Classification of Breast Tumors Using Elastographic and B-mode Features: Comparison of Automatic Selection of Representative Slice and Physician-Selected Slice of Images

Inter-observer variability and image quality are two key factors that can affect the diagnostic performance of elastography and B-mode ultrasound for breast tumor characterization. The purpose of this study is to use an image quantification method that automatically chooses a representative slice and then segments the tumor contour to evaluate the diagnostic features for tumor characterization. First, the representative slice is selected based on either the stiffness inside the tumor (the signal-to-noise ratio on the elastogram [SNR_e]) or the contrast between the tumor and the surrounding normal tissue (the contrast-to-noise ratio on the elastogram [CNR_e]). Next, the level set method is used to segment the tumor contour. Finally, the B-mode and elastographic features related to the segmented tumor are extracted for tumor characterization. The performance of the representative slice selected using the proposed methods is compared to that of the physician-selected slice in 151 biopsy-proven lesions (89 benign and 62 malignant). The diagnostic accuracies using elastographic features are 82.1% (124/151) for the slice with the maximum CNR_e value, 82.1% (124/151) for the slice with the maximum SNR_e value and 82.8% (125/151) for the physician-selected slice, whereas the diagnostic accuracies using B-mode features are 80.8% (122/151) for the slice with the maximum CNR_e value, 87.4% (132/151) for the slice with the maximum SNR_e value and 84.1% (127/151) for the physician-selected slice. When using both the B-mode and elastographic features to characterize the tumor, the accuracy of diagnosis is 86.1% (130/151) for the slice with the maximum CNR_e value, 90.1% (136/151) for the slice with the maximum SNR_e value and 89.4% (135/151) for the physician-selected slice. Our results show that the representative slice selected by SNR_e and CNR_e could be used to reduce the observer variability and to increase the diagnostic performance by the B-mode and elastographic features.     

Performance Optimization in Elastography: Multicompression with Temporal Stretching

A general theoretical framework known as the strain filter has been previously used to evaluate the performance in elastography. The strain filter describes the relationship among the resolution, dynamic range, sensitivity and elastographic SNR (SNR_e), and may be plotted as a graph of the upper bound of the SNR_evs. the strain experienced by the tissue, for a desired elastographic axial resolution as determined by the data window length. The ideal strain filter has an infinitely high, flat all-pass characteristic shape in thestrain domain, which means that all local tissue strains are displayed in the elastogram with infinite SNR_e; it also means that the strain dynamic range in the elastogram is infinite as well. Practical strain filters obtained using a single tissue compression have abandpasscharacteristic shape in the strain domain, where the −3 dB width of this bandpass characteristic may be defined as the elastographic dynamic range. In this paper, we present an optimal technique for stretching multicompression elastography, practiced by selecting the optimum incremental applied strain using the strain filter. Two techniques, temporal stretching and multicompression elastography, are combined in this paper to improve elastogram quality. Stretching multicompression elastography using the optimal applied strain increment alters the shape of the strain filter from its bandpass characteristic to a more desirable high-emphasis filter. The dynamic range of optimal stretching multicompression elastography is limited only by tissue nonlinearities. This optimal applied strain increment minimizes signal decorrelation and achieves the maximum achievable elastographic SNR_e.     

基于敏感性编码及压缩感知技术优化颅脑MR三维相位对比静脉造影成像序列

目的 对比以不同加速因子（acceleration factors，AF）敏感性编码（SENSE）与压缩感知（CS）及SENSE组合（CS-SENSE）技术所获颅脑三维相位对比MR静脉造影（3D PC-MRV）图像质量，以优化序列。方法 前瞻性对26名健康志愿者以AF分别为6和9的SENSE技术，以及AF分别为9、12、15及18的CS-SENSE技术采集颅脑3D PC-MRV，并依次记为MRV_SENSE6、MRV_SENSE9、MRV_CS9、MRV_CS12、MRV_CS15和MRV_CS18。比较上矢状窦（SSS）和左（L）、右（R）侧乙状窦（SiS）在各组3D PC-MRV软组织图中，以及SSS和左（L）、右（R）侧横窦（TRS）的信噪比（SNR）和对比度噪声比（CNR）在各组3D PC-MRV幅度图中的差异；对比整体图像质量及静脉窦和脑静脉结构可视化主观评分。结果 3D PC-MRV软组织图中，除CNR_R-SiS外，MRV_SENSE6的SNR_SSS、CNR_SSS、SNR_R-SiS及SNR_L-SiS均高于MRV_SENSE9（P均<0.05），MRV_CS9、MRV_CS12及MRV_CS15图像各参数均高于MRV_SENSE9（P均<0.05）而与MRV_SENSE6差异均无统计学意义（P均>0.05），MRV_CS18的SNR_R-SiS和SNR_L-SiS均低于MRV_SENSE6，CNR_L-SiS高于MRV_SENSE9，SNR_SSS、SNR_R-SiS及SNR_L-SiS低于MRV_CS9及MRV_CS12，SNR_R-SiS低于MRV_CS15（P均<0.05），其余参数差异均无统计学意义（P均>0.05）；3D PC-MRV幅度图中，MRV_SENSE6各参数均高于MRV_SENSE9，MRV_CS9及MRV_CS12均高于MRV_SENSE6，MRV_CS9、MRV_CS12、MRV_CS15及MRV_CS18均高于MRV_SENSE9，MRV_CS15及MRV_CS18均低于MRV_CS9，MRV_CS18低于MRV_CS12（P均<0.05），其余各参数差异均无统计学意义（P均>0.05）；对图像质量的主观评分结果与上述客观评价结果相似。结论 相比SENSE，基于CS-SENSE的3D PC-MRV可在更短时间内获得质量更优的颅脑静脉图像；AF取12为优化序列。     

声弹性成像在乳腺肿块鉴别诊断中的应用

目的探讨声弹性成像在乳腺良恶性肿块鉴别中的应用价值。方法应用常规超声和声弹性成像对52例患者共65个肿块进行检查,以病理诊断为标准。结果常规超声诊断乳腺癌的灵敏度为62.5%（10/16）,特异度为71.4%（35/49）,准确率为69.2%（45/65）;声弹性成像诊断乳腺癌的灵敏度为75.0%（12/16）,特异度为93.9%（46/49）,准确率为89.2%（58/65）。声弹性成像诊断符合率显著高于常规超声诊断（P〈0.01）。结论声弹性成像在乳腺良恶性肿块鉴别中具有重要的临床应用价值。     

‘Image-navigated 3-dimensional late gadolinium enhancement cardiovascular magnetic resonance imaging: feasibility and initial clinical results’

Background

Image-navigated 3-dimensional late gadolinium enhancement (iNAV-3D LGE) is an advanced imaging technique that allows for direct respiratory motion correction of the heart. Its feasibility in a routine clinical setting has not been validated.

Methods

Twenty-three consecutive patients referred for cardiovascular magnetic resonance (CMR) examination including late gadolinium enhancement (LGE) imaging were prospectively enrolled. Image-navigated free-breathing 3-dimensional (3D) T1-weighted gradient-echo LGE and two-dimensional (2D LGE) images were acquired in random order on a 1.5 T CMR system. Images were assessed for global, segmental LGE detection and transmural extent. Objective image quality including signal-to-noise (SNR), contrast-to-noise (CNR) and myocardial/blood sharpness were performed.

Results

Interpretable images were obtained in all 2D–LGE and in 22/23 iNAV-3D LGE exams, resulting in a total of 22 datasets and 352 segments. LGE was detected in 5 patients with ischemic pattern, in 7 with non-ischemic pattern, while it was absent in 10 cases. There was an excellent agreement between 2D and 3D data sets with regard to global, segmental LGE detection and transmurality. Blood-myocardium sharpness measurements were also comparable between the two techniques. SNR_blood and CNR_blood-myo was significantly higher for 2D LGE (P?<?0.001, respectively), while SNR_myo was not statistically significant between 2D LGE and iNAV-3D LGE.

Conclusion

Diagnostic performance of iNAV-3D LGE was comparable to 2D LGE in a prospective clinical setting. SNR_blood and CNR_blood-myo was significantly lower in the iNAV-3D LGE group.

     

Feasibility of 3D black-blood variable refocusing angle fast spin echo cardiovascular magnetic resonance for visualization of the whole heart and great vessels in congenital heart disease

Background

Volumetric black-blood cardiovascular magnetic resonance (CMR) has been hampered by long scan times and flow sensitivity. The purpose of this study was to assess the feasibility of black-blood, electrocardiogram (ECG)-triggered and respiratory-navigated 3D fast spin echo (3D FSE) for the visualization of the whole heart and great vessels.

Methods

The implemented 3D FSE technique used slice-selective excitation and non-selective refocusing pulses with variable flip angles to achieve constant echo signal for tissue with T1 (880?ms) and T2 (40?ms) similar to the vessel wall. Ten healthy subjects and 21 patients with congenital heart disease (CHD) underwent 3D FSE and conventional 3D balanced steady-state free precession (bSSFP). The sequences were compared in terms of ability to perform segmental assessment, local signal-to-noise ratio (SNR_l) and local contrast-to-noise ratio (CNR_l).

Results

In both healthy subjects and patients with CHD, 3D FSE showed superior pulmonary vein but inferior coronary artery origin visualisation compared to 3D bSFFP. However, in patients with CHD the combination of 3D bSSFP and 3D FSE whole-heart imaging improves the success rate of cardiac morphological diagnosis to 100% compared to either technique in isolation (3D FSE, 23.8% success rate, 3D bSSFP, 5% success rate). In the healthy subjects SNR_l for 3D bSSFP was greater than for 3D FSE (30.1?±?7.3 vs 20.9?±?5.3; P?=?0.002) whereas the CNR_l was comparable (17.3?±?5.6 vs 17.4?±?4.9; P?=?0.91) between the two scans.

Conclusions

The feasibility of 3D FSE for whole-heart black-blood CMR imaging has been demonstrated. Due to their high success rate for segmental assessment, the combination of 3D bSSFP and 3D FSE may be an attractive alternative to gadolinium contrast enhanced morphological CMR in patients with CHD.

     

Role of Shear Wave Sonoelastography in Differentiation Between Focal Breast Lesions

Our goal in this study was to evaluate the relevance of shear wave sonoelastography (SWE) in the differential diagnosis of masses in the breast with respect to ultrasound (US). US and SWE were performed (Aixplorer System, SuperSonic Imagine, Aix en Provence, France) in 76 women (aged 24 to 85) with 84 lesions (43 malignant, 41 benign). The study included BI-RADS-US (Breast Imaging Reporting and Data System for Ultrsound) category 3–5 lesions. In elastograms, the following values were calculated: mean elasticity in lesions (E_av.l) and in fat tissue (E_av.f.) and maximal (E_max.adj.) and mean (E_av.adj.) elasticity in lesions and adjacent tissues. The sensitivity and specificity of the BI-RADS category 4a/4b cutoff value were 97.7% and 90.2%. For an E_av.adj. of 68.5 kPa, the cutoff sensitivity was 86.1% and the specificity was 87.8%, and for an E_max.adj. of 124.1 kPa, 74.4% and 92.7%, respectively. For BI-RADS-US category 3 lesions, E_av.l, E_max.adj. and E_av.adj. were below cutoff levels. On the basis of our findings, E_av.adj. had lower sensitivity and specificity compared with US. E_max.adj. improved the specificity of breast US with loss of sensitivity.     

实时剪切波弹性成像技术鉴别诊断肺良恶性周围型肿块

目的 探讨实时剪切波弹性成像（SWE）技术鉴别诊断肺部良恶性周围型肿块的价值。方法 采用SWE技术测量112例周围型肺部肿块患者的杨氏模量值,分析良恶性组及恶性病变不同病理类型亚组间的杨氏模量最大值（E_max）和平均值（E_mean）的差异。以病理结果为金标准,绘制ROC曲线获得其鉴别诊断良恶性肿块的效能。结果 周围型肺部肿块良恶性组间E_max及E_mean差异均有统计学意义（t=－2.78、－3.28,P均<0.01）,恶性组不同病理类型亚组间E_max及E_mean差异均无统计学意义（P均>0.05）。E_max和E_mean鉴别诊断肺良恶性肿块的阈值分别为10.35 kPa和5.85 kPa,AUC分别为0.74（P=0.003）、0.81（P=0.001）,敏感度、特异度、阳性预测值、阴性预测值分别为74.36%、72.22%、85.29%、57.52%和81.58%、80.78%、89.57%和67.67%。结论 SWE技术可用于评估周围型肺部肿块的弹性特征,为鉴别肺部良恶性周围型肿块提供了重要的影像学手段。     

Evaluation of Tissue Stiffness Around Lesions by Sound Touch Shear Wave Elastography in Breast Malignancy Diagnosis

The aim of the study described here was to assess the evaluation of tissue stiffness around lesions by sound touch shear wave elastography (STE) in breast malignancy diagnosis. This was an institutional ethics committee–approved, single-center study. A total of 90 women with breast masses examined with conventional ultrasound and STE were eligible for enrollment from December 2020 to July 2021. The maximum and mean elastic values of masses, E_max and E_mean, were determined. Shell function was used to measure the maximum and mean elastic values of tissues around masses in annular shells 0.5, 1.0, 1.5 and 2.0 mm wide, recorded as corresponding E_max-shell and E_mean-shell. All parameters were analyzed and compared with histopathologic results. Receiver operating characteristic curves were constructed to assess diagnostic performance. Logistic regression analysis was conducted to determine the best diagnostic model. Collagen fiber content of tissues around breast lesions was evaluated using Masson staining and ImageJ software. Ninety women with breast masses were included in this study; 50 had benign (mean diameter 15.84 ± 4.39 mm) and 40 had malignant (mean diameter 17.40 ± 5.42 mm) masses. The diagnostic value of E_{max-shell-2.0} was the highest (area under the curve = 0.930) with a sensitivity of 87.5% and specificity of 88%. According to stepwise logistic regression analysis, E_{max-shell-2.0} and age were independent predictors of malignancy. E_{max-shell-2.0} was also found to be highly correlated with the collagen fiber content of tissue in the malignant group (r = 0.877). Tissue stiffness around lesions measured by STE is a useful metric in identifying malignant breast masses by reflecting collagen fiber content, and E_{max-shell-2.0} performs best.     

Quantitative Elastography of Rectal Lesions: The Value ofShear Wave Elastography in Identifying Benign and Malignant Rectal Lesions

We evaluate the value of shear wave elastography (SWE) in diagnosing benign and malignant rectal lesions. A total of 96 lesions were reviewed in this study; endorectal ultrasound (ERUS) and SWE examinations were performed before surgery in all cases. Elasticity parameters including mean elastographic index (E_mean), maximum elastographic index (E_max) and minimum elastographic index (E_min) were analyzed. Correlations between elastographic parameters and histopathological results were studied. Inter-observer and intra-observer agreement was analyzed. Of the 96 rectal lesions, 72 were malignant and 24 were benign. Compared with ERUS, ERUS?+?SWE had higher sensitivity (93.0% vs. 88.9%), specificity (83.3% vs. 79.2%), positive predictive value (94.4% vs. 92.7%), negative predictive value (80.0% vs. 70.4%) and overall accuracy (90.6% vs. 86.4%). In receiver operating characteristic curve analysis, E_mean and E_max had larger areas under the curve: 0.92 and 0.91, respectively. The optimal cutoff value was 61.3 kPa for E_mean (sensitivity?=?88.9%, specificity?=?87.5%) and 63.4 kPa for E_max (sensitivity?=?94.4%, specificity?=?83.3%). We obtained κ values of 0.83 (95% confidence interval [CI]: 0.72–0.95) for ERUS and 0.90 (95% CI: 0.81–0.99) for ERUS?+?SWE of differential diagnosis in two observers. The intra-class correlation coefficients for intra-observer variability of stiffness (E_mean) in malignant lesions, benign lesions, surrounding normal rectal wall in malignant lesions and surrounding normal rectal wall in benign lesions were 0.91 (95% CI: 0.86–0.94), 0.94 (95% CI: 0.88–0.97), 0.92 (95% CI: 0.88–0.95) and 0.89 (95% CI: 0.77–0.95), respectively. SWE is a promising tool that yields valuable quantitative data additional to that provided by ERUS examination in rectal lesions. The cutoff value 61.3 kPa for E_mean may serve as a complementary tool in diagnosis of rectal lesions.     

Computer-Aided Diagnosis Based on Quantitative Elastographic Features with Supersonic Shear Wave Imaging

Supersonic shear wave imaging (SSI) has recently been explored as a technique to evaluate tissue elasticity modulus and has become a valuable tool for tumor characterization. The purpose of this study was to develop a novel computer-aided diagnosis (CAD) system that can acquire quantitative elastographic information from color SSI elastography images automatically and objectively for the purpose of classifying benign and malignant breast tumors. Conventional ultrasonography (US) and SSI elastography images of 125 breast tumors (81 benign, 44 malignant), in 93 consecutive patients (mean age: 40 y, age range: 16–75 y), were obtained. After reconstruction of tissue elasticity data and automatic segmentation of each breast tumor, 10 quantitative elastographic features of the tumor and peri-tumoral areas, respectively (elasticity modulus mean, maximum and standard deviation, hardness degree and elasticity ratio), were computed and evaluated. A support vector machine (SVM) classifier was used for optimum classification via combination of these features. The B-mode Breast Imaging Reporting and Data System (BI-RADS) was used to compare gray-scale US and SSI elastography with respect to diagnostic performance. Histopathologic examination was used as the reference standard. Student's t-test, the Mann-Whitney U-test, the point biserial correlation coefficient and receiver operating characteristic curve analysis were performed for statistical analysis. As a result, the accuracy, sensitivity, specificity, positive predictive value and negative predictive value of benign/malignant classification were 95.2% (119/125), 90.9% (40/44), 97.5% (79/81), 95.2% (40/42) and 95.2% (79/83) for the CAD scheme, respectively, and 79.2% (99/125), 90.9% (40/44), 72.8% (59/81), 64.5% (40/62) and 93.7% (59/63) for BI-RADS assessment, respectively. The area under the receiver operating characteristic curve (A_z value) for the proposed CAD system using the combination of elastographic features was significantly higher than the A_z value for visual assessment by the radiologists using BI-RADS (0.97 vs. 0.91). The results indicate that SSI elastography could be used for computer-aided feature extraction, and the proposed CAD method could improve the diagnostic accuracy of classification of breast tumors to avoid unnecessary biopsy. Furthermore, elastographic features of the peri-tumoral area have the potential to provide critical information in differential diagnosis.     

Analysis of Elastographic and B-mode Features at Sonoelastography for Breast Tumor Classification

The purpose of this study was to evaluate the accuracy of neural network analysis of elastographic features at sonoelastography for the classification of biopsy-proved benign and malignant breast tumors. Sonoelastography of 181 solid breast masses (113 benign and 68 malignant tumors) was performed for 181 patients (mean age, 47 years; range, 24–75 years). After the manual segmentation of the tumors, five elastographic features (strain difference, strain ratio, mean, median and mode) and six B-mode features (orientation, undulation, angularity, average gradient, gradient variance and intensity variance) were computed. A neural network was used to classify tumors by the use of these features. The Student's t test and receiver operating characteristic (ROC) curve analysis were used for statistical analysis. Area under ROC curve (Az) values of the three elastographic features– mean (0.87), median (0.86) and mode (0.83)–were significantly higher than the Az values for the six B-mode features (0.54–0.69) (p < 0.01). Accuracy, sensitivity, specificity and Az of the neural network for the classification of solid breast tumors were 86.2% (156/181), 83.8% (57/68), 87.6% (99/113) and 0.84 for the elastographic features, respectively, and 82.3% (149/181), 70.6% (48/68), 89.4% (101/113) and 0.78 for the B-mode features, respectively, and 90.6% (164/181), 95.6% (65/68), 87.6% (99/113) and 0.92 for the combination of the elastographic and B-mode features, respectively. We conclude that sonoelastographic images and neural network analysis of features has the potential to increase the accuracy of the use of ultrasound for the classification of benign and malignant breast tumors. (E-mail: rfchang@csie.ntu.edu.tw)     

Sonoelastographic Strain Index for Differentiation of Benign and Malignant Nonpalpable Breast Masses

Objective. The purpose of this study was to evaluate the diagnostic potential of the sonoelastographic strain index for differentiation of nonpalpable breast masses. Methods. Ninety‐nine nonpalpable breast masses (79 benign and 20 malignant) in 94 women (mean age, 45 years; range, 21–68 years) who had been scheduled for a sonographically guided core biopsy were examined with B‐mode sonography and sonoelastography. Radiologists who had performed the biopsies analyzed the B‐mode sonograms and provided American College of Radiology Breast Imaging Reporting and Data System categories. The strain index (fat to lesion strain ratio) was calculated by dividing the strain value of the subcutaneous fat by that of the mass. The histologic result from the sonographically guided core biopsy was used as a reference standard. The diagnostic performance of the strain index and that of B‐mode sonography were compared by receiver operating characteristic (ROC) curve analysis. Results. The mean strain index values ± SD were 6.57 ± 6.62 (range, 1.29–28.69) in malignant masses and 2.63 ± 4.57 (range, 0.54–38.76) in benign masses (P = .019). The area under the ROC curve values were 0.835 (95% confidence interval [CI], 0.747–0.902) for B‐mode sonography and 0.879 (95% CI, 0.798–0.936) for the strain index (P = .490). The sensitivity, specificity, positive predictive value, and negative predictive value were 95% (19 of 20), 75% (59 of 79), 48% (19 of 39), and 98% (59 of 60), respectively, when a best cutoff point of 2.24 was used. Conclusions. The strain index based on the fat to lesion strain ratio has diagnostic performance comparable with that of B‐mode sonography for differentiation of benign and malignant breast masses.     

不同阈值勾画18F-FDG PET/CT心脏肿瘤ROI鉴别其良恶性

目的 评价采用不同阈值勾画¹⁸F-FDG PET/CT图像中病灶ROI鉴别心脏良恶性肿瘤的价值。方法 纳入64例心脏肿瘤患者（65个病灶）,根据病理学或长期随访结果分为良性组（n=27）和恶性组（n=38）。采用3种阈值（Th 2.5、Th 40%和Th bgd）勾画心脏肿物,测量并比较病灶¹⁸F-FDG PET/CT代谢和形态学参数,包括最大标准摄取值（SUV_max）、平均标准摄取值（SUV_mean）、代谢肿瘤体积（MTV）、病灶糖酵解总量（TLG）、最大CT （CT_max）值、平均CT （CT_mean）值及CT值中位数（CT_median）。以多因素Logistic回归分析良、恶性组差异具有统计学意义的参数,绘制受试者工作特征（ROC）曲线,计算曲线下面积（AUC）,评价3种阈值诊断心脏良恶性肿瘤的效能。结果 采用3种阈值勾画ROI得到的肿瘤SUV_max一致,其鉴别诊断心脏良恶性肿瘤的AUC均为0.92;良、恶性肿瘤之间SUV_mean、MTV及TLG差异均具有统计学意义（P均<0.05）。根据SUV_mean诊断良、恶性肿瘤时,以阈值Th 40%的诊断效能最佳;以MTV及TLG诊断时,阈值Th 2.5均具最佳效能。多因素Logistic回归结果显示Th 40%与Th bgd诊断效能均较好,且Th bgd的敏感度及准确率均高于Th 40%。结论 根据PET代谢参数可鉴别心脏良恶性肿瘤。SUV_max截断值为6.75时,鉴别心脏良恶性肿瘤具有较好效能;采用多参数评价时,3种阈值中,以Th bgd效能最优。     

Endoscopic ultrasound elastography: the first step towards virtual biopsy? Preliminary results in 49 patients

BACKGROUND AND STUDY AIMS: It is well known that some diseases, such as cancer, lead to changes in the hardness of tissue. Sonoelastography, a technique that allows the elasticity of tissue to be assessed during ultrasound examination, provides the ultrasonographer with important additional information that can be used for diagnosis. The aim of this study was to evaluate the ability of endoscopic ultrasound elastography to differentiate between benign and malignant pancreatic masses and lymph nodes. PATIENTS AND METHODS: During a 12-month period, 49 patients underwent endoscopic ultrasound (EUS) examinations with elastography, conducted by a single endoscopist. Twenty-four patients underwent evaluation of a pancreatic mass (mean diameter 24.7 +/- 11.1 mm) and 25 underwent evaluation of 31 lymph nodes. The mean diameter of the lymph nodes was 19.7 +/- 8.6 mm, and they were found in the cervical area (n = 3), mediastinum (n = 17), celiac arterial trunk region (n = 5), and aortocaval region (n = 6). RESULTS: The sonoelastography images of pancreatic masses were interpreted as benign in four cases and malignant in 20. The sensitivity and specificity of sonoelastography in the diagnosis of malignant lesions were 100% and 67%, respectively. The sonoelastography images of the lymph nodes were interpreted as showing malignancy in 22 cases, benign conditions in seven, and indeterminate status in two. The sensitivity and specificity of sonoelastography for evaluating malignant lymph-node invasion were 100% and 50%, respectively. CONCLUSIONS: EUS elastography is potentially capable of further defining the tissue characteristics of benign and malignant lesions but specifity has to be improved. It can be used to guide biopsy sampling for diagnosis.     

CT灌注成像在孤立性肺结节中的应用

目的探讨CT灌注成像对孤立性肺结节(SPN)的诊断与鉴别诊断价值.方法对34例SPN先行薄层平扫,再行同层动态增强扫描.在动态增强时间-密度曲线基础上,测量病灶增强的最大比值(PHSPN/PTSPN)、强化峰值(PHSPN)及达到最大峰值所需的时间(PTSPN),并测量与病灶同层的主动脉峰值(PHAA).根据以上测得数据,计算SPN增强峰值与主动脉增强峰值比(PHSPN/PHAA),SPN灌注量(ml·min-1·ml-1)=SPN增强最大比值(Hu·min-1)/动脉增强的峰值(Hu).结果恶性SPN和多血性良性SPN较少血性良性SPN有更高的强化峰值PHSPN和PHSPN/PHAA.而恶性SPN与多血性良性SPN的PHSPN和PHSPN/PHAA无显著差异.多血性良性SPN增强前密度明显低于恶性SPN.恶性SPN与多血性良性SPN的灌注量明显高于少血性良性SPN.结论CT灌注成像能反映病灶的血供信息,为孤立性肺结节性质的鉴别诊断提供证据.     

Diagnostic Performance of Ultrasound Shear Wave Elastography in Solid Small (≤4 cm) Renal Parenchymal Masses

The aim of the study was to analyze the diagnostic performance of shear wave elastography (SWE) in differentiating between malignant and benign solid renal parenchymal masses ≤4 cm, compared with conventional ultrasound. A total of 20 healthy volunteers and 117 patients had been included in this study. Conventional ultrasound and SWE were performed in all volunteers and patients. The elasticity of healthy cortex and the elastic parameters of tumors such as mean elasticity (E_mean), minimum elasticity (E_min), maximum elasticity (E_max), standard deviation and elasticity ratio of the lesion to surrounding cortex (E_ratio) were measured on SWE images. Diagnostic performance of SWE was compared with that of conventional ultrasound. The cortical elasticity values of healthy right and left kidneys were 4.7 ± 1.7 and 4.5 ± 1.5 kPa, respectively. Of the 117 renal tumors, 68 were renal cell carcinomas (RCCs) and 49 were benign. E_mean, E_min and E_ratio were significantly lower in RCCs compared with benign lesions: E_mean 7.2 ± 2.5 kPa versus 10.0 ± 2.4 kPa, E_min 2.5 ± 2.4 kPa versus 5.6 ± 2.3 kPa, E_ratio 1.6 ± 0.5 versus 2.2 ± 0.6 (all p values < 0.001). The cutoff values of 9.15 kPa for E_mean, 3.55 kPa for E_min and 1.99 for E_ratio had the highest areas under the receiver operating characteristics curve (0.801 for E_mean, 0.832 for E_min and 0.806 for E_ratio). Combining E_mean, E_min and E_ratio with conventional ultrasound improved the specificity for predicting RCCs to 87.8%, but the sensitivity was not increased.     

Contrast material injection protocol with the flow rate adjusted to the heart rate for dual source CT coronary angiography

To investigate the effect on coronary arterial attenuations of contrast material flow rate adjusted to a patient’s heart rate during dual source CT coronary angiography (DSCT-CCTA). A total of 296 consecutive patients (mean age: 58.7 years) undergoing DSCT-CCTA without previous coronary stent placement, bypass surgery, congenital or valvular heart disease were included. The image acquisition protocol was standardized (120 kV, 380 mAs) and retrospective electrocardiograph (ECG) gating was used. Patients were randomly assigned to one of three groups [flow rate: G1: dosage/16, G2: dosage/(scan time +8), G3: fixed flow rate]. The groups were compared with respect to the attenuations of the ascending aorta (AA) above coronary ostia, the left main coronary artery (LM), the proximal right coronary artery (RCA), the left anterior descending artery (LAD), the left circumflex artery (LCX), and the contrast to noise ratio of the LM (LM_CNR) and the proximal RCA (RCA_CNR). Correlations between heart rate and attenuation of the coronary arteries were evaluated in three groups with linear regression. There was no significant difference in the three groups among the mean attenuations of AA (P = 0.141), LM (P = 0.068), RCA (P = 0.284), LM_CNR (P = 0.598) and RCA_CNR (P = 0.546). The attenuations of the LAD and the LCX in group 1 were slightly higher than those in group 2 and 3 (P < 0.05). In group 1, the attenuations of the AA (P < 0.01), LM (P < 0.01), RCA (P < 0.01), LAD (P = 0.02) and LCX (P < 0.01) decreased, respectively, with an increasing heart rate. A similar finding was detected in group 3 (AA: P < 0.01, LM: P < 0.01, RCA: P < 0.01, LAD: P < 0.01and LCX: P < 0.01). In contrast, the attenuations of the AA (P = 0.55), LM (P = 0.27), RCA (P = 0.77), LAD (P = 0.22) and LCX (P = 0.74) had no significant correlation with heart rate in group 2. In all three groups, LM_CNR (P = 0.77, 0.69 and 0.73 respectively) and RCA_CNR (P = 0.75, 0.39 and 0.61 respectively) had no significant correlation with heart rate. Contrast material flow rate adjusted to heart rate can diminish the influence of heart rate on attenuations of the coronary arteries in DSCT-CCTA.     

剪切波弹性成像鉴别乳腺影像报告和数据系统(BI-RADS)4类乳腺肿块

目的探讨剪切波弹性成像(SWE)鉴别乳腺影像报告和数据系统(BI-RADS)4类乳腺肿块的价值。方法回顾性分析经术后病理证实的96个BI-RADS 4类乳腺肿块,比较良性(良性组,n=43)及恶性肿块(恶性组,n=53)剪切波参数,包括弹性最大值(SWE max)、最小值(SWE min)和平均值(SWE mean);以受试者工作特征(ROC)曲线确定SWE max、SWE min及SWE mean的截断值,比较其ROC曲线下面积(AUC)、敏感度、特异度和准确率,评价并比较SWE对BI-RADS 4a、4b及4c亚分类的诊断准确率。结果良性组SWE max和SWE mean均低于恶性组(P均<0.01),组间SWE min差异无统计学意义(P>0.05);SWE max、SWE mean的AUC分别为0.86、0.83,均高于SWE min的AUC(0.59,P均<0.01);SWE max诊断敏感度、特异度和准确率分别为96.23%、81.40%和89.58%,SWE mean分别为94.34%、76.74%和86.46%,均明显高于SWE min的34.00%、37.21%和35.42%(P均<0.01);SWE max和SWE mean的AUC及其诊断BI-RADS 4类乳腺良恶性肿块的敏感度、特异度、准确率差异均无统计学意义(P均>0.05)。SWE max和SWE mean对BI-RADS 4a、4b及4c乳腺肿块的诊断准确率明显高于SWE min(P<0.05)。结论BI-RADS 4类乳腺恶性肿块的SWE max和SWE mean均高于良性肿块。高频超声SWE可有效鉴别BI-RADS 4类乳腺良恶性肿块,SWE max和SWE mean的诊断效能优于SWE min。