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.     

Predictive model for contrast-enhanced ultrasound of the breast: Is it feasible in malignant risk assessment of breast imaging reporting and data system 4 lesions?

AIM: To build and evaluate predictive models for contrast-enhanced ultrasound (CEUS) of the breast to distinguish between benign and malignant lesions. METHODS: A total of 235 breast imaging reporting and data system (BI-RADS) 4 solid breast lesions were imaged via CEUS before core needle biopsy or surgical resection. CEUS results were analyzed on 10 enhancing patterns to evaluate diagnostic performance of three benign and three malignant CEUS models, with pathological results used as the gold standard. A logistic regression model was developed basing on the CEUS results, and then evaluated with receiver operating curve (ROC). RESULTS: Except in cases of enhanced homogeneity, the rest of the 9 enhancement appearances were statistically significant (P < 0.05). These 9 enhancement patterns were selected in the final step of the logistic regression analysis, with diagnostic sensitivity and specificity of 84.4% and 82.7%, respectively, and the area under the ROC curve of 0.911. Diagnostic sensitivity, specificity, and accuracy of the malignant vs benign CEUS models were 84.38%, 87.77%, 86.38% and 86.46%, 81.29% and 83.40%, respectively. CONCLUSION: The breast CEUS models can predict risk of malignant breast lesions more accurately, decrease false-positive biopsy, and provide accurate BI-RADS classification.     

Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions?

PURPOSE: To assess the relevance of the signal intensity time course for the differential diagnosis of enhancing lesions in dynamic magnetic resonance (MR) imaging of the breast. MATERIALS AND METHODS: Two hundred sixty-six breast lesions were examined with a two-dimensional dynamic MR imaging series and subtraction postprocessing. Time-signal intensity curves of the lesions were obtained and classified according to their shapes as type I, which was steady enhancement; type II, plateau of signal intensity; or type III, washout of signal intensity. Enhancement rates and curve types of benign and malignant lesions were compared. RESULTS: There were 101 malignant and 165 benign lesions. The distribution of curve types for breast cancers was type I, 8.9%; type II, 33.6%; and type III, 57.4%. The distribution of curve types for benign lesions was type I, 83.0%; type II, 11.5%; and type III, 5.5%. The distributions proved significantly different (chi 2 = 139.6; P < .001). The diagnostic indices for signal intensity time course were sensitivity, 91%; specificity, 83%; and diagnostic accuracy, 86%. The diagnostic indices for the enhancement rate were sensitivity, 91%; specificity, 37%; and diagnostic accuracy, 58%. CONCLUSION: The shape of the time-signal intensity curve is an important criterion in differentiating benign and malignant enhancing lesions in dynamic breast MR imaging. A type III time course is a strong indicator of malignancy and is independent of other criteria.     

Management of breast magnetic resonance imaging-detected lesions

Breast magnetic resonance imaging (MRI) has become an essential component of breast imaging. Whether it is used as a problem-solving tool or a screening test or for staging patients with breast cancer, it detects many lesions in the breast. The challenge for the radiologist is to distinguish significant from insignificant lesions and to direct their management. A brief summary of the terminology according to the American College of Radiologists lexicon will be provided. This review article will cover the differential diagnosis of enhancing lesions, including masses and nonmass enhancement, from benign and malignant causes. Some of the specific morphologic and kinetic features that help to differentiate benign from malignant lesions will be illustrated, and positive predictive values of these features will be reviewed. The various methods of investigating enhancing lesions of the breast will be discussed, including second-look ultrasound, ultrasound-guided biopsy, stereotactic biopsy, and MRI-guided biopsy. A practical approach to the management of MRI-detected lesions will include timing of follow-up, when to biopsy and when to ignore enhancing lesions in the breast.     

Magnetization transfer ratio as a predictor of malignancy in breast lesions: preliminary results.

MRI is an important tool for investigating breast cancer. Although recognized as the method of choice for screening high-risk patients, and for other indications the role of MRI for lesion characterization remains controversial. Recently some authors have advocated the use of morphologic and postcontrast features for this purpose. Quantitative breast MRI techniques have not been applied extensively in breast diseases. Magnetization transfer (MT) is a quantitative MR technique commonly used to investigate neurological diseases. In breast diseases the use of MT has been limited to improving visualization of areas of enhancement in postcontrast images. The purpose of this study was to evaluate the feasibility and utility of MT in discriminating benign from malignant breast lesions. Fifty-two lesions, BIRADS 4 and 5, from 49 patients, were prospectively evaluated using the MT ratio (MTR). Patients were divided into two groups: benign and malignant lesions. The MTR of fat, pectoralis major muscle, fibroglandular tissue, and breast lesions were calculated. A statistically significant difference was found between MTR from benign and malignant lesions (P < 0.001). Preliminary results suggest that MT can be used to evaluate breast lesions. Further studies are necessary to better define the utility and applicability of this technique.     

Characterization of breast lesion morphology with delayed 3DSSMT: an adjunct to dynamic breast MRI

The purpose of the study was to determine the sensitivity and specificity of various morphologic criteria in distinguishing malignant from benign breast lesions using a new sequence (3DSSMT) performed immediately after dynamic breast MRI. 3DSSMT combines a water-selective spectral-spatial excitation and an on-resonance magnetization transfer pulse with three-dimensional spoiled gradient-echo imaging. Morphologic features of 87 pathologically confirmed lesions were analyzed. The presence of either skin thickening, or a combination of a spiculated or microlobulated border, with a rim, ductal, linear, or clumped enhancement pattern was 94% specific and 54% sensitive for malignancy. Conversely, the presence of either a perfectly smooth border, a well-defined margin, non-enhancing internal septations, or a macrolobulated border was 97% specific and 35% sensitive for a benign diagnosis. In conclusion, delayed 3DSSMT discriminates a significant number of benign and malignant breast lesions; it has the potential to improve the diagnostic accuracy of dynamic breast MRI.     

Multimodality imaging features of idiopathic granulomatous mastitis: outcome of 12 years of experience

Purpose

This study was done to determine mammographic, sonographic and magnetic resonance imaging (MRI) appearances of idiopathic granulomatous mastitis, an entity clinically and radiographically resembling breast carcinoma.

Materials and methods

A total of 36 women (mean age 37 years, range 21?C51 years) with histopathological diagnosis of idiopathic granulomatous mastitis were enrolled in the study. The Breast Imaging Reporting and Data System (BI-RADS) was used to categorise the levels of suspicion of malignancy on mammography. Mammography findings were classified also according to density, margin, architectural distortion and number of lesions. Lesions were classified according to number, heterogeneity and echogenic features on sonography. Dynamic MRI findings were categorised as enhancing mass lesion, nonmass lesion or both mass lesions and nonmass lesions together. Subclassification criteria for MRI included lesion shape, margin, border and internal enhancement pattern.

Results

The most common mammographic finding was either focal or diffuse asymmetric density (n=15, 44%). The most common sonographic findings were solitary or multiple circumscribed heterogeneous hypoechoic masses (n=19, 52%). Among other sonographic findings were diffuse abscess formation with fistulae and massive parenchymal heterogeneity and hypoechogenicity in 12 (33%) and five (13%) women, respectively. On MRI, enhancing mass lesions were detected in 24 patients, whereas enhancing nonmass lesions were observed in 28. Sixteen patients had both enhancing mass lesions and nonmass lesions together.

Conclusions

Although not characteristic for this entity, asymmetric density on mammography, solitary or multiple clustered heterogeneous hypoechogenicity with a tubular configuration on sonography and round, smooth-contoured masslike lesion with rim enhancement or segmental non-mass-like lesion on MRI are the most common features of the disease.     

Classification of small contrast enhancing breast lesions in dynamic magnetic resonance imaging using a combination of morphological criteria and dynamic analysis based on unsupervised vector-quantization

PURPOSE: To evaluate the diagnostic value of breast magnetic resonance imaging (MRI) in small focal lesions using dynamic analysis based on unsupervised vector quantization in combination with a score for morphologic criteria. MATERIALS AND METHODS: We examined 85 mammographically indetermintate lesions (BIRADS 3-4; 47 malignant, mean lesion size 1.2 cm; 38 benign, mean lesion size 1.1 cm). MRI was performed with a dynamic T1-weighted gradient echo sequence (1 precontrast and 5 postcontrast series). Lesions with an initial contrast enhancement >/=50% were selected with semiautomatic segmentation. For conventional dynamic analysis, we calculated the mean initial signal increase and postinitial course of all voxels included in a lesion. Secondly, all voxels within the lesions were assigned to 4 clusters using minimal-free-energy vector quantization. Dynamic and morphologic criteria were summarized in a diagnostic score and evaluated by receiver operating characteristic analysis. RESULTS: In the present collection of small lesions, morphologic criteria [area under the curve (AUC) = 0.610] were inferior to dynamic criteria in the detection of breast cancer. Dynamic analysis with vector quantization (AUC = 0.760) presented slightly better results compared with standard dynamic analysis (AUC = 0.693). There was no benefit for combined morphologic and dynamic analysis. CONCLUSION: In small MR-mammographic lesions, dynamic analysis with vector quantization alone tends to result in a higher diagnostic accuracy compared with combined morphologic and dynamic analysis.     

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.     

Magnetic resonance imaging characteristics of fibrocystic change of the breast

OBJECTIVE: The objective of this study was to identify magnetic resonance imaging (MRI) characteristics of fibrocystic change (FCC) of the breast. MATERIALS AND METHODS: Fourteen patients with a histopathologic diagnosis of solitary FCC of the breast underwent x-ray mammography and MRI of the breast. Three experienced breast imaging radiologists retrospectively reviewed the MRI findings and categorized the lesions on morphologic and kinetic criteria according to the ACR BI-RADS-MRI Lexicon. RESULTS: The most striking morphologic feature of fibrocystic change was nonmass-like regional enhancement found in 6 of 14 (43%) FCC lesions. Based on morphologic criteria alone, 12 of 14 (86%) lesions were correctly classified as benign. According to analysis of the time-intensity curves, 10 of 14 (71%) FCC lesions were correctly classified as benign. CONCLUSION: Although FCC has a wide spectrum of morphologic and kinetic features on MRI, it most often presents as a mass or a nonmass-like regional enhancing lesion with benign enhancement kinetics.     

磁共振动态增强扫描诊断乳腺病变的应用价值

 目的 探讨磁共振动态增强扫描诊断乳腺病变的应用价值.方法 对40例乳腺疾病患者(33个良性病灶,24个恶性病灶)分别进行磁共振平扫和动态增强扫描检查,分析病灶强化的形态特征,测量动态增强的时间-信号强度曲线分布类型、峰值时间和早期增强率.结果 多数病灶在磁共振平扫时未被检出,结合增强后的形态特征对乳腺癌的检出敏感性为75.0%,特异性为69.7%,准确性为71.9%.良、恶性病灶时间-信号强度曲线、峰值时间及早期增强率分布的差异均有统计学意义(P<0.01),诊断敏感性分别为91.7%、87.5%和75.0%,特异性分别为87.9%、87.9%和84.8%,准确性分别为89.5%、87.7%和80.7%.联合上述指标诊断乳腺癌的敏感性为95.8%,特异性87.9%,准确性为91.2%.结论 时间-信号强度曲线、峰值时间及早期增强率在乳腺良、恶性病变诊断中具有较高的敏感性和特异性,结合增强的形态特征,对乳腺病变的诊断及鉴别诊断有重要价值.     

Contrast-enhanced 3.0-T breast MRI for characterization of breast lesions: increased specificity by using vascular maps

Purpose: To assess the diagnostic accuracy of contrast-enhanced 3.0-T breast magnetic resonance imaging (MRI) for differentiating benign from malignant breast masses and subsequently to test if specificity could be further improved by scoring of the overall ipsilateral breast vascularity. Materials and methods: Fifty-four patients were prospectively enrolled in the study and underwent contrast-enhanced 3.0-T breast MRI. MR images were evaluated and classified according to the MRI BI-RADS lexicon criteria. Lesion size, number of lesions, and localization in the breast were systematically assessed. Maximum intensity projections (MIPS) were obtained by using high-resolution contrast-enhanced (0.1 mmol/kg gadobutrol) fat-saturated T1-weighted images. Breast vascularization was scored according to the methods from Sardanelli et al. by measuring the number, diameter, and length of the vessels on the MIPS. The score ranged from 0 (indicating absent or low breast vascularity) to 3 (indicating high breast vascularity). Results: Final analysis of 56 lesions revealed 25 (45%) malignant lesions and 31 (55%) benign lesions. Correlation with the MRI BI-RADS classification revealed cancer in none (0%) of the BI-RADS II lesions, in 1 (12%) of the BI-RADS III lesions, in 5 (83%) of the BI-RADS IV lesions, and in 19 (100%) of the BI-RADS V lesions. Based on morphologic and kinetic data analysis, the sensitivity and specificity of 3.0-T breast MRI was 100% (25/25) and 74% (23/31), respectively. After adjustment for the breast vascularity score, specificity significantly (p = 0.048) increased to 87% (27/31) without affecting sensitivity. Conclusion: Diagnostic accuracy of contrast-enhanced 3.0-T breast MRI increased significantly when the vascularity score was added to the standard morphologic and kinetic data analysis, resulting in a specificity of 87% without affecting sensitivity, which remained 100%.     

乳腺X线摄影、超声、MRI对乳腺非肿块强化病灶诊断价值的对照研究

目的：比较乳腺 X 线摄影、超声及 MRI 对乳腺 MRI 非肿块强化(NME)病灶的诊断效能。方法回顾性分析116例(123个病灶)患者乳腺 MRI NME 病灶的乳腺 X 线摄影、超声及 MRI 的影像学表现。结果病理结果恶性99例,良性24例,乳腺X 线摄影、超声及 MRI 的敏感度分别为72.73%、65.66%、84.85%,特异度分别为66.67%、79.17%、79.17%,准确度分别为71.54%、68.29%、83.74%,阳性预测值分别为90.00%、92.86%、94.88%,阴性预测值分别为37.21%、35.85%、55.88%。MRI 对 NME 病灶的敏感度、特异度、准确度、阳性预测值及阴性预测值均明显高于乳腺 X 线摄影和超声(P <0.05)。且 MRI 与 MRI+乳腺 X 线摄影及 MRI+乳腺 X 线摄影+超声结果相近,差别无统计学意义。结论MRI 对于乳腺 NME 病灶有较高的诊断价值,应作为首选检查方法。     

Detection of breast cancer with conventional mammography and contrast-enhanced MR imaging

The aim of this study was to compare the diagnostic performance of conventional mammography and dynamic contrast-enhanced fast 3D gradient-echo (GRE) MRI regarding the detection and characterization of breast lesions relative to histopathologic analysis and to assess the results of a combined evaluation of both methods. fifty consecutive patients with 63 histopathologically verified breast lesions underwent dynamic contrast-enhanced GRE MRI in addition to routine conventional mammography. All lesions were classified by both methods on a five-point scale as benign or malignant, and the results were correlated to histopathology. Conventional mammography and dynamic MRI yielded a sensitivity and specificity of 82 and 64 %, and 92 and 76 %, respectively. The difference between the results was statistically not significant (p > 0.05) with areas under the receiver-operating-characteristics curves of 0.807 for mammography and 0.906 for MR imaging. Combination of the results of both methods slightly increased the sensitivity for detection of breast cancer to 95 % but decreased specificity to 52 %. In this selected patient subset, including only patients referred for excisional biopsy, contrast-enhanced dynamic MRI proved more sensitive and specific than conventional mammography regarding the detection of malignancy. While a combination of both methods yields a slightly improved sensitivity, specificity is vastly reduced. Received 5 May 1997; Revision received 14 July 1997; Accepted 7 August 1997     

The role of contrast-enhanced ultrasound in the diagnosis of malignant non-mass breast lesions and exploration of diagnostic criteria

Objectives:To assess the value of contrast-enhanced ultrasound (CEUS) for diagnosing malignant non-mass breast lesions (NMLs) and to explore the CEUS diagnostic criteria.Methods:A total of 116 patients with 119 NMLs detected by conventional US were enrolled. Histopathological results were used as the reference standard. The enhancement characteristics of NMLs in CEUS were compared between malignant and benign NMLs. The CEUS diagnostic criteria for malignant NMLs were established using independent diagnostic indicators identified by binary logistic regression analysis. The diagnostic performance of Breast Imaging Reporting and Data System-US (BI-RADS-US), CEUS, and BI-RADS-US combined with CEUS was evaluated and compared.Results:Histopathological results showed 63 and 56 benign and malignant NMLs. Enhancement degree (OR = 5.75, p = 0.003), enhancement area (OR = 4.25, p = 0.005), and radial or penetrating vessels (OR = 7.54, p = 0.003) were independent diagnostic indicators included to establish the CEUS diagnostic criteria. The sensitivity and specificity of BI-RADS-US, CEUS, and BI-RADS-US combined with CEUS were 100 and 30.2%, 80.4 and 74.6%, and 94.6 and 77.8%, respectively; the corresponding areas under the receiver operating characteristic curve (AUC) were 0.819, 0.775, and 0.885, respectively.Conclusions:CEUS has a high specificity in malignant NML diagnosis based on the diagnostic criteria including enhancement degree, enhancement area, and radial or penetrating vessels, but with lower sensitivity than BI-RADS-US. The combination of CEUS and BI-RADS-US is an effective diagnostic tool with both high sensitivity and specificity for the diagnosis of malignant NMLs.Advances in knowledge:In this study, we assessed the diagnostic value of CEUS for malignant NMLs and constructed a feasible diagnostic criterion. We further revealed that the combination of CEUS and BI-RADS-US has a high diagnostic value for malignant NMLs.     

磁共振DWI检查在肺内良恶性病变鉴别诊断中的价值

目的:探讨磁共振DWI检查中ADC值和LSR值对肺内良恶性病变的鉴别诊断价值。方法:收集经肺部CT检查发现肺部大于1cm结节或肿块的55名患者,所有患者均行磁共振常规检查和DWI(b=600s/mm^2)扫描,分析肺内良恶性病变ADC值和LSR值的特点。结果 :ADC值和LSR值诊断肺内良恶性病变ROC曲线下面积为0.787和0.783,最佳诊断阈值为1.53×10^-3mm^2/s和1.075。ADC值和LSR值诊断肺内良恶性病变的灵敏度分别为79.1%和72.1%,特异度分别为73.3%和86.7%,两者之间灵敏度与特异度差异没有统计学意义(P=0.44,0.48);将ADC值和LSR值联合诊断肺内良恶性病变的灵敏度为93.0%,高于任何单一的诊断方法(P=0.04,0.0077);特异度为73.3%,与单一诊断之间比较,差异没有统计学意义(P=1,0.48)。ADC值、LSR值以及ADC值联合LSR值诊断肺内良恶性病变的阳性预测值、阴性预测值、阳性似然比、阴性似然比、约登指数和准确率分别为87.2%,57.9%,2.96,0.29,52.4%,77.6%;93.9%,52.0%,5.4,0.32,58.8%,75.9%;90.9%,78.6%,3.48,0.23,66.3%,87.9%。结论:磁共振DWI检查对鉴别肺内良恶性病变具有诊断价值,将ADC值和LSR值联合起来诊断的灵敏度高于单一诊断方式。