• Machine-learning algorithm radiomics can help to differentiate primary central PCNSL from GBM. • This approach yields a higher diagnostic accuracy than visual analysis by radiologists. • Radiomics can strengthen radiologists' diagnostic decisions whenever conventional MRI sequences are available.

MR findings of early infectious spondylodiscitis are non-specific and may be confused with those of other conditions. Therefore, it is important to recognize early MR signs of conditions, such as inappreciable cortical changes in endplates, confusing marrow signal intensities of vertebral bodies, and inflammatory changes in paraspinal soft tissues, and subligamentous and epidural spaces. In addition, appreciation of direct inoculation, such as in iatrogenic spondylodiscitis may be important, because the proportion of patients who have undergone recent spine surgery or a spinal procedure is increasing. In this review, the authors focus on the MR findings of early spondylodiscitis, atypical findings of iatrogenic infection, and the differentiation between spondylodiscitis and other disease entities mimicking infection.

The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12-20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834-0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.

B reast MRI has been commonly used for cancer staging in women with newly diagnosed breast cancer, although controversy remains regarding its generalized use (1,2). In this preoperative setting, breast MRI has been reported to depict additional occult cancer in 10%-30% of ipsilateral breasts (3-5) and in 3%-5% of contralateral breasts in women with breast cancer (3,6,7). Furthermore, preoperative MRI features have been suggested as prognostic imaging markers that can be used to predict outcomes (8)(9)(10)(11)(12). Research is ongoing to identify reliable MRI biomarkers that can guide clinicians in decision making and potentially enable personalized treatment for breast cancer.Breast dynamic contrast material-enhanced (DCE) MRI depicts detailed morphologic features of breast tumors and reveals enhancement kinetics, which may reflect angiogenesis. Commercially available computer-aided diagnosis (CAD) systems provide clinicians with quantitative kinetic information regarding breast tumors on a pixel-by-pixel basis. These CAD systems have been shown to increase the specificity of DCE MRI diagnoses compared with assessments by radiologists through the exclusion of lesions with low threshold enhancement; moreover, they can reduce interpretation time by performing automatic analyses (13)(14)(15). Recent studies have suggested that survival outcomes and CAD-measured kinetic features of breast cancer as observed at preoperative MRI are associated. Kim et al showed that higher values of peak enhancement and washout component were associated with worse disease-free survival (10). Nam et al also found a relationship between higher peak enhancement and poor diseasefree survival (11). However, to our knowledge, there have been no studies of the associations between CAD-extracted kinetic features and distant metastasis outcomes in women with breast cancer. Because angiogenesis plays an important role in tumor growth, tumor progression, and metastasis (16,17), there is a potential for tumor enhancement kinetics to be associated with distant metastasis outcomes.

Background The associations between diffusion kurtosis imaging (DKI)‐derived parameters and clinical prognostic factors of breast cancer have not been fully evaluated; this knowledge may have implications for outcome prediction and treatment strategies. Purpose To determine associations between quantitative diffusion parameters derived from DKI and diffusion‐weighted imaging (DWI) and the prognostic factors and molecular subtypes of breast cancer. Study Type Retrospective. Population A total of 383 women (mean age, 53.8 years; range, 31–82 years) with breast cancer who underwent preoperative breast MRI including DKI and DWI. Field Strength/Sequence A 3.0 T; DKI using a spin‐echo echo‐planar imaging (EPI) sequence (b values: 200, 500, 1000, 1500, and 2000 sec/mm2), DWI using a readout‐segmented EPI sequence (b values: 0 and 1000 sec/mm2) and dynamic contrast‐enhanced breast MRI. Assessment Two radiologists (J.Y.K. and H.S.K. with 9 years and 1 year of experience in MRI, respectively) independently measured kurtosis, diffusivity, and apparent diffusion coefficient (ADC) values of breast cancer by manually placing a regions of interest within the lesion. Diffusion measures were compared according to nodal status, grade, and molecular subtypes. Statistical Tests Kruskal–Wallis test, Mann–Whitney U test with Bonferroni correction, receiver operating characteristic (ROC) analysis, and multivariate logistic regression analysis. (Statistical significance level of P < 0.05). Results All diffusion measures showed significant differences according to axillary nodal status and histological grade. Kurtosis showed significant differences among molecular subtypes. The luminal subtype (median 1.163) showed a higher kurtosis value compared to the HER2‐positive (median 0.962) or triple‐negative subtypes (median 1.072). ROC analysis for differentiating HER2‐positive from luminal subtypes revealed that kurtosis yielded the highest area under the curve of 0.781. In multivariate analyses, kurtosis remained a significant factor associated with differentiation between HER2‐positive and luminal (odds ratio [OR] = 0.993), triple‐negative and luminal (OR = 0.995), and HER2‐positive and triple‐negative subtypes (OR = 0.994). Data conclusion Quantitative diffusion parameters derived from DKI and DWI are associated with prognostic factors for breast cancer. Moreover, DKI‐derived kurtosis can help distinguish between the molecular subtypes of breast cancer. Evidence Level 4 Technical Efficacy 3

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Objective: To determine whether shear-wave elastography (SWE)-measured tumor stiffness is associated with disease-free survival in females with early-stage invasive breast cancer. Methods: This retrospective study included 202 consecutive females (mean age, 52.9 years; range, 25–84 years) with newly diagnosed T1–two breast cancer who underwent preoperative SWE between April 2015 and January 2016. Tumor stiffness was assessed and quantitative SWE features of each breast lesion were obtained by a breast radiologist. Cox proportional hazards models were used to identify associations between SWE features and disease-free survival after adjusting for clinicopathologic factors. Results: Fifteen (7.4%) patients exhibited recurrence after a median follow-up of 56 months. Mean (Emean), minimum, and maximum elasticity values were higher in females with recurrence than in those without recurrence (184.4, 138.3, and 210.5 kPa vs 134.9, 101.7, and 163.6 kPa, respectively; p = 0.005, p = 0.005, and p = 0.012, respectively). Receiver operating characteristics curve analysis for prediction of recurrence showed that Emean yielded the largest area under the curve (0.717) among the quantitative SWE parameters, and the optimal cut-off value was 121.7 kPa. Multivariable Cox proportional hazards analysis revealed that higher Emean (>121.7 kPa) [adjusted hazard ratio (HR), 10.01; 95% CI: 1.31–76.33; p = 0.026] and lymphovascular invasion (adjusted HR, 7.72; 95% CI: 1.74–34.26; p = 0.007) were associated with worse disease-free survival outcomes. Conclusion: Higher SWE-measured Emean was associated with worse disease-free survival in females with early-stage invasive breast cancer. Advances in knowledge: Tumor stiffness assessed with shear-wave elastography might serve as a quantitative imaging biomarker of disease-free survival in females with T1–two breast cancer.