Relationship of temporal resolution to diagnostic performance for dynamic contrast enhanced MRI of the breast

Purpose:

To investigate the relationship between temporal resolution of dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) and classification of breast lesions as benign versus malignant.

Materials and Methods:

Patients underwent T₁‐weighted DCE MRI with 15 s/acquisition temporal resolution using 1.5 Tesla (n = 48) and 3.0T (n = 33) MRI scanners. Seventy‐nine patients had pathologically proven diagnosis and 2 had 2 years follow‐up showing no change in lesion size. The temporal resolution of DCE MRI was systematically reduced as a postprocessing step from 15 to 30, 45, and 60 s/acquisition by eliminating intermediate time points. Average wash‐in and wash‐out slopes, wash‐out percentage changes, and kinetic curve shape (persistently enhancing, plateau, or wash‐out) were compared for each temporal resolution. Logistic regression and receiver operating characteristic (ROC) curve analysis were used to compare kinetic parameters and diagnostic accuracy.

Results:

Sixty patients (74%) had malignant lesions and 21 patients (26%) had benign lesions. All temporal‐resolution parameters significantly predicted benign versus malignant diagnosis (P < 0.05). However, 45 s/acquisition and higher temporal‐resolution datasets showed higher accuracy than the 60 s/acquisition dataset by ROC curve analysis (0.72 versus 0.69 for average wash‐in slope; 0.85 versus 0.82, for average wash‐out slope; and 0.88 versus 0.80 for kinetic curve shape assessment, for 45 s/acquisition versus 60 s/acquisition temporal‐resolution datasets, respectively (P = 0.027).

Conclusion:

DCE MRI data with at least 45‐s temporal resolution maximized the agreement between the kinetic parameters and correct classification of benign versus malignant diagnosis. J. Magn. Reson. Imaging 2009;30:999–1004. © 2009 Wiley‐Liss, Inc.     

Differentiation of malignant and benign breast lesions using magnetization transfer imaging and dynamic contrast‐enhanced MRI

Purpose:

To evaluate feasibility of using magnetization transfer ratio (MTR) in conjunction with dynamic contrast‐enhanced MRI (DCE‐MRI) for differentiation of benign and malignant breast lesions at 3 Tesla.

Materials and Methods:

This prospective study was IRB and HIPAA compliant. DCE‐MRI scans followed by MT imaging were performed on 41 patients. Regions of interest (ROIs) were drawn on co‐registered MTR and DCE postcontrast images for breast structures, including benign lesions (BL) and malignant lesions (ML). Initial enhancement ratio (IER) and delayed enhancement ratio (DER) were calculated, as were normalized MTR, DER, and IER (NMTR, NDER, NIER) values. Diagnostic accuracy analysis was performed.

Results:

Mean MTR in ML was lower than in BL (P < 0.05); mean DER and mean IER in ML were significantly higher than in BL (P < 0.01, P < 0.001). NMTR, NDER, and NIER were significantly lower in ML versus BL (P < 0.007, P < 0.001, P < 0.001). IER had highest diagnostic accuracy (77.6%), sensitivity (86.2%), and area under the ROC curve (.879). MTR specificity was 100%. Logistic regression modeling with NMTR and NIER yielded best results for BL versus ML (sensitivity 93.1%, specificity 80%, AUC 0.884, accuracy 83.7%).

Conclusion:

Isolated quantitative DCE analysis may increase specificity of breast MR for differentiating BL and ML. DCE‐MRI with NMTR may produce a robust means of evaluating breast lesions. J. Magn. Reson. Imaging 2013;37:138–145. © 2012 Wiley Periodicals, Inc.     

Principal component analysis of breast DCE‐MRI adjusted with a model‐based method

Purpose:

To investigate a fast, objective, and standardized method for analyzing breast dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) applying principal component analysis (PCA) adjusted with a model‐based method.

Materials and Methods:

3D gradient‐echo DCE breast images of 31 malignant and 38 benign lesions, recorded on a 1.5T scanner, were retrospectively analyzed by PCA and by the model‐based three‐timepoints (3TP) method.

Results:

Intensity‐scaled (IS) and enhancement‐scaled (ES) datasets were reduced by PCA yielding a first IS‐eigenvector that captured the signal variation between fat and fibroglandular tissue; two IS‐eigenvectors and the two first ES‐eigenvectors captured contrast‐enhanced changes, whereas the remaining eigenvectors captured predominantly noise changes. Rotation of the two contrast‐related eigenvectors led to a high congruence between the projection coefficients and the 3TP parameters. The ES‐eigenvectors and the rotation angle were highly reproducible across malignant lesions, enabling calculation of a general rotated eigenvector base. Receiver operating characteristic (ROC) curve analysis of the projection coefficients of the two eigenvectors indicated high sensitivity of the first rotated eigenvector to detect lesions (area under the curve [AUC] > 0.97) and of the second rotated eigenvector to differentiate malignancy from benignancy (AUC = 0.87).

Conclusion:

PCA adjusted with a model‐based method provided a fast and objective computer‐aided diagnostic tool for breast DCE‐MRI. J. Magn. Reson. Imaging 2009;30:989–998. © 2009 Wiley‐Liss, Inc.     

Differential diagnosis of mammographically and clinically occult breast lesions on diffusion‐weighted MRI

Purpose:

To investigate the diagnostic performance of diffusion‐weighted imaging (DWI) for mammographically and clinically occult breast lesions.

Materials and Methods:

The study included 91 women with 118 breast lesions (91 benign, 12 ductal carcinoma in situ [DCIS], 15 invasive carcinoma) initially detected on dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) and assigned BI‐RADS category 3, 4, or 5. DWI was acquired with b = 0 and 600 s/mm². Lesion visibility was assessed on DWI. Apparent diffusion coefficient (ADC) values were compared between malignancies, benign lesions, and normal (no abnormal enhancement on DCE‐MRI) breast tissue, and the diagnostic performance of DWI was assessed based on ADC thresholding.

Results:

Twenty‐four of 27 (89%) malignant and 74/91 (81%) benign lesions were hyperintense on the b = 600 s/mm² diffusion‐weighted images. Both DCIS (1.33 ± 0.19 × 10^?3 mm²/s) and invasive carcinomas (1.30 ± 0.27 × 10^?3mm²/s) were lower in ADC than benign lesions (1.71 ± 0.43 × 10^?3mm²/s; P < 0.001), and each lesion type was lower in ADC than normal tissue (1.90 ± 0.38 × 10^?3mm²/s, P ≤ 0.001). Receiver operating curve (ROC) analysis showed an area under the curve (AUC) of 0.77, and sensitivity = 96%, specificity = 55%, positive predictive value (PPV) = 39%, and negative predictive value (NPV) = 98% for an ADC threshold of 1.60 × 10^?3mm²/s.

Conclusion:

Many mammographically and clinically occult breast carcinomas were visibly hyperintense on diffusion‐weighted images, and ADC enabled differentiation from benign lesions. Further studies evaluating DWI while blinded to DCE‐MRI are necessary to assess the potential of DWI as a noncontrast breast screening technique. J. Magn. Reson. Imaging 2010;1:562–570. © 2010 Wiley‐Liss, Inc.

     

Role of novel magnetic resonance imaging sequences in characterization of ovarian masses

Introduction

Differentiating a benign from a malignant adnexal mass would provide a basis for optimal preoperative planning and may also reduce the number of unnecessary laparotomies patients undergoing treatment for benign disease. MRI provides additional information on the composition of soft-tissue masses using differences in MR relaxation properties seen in various types of tissue. More recently developed MRI sequences, like diffusion weighted, susceptibility weighted, and dynamic contrast enhancement sequences provided additional capacities for adnexal lesion tissue characterization.

Aim of the work

The aim of this work was to study the role of MRI including the novel sequences, namely dynamic contrast enhanced MRI (DCE–MRI), diffusion weighted images (DWI) and susceptibility weighted images (SWI) in the characterization of ovarian masses.

Patients and methods

This study included 25 patients having indeterminate adnexal masses at ultrasound. They were subjected to pelvic MRI, including T1, T2, T1 fat sat sequences, as well as the DWI, SWI, and DCE sequences. Final diagnosis was reached through histopathological data, or therapeutic response.

Results

All endometriomas showed blooming on SWI. All malignant lesions showed restricted diffusion and type III DCE curves.

Conclusion

MRI, especially the more recent sequences (DWI, SWI and DCE) allows accurate characterization of ovarian lesions.     

Added value of breathhold diffusion‐weighted MRI in detection of small hepatocellular carcinoma lesions compared with dynamic contrast‐enhanced MRI alone using receiver operating characteristic curve analysis

Purpose

To evaluate the added value of single‐breathhold diffusion‐weighted MRI (DWI) in detection of small hepatocellular carcinoma (HCC) lesions (≤2 cm) in patients with chronic liver disease, by comparing the detection sensitivity of combined DWI/conventional dynamic contrast‐enhanced (DCE)‐MRI to that of conventional DCE‐MRI alone.

Materials and Methods

A total of 37 patients with chronic liver diseases underwent abdominal MRI at 1.5T, including T1‐weighted imaging (T1WI), T2‐weighted imaging (T2WI), and 2D conventional DCE. For each patient study, axial DWI was performed with a single‐shot echo‐planar imaging (EPI) sequence using a modified sensitivity‐encoding (mSENSE) technique with b‐value of 500 seconds/mm². A total of 20–24 slices were obtained during a 15–17‐second breathhold. Two observers independently interpreted the combined DWI/conventional DCE‐MRI images and the conventional DCE‐MRI images alone in random order. For all small HCC lesions, the diagnostic performance using each imaging set was evaluated by receiver operating characteristic (ROC) curve analysis. Sensitivity and positive predictive values were also calculated and analyzed.

Results

A total of 47 small HCCs were confirmed as final result. The area under the ROC curve (Az) of combined DWI/conventional DCE‐MRI images (observer 1, 0.922; observer 2, 0.918) were statistically higher than those of conventional DCE‐MRI alone (observer 1, 0.809; observer 2, 0.778) for all small HCC lesions (P < 0.01). The lesion detection sensitivities using the combined technique for both observers were significantly higher than those using conventional DCE‐MRI alone (P < 0.01). The sensitivity values for two observers using the combined technique were 97.87% and those using conventional DCE‐MRI alone were 85.11% to 82.98%. The positive predictive values for two observers using the combined imaging technique (97.87%) were slightly higher than those using conventional DCE‐MRI alone (92.86–93.02%), but there was no significant difference between the two imaging sets.

Conclusion

Combined use of breathhold DWI with conventional DCE‐MRI helped to provide higher sensitivities than conventional DCE‐MRI alone in the detection of small HCC lesions in patients with chronic liver disease. J. Magn. Reson. Imaging 2009;29:341–349. © 2009 Wiley‐Liss, Inc.     

The diverse pathology and kinetics of mass, nonmass, and focus enhancement on MR imaging of the breast

Purpose:

To compare the pathology and kinetic characteristics of breast lesions with focus‐, mass‐, and nonmass‐like enhancement.

Materials and Methods:

A total of 852 MRI detected breast lesions in 697 patients were selected for an IRB approved review. Patients underwent dynamic contrast enhanced MRI using one pre‐ and three to six postcontrast T₁‐weighted images. The “type” of enhancement was classified as mass, nonmass, or focus, and kinetic curves quantified by the initial enhancement percentage (E₁), time to peak enhancement (T_peak), and signal enhancement ratio (SER). These kinetic parameters were compared between malignant and benign lesions within each morphologic type.

Results:

A total of 552 lesions were classified as mass (396 malignant, 156 benign), 261 as nonmass (212 malignant, 49 benign), and 39 as focus (9 malignant, 30 benign). The most common pathology of malignant/benign lesions by morphology: for mass, invasive ductal carcinoma/fibroadenoma; for nonmass, ductal carcinoma in situ (DCIS)/fibrocystic change(FCC); for focus, DCIS/FCC. Benign mass lesions exhibited significantly lower E₁, longer T_peak, and lower SER compared with malignant mass lesions (P < 0.0001). Benign nonmass lesions exhibited only a lower SER compared with malignant nonmass lesions (P < 0.01).

Conclusion:

By considering the diverse pathology and kinetic characteristics of different lesion morphologies, diagnostic accuracy may be improved. J. Magn. Reson. Imaging 2011;33:1382–1389. © 2011 Wiley‐Liss, Inc.     

Value of diffusion‐weighted magnetic resonance images for discrimination of focal benign and malignant hepatic lesions: A meta‐analysis

Purpose:

To evaluate the ability of DW‐MRI in differentiating malignant hepatic tumors from benign lesions.

Materials and Methods:

Meta‐analysis of 14 diagnostic studies was used. A systematic search in Medline, Embase, Web of Science (from January, 1966, to October, 2009), and Cochrane Controlled Clinical Trials Register Database (through third Quarter 2009) was used with screening of the literature.

Results:

A meta‐analysis of all 95 published studies was performed. Fourteen studies fulfilled the inclusion criteria (804 patients with 1665 hepatic lesions). The global sensitivity was 0.91 (95% confidence interval [CI], 0.86–0.94), the specificity was 0.93 (95% CI, 0.86–0.97), the positive likelihood ratio (PLR) was 13.10 (95% CI, 6.30–27.26), the negative likelihood ratio (NLR) was 0.10 (95% CI, 0.06–0.15), and the diagnostic odds ratio (DOR) was 133.76 (95% CI, 49.77–359.45). The area under the curve of the summary receiver operator characteristic (SROC) was 0.96 (95% CI 0.94–0.98).

Conclusion:

Diffusion‐weighted magnetic resonance imaging is potential technically feasible to differentiate malignant from benign focal liver lesions. Apparent diffusion coefficient measurements can be useful in providing rapid quantifiable information. J. Magn. Reson. Imaging 2010;32:130–137. © 2010 Wiley‐Liss, Inc.     

Diffusion-weighted imaging in breast lesion evaluation

Purpose

The purpose of this study was to investigate the ability of diffusion-weighted imaging (DWI) and the apparent diffusion coefficient (ADC) in the detection and characterisation of breast lesions.

Materials and methods

From September 2005 to September 2007, 86 patients with breast lesions who underwent magnetic resonance imaging (MRI) in our department were included in our study. MRI was performed with a 1.5-T unit using a standard protocol including DWI sequence. For each breast lesion, the ADC value was calculated and compared with that of normal breast tissue and to the definitive pathological diagnosis. Mann-Whitney U and Kruskal-Wallis tests were used for statistical analysis.

Results

A total of 126 breast lesions were detected. Pathology results revealed 100 malignant and 26 benign lesions. Mean diameter of lesions was 26.02 mm (range 4–90 mm), including 52 lesions ≤15 mm in size. Mean ADC value of normal glandular tissue was 1.55×10^?3 mm²/s. Mean ADC value of malignant lesions was 0.97×10^?3 mm²/s. Mean ADC value for benign lesions was 1.66×10^?3 mm²/s. Benign lesions showed ADC values significantly higher than malignant lesions (p<0.0001).

Conclusions

DWI provides reliable information to support MRI diagnosis of breast masses. ADC value appears a promising adjunctive parameter in distinguishing malignant from benign breast lesions.     

Diagnostic usefulness of water-to-fat ratio and choline concentration in malignant and benign breast lesions and normal breast parenchyma: an in vivo (1) H MRS study

Purpose:

To compare total choline concentrations ([Cho]) and water‐to‐fat (W/F) ratios of subtypes of malignant lesions, benign lesions, and normal breast parenchyma and determine their usefulness in breast cancer diagnosis. Reference standard was histology.

Materials and Methods:

In this HIPPA compliant study, proton MRS was performed on 93 patients with suspicious lesions (>1 cm) who underwent MRI‐guided interventional procedures, and on 27 prospectively accrued women enrolled for screening MRI. (W/F) and [Cho] values were calculated using MRS data.

Results:

Among 88 MRS‐evaluable histologically‐confirmed lesions, 40 invasive ductal carcinoma (IDC); 10 invasive lobular carcinoma (ILC); 4 ductal carcinoma in situ (DCIS); 3 invasive mammary carcinoma (IMC); 31 benign. No significant difference observed in (W/F) between benign lesions and normal breast tissue. The area under curve (AUC) of receiver operating characteristic (ROC) curves for discriminating the malignant group from the benign group were 0.97, 0.72, and 0.99 using [Cho], (W/F) and their combination as biomarkers, respectively. (W/F) performs significantly (P < 0.0001;AUC = 0.96) better than [Cho] (AUC = 0.52) in differentiating IDC and ILC lesions.

Conclusion:

Although [Cho] and (W/F) are good biomarkers for differentiating malignancy, [Cho] is a better marker. Combining both can further improve diagnostic accuracy. IDC and ILC lesions have similar [Cho] levels but are discriminated using (W/F) values. J. Magn. Reson. Imaging 2011;33:855–863. © 2011 Wiley‐Liss, Inc.     

Pilot study of improved lesion characterization in breast MRI using a 3D radial balanced SSFP technique with isotropic resolution and efficient fat‐water separation

Purpose

To assess a 3D radial balanced steady‐state free precession (SSFP) technique that provides submillimeter isotropic resolution and inherently registered fat and water image volumes in comparison to conventional T2‐weighted RARE imaging for lesion characterization in breast magnetic resonance imaging (MRI).

Materials and Methods

3D projection SSFP (3DPR‐SSFP) combines a dual half‐echo radial k‐space trajectory with a linear combination fat/water separation technique (linear combination SSFP). A pilot study was performed in 20 patients to assess fat suppression and depiction of lesion morphology using 3DPR‐SSFP. For all patients fat suppression was measured for the 3DPR‐SSFP image volumes and depiction of lesion morphology was compared against corresponding T2‐weighted fast spin echo (FSE) datasets for 15 lesions in 11 patients.

Results

The isotropic 0.63 mm resolution of the 3DPR‐SSFP sequence demonstrated improved depiction of lesion morphology in comparison to FSE. The 3DPR‐SSFP fat and water datasets were available in a 5‐minute scan time while average fat suppression with 3DPR‐SSFP was 71% across all 20 patients.

Conclusion

3DPR‐SSFP has the potential to improve the lesion characterization information available in breast MRI, particularly in comparison to conventional FSE. A larger study is warranted to quantify the effect of 3DPR‐SSFP on specificity. J. Magn. Reson. Imaging 2009;30:135–144. © 2009 Wiley‐Liss, Inc.     

Enhanced mass on contrast-enhanced breast MR imaging: Lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images

Purpose

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 enhanced mass on breast MR imaging and to find the strongest discriminators between carcinoma and benignancy.

Materials and Methods

We analyzed consecutive breast MR images in 270 patients; however, 13 lesions in 93 patients were excluded based on our criteria. We analyzed tumor size, shape, margin, internal mass enhancement, kinetic curve pattern, and apparent diffusion coefficient (ADC) values. We applied univariate and multivariate analyses to find the strongest indicators of malignancy and calculate a predictive probability for malignancy. We added the corresponding categories to these prediction probabilities for malignancy and calculated diagnostic accuracy when we consider category 4b, 4c, and 5 lesions as malignant and category 4a, 3, and 2 lesions as benign. In a validation study, 75 enhancing lesions in 71 patients were examined consecutively.

Results

Irregular margin, heterogeneous internal enhancement, rim enhancement, plateau time–intensity curve (TIC) pattern, and washout TIC pattern were the strongest indicators of malignancy as well as past studies, and ADC values less than 1.1 × 10^?3 mm²/s were also the strongest indicators of malignancy. In a validation study, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 92% (56/61), 86% (12/14), 97% (56/58), 71% (12/17), and 91% (68/75), respectively.

Conclusion

The combination of DWI and DCE‐MRI could produce high diagnostic accuracy in the characterization of enhanced mass on breast MR imaging. J. Magn. Reson. Imaging 2008;28:1157–1165. © 2008 Wiley‐Liss, Inc.

     

Probability of malignancy for lesions detected on breast MRI: a predictive model incorporating BI-RADS imaging features and patient characteristics

Objectives

To predict the probability of malignancy for MRI-detected breast lesions with a multivariate model incorporating patient and lesion characteristics.

Methods

Retrospective review of 2565 breast MR examinations from 1/03?C11/06. BI-RADS 3, 4 and 5 lesions initially detected on MRI for new cancer or high-risk screening were included and outcomes determined by imaging, biopsy or tumor registry linkage. Variables were indication for MRI, age, lesion size, BI-RADS lesion type and kinetics. Associations with malignancy were assessed using generalized estimating equations and lesion probabilities of malignancy were calculated.

Results

855 lesions (155 malignant, 700 benign) were included. Strongest associations with malignancy were for kinetics (washout versus persistent; OR 4.2, 95% CI 2.5?C7.1) and clinical indication (new cancer versus high-risk screening; OR 3.0, 95% CI 1.7?C5.1). Also significant were age >?=?50?years, size >?=?10?mm and lesion-type mass. The most predictive model (AUC 0.70) incorporated indication, size and kinetics. The highest probability of malignancy (41.1%) was for lesions on MRI for new cancer, >?=?10?mm with washout. The lowest (1.2%) was for lesions on high-risk screening, <10?mm with persistent kinetics.

Conclusions

A multivariate model shows promise as a decision support tool in predicting malignancy for MRI-detected breast lesions.     

扩散加权成像与MRI动态增强检测小乳腺癌的比较研究

目的 比较扩散加权成像(DWI)与动态对比增强MR成像(DCE MRI)对小乳腺癌的检出敏感性,并评价DWI的临床应用价值.方法 经病理证实的48例共70个乳腺小病灶(最大径≤2 cm)被纳入研究对象,其中恶性病灶45个,良性25个.所有患者均行DWI和DCE MRI,DCEMRI采用快速小角度激发(FLASH)序列,绘制病灶的时间.信号强度曲线(TIC),DWI采用回波平面成像(EPI)序列加用全局自动校准部分并行采集(GRAPPA)技术,取2个扩散敏感因子(b)值(800、1000 s/mm2)行横断面扫描,测量病灶的表观扩散系数(ADC)值.对2种检查方法 的诊断结果 进行比较.结果 DCE MRI正确诊断了40个小乳腺癌及19个良性小病灶,TIC显示小乳腺癌的敏感性及阳性预测值分别为88.9%(40/45)及87.0%(40/46).DWI中,在2种b值(800、1000 s/mm2)条件下小乳腺癌平均ADC值分别为(1.153±0.192)×10-3和(1.079±0.186)×10-3 mm2/s,而良性小病灶的平均ADC值为(1.473±0.252)×10-3和(1.419±0.255)×10-3 mm2/s;同组患者在2种b值条件下的ADC值差异无统计学意义(P＞0.05),而良恶性2组小病灶的ADC值差异有统计学意义(P＜0.01);b值取1000 s/mm2 时,根据DWI信号结合ADC值测量结果 可以正确诊断39个小乳腺癌及19个良性小病灶,其对小乳腺癌检出的敏感性及阳性预测值均为86.7%(39/45).DWI与DCEMRI的诊断结果 有很好的一致性,DWI联合DCE MRI可以提高检出的敏感性及阳性预测值,分别达93.3%(42/45))及91.3%(42/46).结论 DWI对小乳腺癌具有较高的检出率,且ADC值的测量可以为良恶性病变的鉴别提供有价值的诊断信息.     

Utility of second-look ultrasound in the management of incidental enhancing lesions detected by breast MR imaging

Purpose

To assess the utility of second-look ultrasound (US) for identifying and characterising incidental enhancing lesions detected by breast magnetic resonance imaging (MRI).

Materials and methods

From among 655 consecutive breast MRI studies, 62 lesions (MRI visible, nonpalpable, occult at first-look US and mammography) were recommended for second-look US. MRI enhancement of lesions was mass-like in 59 cases (95%) and non-mass-like in three (5%). Forty-two lesions (68%) were ??10 mm; only three lesions (5%) were >20 mm. Of all lesions, the Breast Imaging Reporting and Data System (BI-RADS) MRI category was highly suggestive of malignancy in six cases (10%), suspicious abnormality in 33 (53%) and probably benign in 23 (37%). The correlation between MRI lesion appearance, lesion size, histopathology findings and detection rate at second-look US were analysed. The reference standard was histopathology and/or follow-up (range 18?C24 months). Statistical analysis was performed with the Fisher exact test.

Results

Second-look US identified 44 out of 62 (71%) lesions depicted at MRI. The detection rate at second-look US was higher for mass-like MRI lesions (75%) than nonmass-like lesions (0%), for lesion size >10mm (90%) and for BI-RADS 4 lesions (88%). Second-look US-guided biopsy detected 12 out of 17 (71%) malignant lesions. There was no correlation between the likelihood of carcinoma and the presence of a sonographic correlate.

Conclusions

Second-look US is a reliable problemsolving tool in identifying and characterising most incidental MRI findings. It contributes to accurately selecting the cases in which MRI-guided biopsy is required.     

Characterization of malignancy of adnexal lesions using ADC entropy: Comparison with mean ADC and qualitative DWI assessment

Purpose:

To establish the utility of apparent diffusion coefficient (ADC) entropy in discrimination of benign and malignant adnexal lesions, using histopathology as the reference standard, via comparison of the diagnostic performance of ADC entropy with mean ADC and with visual assessments of adnexal lesions on conventional and diffusion‐weighted sequences.

Materials and Methods:

In all, 37 adult female patients with an ovarian mass that was resected between June 2006 and January 2011 were included. Volume‐of‐interest was drawn to incorporate all lesion voxels on every slice that included the mass on the ADC map, from which whole‐lesion mean ADC and ADC entropy were calculated. Two independent radiologists also rated each lesion as benign or malignant based on visual assessment of all sequences. The Mann–Whitney test and logistic regression for correlated data were used to compare performance of mean ADC, ADC entropy, and the visual assessments.

Results:

No statistically significant difference was observed in mean ADC between benign and malignant adnexal lesions (P = 0.768). ADC entropy was significantly higher in malignant than in benign lesions (P = 0.009). Accuracy was significantly greater for ADC entropy than for mean ADC (0.018). ADC entropy and visual assessment by the less‐experienced reader showed similar accuracy (P ≥ 0.204). The more experienced reader's accuracy was significantly greater than that of all other assessments (P ≤ 0.039).

Conclusion:

ADC entropy showed significantly greater accuracy than the more traditional metric of mean ADC for distinguishing benign and malignant adnexal lesions. Although whole‐lesion ADC entropy provides a straightforward and objective measurement, its potential benefit decreases with greater reader experience. J. Magn. Reson. Imaging 2013;37:164–171. © 2012 Wiley Periodicals, Inc.     

Diffusion-weighted magnetic resonance imaging in focal breast lesions: analysis of 78 cases with pathological correlation

Purpose

This study assessed the usefulness of magnetic resonance diffusion-weighted imaging (DWI) in distinguishing between benign and malignant breast lesions.

Materials and methods

Gadolinium-enhanced magnetic resonance imaging (MRI) and DWI with determination of the apparent diffusion coefficient (ADC) were performed on 78 women, each with a focal breast lesion at least 7 mm in diameter, which was studied by cytology or histology.

Results

Final diagnoses were obtained by cytology in 29 cases and histology in 49 (11 percutaneous biopsies and 38 surgical specimens). There were 43 benign lesions (13 fibrocystic disease, eight fibroadenoma, seven adenosis, five normal breast tissue, four inflammatory lesions, three intramammary lymph nodes, two scleroelastosis and one fat necrosis) and 35 malignant lesions (30 invasive ductal carcinoma, two invasive lobular carcinoma, one ductal carcinoma in situ, one carcinomatous mastitis and one metastasis from neuroendocrine carcinoma). The mean ADC values were 1.677±0.151 for benign lesions and 1.298±0.129 for malignant lesions (p<0.001). With an ADC cutoff value of 1.48, DWI had 88.6% sensitivity [confidence interval (CI) 78.1%?C99.1%] and 95.3% specificity (CI 88.9%?C100%), with 31 true positives, four false negatives (three invasive ductal carcinoma and one carcinomatous mastitis), 41 true negatives and two false positives (one fat necrosis and one fibroadenoma). With the cutoff value set at 1.52, DWI sensitivity (35 true positive, no false negative) was 100% and specificity was 86% (CI 75.7%?C96.3%) due to 37 true negatives and six false positives (an additional two fibroadenoma and two fibrocystic disease compared with those recorded with the cutoff set at 1.48). The overall accuracy of DWI considering both cutoff values (72 correct evaluations out of 78 cases) was 92.3% (CI 86.4%?C98.2%).

Conclusions

DWI is a reliable tool for characterising focal breast lesions.     

MR 动态增强联合扩散加权成像对壶腹区良恶性病变的鉴别

目的：研究M R动态增强联合扩散加权成像（DWI）在鉴别壶腹区良恶性病变的价值。方法回顾性分析43例胆总管下段狭窄患者的M R动态增强及DWI的数据。其中包括32例恶性病变和11例慢性炎症。1位影像医生对壶腹周围良恶性病变的M R动态增强信号强度及DWI信号进行分析,另外2位影像医生对壶腹周围病变的M R动态增强影像以及M R动态增强联合DWI影像进行评估。应用 Logistic回归分析比较灵敏度及特异性。结果壶腹周围良恶性病变MR动态增强表现差异无统计学意义;DWI影像中,壶腹周围癌比炎症更多地表现为高信号,表观扩散系数（ADC）图表现为低信号（P＜0．001）。2位读片者在结合DWI影像后对恶性壶腹周围病变的诊断灵敏度均有提高,分别从84．4％提高到96．9％和从87．7％提高到96．6％。结论 M R动态增强联合DWI可提高鉴别壶腹周围区良恶性狭窄的诊断准确率。     

Diagnostic performances of shear-wave elastography for identification of malignant breast lesions: a meta-analysis

Purpose

To examine the performance of shear-wave elastography (SWE) for the differentiation of benign and malignant breast lesions using a meta-analysis.

Materials and methods

PubMed, Embase and the Cochrane library were searched for studies published up to January 2014. The references of retrieved relevant articles were reviewed to identify potential publications. Random-effect meta-analysis was conducted to assess the overall sensitivity and specificity of SWE in the differentiation of breast lesions.

Results

A total of 11 articles, including 2424 patients, were included in the present meta-analysis. The summarized sensitivity and specificity of the shear wave elastography performance based on maximum elasticity were 0.93 (95 % CI 0.91–0.95) and 0.81 (95 % CI 0.78–0.83), respectively. For the mean elasticity, the summarized sensitivity and specificity were 0.94 (95 % CI 0.92–0.96) and 0.71 (95 % CI 0.69–0.74), respectively. The summarized sensitivity and specificity were 0.77 (95 % CI 0.70–0.83) and 0.88 (95 % CI 0.84–0.91) for the SD of elasticity.

Conclusion

SWE has a high sensitivity and specificity in the differentiation of benign and malignant breast lesions. More large and prospective studies are warranted to further examine the performance of SWE.