Purpose To determine the prognostic value of peritumoral edema identified at preoperative breast magnetic resonance (MR) imaging for disease recurrence in patients with invasive breast cancer. Materials and Methods Between January 2011 and December 2012, 353 women (median age, 49 years; range, 27-77 years) with invasive breast cancer who had undergone preoperative MR imaging and mastectomy or breast-conserving surgery were identified. Two radiologists independently reviewed peritumoral edema on the basis of the degree of the signal intensity surrounding the tumor on T2-weighted images. The association of disease recurrence with peritumoral edema and clinical-pathologic features was assessed by using the multivariate Cox proportional hazards model and the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI) indexes. Results Twenty-four patients (6.8%) had disease recurrence after 27.2 months of median follow-up. At multivariate analysis, higher N stage (hazard ratio = 4.84, P = .002) and the presence of lymphovascular invasion (hazard ratio = 2.48, P = .044) and peritumoral edema (hazard ratio = 2.77, P = .022) were independent factors associated with disease recurrence. IDI and continuous NRI showed significant improvement in the accuracy of the association with disease recurrence when peritumoral edema was added to established clinical-pathologic features (IDI = 0.061, P < .001; continuous NRI = 0.334, P = .012). Conclusion Peritumoral edema identified at preoperative MR imaging is independently associated with disease recurrence. Peritumoral edema assessment may provide better prognostication in patients with invasive breast cancer. RSNA, 2018.

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1037-1044.

Objectives The properties of brain tissue undergo dynamic changes during maturation. T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) are now simultaneously quantifiable within a clinically acceptable time, using a synthetic magnetic resonance imaging (MRI) sequence. This study aimed to provide age-specific reference values for T1, T2, and PD in children, using synthetic MRI. Materials and Methods We included 89 children (median age, 18 months; range, 34 weeks of gestational age to 17 years) who underwent quantitative MRI, using a multidynamic, multiecho sequence on 3 T MRI, between December 2015 and November 2016, and had no abnormal MRI/neurologic assessment findings. T1, T2, and PD were simultaneously measured in each of the 22 defined white matter and gray matter regions of interest. The measured values were plotted against age, and a curve fitting model that best explained the age dependence of tissue values was identified. Age-specific regional tissue values were calculated using a fit equation. Results The tissue values of all brain regions, except cortical PD, decreased with increasing age, and the robust negative association was best explained by modified biexponential model of the form Tissue values = T1 × exp (−C1 × age) + T2 × exp (−C2 × age). The quality of fit to the modified biexponential model was high in white matter and deep gray matter (white matter, R 2 = 97%–99% [T1], 88%–95% [T2], 88%–97% [PD]; deep gray matter, R 2 = 96%–97% [T1], 96% [T2], 49%–88% [PD]; cortex, 70%–83% [T1], 87%–90% [T2], 5%–27% [PD]). The white matter and deep gray matter changed the most dynamically within the first year of life. Conclusions Our study provides age-specific regional reference values, from the neonate to adolescent, of T1, T2, and PD, which could be objective tools for assessment of normal/abnormal brain development using synthetic MRI.