High signal renal tumors on DWI: the diagnostic value of morphological characteristics

Purpose

To assess the usefulness of morphological characteristics of diffusion-weighted imaging (DWI) for differentiating malignant renal tumors from benign renal tumors, and clear cell renal cell carcinoma (RCC) from non-clear cell RCC at 3.0 T.

Methods

The study included 249 patients with 251 histopathologically confirmed renal tumors that showed high signal on DWI. For each tumor, two radiologists independently evaluated apparent diffusion coefficient (ADC) values and morphological characteristics of DWI. The differences in the quantitative and qualitative magnetic resonance imaging (MRI) features determined by the readers were assessed. The ADC values between malignant and benign renal tumors and between clear cell and non-clear cell RCC were compared using Mann–Whitney tests. The proportional differences of morphological characteristics of DWI between malignant and benign renal tumors and between clear cell and non-clear cell RCC were compared using Chi-square tests.

Results

There were no significant differences in the quantitative and qualitative MRI features determined by the readers. The ADC values for malignant renal tumors were statistically significantly higher than those for benign renal tumors (p < 0.05), and the ADC values for clear cell RCC were statistically significantly higher than those for non-clear cell RCC (p < 0.05). The proportion of morphological characteristics of DWI between malignant and benign renal tumors was statistically significantly different at ring, nodular, flaky high signal. The proportion of morphological characteristics of DWI between clear cell and non-clear cell RCC was statistically significantly different at uniform high signal.

Conclusions

The morphological characteristics of DWI are useful in differentiating renal tumors.

     

Role of MR texture analysis in histological subtyping and grading of renal cell carcinoma: a preliminary study

Purpose

The study evaluated the usefulness of magnetic resonance imaging (MRI) texture parameters in differentiating clear cell renal carcinoma (CC-RCC) from non-clear cell carcinoma (NC-RCC) and in the histological grading of CC-RCC.

Materials and methods

After institutional ethical approval, this retrospective study analyzed 33 patients with 34 RCC masses (29 CC-RCC and five NC-RCC; 19 low-grade and 10 high-grade CC-RCC), who underwent MRI between January 2011 and December 2012 on a 1.5-T scanner (Avanto, Siemens, Erlangen, Germany). The MRI protocol included T2-weighted imaging (T2WI), diffusion-weighted imaging [DWI; at b 0, 500 and 1000 s/mm² with apparent diffusion coefficient (ADC) maps] and T1-weighted pre and postcontrast [corticomedullary (CM) and nephrographic (NG) phase] acquisition. MR texture analysis (MRTA) was performed using the TexRAD research software (Feedback Medical Ltd., Cambridge, UK) by a single reader who placed free-hand polygonal region of interest (ROI) on the slice showing the maximum viable tumor. Filtration histogram-based texture analysis was used to generate six first-order statistical parameters [mean intensity, standard deviation (SD), mean of positive pixels (MPP), entropy, skewness and kurtosis] at five spatial scaling factors (SSF) as well as on the unfiltered image. Mann–Whitney test was used to compare the texture parameters of CC-RCC versus NC-RCC, and high-grade versus low-grade CC-RCC. P value < 0.05 was considered significant. A 3-step feature selection was used to obtain the best texture metrics for each MRI sequence and included the receiver-operating characteristic (ROC) curve analysis and Pearson’s correlation test.

Results

The best performing texture parameters in differentiating CC-RCC from NC-RCC for each sequence included (area under the curve in parentheses): entropy at SSF 4 (0.807) on T2WI, SD at SSF 4 (0.814) on DWI b500, SD at SSF 6 (0.879) on DWI b1000, mean at SSF 0 (0.848) on ADC, skewness at SSF 2 (0.854) on T1WI and skewness at SSF 3 (0.908) on CM phase. In differentiating high from low-grade CC-RCC, the best parameters were: entropy at SSF 6 (0.823) on DWI b1000, mean at SSF 3 (0.889) on CM phase and MPP at SSF 5 (0.870) on NG phase.

Conclusion

Several MR texture parameters showed excellent diagnostic performance (AUC > 0.8) in differentiating CC-RCC from NC-RCC, and high-grade from low-grade CC-RCC. MRTA could serve as a useful non-invasive tool for this purpose.

     

DWI结合ADC值鉴别诊断睾丸生殖细胞瘤

目的 探讨DWI结合ADC值鉴别诊断睾丸精原细胞瘤和非精原细胞瘤的价值。方法 回顾性分析经手术及病理证实的22例睾丸生殖细胞瘤患者,其中精原细胞瘤10例,非精原细胞瘤12例。均行MRI平扫、DWI扫描,并测量不同肿瘤实质部分的ADC值,采用独立样本t检验比较精原细胞瘤和非精原细胞瘤ADC值的差异。结果 10例精原细胞瘤的DWI多呈均匀性高信号,平均ADC值为（0.63±0.12）×10^-3 mm²/s,12例非精原细胞瘤的DWI多呈不均匀高信号,平均ADC值为（0.98±0.22）×10^-3 mm²/s,二者的ADC值差异有统计学意义（t=4.61,P<0.01）。结论 DWI结合ADC值有助于鉴别精原细胞瘤与非精原细胞瘤。     

3.0 T磁共振扩散峰度成像联合扩散加权成像评估侵袭性前列腺癌

目的探讨3.0 T磁共振扩散峰度成像联合扩散加权成像在侵袭性前列腺癌诊断中的价值。方法回顾性分析2015年5月~2019年6月我院经前列腺穿刺活检确诊并行磁共振扩散峰度成像和扩散加权成像进行诊断的患者共80例,包括49例侵袭性前列腺癌患者和31例良性前列腺增生患者。依据Gleason评分（GS）将侵袭性前列腺癌患者分为低级别组（GS≤3+3）和中、高级别组（GS≥3+4）;获得DKI表观峰度系数（K_app）和扩散加权成像表观扩散系数（ADC）。比较侵袭性前列腺癌与良性前列腺增生之间K_app和ADC的差异,以及扩散峰度成像和扩散加权成像参数与Gleason评分的相关性,绘制ROC曲线评估二者诊断效能。结果49例侵袭性前列腺癌患者共绘制肿瘤感兴趣区65个,包括低级别26个,中、高级别39个。相比低级别侵袭性前列腺癌和良性前列腺增生,中、高级别侵袭性前列腺癌的ADC值较低,K_app值较高（P<0.01）。诊断侵袭性前列腺癌和对其进行分级时,K_app的曲线下面积均小于ADC（0.947 vs 0.978,P<0.001;0.689 vs 0.894,P=0.008）;二者联合诊断侵袭性前列腺癌和对其进行分级时,曲线下面积大于K_app（0.979 vs 0.947,P=0.013;0.934 vs 0.689,P<0.001）,二者联合诊断和分级的曲线下面积大于ADC,但差异无统计学意义（P>0.05）;二者联合对侵袭性前列腺癌分级的特异性较单独采用K_app要高（0.838 vs 0.730,P=0.035）。结论ADC和K_app参数均可用于诊断和评估侵袭性前列腺癌的侵袭性,扩散峰度成像联合扩散加权成像诊断和评估侵袭性前列腺癌的侵袭性并没有表现出比单独应用扩散加权成像具有更高的诊断效能。      

Juxtatumoral perinephric fat analysis in clear cell renal cell carcinoma

Purpose

The purpose of the study was to evaluate the feasibility of using contrast-enhanced computed tomography (CECT)-based texture analysis (CTTA) metrics to differentiate between juxtatumoral perinephric fat (JPF) surrounding low-grade (ISUP 1–2) versus high-grade (ISUP 3–4) clear cell renal cell carcinoma (ccRCC).

Methods

In this IRB-approved study, we retrospectively queried the surgical database between June 2009 and April 2016 and identified 83 patients with pathologically confirmed ccRCC (low grade: n = 54, mean age = 61.5 years, 18F/35M; high grade n = 30, mean age = 61.7 years, 8F/22M) who also had pre-operative multiphase CT acquisitions. CT images were transferred to a 3D workstation, and nephrographic phase JPF regions were manually segmented. Using an in-house developed Matlab program, a CTTA panel comprising of texture metrics extracted using six different methods, histogram, 2D- and 3D-Gray-level co-occurrence matrix (GLCM) and Gray-level difference matrix (GLDM), and 2D-Fast Fourier Transform (FFT) analyses, was applied to the segmented images to assess JPF textural heterogeneity in low- versus high-grade ccRCC. Univariate analysis and receiver-operator characteristics (ROC) analysis were used to assess interclass differences in texture metrics and their prediction accuracy, respectively.

Results

All methods except GLCM consistently revealed increased heterogeneity in the JPF surrounding high- versus low-grade ccRCC. FFT showed increased complexity index (p < 0.01). Histogram analysis showed increased kurtosis and positive skewness in (p < 0.03), and GLDM analysis showed decreased measure of correlation coefficient (MCC) (p < 0.04). Several of the GLCM metrics showed statistically significant (p < 0.04) textural differences between the two groups, but with no consistent trend. ROC analysis showed that MCC in GLCM analysis had an area under the curve of 0.75.

Conclusions

Our study suggests that CTTA of ccRCC shows statistically significant textural differences in JPF surrounding high- versus low-grade ccRCC.

     

宫颈癌大小和病理分化程度与ADC值的相关性

目的 探讨宫颈癌癌灶大小及病理分化程度与ADC值的关系.方法 收集确诊为宫颈癌的患者53例,均于治疗前接受常规MR及DWI检查,b=1000 s/mm2,记录其病理类型、分化程度.采用后处理工作站的像素分析软件划定ROI,测量肿瘤ADC值和大小,并分析相互间的关系.结果 肿瘤平均ADC值为(1.05±0.17)×10-3mm2/s,与病灶横断面最大径(r=-0.28,P=0.04)及体积(r=-0.40,P＜0.01)均呈负相关;不同分化程度的宫颈癌病灶横断面最大径、体积及ADC值间差异均无统计学意义(P均＞0.05).结论 宫颈癌病灶体积越大,ADC值越趋向于低;而ADC值及体积大小均不能反映肿瘤的分化程度.     

ADC值鉴别诊断脑实质室管膜瘤与胶质母细胞瘤

目的 探讨DWI和ADC值对脑实质室管膜瘤和胶质母细胞瘤的诊断及鉴别诊断价值。方法 收集经术后病理证实的27例脑实质室管膜瘤和34例胶质母细胞瘤患者的影像学资料。对患者行常规MR平扫、增强扫描及DWI检查,并测量肿瘤实质的平均ADC值,并进行统计学分析,采用ROC曲线评价ADC值的诊断价值。结果 15例脑实质室管膜瘤DWI呈高信号,ADC值为(0.90±0.14)×10^-3 mm²/s,32例胶质母细胞瘤DWI呈明显高信号,ADC值为(0.72±0.07)×10^-3mm²/s,低于室管膜瘤,差异有统计学意义(t=6.75,P<0.001)。以ADC值0.79×10^-3mm²/s为阈值诊断脑实质室管膜瘤与胶质母细胞瘤,敏感度为85.2%,特异度为97.1%,准确率为91.8%。结论 DWI及ADC值在脑实质室管膜瘤和胶质母细胞瘤的诊断及鉴别诊断中具有重要参考价值,可提高其诊断正确率。     

肝外胆管癌磁共振扩散加权成像中b值的选择

目的 评价不同b值磁共振扩散加权成像(DWI)对肝外胆管癌的显示能力,确定肝外胆管癌DWI的较佳b值;并探讨表观扩散系数(ADC)值与肝外胆管癌分化程度的关系.方法 对25例肝外胆管癌患者术前行DWI (b=100、300、500、800、1000 s/mm2) 和常规MRI.测量肿瘤的ADC值,计算多b值扩散成像和T2WI图像中的信噪比(SNR)、对比噪声比(CNR)及信号强度比(SIR)等数据;对经手术病理证实的患者进行病理分级,比较不同b值时不同分化程度肿瘤的ADC值,并进行统计学分析.结果 23例肝外胆管癌由DWI检出,DWI诊断肝外胆管癌的敏感度为92.00%.随着b值的升高,肿瘤的SNR和肿瘤与正常肝脏的CNR逐渐下降,而肿瘤的SIR逐渐升高.b值为800 s/mm2时DWI图像肿瘤与正常肝脏的CNR、肿瘤的SIR和SNR均高于T2WI图像,差异有统计学意义(P<0.05).随着b值的增高,肿瘤ADC值逐渐变小.结论 b=800 s/mm2是肝外胆管癌扩散加权成像的较佳b值,可以得到良好显示的肝外胆管癌DWI图像;病灶ADC值随着癌组织分化程度的降低而减小.     

扩散加权联合动态对比增强磁共振成像鉴别诊断腮腺良恶性肿瘤

目的 探讨DWI联合动态对比增强磁共振成像（DCE-MRI）在腮腺良恶性肿瘤鉴别诊断中的价值。方法 收集90例腮腺肿瘤患者共94个病灶,其中良性75个、恶性19个。对所有患者术前均行DWI和DCE-MRI检查,分析各病灶的ADC值和时间-信号强度曲线（TIC）类型。绘制ROC曲线,比较ADC值、TIC及两者联合对腮腺良恶性肿瘤的鉴别诊断效能。结果 恶性肿瘤的ADC值[（1.02±0.25）×10^-3 mm²/s]显著低于良性肿瘤的ADC值[（1.38±0.44）×10^-3 mm²/s;t=5.170,P<0.001]。将表现为A型（流入型）、B型（廓清型）和D型（平坦型）曲线判为良性肿瘤、C型（平台型）曲线判为恶性肿瘤时,诊断腮腺肿瘤良恶性的敏感度为0.62,特异度为0.92;C型曲线患者中,以ADC<1.36×10^-3 mm²/s诊断恶性肿瘤时,敏感度为0.92,特异度为0.95。结论 良恶性腮腺肿瘤间ADC值存在重叠,鉴别诊断时不应单纯依赖DWI;TIC表现为A、B、D型多提示良性肿瘤,C型常提示恶性肿瘤;TIC曲线为C型时,联合ADC值可明显提高对良恶性肿瘤的鉴别诊断效能。     

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs)

Purpose

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features.

Methods

Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared.

Results

Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10–25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50–78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18–0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004).

Conclusion

Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

     

扩散加权成像鉴别诊断鼻咽癌和鼻咽部淋巴瘤

目的 探讨DWI鉴别诊断鼻咽癌（NPC）及鼻咽部淋巴瘤（NPL）的价值。方法 回顾性分析经病理证实的22例NPC和27例NPL的 平扫、增强MRI及DWI图像,对比分析两者的平均ADC值和病灶与未受侵翼外肌ADC值的比值（rADC值）,应用ROC曲线分析以ADC值、rADC值鉴别诊断NPC与NPL的效能。结果 NPC与NPL均于T1WI呈等或稍低信号、T2WI呈稍高信号。NPC于DWI（b=1000 s/mm²）上呈稍高信号、ADC图上呈等低信号,NPL于DWI（b=1000 s/mm²）上呈高信号、ADC图上呈低信号。NPC组ADC值为（842.34±94.66）×10^-6 mm²/s、rADC值为0.74±0.08。NPL组ADC值为（652.15±83.47）×10^-6 mm²/s、rADC值为0.56±0.08。两组病灶ADC值、rADC值的差异均具有统计学意义（P均<0.001）。应用ADC值鉴别NPC与NPL的曲线下面积为0.943,最佳鉴别阈值为736.5×10^-6 mm²/s,敏感度为90.9%,特异度为85.2%;应用rADC值进行鉴别的曲线下面积为0.951,最佳鉴别阈值为634.0×10^-6 mm²/s,敏感度为95.5%,特异度为81.5%。结论 DWI、ADC值及rADC值有助于鉴别诊断NPC与NPL。     

磁共振成像技术的联合应用诊断星形细胞瘤

目的应用磁共振弥散加权成像(DWI)、灌注加权成像(PWI)及波谱成像(MRS),探讨ADC值、rCBV值和各代谢产物比值在术前评价星形细胞瘤组织学分级中的价值.方法共收集了41例经病理证实的星形细胞瘤,进行DWI及MRS成像,增强后行PWI及普通增强扫描.获得DW、PW伪彩图和代谢产物曲线,利用分析软件包Function-Tool计算ADC值、rCBV值和NAA/Cr,Ch/Cr,NAA/Ch值.结果高度恶性星形细胞瘤(21例)ADC值、rCBV值及NAA/Cr,Ch/Cr,NAA/Ch值分别为(1.38±0.37)mm2/s(0.61～2.03 mm2/s)、4.04±1.75(1.98～8.31)、0.68±0.25(0.24～1.23)、4.87±1.89(2.33～7.99)及0.18±0.11(0.06～0.47).低度恶性星形细胞瘤(20例)ADC值、rCBV值及NAA/Cr,Ch/Cr,NAA/Ch值分别为(1.63±0.30)mm2/s(1.08～2.13 mm2/s)、1.64±0.90(0.23～3.58)、0.97±0.42(0.46～2.30)、2.36±1.22(1.14～6.38)及0.45±0.36(0.16～1.71).结论 DWI、PWI及MRS对星形细胞瘤的术前分级具有重要价值.     

弥散加权成像鉴别诊断儿童良恶性肝肿瘤

目的 观察弥散加权成像(DWI)鉴别诊断儿童良恶性肝肿瘤的价值.方法 回顾性分析32例肝肿瘤患儿资料,经病理和影像征象确诊良性(良性组)、恶性(恶性组)各16例,观察并比较2组肿瘤DWI信号特征、最大ADC值(ADCmax)、最小ADC值(ADCmin)和平均ADC值(ADCave);采用受试者工作特征(ROC)曲线分...     

Diffusion Profiling <Emphasis Type="Italic">via</Emphasis> a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas,Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status

Purpose

Presurgical grading, estimation of growth kinetics, and other prognostic factors are becoming increasingly important for selecting the best therapeutic approach for meningioma patients. Diffusion-weighted imaging (DWI) provides microstructural information and reflects tumor biology. A novel DWI approach, histogram profiling of apparent diffusion coefficient (ADC) volumes, provides more distinct information than conventional DWI. Therefore, our study investigated whether ADC histogram profiling distinguishes low-grade from high-grade lesions and reflects Ki-67 expression and progesterone receptor status.

Procedures

Pretreatment ADC volumes of 37 meningioma patients (28 low-grade, 9 high-grade) were used for histogram profiling. WHO grade, Ki-67 expression, and progesterone receptor status were evaluated. Comparative and correlative statistics investigating the association between histogram profiling and neuropathology were performed.

Results

The entire ADC profile (p10, p25, p75, p90, mean, median) was significantly lower in high-grade versus low-grade meningiomas. The lower percentiles, mean, and modus showed significant correlations with Ki-67 expression. Skewness and entropy of the ADC volumes were significantly associated with progesterone receptor status and Ki-67 expression. ROC analysis revealed entropy to be the most accurate parameter distinguishing low-grade from high-grade meningiomas.

Conclusions

ADC histogram profiling provides a distinct set of parameters, which help differentiate low-grade versus high-grade meningiomas. Also, histogram metrics correlate significantly with histological surrogates of the respective proliferative potential. More specifically, entropy revealed to be the most promising imaging biomarker for presurgical grading. Both, entropy and skewness were significantly associated with progesterone receptor status and Ki-67 expression and therefore should be investigated further as predictors for prognostically relevant tumor biological features. Since absolute ADC values vary between MRI scanners of different vendors and field strengths, their use is more limited in the presurgical setting.

     

读出方向分段采样DWI鉴别舌良恶性病变

目的 探讨读出方向分段采样（RESOLVE）DWI对舌良恶性病变的鉴别诊断价值。方法 回顾性分析经临床及病理证实的120例舌部病变患者的资料,患者术前均接受常规MR检查及RESOLVE DWI。测量病变的ADC值,比较舌良恶性病变间ADC值的差异,应用ROC曲线评价ADC值的诊断舌良恶性病变的价值。结果 120例舌部病变均单发,其中良性病变56例,恶性病变64例。良性病变ADC值为（1.81±0.45）×10^-3 mm²/s,恶性病变为（1.02±0.24）×10^-3 mm²/s,二者差异有统计学意义（t''=12.21,P<0.001）。以ADC值诊断舌部良恶性病变的ROC曲线AUC为0.976（P<0.001）,以ADC值=1.25×10^-3 mm²/s为临界值,诊断舌良恶性病变的敏感度为94.64%（53/56）,特异度为93.75%（60/64）。结论 RESOLVE DWI鉴别诊断舌良恶性病变具有一定参考价值。     

DWI和最小ADC值鉴别诊断儿童颅内间变性室管膜瘤与室管膜瘤

目的 探讨DWI和最小ADC值鉴别诊断儿童颅内间变性室管膜瘤与室管膜瘤的价值。方法 回顾性分析22例经手术及病理证实的儿童颅内间变性室管膜瘤及室管膜瘤的MRI资料,其中室管膜瘤8例、间变性室管膜瘤14例,所有患儿术前均接受MR平扫、增强和DWI检查。测量肿瘤实质部分的最小ADC值,比较两者之间的差异,并以ROC曲线分析其诊断效能。结果 间变性室管膜瘤最小ADC值为（0.579±0.245）×10^-3 mm²/s,室管膜瘤最小ADC值为（0.943±0.128）×10^-3 mm²/s,差异有统计学意义（t=3.881,P=0.001）。ROC曲线结果显示,AUC为0.884（P=0.003）,以最小ADC值=0.695×10^-3 mm²/s为临界值,鉴别诊断2种肿瘤的敏感度为100%,特异度为71.4%。结论 最小ADC值在儿童颅内间变性室管膜瘤与室管膜瘤的鉴别诊断中具有较高临床应用价值,可作为常规MR检查的有效补充。     

扩散加权成像诊断鼻咽癌放疗后颅底斜坡复发

目的 探讨DWI诊断鼻咽癌颅底斜坡复发瘤价值。方法 收集经病理活检或随访证实的22例鼻咽癌放疗后颅底斜坡复发瘤患者和48例无复发患者,分析其常规MRI以及DWI特征,比较二者ADC值的差异,绘制ROC曲线,确定ADC诊断鼻咽癌颅底斜坡复发瘤的阈值。结果 MR平扫示复发与无复发患者的病灶均呈稍长T1稍长T2信号,增强后呈无强化至明显强化。复发患者中,77.27%（17/22）病灶DWI呈高信号,18.18%（4/22）呈等信号,其中21例（21/22,95.45%）病灶ADC图像均呈低或稍低信号;1例（1/22,4.55%）病灶DWI呈等信号、ADC图像呈稍高信号。无复发患者中,91.67%（44/48）病灶DWI呈高信号、ADC图像呈等或稍高信号,8.33%（4/48）病灶DWI呈等或稍低信号,ADC图像呈等或稍低信号。复发患者与无复发患者病灶ADC值差异有统计学意义[（0.78±0.17）]×10^-3mm²/s vs（1.67±0.34）×10^-3mm²/s, P=0.002）。以1.018×10^-3mm²/s为ADS诊断复发瘤阈值,其诊断敏感度和特异度分别为95.45%（21、22）和91.67%（44、48）,ROC曲线下面积为0.984。结论 DWI诊断鼻咽癌颅底斜坡复发瘤效能较高,具有重要临床应用价值。     

弥散加权成像b值及表观扩散系数预测膀胱癌侵袭性

目的 探讨磁共振弥散加权成像（DWI）b值和表观扩散系数（ADC）评估膀胱癌侵袭性的价值。方法 回顾性分析经病理证实的58例膀胱癌患者（64个病灶）,均接受常规MRI和DWI,梯度扩散因子b值分别取0、600、1 000和1 500 s/mm²,根据膀胱癌病理表型将其分为低、中、高侵袭性。测量不同b值下的肿瘤ADC值,分析膀胱癌侵袭性与ADC值的相关性;通过ROC曲线评价ADC值在膀胱癌侵袭性上的诊断效能。结果 高侵袭性组膀胱癌平均直径（3.37±1.58）cm,显著大于低侵袭性组[（2.18±0.51）cm]和中侵袭性组[（2.32±0.53）cm,P均<0.01）;ADC值与膀胱癌侵袭性呈负相关（r=-0.673,P<0.05）;b值取1 500 s/mm²时可清晰显示病灶,图像对比度较高;ADC值对于直径<2.5 cm肿瘤的诊断特异度及准确度更好;ROC曲线显示ADC值0.93×10^-3 mm²/s是判断膀胱癌侵袭性的最佳阈值。结论 DWI及ADC可用于预测膀胱癌侵袭性,尤其是小直径膀胱癌,并为后期治疗提供临床指导。     

扩散峰度成像在胶质瘤分级和预测细胞增殖中的诊断效能

目的 探讨MR扩散峰度成像（DKI）在胶质瘤分级的价值,及其与Ki-67标记指数的相关性。方法 收集经手术病理证实的脑胶质瘤患者32例,根据病理结果分为高级别胶质瘤组（HGG组,n=18）和低级别胶质瘤组（LGG组,n=14）,术前行常规MR、DWI及DKI扫描,测定肿瘤实质区的平均扩散峰度（MK）、轴向扩散峰度（Ka）、径向扩散峰度（Kr）、平均扩散系数（MD）、部分各向异性（FA）和ADC值,比较高低级别胶质瘤各参数值的差异和诊断效能、肿瘤区各参数与Ki-67标记指数的相关性。结果 高低级别胶质瘤各参数值差异均有统计学意义（P均<0.01）。HGG组的MK、Ka、Kr、FA值高于LGG组,而MD、ADC值低于LGG组。MK在鉴别高低级别胶质瘤的ROC曲线下面积最大（0.82,P<0.01）,特异度最高（90.40%）;ADC值敏感度最高（80.20%）。MK、Ka、Kr、MD和ADC值与Ki-67标记指数均有相关性,MK值与Ki-67标记指数相关性最大（r_s=0.61,P<0.01）。结论 DKI参数对鉴别高低级别胶质瘤有一定的价值,其诊断效能总体高于传统扩散参数。DKI参数值对预测肿瘤细胞增殖有潜在价值。     

磁共振扩散加权成像鉴别诊断鼻腔、鼻窦实性肿块的适宜b值

目的 探讨MR DWI鉴别诊断鼻腔、鼻窦实性肿块的适宜b值。方法 对61例鼻腔、鼻窦肿块患者术前行常规MR及DWI扫描,选取b值为500、1000 s/mm²,测量病变实性部位ROI的ADC值,将结果与组织病理学结果对照。比较良恶性病变ADC值的差异。分别在两种b值下以鼻腔、鼻窦良恶性肿块的ADC值作为临界点绘制ROC曲线,计算曲线下面积（Az）,确定诊断阈值,评价诊断效能并进行比较。结果 b=500 s/mm²时,21例恶性肿块和40例良性肿块的平均ADC值为（1.07±0.32）×10^-3 mm²/s、（1.90±0.62）×10^-3 mm²/s（P<0.001）,Az为0.929,以ADC值=1.31×10^-3 mm²/s作为预测鼻腔、鼻窦良恶性病变的诊断阈值,其敏感度为85.7%,特异度为95.0%,准确率为91.8%。b=1000 s/mm²时,21例恶性肿块和40例良性肿块的平均ADC值分别为（0.86±0.25）×10^-3 mm²/s、（1.55±0.41）×10^-3 mm²/s（P<0.001）,Az为0.963,以ADC值=1.10×10^-3 mm²/s作为预测鼻腔鼻窦良恶性病变的诊断阈值,其敏感度为85.7%,特异度为97.5%,准确率为93.4%。两组b值的Az间差异无统计学意义（P>0.05）。b=500 s/mm²时的图像信噪比明显高于b=1000 s/mm²的信噪比。结论 b=500 s/mm²时在保证更好图像质量的同时具有较好的诊断效能,更适宜鼻腔、鼻窦肿块的鉴别诊断。