10-3mm2/s) and non-responder(0.95±0.15×10-3mm2/s) before therapy (t=0.694,P=0.411).The ADCs of responders significantly increased after each cycle of NACT.while the ADCs of non-responder and the contralateral disease-free breast tissure stayed invariable after therapy.Conclusion:ADC is more useful for predicting early tumor response to the neoadjuvant chemotherapy.

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