Update of Breast MR Imaging Architectural Interpretation Model

Nunes, Linda White; Schnall, Mitchell D.; Orel, Susan G.

doi:10.1148/radiology.219.2.r01ma44484

Cited by 191 publications

(123 citation statements)

References 19 publications

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“…They concluded that morphological criteria were useful features, but that standardization was also important. Other recent studies have confirmed that smooth or lobulated borders are architectural features that are highly predictive of benign disease (3,4).…”

mentioning

confidence: 86%

Breast lesion analysis of shape technique: Semiautomated vs. manual morphological description

Liney

Sreenivas

Gibbs

et al. 2006

Magnetic Resonance Imaging

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Purpose: To investigate the efficacy of an automated method of shape measurement for improving the discrimination of benign and malignant breast lesions. Materials and Methods:A total of 47 breast lesions (32 malignant and 15 benign) were examined using a 1.5 Tesla system. Regions of interest (ROIs) were manually drawn and extracted from high-resolution, fat-suppressed, postcontrast images, or were extracted with the use of a semiautomated computer algorithm. Shape parameters (i.e., complexity, convexity, circularity, and degree of elongation) were determined to assess whether they could be used to discriminate breast lesions.Results: Convexity differed significantly between the benign and malignant groups for both ROI methods. In addition, the semiautomated method demonstrated significantly different values of complexity. Conclusion:This work demonstrates the usefulness of several shape descriptors for characterizing breast lesions, and shows that the automated method of analysis improves the discrimination and standardization of data.

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confidence: 86%

Breast lesion analysis of shape technique: Semiautomated vs. manual morphological description

Liney

Sreenivas

Gibbs

et al. 2006

Magnetic Resonance Imaging

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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).…”

mentioning

confidence: 98%

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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“…4,5,[21][22][23] Buadu and associates 9 reported diŠerent patterns of rim enhancement and concluded that early rim enhancement with progression to the center was fairly speciˆc for carcinomas. Matsubayashi's group 10 reported that whereas early Fig.…”

Section: Magnetic Resonance In Medical Sciencesmentioning

confidence: 99%

Dynamic High-Spatial-Resolution MR Imaging of Invasive Ductal Carcinoma: Influence of Histological Scirrhous Component on MR Descriptors

2006

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Purpose: The purpose of this study was to assess the relationship between the amount of scirrhous component in invasive ductal carcinoma and its MR characteristics.Materials and Methods: We retrospectively reviewed 71 consecutive patients with invasive ductal carcinoma smaller than 25 mm (average, 16.6 mm) in diameter. The scirrhous component was deˆned as invasive foci in small clusters of cancer cells showing desmoplasia. Invasive ductal carcinoma was subclassiˆed into 3 groups in accordance with the amount of the scirrhous component (scirrhous component degree; SCD): SCD I (scirrhous component less than 20z), SCD II (intermediate), and SCD III (more than 80z). Dynamic magnetic resonance (MR) imaging was performed using volumetric interpolated sequence. Prior to dynamic study, T 2 *-weightedˆrst-pass perfusion images were obtained before, during, and after bolus injection of 0.1 mmol Gd-DTPA W kg.Results: Twenty-eight lesions were classiˆed as SCD I, 14 as SCD II, and 29 as SCD III. Mass margin and signal intensity loss in the perfusion study were signiˆcantly diŠerent among the 3 SCD groups (Pº0.001). The kinetic patterns were signiˆcantly diŠerent among the 3 SCD groups (P＝0.04), and between SCD I W II and SCD III (P＝0.03). The presence of enhancing internal septations was signiˆcantly diŠerent between SCD I W II and SCD III carcinomas (P＝0.05). Central enhancement was only observed in SCD I carcinoma (4z; 3W 71).Conclusion: The histological predominance of the scirrhous component in invasive ductal carcinoma may be one explanation for the diŠerences in morphologic and kinetic patterns on MR imaging.

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Update of Breast MR Imaging Architectural Interpretation Model

Abstract: Additional investigation yielded a slightly modified model, but the diagnostic performance characteristics remain high, similar to those originally published.

Cited by 191 publications

References 19 publications

Breast lesion analysis of shape technique: Semiautomated vs. manual morphological description

Breast lesion analysis of shape technique: Semiautomated vs. manual morphological description

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

Dynamic High-Spatial-Resolution MR Imaging of Invasive Ductal Carcinoma: Influence of Histological Scirrhous Component on MR Descriptors

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