Diagnostic Architectural and Dynamic Features at Breast MR Imaging: Multicenter Study

Schnall, Mitchell D.; Blume, Jeffrey D.; Bluemke, David A.; DeAngelis, Gia A.; DeBruhl, Nanette; Harms, Steven E.; Heywang‐Köbrunner, Sylvia H.; Hylton, Nola; Kuhl, Christiane K.; Pisano, Etta D.; Causer, Petrina; Schnitt, Stuart J.; Thickman, David; Stelling, Carol B.; Weatherall, Paul T.; Lehman, Constance D.; Gatsonis, Constantine

doi:10.1148/radiol.2381042117

Cited by 472 publications

(378 citation statements)

References 32 publications

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“…Dynamic contrast-enhanced breast MR imaging (DCE-MRI) has been reported to have high sensitivity for cancer detection, reportedly as high as 88%-100%, but specificity may be relatively low as 68%-96% (4 -6,8,9). The high diagnostic value of the time-intensity curve (TIC) derived from DCE-MRI has been well documented in past studies (1)(2)(3)(4)(5)(6)(7)(8)(9)(10). Moreover, MR imaging has recently been used to analyze combined morphologic characteristics and kinetic enhancement patterns of breast lesions, and a combination of these parameters shows high positive predictive value (8,9).…”

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confidence: 98%

“…MAGNETIC RESONANCE IMAGING (MRI) of the breast is increasingly used as an important tool for detecting breast cancer or preoperative diagnosis of breast cancer to determine the area of tumor spreading or to find additional lesions (1)(2)(3)(4)(5)(6)(7). Dynamic contrast-enhanced breast MR imaging (DCE-MRI) has been reported to have high sensitivity for cancer detection, reportedly as high as 88%-100%, but specificity may be relatively low as 68%-96% (4 -6,8,9).…”

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confidence: 99%

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

Yabuuchi

Matsuo

Okafuji

et al. 2008

Magnetic Resonance Imaging

176

166

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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 ϫ 10 Ϫ3 mm 2 /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.

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confidence: 99%

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

Yabuuchi

Matsuo

Okafuji

et al. 2008

Magnetic Resonance Imaging

176

166

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“…Dynamic contrast-enhanced MR imaging (DCE-MRI) is emerging as an important complementary diagnostic tool for early detection of breast cancer [1]. It involves characterizing temporal response of a tumor to a contrast agent prior to analyzing discriminating features between various tumor types.…”

Section: Introductionmentioning

confidence: 99%

“…High sensitivity of DCE-MRI to breast cancer detection is, however, confounded by its relatively low specificity [2]. Existing approaches attempt to improve low specificity through better segmentation [3] and/or complete characterization of tumor (using architectural and dynamic features [4,1]). …”

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confidence: 99%

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Segmentation and Classification of Breast Tumor Using Dynamic Contrast-Enhanced MR Images

Zheng

Baloch

Englander

et al.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007

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Abstract. Accuracy of automatic cancer diagnosis is largely determined by two factors, namely, the precision of tumor segmentation, and the suitability of extracted features for discrimination between malignancy and benignancy. In this paper, we propose a new framework for accurate characterization of tumors in contrast enhanced MR images. First, a new graph cut based segmentation algorithm is developed for refining coarse manual segmentation, which allows precise identification of tumor regions. Second, by considering serial contrast-enhanced images as a single spatio-temporal image, a spatio-temporal model of segmented tumor is constructed to extract Spatio-Temporal Enhancement Patterns (STEPs). STEPs are designed to capture not only dynamic enhancement and architectural features, but also spatial variations of pixel-wise temporal enhancement of the tumor. While temporal enhancement features are extracted through Fourier transform, the resulting STEP framework captures spatial patterns of temporal enhancement features via moment invariants and rotation invariant Gabor textures. High accuracy of the proposed framework is a direct consequence of this two pronged approach, which is validated through experiments yielding, for instance, an area of 0.97 under the ROC curve.

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Combined Screening With Ultrasound and Mammography vs Mammography Alone in Women at Elevated Risk of Breast Cancer

Berg¹

2008

JAMA

1,327

896

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The US Preventive Services Task Force analysis of 7 randomized trials of mammographic screening found that the point estimate of the reduction in mortality from screening mammography was 22% in women aged 50 years or older and 15% among women between 40 and 49 years, 1 with some individual trials showing far greater benefits in both age groups and with any specific age distinction arbitrary. The magnitude of reduction in mortality seen in individual trials parallels reductions in size distribution 2 and rates of node-positive breast cancer. 3 Mammography can depict calcifications due to malignancy, including ductal carcinoma in situ (DCIS). Invasive cancers, which can spread to lymph nodes and cause systemic metastases, are most often manifest as noncalcified masses 4 and can be mammographically subtle or occult, particularly when the parenchyma is dense. Dense breast tissue is common. More than half of women younger than 50 years 5 have either heterogeneously dense, visually estimated as 51% to 75% glandular, 6 or For editorial comment see p 2203.Context Screening ultrasound may depict small, node-negative breast cancers not seen on mammography.Objective To compare the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography vs mammography alone in women at elevated risk of breast cancer.Design, Setting, and Participants From April 2004 to February 2006, 2809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2637 (96.8%) of the 2725 eligible participants.Main Outcome Measures Diagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound vs mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound vs mammography alone.Results Forty participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1000 women screened (20 of 2637) and increased to 11.8 per 1000 (31 of 2637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1000 women screened (95% confidence interval [CI], 1.1-7.2 per 1000; P=.003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95% CI, 0.67-0.87) and increased to 0.91 (95% CI, 0.84-0.96) for mammography plus ultrasound (P=.003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92%) were invasive with a median size of 10 mm (ra...

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Diagnostic Architectural and Dynamic Features at Breast MR Imaging: Multicenter Study

Abstract: Architectural and dynamic features are important in breast MR imaging interpretation. Multivariate models involving feature assessment have a diagnostic accuracy superior to that of qualitative characterization of the dynamic enhancement pattern.

Cited by 472 publications

References 32 publications

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

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

Segmentation and Classification of Breast Tumor Using Dynamic Contrast-Enhanced MR Images

Combined Screening With Ultrasound and Mammography vs Mammography Alone in Women at Elevated Risk of Breast Cancer

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