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  • Title: The necrosis sign in magnetic resonance-mammography: diagnostic accuracy in 1,084 histologically verified breast lesions.
    Author: Dietzel M, Baltzer PA, Vag T, Herzog A, Gajda M, Camara O, Kaiser WA.
    Journal: Breast J; 2010; 16(6):603-8. PubMed ID: 21070437.
    Abstract:
    Necrosis sign (NS) is a new descriptor for differential diagnosis of breast lesions in magnetic resonance (MR)-mammography (MRM). This study was designed: (a) to analyze diagnostic accuracy of NS in 1,084 histologically verified breast lesions, (b) to assess performance of NS in subgroups. This study was approved by the local ethical committee. All histologically verified lesions having undergone MR-mammography at our institution over 12 years were evaluated by experienced radiologists (> 500 MRM) according to standard protocols and study design (T1w; 0.1 mmol/kg bw gadolinium diethylenetriamine penta-acetic acid; T2-turbo spin echo (TSE)). Patients with history of breast biopsy (surgically, minimal-invasive), radiation- or chemotherapy ≤ 1 year before MRM were excluded. NS was assessed on T2w-TSE sequences and was rated positive if a hyperintense center in a hypointense lesion could be visualized (chi-squared test). One thousand and eighty-four lesions were available for statistical analysis (648: malignant, 436: benign). NS was significantly associated with malignancy (p < 0.001), providing specificity and positive predictive value (PPV) of 96.1% and 78.8%. Malignant lesions > 20 mm presented significantly more often NS (p < 0.001) than neoplasias ≤ 20 mm. There was no difference regarding prevalence of NS in small versus advanced benign lesions (n.s.), leading to better performance of NS in lesions > 20 mm (PPV: 87.8%). Correlation between NS and Grading of invasive carcinomas was significant. In this study of 1,084 lesions necrosis sign was a specific and highly predictive feature for differential diagnosis in MRM (Specificity: 96.1%; PPV: 78.8%). This particularly counts for advanced lesions (PPV 87.8%). As this new descriptor correlates with Grading, it could be used as an initial estimate of patient's prognosis.
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