MRI to Predict Nipple Involvement in Breast Cancer Patients

Piato, José Roberto Morales; Andrade, Roberta Dantas Jales Alves de; Chala, Luciano Fernandes; Barros, Nestor de; Mano, Max Senna; Melitto, Alnexadre Santos; Gonçalves, Rodrigo; Soares, José Maria; Baracat, Edmund Chada; Filassi, José Roberto

doi:10.2214/ajr.15.15187

Cited by 22 publications

(7 citation statements)

References 25 publications

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“…The incidence of malignant NAC invasion by underlying breast cancer varies in different studies from 5.6 to 24.6% [14][15][16]. One study showed that malignant invasion of the NAC by underlying breast [1,3,[7][8][9][10][11][12][13][14][15][16]. It was stated that both tumor nipple distance and abnormal enhancement extending from the tumor to the nipple base were the most important predictors of malignant NAC invasion on MRI [9,10].…”

Section: Discussionmentioning

confidence: 99%

Prediction of nipple-areolar complex involvement by breast cancer: role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

EL-Adalany

El-Razek

EL-Metwally

2021

Egypt J Radiol Nucl Med

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Background Skin-sparing and nipple-sparing mastectomies were considered as alternative techniques for modified radical mastectomy. In patients who are candidates for nipple-sparing mastectomy, preoperative assessment of the nipple-areolar complex (NAC) is essential for adequate surgical planning. Breast MRI is highly sensitive for cancer detection and has an important role in disease staging. The aim of this study was to estimate the role of DCE-MRI in predicting malignant NAC invasion by underlying breast cancer and assess the best predictors on MRI that can suspect malignant NAC invasion. Results Out of the 125 patients with breast cancer, 33 patients (26.4%) showed malignant NAC invasion. On basis of multivariate analysis, abnormal nipple enhancement, tumor nipple enhancement, tumor nipple distance ≤ 2 cm, and abnormal and asymmetric nipple morphology were all significant predictors of malignant NAC invasion (P < 0.001) with abnormal unilateral nipple enhancement as the most important independent MRI predictor of malignant NAC invasion (odds ratio = 61.07, 95% CI 12.81–291.22, P < 0.001). When combining more than positive suspicious MRI features, DCE-MRI had 66.6% sensitivity, 76% specificity, 50% PPV, 86.4% NPV, and 73.6% accuracy in prediction of malignant NAC invasion. Conclusion DCE-MRI could predict malignant NAC invasion with abnormal unilateral nipple enhancement as the most important independent MRI predictor.

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Section: Discussionmentioning

confidence: 99%

Prediction of nipple-areolar complex involvement by breast cancer: role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

EL-Adalany

El-Razek

EL-Metwally

2021

Egypt J Radiol Nucl Med

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“…As NSM gains popularity, the dilemma of prerequisites for this surgery becomes more relevant. At our institution, we have followed stringent criteria with one condition for preserving the NAC being a safe TND that could be reliably measured by MRI (21,22). For the present study, our inclusion criteria entailed a TND ≥2.0 cm as estimated by this imaging method.…”

Section: Discussionmentioning

confidence: 99%

Nipple-sparing mastectomy for early breast cancer: the importance of intraoperative evaluation of retroareolar margins and intra-nipple duct removal

Heinzen¹,

Barros²,

Carvalho³

et al. 2020

Gland Surg

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Background: Nipple-sparing mastectomy (NSM) is increasingly performed for breast cancer (BC) treatment. To ensure local control with this procedure, it is important to obtain clear surgical margins. Here, we aimed to estimate the confidence in intraoperative evaluation of the retroareolar margin (IERM) and the necessity of removing the intra-nipple ducts.Methods: In this retrospective cohort study, we evaluated 224 BC (infiltrating carcinoma 178, ductal carcinoma in situ 46) patients, who underwent NSM. IERM was determined via cytology and frozen sections. Following gland removal, the intra-nipple ducts were excised and embedded in paraffin for analysis.The retroareolar tissue was also paraffin-embedded and reanalyzed for definitive evaluation of retroareolar margins (DERM). The IERM predictive capacity in relation to DERM and the frequency of intra-nipple duct involvement were estimated.Results: IERM classified the sub-nipple areolar complex area as cancer-free in 219 cases (97.8%). The condition of clear retroareolar margin was confirmed by DERM in 216 cases (98.6%). The IERM accuracy was estimated as 98.6%. Ductal carcinoma in situ was detected in intra-nipple ducts using paraffin sections in 1.8% of the cases, despite clear IERM (4/219). Conclusions:In conclusion, IERM affords high accuracy and its results are suitable to manage the nippleareolar complex. Nevertheless, some patients may retain residual disease in the intra-nipple ducts; thus, these ducts should ideally be removed during NSM.

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“…Compared to mammography, which is a 2D imaging modality, breast MRI provides a 3D evaluation of the whole breast, thus reducing the loss of spatial information about tumour extent and location. For that reason, MRI has been considered as the method of choice to preoperatively predict occult nipple involvement [20, 21].…”

Section: Discussionmentioning

confidence: 99%

Nipple-sparing mastectomy: external validation of a three-dimensional automated method to predict nipple occult tumour involvement on preoperative breast MRI

et al. 2019

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Background Preoperative evaluation of nipple-areola complex (NAC) tumour involvement is crucial to select patients candidates for nipple-sparing mastectomy. Our aim was to validate a previously developed automated method able to compute the three-dimensional (3D) tumour-to-NAC distance (the most predictive parameter of nipple involvement), using magnetic resonance imaging (MRI) datasets acquired with a scanner and protocol different from those of the development phase. Methods We performed a retrospective analysis of 77 patients submitted to total mastectomy and preoperatively studied with MRI. The new method consisted of automated segmentation of both NAC and tumour and subsequent computation of the 3D distance between them; standard manual two-dimensional segmentation was independently performed. Paraffin-embedded section examination of the removed NAC was performed to identify the neoplastic involvement. The ability of both methods to discriminate between patients with and without NAC involvement was compared using receiver operating characteristic (ROC) analysis. Results The 3D tumour-to-NAC distance was correctly computed for 72/77 patients (93.5%); tumour and NAC segmentation method failed in two and three cases, respectively. The diagnostic performance of the 3D automated method at best cut-off values was consistently better than that of the 2D manual method (sensitivity 78.3%, specificity 71.4%, positive predictive value 87.5%, negative predictive value 56.3%, and AUC 0.77 versus 73.9%, 61.2%, 47.2%, 83.3%, and 0.72, respectively), even if the difference did not reach statistical significance ( p = 0.431). Conclusions The introduction of the 3D automated method in a clinical setting could improve the diagnostic performance in the preoperative assessment of NAC tumour involvement.

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MRI to Predict Nipple Involvement in Breast Cancer Patients

Abstract: Breast MRI is a safe noninvasive method to preoperatively evaluate breast cancer patients eligible for NSM with a high specificity and a high negative predictive value when enhancement between the index lesion and the nipple and nipple retraction are analyzed.

Cited by 22 publications

References 25 publications

Prediction of nipple-areolar complex involvement by breast cancer: role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

Prediction of nipple-areolar complex involvement by breast cancer: role of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)

Nipple-sparing mastectomy for early breast cancer: the importance of intraoperative evaluation of retroareolar margins and intra-nipple duct removal

Nipple-sparing mastectomy: external validation of a three-dimensional automated method to predict nipple occult tumour involvement on preoperative breast MRI

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