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Non-mass enhancement (NME) in breast MRI is the most common feature of ductal carcinoma in situ (DCIS). We sought to evaluate the interobserver variability and positive predictive value (PPV) for malignancy of NME descriptors using the fifth edition BI-RADS lexicon focusing on the newly introduced “clustered ring enhancement” pattern. Breast MRIs of 129 patients who had undergone MRI-guided vacuum-assisted biopsy (VAB) in our institution were reviewed. Studies assessed as NME were classified according to the fifth edition BI-RADS lexicon by two breast radiologists. Consensus was reached by involving a third radiologist. Interobserver variability and PPV for malignancy were assessed. Seventy-two of 129 studies were assessed as NME. The disagreement rate in the first assessment step (mass vs. NME) was low at 9.3% (ĸ = 0.81, 95% confidence interval [CI] 0.71–0.91). The disagreement rate for distribution patterns was 23.6% (ĸ = 0.67, 95% CI 0.54–0.80) and 22.2% (ĸ = 0.69, 95% CI 0.56–0.81) for internal enhancement patterns. Clustered ring enhancement (PPV 53.85, p = 0.038) and segmental distribution (PPV 62.5%, p = 0.028) had the highest malignancy rates among internal enhancement and distribution patterns with a significant result; the combination of clustered ring enhancement and segmental distribution raised the malignancy rate by approximately 4% (PPV 66.67%, p = 0.049). There was a high agreement rate among readers when differentiating NME from mass lesions. The agreement rate was lower when assessing the distribution and internal enhancement pattern descriptors, but still substantial. The descriptors clustered ring enhancement and segmental distribution were significant predictors of malignancy. • Non-mass enhancement is a common morphological feature of non-invasive breast cancer (DCIS) in MRI. Differentiation between potentially malignant and benign changes may be very challenging. • Since clustered ring enhancement and segmental distribution are both significant predictors of malignancy, the awareness of this important finding, combined with high-quality image interpretation skills, may improve the tumor detection rate. • The combination of clustered ring enhancement and segmental distribution increases the positive predictive value for malignancy, which may be relevant for clinical practice.

Awareness of risk factors associated with impending fracture and its radiologic appearance allows early diagnosis, supports prophylactic surgical treatment, and prevents the multiple complications of a pathologic fracture. Because the femur is the most common long bone affected by metastatic bone lesions, we address this clinically relevant site in this review. The key to early detection of risky bone lesions is familiarity with the possible clinical presentation, biomechanical effects of the anatomical site (femoral head and neck, intertrochanteric zone, proximal diaphysis), and the lesion types (lytic, blastic, or mixed). Awareness of the possible treatment strategies depending on the characteristics just listed allows high-quality targeted reporting.