In:
Journal of Magnetic Resonance Imaging, Wiley, Vol. 46, No. 4 ( 2017-10), p. 1028-1036
Kurzfassung:
To investigate whether diffusion‐weighted imaging (DWI) features could assist in determining which high‐risk lesions identified on dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) and diagnosed on core needle biopsy (CNB) will upgrade to malignancy on surgical excision. Materials and Methods This Institutional Review Board (IRB)‐approved prospective study included participants with MRI‐detected Breast Imaging Reporting and Data System (BI‐RADS) 4 or 5 lesions with high‐risk pathology on CNB who underwent surgical excision. Twenty‐three high‐risk lesions detected on 3T breast MRI in 20 women (average age = 54 ± 9 years) were evaluated, of which six lesions (26%) upgraded to malignancy at surgery. DCE, DWI characteristics, and clinical factors were compared between high‐risk lesions that upgraded to malignancy on surgical excision and those that did not. Logistic regression modeling was performed to identify features that optimally predicted upgrade to malignancy, with performance described using area under the receiver operating characteristic curve (AUC). Results High‐risk lesions that upgraded on excision demonstrated lower apparent diffusion coefficient (ADC) than those that did not (median, 1.08 × 10 −3 mm 2 /s vs.1.39 × 10 −3 mm 2 /s, P = 0.046), and a trend of greater maximum lesion size (median, 24 mm vs. 8 mm, P = 0.053). There were no significant differences in lesion type (mass vs. nonmass enhancement, P = 1.0) or kinetic features ( P = 0.78 for peak initial enhancement; P = 1.0 for worst curve type) among the high‐risk cohorts. A model incorporating maximum lesion size and ADC provided optimal performance to predict upgrade to malignancy (AUC = 0.89). Conclusion ADC and maximum lesion size on MRI show promise for predicting which MRI‐detected high‐risk lesions will upgrade to malignancy at surgical excision. Level of Evidence: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1028–1036.
Materialart:
Online-Ressource
ISSN:
1053-1807
,
1522-2586
Sprache:
Englisch
Verlag:
Wiley
Publikationsdatum:
2017
ZDB Id:
1497154-9
