Descriptors of Malignant Non-mass Enhancement of Breast MRI

Machida, Youichi; Shimauchi, Akiko; Tozaki, Mitsuhiro; Kuroki, Yoshio; Yoshida, Tsuyoshi; Fukuma, Eisuke

doi:10.1016/j.acra.2016.01.014

Cited by 17 publications

(14 citation statements)

References 25 publications

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“…In terms of the MRI morphologic features of diagnosed DCIS, an irregular shape, not-circumscribed margins, rim-enhancing masses, and clumped or clustered ring-enhancing NMEs were significantly associated with a histologic upgrade in our study. This is consistent with previous reports indicating that suspicious morphologic imaging features indicate a likelihood of malignancy [ 16 , 20 , 30 – 34 ]. Hahn et al reported that a spiculated mass, segmental distribution, clustered ring enhancement of an NME, and enhancement kinetics showing a strong initial enhancement with subsequent washout were significantly more frequent in mIDC than in DCIS [ 16 ].…”

Section: Discussionsupporting

confidence: 93%

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ

et al. 2020

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Background: The upgrade rate of biopsy-confirmed ductal carcinoma in situ (DCIS) to invasive carcinoma is up to 50% on final pathology. We investigated MRI and clinicopathologic predictors of the invasive components of DCIS diagnosed by preoperative biopsy and then compared MRI features between patients with DCIS, microinvasive ductal carcinoma (mIDC), and invasive ductal carcinoma (IDC) diagnosed on final pathology. Methods: Two hundred and one patients with 206 biopsy-confirmed DCIS lesions were enrolled. MRI and clinicopathologic features were used to predict either mIDC or IDC via a cumulative logistic regression analysis. For the lesions detected on MRI, morphologic and kinetic analyses were performed using the Chi-square, Fisher's exact, and Kruskal-Wallis tests. Results: Of all the lesions, 112 (54.4%) were diagnosed as DCIS, 50 (24.3%) were upgraded to mIDC, and 44 (21.4%) to IDC. The detection on MRI as mass (Odds ratio (OR) = 8.84, 95% confidence interval (CI) = 1.05-74.04, P = 0.045) or non-mass enhancement (NME; OR = 11.17, 95% CI = 1.35-92.36, P = 0.025), negative progesterone receptor (PR; OR = 2.40, 95% CI = 1.29-4.44, P = 0.006), and high Ki-67 level (OR = 2.42, 95% CI = 1.30-4.50, P = 0.005) were significant independent predictors of histologic upgrade. On MRI, 87 (42.2%) lesions appeared as mass and 107 (51.9%) as NME. Irregularly shaped, not-circumscribed, heterogeneous, or rim-enhancing masses with intratumoral high signal intensity or peritumoral edema, clumped or clustered ring-enhancing NMEs, and high peak enhancement were significantly associated with histologic upgrade (P < 0.001). Conclusion: MRI detection, negative PR, and high Ki-67 levels are associated with a histologic upgrade in patients with biopsy-confirmed DCIS. Suspicious MRI features are more frequent in such patients.

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Section: Discussionsupporting

confidence: 93%

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ

et al. 2020

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“…In the present study, inter-observer agreement was almost perfect for the distributions (ICC ¼ 0.957; P < 0.001) and was excellent to good for the IEPs, whereas Machida et al (7) found only fair to moderate inter-observer agreement (k ¼ 0.26-0.45) for the distributions and moderate agreement (k ¼ 0.41-0.42) for a clustered ring IEP. We ascribe the better results obtained in the present study to the consensus pretesting conducted by the two readers using the BI-RADS lexicon fifth edition.…”

Section: Discussioncontrasting

confidence: 57%

“…Machida et al. (7) showed a clustered ring IEP had higher odds of containing an invasive component. In another study (24), the authors demonstrated clustered ring enhancement was significantly more common in microinvasive ductal carcinoma than in DCIS (57.1%).…”

Section: Discussionmentioning

confidence: 99%

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Patterns of malignant non-mass enhancement on 3-T breast MRI help predict invasiveness: using the BI-RADS lexicon fifth edition

et al. 2018

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Background Non-mass enhancements (NME) with invasive components account for 10-42% of total malignant NMEs. The factors associated with invasiveness on magnetic resonance imaging (MRI) could be useful for clinical assessment and treatment. Purpose To evaluate the clinical significances of the distributions and internal enhancement patterns (IEP) of malignant NMEs on 3-T breast MRI. Material and Methods A total of 448 consecutive women with newly diagnosed breast cancer that had undergone preoperative MRI and surgery between February 2013 and March 2016 were identified. After exclusions, 72 malignant NMEs without a mass in 72 women (mean age = 51.5 years) were included. Two readers independently assessed distributions and IEPs of NME, according to the Breast Imaging Reporting and Data System lexicon fifth edition. Collected data included the presence of invasion and histopathologic factors. Results A clustered ring IEP was significantly associated with invasive cancer (75.0%, P = 0.001, Reader1; 72.9%, P < 0.001, Reader 2), absence of necrosis (79.0%, P < 0.001; 72.1%, P < 0.001, respectively), and high Ki-67 expression (74.2%, P = 0.048; 74.2%, P = 0.003, respectively). A clumped IEP was related to ductal carcinoma in situ (33.3%, P = 0.025; 50.0%, P = 0.001, respectively), absence of lymph node metastasis (24.1%, P = 0.029; 31.5%, P = 0.030, respectively), and presence of necrosis (34.5%, P = 0.003; 44.8%, P = 0.001, respectively). Conclusion The presence of a clustered ring IEP in patients with breast cancer was found to be significantly associated with invasive breast cancer and high Ki-67 expression.

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“…With increased utilization of MRI, many NME lesions have been detected incidentally in benign and malignant lesions. The features of NME lesions on MRI, with the highest positive predictive values (PPV) for malignancy were segmental distribution, clustered ring, or clumped enhancement (6–9). Contrast-enhanced breast MRI achieves high sensitivity in detecting NME lesions, but it has relatively low specificity in distinguishing between benign and malignant lesions.…”

Section: Introductionmentioning

confidence: 99%

The cone-beam breast computed tomography characteristics of breast non-mass enhancement lesions

Kang

Zhong

2020

Acta Radiol

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Background Cone-beam computed tomography (CBBCT) of the breast is emerging as a way of improving breast cancer diagnostic yield. Purpose To find characteristics of non-mass enhancement (NME) lesions on breast CBBCT and to identify the characteristics that distinguish malignant and benign lesions. Material and Methods Breast CBBCT images of 84 NME lesions were analyzed. Internal enhancement distribution and patterns, calcification distribution and suspicious morphology, and ΔHU enhancement values were compared between post-contrast and pre-contrast malignant and benign lesions. Univariate analyses were applied to find the strongest indicators of malignancy, and logistic regression analysis was used to develop a fitting equation for the combined diagnostic model. Results In the 84 NME lesions, the indicators of malignancy were as follows: segmental enhancement distribution ( P = 0.011, 53.62% sensitivity, 86.67% specificity, 94.87% positive predictive value [PPV], and 28.89% negative predictive value [NPV]), clumped internal enhancement patterns ( P = 0.017, 50.72% sensitivity, 86.67% specificity, 94.59% PPV, and 27.66% NPV), ΔHU ≥ 93.57 Hounsfield units (HU) ( P = 0.004, 66.67% sensitivity, 73.33% specificity, 92.00% PPV, and 32.35% NPV), and NME lesions with calcification ( P = 0.002, 36.23% sensitivity, 20.00% specificity, 82.14% PPV, and 67.57% NPV). The fitting equation for the combined diagnostic model was as follows: Logit (P) = –0.579 +1.318 × enhancement distribution + 1.000 × internal enhancement patterns + 1.539 × ΔHU value + 1.641 ×NME type. Conclusion Individual diagnostic criteria based on breast CBBCT characteristics (segmental enhancement distribution, clumped internal enhancement patterns, ΔHU values > 93.57 HU, and NME lesions with calcification) had high specificity and PPV; when combined, they had high sensitivity in predicting malignant NME lesions.

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Descriptors of Malignant Non-mass Enhancement of Breast MRI

Cited by 17 publications

References 25 publications

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ

The role of MRI and clinicopathologic features in predicting the invasive component of biopsy-confirmed ductal carcinoma in situ

Patterns of malignant non-mass enhancement on 3-T breast MRI help predict invasiveness: using the BI-RADS lexicon fifth edition

The cone-beam breast computed tomography characteristics of breast non-mass enhancement lesions

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