体素内不相干运动联合扩散峰度成像模型对乳腺良恶性病灶的鉴别诊断价值

目的:探讨体素内不相干运动(IVIM)技术联合扩散峰度成像(DKI)对乳腺良恶性病变的鉴别诊断价值.方法:137例女性患者(共153个病灶)行双侧乳腺多b值DWI检查(b=0～2000 s/mm2);分别使用IVIM、DKI模型获得病灶的真性扩散系数(D)、灌注相关扩散系数(D*)、灌注分数(f)以及平均扩散峰度系数(MK)、平均扩散系数(MD)和ADC值.分析这些参数在乳腺良恶性病变中的变化规律,采用受试者工作特性曲线(ROC)评估各参数的诊断效能.结果:良恶性病灶的D、f、MK、ADC和MD值的中位数差异有统计学意义(P值分别为0.000、0.020、0.000、0.000和0.000),良恶性病灶D*值的差异无统计学意义(P=0.480).D值与和MK、ADC和MD值在鉴别乳腺良恶性病变中的可靠性相当,两两比较差异无统计学意义(P值均大于0.1).当MK值及D、ADC和MD值的阈值分别取0.8073及0.9536×10-3、1.1436×10-3和1.5657×10 3mm2/s时,鉴别良恶性病灶的敏感度和特异度依次分别为(95.7％,84.2％)及(95.7％,81.6％)、(96.5％,84.2％)和(93.9％,84.2％).ROC曲线分析得出D值的诊断效能最大(AUC=0.91).联合D值和MK值的AUC这0.92.结论:采用1VIM和DKI模型获得的相关参数有助于乳腺良恶性病灶的鉴别,以IVIM模型中的真性扩散系数的诊断敏感性和特异性较高,联合真性扩散系数和扩散峰度系数的诊断效能最高.     

DKI与DWI在乳腺良恶性病变诊断价值的对照研究

目的评估磁共振弥散峰度成像(DKI)与弥散加权成像(DWI)对乳腺良恶性病变诊断价值及效能差异。方法对31例乳腺占位性病变的女性患者行乳腺常规磁共振扫描(T_1WI,T_2WI)、动态增强扫描及DWI和DKI扫描,所有病变均经手术或穿刺病理证实。总共37个病灶,其中良性病变9个,恶性病变28个。分析病变大小、形态、边界等基本情况以及测定表观弥散系数(ADC)、平均峰度(MK)及平均弥散系数(MD)值。采用ROC曲线评估ADC、MK及MD鉴别良恶性病变的价值及差异。结果恶性病变多表现为形态不规则、边界不清晰;恶性病变多为平台型强化;良性病变的MK低于恶性病变;良性病变的MD、ADC均高于恶性病变,具有显著的统计学意义(P0.01)。ROC曲线显示MK的曲线下面积(AUC)、敏感度及特异度均为最高,分别为0.91,0.93及0.89。结论 DKI比传统DWI在乳腺良恶性病变方面有更高的诊断效能。     

区分良性和恶性孤立性肺部实性病灶:体素内不相干运动成像和扩散峰度成像是否优于传统的扩散加权成像

正摘要目的定量比较单指数和双指数扩散加权成像(DWI)和扩散峰度成像(DKI)在鉴别良性和恶性孤立性肺部病灶(SPL)中各种扩散参数的诊断价值。方法采用3 T MRI     

鉴别良恶性肾肿瘤：IVIM和扩散峰度成像是否优于DWI?

正目的定量比较常规扩散加权成像(DWI)、体素内不相干运动(IVIM)和扩散峰度成像(DKI)在鉴别良恶性肾肿瘤中的诊断价值。方法共180例肾肿瘤病人进行多b值     

MR扩散加权成像对卵巢病变定性诊断的研究

目的 探讨扩散加权像(DWI)对卵巢病变的鉴别诊断价值.资料与方法 73例81个病理证实的卵巢病变术前行常规MRI和DWI.比较不同性质病变囊性部分及实性部分间表观扩散系数(ADC)值及指数表观扩散系数(eADC)值差异.结果 良、恶性卵巢肿瘤间囊性部分ADC值和eADC值的鉴别诊断阈值分别为2.755×10-3 mm2/s和6.455×10-2,而实性部分ADC值和eADC值的最佳阈值分别为1.195×10-3 mm2/s和29.55×10-2.结论 DWI ADC值和eADC值有助于卵巢良、恶性肿瘤的鉴别诊断.     

磁共振扩散峰度成像在乳腺良恶性病变鉴别诊断中的价值

【摘要】目的：探讨磁共振扩散峰度成像（DKI）在乳腺良恶性病变鉴别诊断中的价值。方法：回顾性分析经穿刺活检或手术病理证实的45例乳腺病变患者的病例资料。45例患者共53个病灶,其中良性病灶31个（23例）,恶性病灶22个（22例）,所有患者均行双侧乳腺的常规MRI检查及DKI扫描,通过后处理工作站获得乳腺良、恶性病变组织的平均峰度（MK）、轴向峰度（AK）、径向峰度（RK）值。采用Mann-Whitney U秩和检验比较MK、AK及RK值在乳腺良、恶性病变中的统计学差异。采用受试者操作特性（ROC）曲线评价上述参数对乳腺良、恶性病变的诊断效能。结果：乳腺恶性病变的MK、AK及RK值均明显高于良性病变,且差异均具有统计学意义（P均<0.001）。MK、AK、RK的ROC曲线下面积(AUC)分别是0.886、0.930、0.881;良恶性诊断界值分别为0.45900、0.7250、0.3430;敏感度分别为95.6%、86.4%、90.9%;特异度分别为64.5 %、87.1%、66.7%。结论：DKI获得的MK、AK、RK在乳腺良恶性病变的鉴别诊断中具有一定的价值。     

MRI动态增强扫描联合扩散峰度成像对乳腺良恶性病变的鉴别诊断价值

目的:探讨MRI动态增强扫描(DCE-MRI)联合扩散峰度成像(DKI)对乳腺良恶性病变的鉴别诊断价值。方法 :收集因乳腺病变行MRI检查的患者45例共50个病灶,其中良性病灶21个(良性组),恶性病灶29个(恶性组)。按DCE-MRI、DCE-MRI联合DKI 2种方法对乳腺病变进行分类,比较各组间DKI参数平均扩散系数(MD)值、平均扩散峰度(MK)值及2种分类方法的诊断效能。结果:恶性组MK值(0.90±0.19)×10~(-3)mm~2/s高于良性组(0.54±0.13)×10~(-3)mm~2/s与对照组(0.48±0.13)×10~(-3)mm~2/s,恶性组MD值(1.41±0.32)×10~(-3)mm~2/s低于良性组(1.98±0.38)×10~(-3)mm~2/s与对照组(2.25±0.26)×10~(-3)mm~2/s。以1.61×10~(-3)mm~2/s、0.73×10~(-3)mm~2/s作为MD、MK值的临界值时,可鉴别诊断乳腺良恶性病变。DCE-MRI鉴别诊断乳腺良恶性病变的敏感度、特异度、阳性预测值、阴性预测值、准确率分别为93.0%、71.4%、81.8%、88.2%、84.0%,DCE-MRI联合DKI为93.0%、85.7%、90.0%、90.0%、90.0%。2种方法的AUC分别为0.86、0.92。结论:DKI有助于乳腺病变的诊断,联合DCE-MRI可提高对乳腺病变的诊断效能。     

卵巢良恶性病变的磁共振扩散加权成像分析及应用

目的 探讨卵巢良、恶性病变磁共振扩散加权成像(DWI)的特征.方法 回顾分析117个经手术病理证实的卵巢良、恶性病灶的影像资料,测量b值＝50、400、800 s/mm2 时良、恶性病变软组织成分的信号强度, 比较对比噪声比(CNR)和ADC值,分析不同囊性成分常规图像、DWI特征及ADC值均值.结果 显示病变最佳b值＝800 s/mm2.恶性病变软组织成分b值＝800 s/mm2对比噪声比(CNR)高于良性病变,ADC值低于良性病变.ADC值可以预测但不能确定囊性成分性质.结论 结合常规MRI,DWI有助于卵巢良、恶性小病灶显示及鉴别诊断.     

3.0T MRI评价原发性卵巢肿块:MRI和DWI对其分类的价值

目的:探讨3T MRI对原发性卵巢肿块的鉴别诊断价值。方法:95个经组织病理学证实的原发性卵巢肿块均行MRI检查,比较良恶性病灶的基本特征、成份以及其在常规MRI和DWI图像的信号特点。结果:本组资料包括18例单纯性卵巢囊肿,22例子宫内膜异位囊肿,26例良性和29例恶性卵巢肿瘤。多数良性肿瘤表现为实性(6/26)和囊性伴有间隔(7/26)。恶性肿瘤(13/29)多表现为囊性伴有实性结节。患者的年龄和肿块的最大径在良、恶性卵巢肿瘤间无统计学显著差异(P=0.339,P=0.082)。在卵巢良性病变和恶性病变间,病灶的传统MRI和DWI信号特点无显著差异(P=0.244,P=0.073),但ADC值在两者间具有统计学显著差异(P=0.000)。结论:3T MRI可以很好地区分原发性附件肿块的信号特点。传统MRI和DWI信号特点无助于鉴别肿块的良、恶性,但ADC值有助于鉴别肿块的良恶性。     

乳腺病变的扩散峰度模型研究

目的研究扩散加权成像(DWI)和扩散峰度成像(DKI)在乳腺疾病鉴别诊断中的价值。方法对36例女性病人行乳腺MR多b值DWI(50~3 000 s/mm2)。根据病变类型     

DKI对动态增强时间-信号曲线呈平台型乳腺纤维腺瘤及乳腺癌的诊断价值

目的探讨扩散峰度成像(DKI)对动态增强时间-信号曲线呈平台型的乳腺纤维腺瘤和乳腺癌的鉴别诊断价值。方法选取DCE-TIC为平台型的20例(20个病灶)乳腺纤维腺瘤患者和61例(64个病灶)乳腺癌患者。测得病变的平均扩散峰度系数(MK)和平均扩散系数(MD)以及ADC值,观察病变形态和强化特征。以病理结果为金标准,采用X²检验比较两类病变间形状、边缘、背景实质强化、内部强化特征、早期强化率的差异;采用两独立样本t检验比较DKI、DWI参数的差异,绘制ROC比较其诊断效能。结果DCE-TIC呈平台型的乳腺纤维腺瘤及乳腺癌,形状、边缘、内部强化特征以及早期强化率差异均有统计学意义(P<0.05),背景实质强化差异无统计学意义(P>0.05);MK、MD、ADC值的差异均有统计学意义(P<0.05),联合MK、MD和ADC,ROC下面积为0.991,敏感度、特异度和准确度分别达0.922、1.000和0.922。结论DKI对DCE-TIC呈平台型乳腺纤维腺瘤及乳腺癌具有良好的鉴别诊断意义,将DKI和DWI联合应用可获得更高的诊断效能。     

同时多层采集技术在乳腺MR高清扩散峰度成像中的可行性研究

目的:探讨同时多层采集技术在乳腺高清扩散峰度成像(RESOLVE DKI)中的应用价值.方法:回顾性分析行乳腺MRI检查并经病理学证实的46例女性患者(48个病变,其中恶性病变41个,良性病变7个)的临床及影像资料,分别采集常规RESOLVE DKI和采用同时多层采集技术RE-SOLVE DKI序列(SMS RESOL...     

扩散峰度成像与扩散加权成像在诊断宫颈鳞癌分级中的价值

目的对比分析扩散峰度成像(DKI)与扩散加权成像(DWI)诊断宫颈鳞癌分级的价值。方法回顾性纳入经术后病理证实的宫颈鳞癌病人42例,年龄39~69岁,平均(54.9±7.9)岁。以病理结果为金标准,分为高中分化组(27例)和低分化组(15例),分别测量2组肿瘤实质区平均扩散峰度(MK)值、平均扩散系数(MD)值及平均表观扩散系数(ADC)值、最小ADC值,采用独立样本t检验比较2组间各参数值的差异,采用受试者操作特征(ROC)曲线评价各参数值的诊断效能及最佳诊断阈值,并根据约登指数确定各参数相应的敏感度和特异度。结果2名观察者测得各参数的一致性均良好(均ICC>0.60,P<0.05)。低分化组的MK值高于高中分化组,而MD、平均ADC、最小ADC值均低于高中分化组(均P<0.05)。采用单一参数鉴别低分化与高中分化宫颈鳞癌时,MK为0.88时,AUC最大(0.877)、敏感度(92.6%)最高;MD为1.04×10^-3mm^2/s时,特异度(86.7%)最高。联合MK、MD和最小ADC值诊断时,AUC最大(0.937),敏感度最高(96.3%)。结论与传统DWI相比,DKI可更有效地鉴别低分化与高中分化宫颈鳞癌,联合应用DKI和DWI参数可有效提高诊断效能。     

MR diffusion kurtosis imaging predicts malignant potential and the histological type of meningioma

PurposeTo explore the value of Diffusion kurtosis imaging (DKI) metrics in the differential diagnosis of meningioma.MethodsFor this study, we retrospectively enrolled 35 patients of cerebral meningioma with DKI which included axial diffusion coefficient (AD), radial diffusion coefficient (RD), mean diffusion coefficient (MD), fractional anisotropy (FA), axial kurtosis (AK), radial kurtosis (RK) and mean kurtosis (MK). All of these metrics were normalized according to contralateral normal-appearing white matter (NAWMc). Patients were divided into two groups (benign and malignant meningioma) and were further analyzed using the independent sample t-test and receiver operating characteristic (ROC) curve. A one-way ANOVA analysis was used to analyze four groups divided according to pathological subtypes.ResultsThe metrics of AD, normalized AD, normalized MD, MK and normalized MK showed a significant difference between benign and malignant group, and MK showed relatively higher diagnostic ability with its cut-off value, area under the curve (AUC), sensitivity and specificity of 0.875, 0.780, 70% and 89%, respectively. The metrics of normalized MD, RD and normalized RD, FA and normalized FA, AK and normalized AK, and RK showed significant difference among four subtypes. MK and RK in meningioma were found to correlate positively with the Ki-67 labeling index (Ki-67 LI).ConclusionsDKI metrics may be used to differentiate benign from malignant meningioma, and also to distinguish some histological subtypes of meningioma. Moreover, DKI metrics may potentially reflect cellular proliferation.     

Application of the diffusion kurtosis model for the study of breast lesions

Objectives

To evaluate diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) in the differentiation and characterisation of breast lesions.

Methods

Thirty-six women underwent breast magnetic resonance imaging (MRI) including a DWI sequence with multiple b-values (50–3,000 s/mm²). Mean values for apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated by lesion type and histological subtype. Differences and correlation between parameters were determined.

Results

Forty-four lesions were found. There were significant differences between benign and malignant lesions for all parameters (ADC, p?=?0.017; MD, p?=?0.028; MK, p?=?0.017). ADC and MD were higher for benign (1.96?±?0.41?×?10^?3 and 2.17?±?0.42?×?10^?3 mm²/s, respectively) than for malignant lesions (1.33?±?0.18?×?10^?3 and 1.52?±?0.50?×?10^?3 mm²/s). MK was higher for malignant (0.61?±?0.27) than benign lesions (0.37?±?0.18). We found differences between invasive ductal carcinoma (IDC) and fibroadenoma (FA) for all parameters (ADC, MD and MK): p?=?0.016, 0.022 and 0.016, respectively. FA and fibrocystic change (FC) showed differences only in MK (p?=?0.016).

Conclusions

Diffusion in breast lesions follows a non-Gaussian distribution. MK enables differentiation and characterisation of breast lesions, providing new insights into microstructural complexity. To confirm these results, further investigation in a broader sample should be performed.

Key Points

? The diffusion kurtosis model provides new information regarding breast lesions ? MD and MK are valid parameters to characterise tissue microstructure ? MK enables improved lesion differentiation ? MK is able to differentiate lesions that display similar ADC values     

扩散峰度成像对上皮性卵巢癌分型的鉴别诊断

目的 探讨扩散峰度成像（DKI）对Ⅰ型与Ⅱ型上皮性卵巢癌（EOC）的鉴别诊断价值。 方法 回顾性收集经手术病理证实的45例EOC病人的临床、病理及影像资料,平均年龄（50±13）岁。根据术后病理结果对EOC病人进行分组,分为Ⅰ型组（24例）和Ⅱ型组（21例）。所有病人均于术前行盆腔DKI检查,由2名放射科医师在DKI各参数伪彩图上分别测量平均扩散峰度（MK）、平行扩散峰度（Ka）、垂直扩散峰度（Kr）、平均扩散系数（MD）、平行扩散系数（Da）、垂直扩散系数（Dr）、各向异性分数（FA）、峰度各向异性分数（FAk）。采用Fisher确切概率检验、独立样本t检验或Mann-Whitney U检验比较2组间临床、病理及影像资料的差异,对差异有统计学意义的参数绘制受试者操作特征（ROC）曲线,分析其鉴别诊断效能。 结果 病理表现上,Ⅰ型中交界性肿瘤占比最高（50.0%）,Ⅱ型中浆液性癌占比最高（61.9%）;Ⅰ型中高分化癌占50%,Ⅱ型多表现为中低分化癌 （76.2%）,Ⅰ型EOC的分化程度高于Ⅱ型;Ⅰ型多数处于Ⅰ期（79.2%）,Ⅱ型多处于Ⅲ期(57.1%)（均P<0.05）。MRI影像上, Ⅰ型病灶多表现为囊性(41.7%)或囊实性（33.3%）,Ⅱ型多表现为实性（52.3%）;Ⅱ型（66.7%）腹水发生率高于Ⅰ型（29.2%）（均P<0.05）。Ⅰ型的MK、Ka和Kr值低于Ⅱ型,MD、Da和Dr值高于Ⅱ型（均P<0.05）。ROC曲线分析显示,MK阈值为0.504时,鉴别2组诊断的曲线下面积（AUC,0.817）最大,诊断敏感度（95.2%）、阴性预测值（92.9%）、准确度（78.9%）也最高,Da阈值为2.190时鉴别诊断的AUC（0.770）最小,而特异度（76.2%）、阳性预测值（75.9%）最高。 结论 DKI序列的定量参数MK、Ka、Kr、MD、Da及Dr均有助于鉴别Ⅰ型与Ⅱ型EOC,其中MK值鉴别诊断效能更大。     

Diffusion-weighted echo-planar MR imaging and ADC mapping in the differential diagnosis of ovarian cystic masses: usefulness of detecting keratinoid substances in mature cystic teratomas

PURPOSE: To elucidate whether apparent diffusion coefficient (ADC) values calculated from echo-planar diffusion-weighted MR imaging (EPDWI) are useful in the differential diagnosis of ovarian cystic masses. MATERIALS AND METHODS: EPDWI was performed in 131 patients with ovarian cystic masses (54 mature cystic teratomas, 35 endometrial cysts, four other benign cysts, 14 benign neoplasms, and 24 malignant neoplasms). The areas of the highest signal intensity on EPDWI (b = 1000 seconds/mm(2)) and the lowest ADC values within the cystic component were evaluated. RESULTS: On qualitative and quantitative analyses, mature cystic teratomas tended to show higher signal intensity and had areas of lower ADC values than endometrial cysts and other benign and malignant neoplasms (P < .005). In vitro scanning of the cystic contents of mature cystic teratomas confirmed that high signal on DWI or low ADC value was attributable to the keratinoid substance within the tumors. The difference in ADC between malignant and benign lesions were significant when mature cystic teratomas and endometrial cysts were included, but was not significant when they were excluded. CONCLUSION: The ADC value may add useful information to the differential diagnosis of ovarian cystic masses in limited populations, such as those with mature cystic teratomas with a small amount of fat.     

Diagnostic accuracy of diffusion-weighted imaging in differentiating benign from malignant ovarian lesions

Purpose

To clarify the diagnostic accuracy of diffusion‐weighted imaging (DWI) in differentiating benign from malignant ovarian lesions.

Materials and Methods

We retrospectively analyzed magnetic resonance images of 123 ovarian lesions in 119 patients. We defined lesions with abnormal signal intensity as malignancy and assessed the location of abnormal intensity within the lesions on DWI. We also assessed the mean and lowest apparent diffusion coefficient (ADC) values of the solid portion for each ovarian lesion.

Results

The majority of malignant ovarian tumors and mature cystic teratomas, and almost half of the endometriomas, showed abnormal signal intensity on DWI, whereas most fibromas and other benign lesions did not. The main locations of abnormal signal intensity were solid portions in malignant ovarian tumors, cystic components suggestive of keratinoid substances and Rokitansky protuberance in mature cystic teratomas, and intracystic clots in endometriomas. On DW imaging, receiver‐operating characteristic analysis yielded mean Az values of 0.703. There was no significant difference in mean and lowest ADC values between malignant and benign lesions.

Conclusion

DWI of ovarian lesions and ADC values of the solid component are not useful for differentiating benign from malignant ovarian lesions. This knowledge is essential in avoiding misinterpretation in the diagnosis of ovarian lesions. J. Magn. Reson. Imaging 2008;28:1149–1156. © 2008 Wiley‐Liss, Inc.     

IVIM成像与DWI在乳腺良恶性病变鉴别诊断中的比较

目的 比较体素内不相干运动(IVIM)成像双指数模型、拉伸指数模型与扩散加权成像(DWI)单指数模型各参数在乳腺良恶性病变鉴别诊断中的价值.方法 回顾性分析257例经病理证实的乳腺病变患者(共276个病灶,包括197个恶性病变,79个良性病变).所有患者均行MRI常规检查及多b值DWI检查,获得传统DWI及IVIM各参数.比较各参数在正常乳腺组织、乳腺良性病变及恶性病变中的统计学差异,采用受试者工作特征(ROC)曲线确定各参数诊断乳腺恶性病变的阈值以及曲线下面积(AUC)、诊断敏感性和特异性.结果 正常乳腺组织、乳腺良性病变及恶性病变的表观扩散系数(ADC)、慢速表观扩散系数(slow ADC)、快速表观扩散系数(fast ADC)、灌注分数(f)、扩散分布指数(DDC)及扩散异质性指数(α)值均有统计学差异(P<0.001).ADC、slow ADC、f、DDC和α的AUC分别为0.865、0.861、0.742、0.85和0.735;ADC、slow ADC、DDC和α的最佳诊断阈值分别为1.105×10-3 mm2/s,0.883×10-3 mm2/s,1.025×10-3 mm2/s和0.842,slow ADC敏感性最高(90.3%),DDC特异性最高(79.5%).双指数模型中slow ADC与fast ADC联合诊断的AUC为0.882;拉伸指数模型DDC与α联合诊断的AUC为0.853.结论 3种模型对于乳腺病变良恶性的鉴别都具有较高的价值,传统ADC的诊断准确性较高,slow ADC敏感性较高,DDC特异性较高.双指数模型中slow ADC与fast ADC联合诊断具有较高的价值.     

Role of diffusion-weighted imaging in the differential diagnosis of benign and malignant lesions of the chest-mediastinum

Purpose

We retrospectively evaluated the role of diffusion-weighted imaging (DWI) with fat and background signal suppression in the differential diagnosis of benign and malignant lesions of the chest-mediastinum by calculating the mean apparent diffusion coefficient (ADC) values.

Materials and methods

Thirty-four patients with lung nodules/mediastinal masses underwent magnetic resonance (MR) imaging of the chest with conventional and DWI sequences. All patients had been previously studied with computed tomography (CT). After magnetic resonance (MR) imaging the patients underwent transthoracic CT-guided biopsy or mediastinoscopy. After the histopathological diagnosis had been obtained, the lesions were retrospectively divided into five groups: adenocarcinomas (n=16), squamous cell carcinomas (n=12), chronic pneumonias (n=2), malignant mediastinal tumours (n=2) and typical carcinoids (n=2). We compared ADC values in the different lesion groups using the Mann-Whitney U test.

Results

There were statistically significant differences (p<0.05) between ADC values of benign and malignant lesions. Using an ADC value of 1.25×10^?3 mm²/s as a threshold, we were able to differentiate malignant from benign lesions with 91% diagnostic accuracy, 90% sensitivity, 100% specificity, 100% positive predictive value and 57% negative predictive value.

Conclusions

Short-tau inversion-recovery echo-planar imaging (STIR-EPI) sequences applied to the chest-mediastinum provided potentially useful images for the differential diagnosis of benign and malignant lesions.