The diagnostic accuracy of the abbreviated breast MRI was not inferior to that of the conventional full diagnostic interpretation, although a slight decline in interobserver agreement was observed.

Metabolic tumour volume (MTV) and total lesion glycolysis (TLG) are positron-emission tomography/computed tomography (PET/CT) variables for predicting multiple myeloma's (MM) outcome. We retrospectively investigated and compared the predictive value of MTV, TLG and high-risk PET/CT variables in clinical practice in 185 patients with newly diagnosed symptomatic MM. High-risk PET/CT findings were defined as the presence of at least one of the following: more than three focal lesions, maximum standardised uptake value (SUV max) >4Á2 and extramedullary disease. MTV was defined as the volume of myeloma lesions visualised on PET/CT with SUV ≥ 2Á5. TLG was calculated as the sum of the product of the average SUV and MTV of all lesions. The mortality prediction optimal cutoff values for MTV and TLG were 56Á4 cm 3 and 166Á4 g, respectively. High-burden MTV (≥56Á4 cm 3), TLG (≥166Á4 g) and high-risk PET/CT findings differed significantly in progression-free survival (PFS) and overall survival (OS). High-burden MTV and TLG findings also predicted survival outcomes in young patients (age <75 years) and patients with high-risk chromosomal abnormalities. High-burden MTV and TLG independently predicted both worse PFS and OS. Pre-treatment MTV and TLG independently predicted survival outcomes in clinical practice and may be more useful than high-risk PET/CT variables.

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BackgroundA new software version of VolparaDensity (Volpara Algorithm version 1.5.1) is capable of calculating volumetric breast density (VBD) using either full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT) images. In this preliminary study, we evaluated the feasibility and consistency of this new automated software.FindingsRaw data from both DBT and FFDM were acquired from women breast cancer screening at our institution between April and August 2015 using. The DBT and FFDM images obtained under a single compression were collected and VBD was measured using fully automated software. A paired t test was used to analyze differences in the VBD calculated from paired FFDM and DBT images. The correlation coefficient (R value) was calculated and p < 0.05 was considered significant. Dualmodality images were acquired in 160 women; VBD data were available for all but one. There was a significant difference in the VBD of individual breasts calculated from DBT and FFDM and when data were compared per case (<0.001 and p = 0.006, respectively). There were very good to excellent correlations between data from FFDM and from DBT (R = 0.78, p < 0.0001; per breast, R = 0.89, p < 0.0001, per case, R = 0.91, p < 0.0001).ConclusionsVBD from DBT was well correlated to that from FFDM, though significant differences were observed between the two.

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Purpose:To compare positive predictive values (PPVs) of linearly distributed nonmass enhancement (NME) with linear and branching patterns and to identify imaging characteristics of NME that would enable classification as Breast Imaging Reporting and Data System category 3 lesions. Materials andMethods:The institutional review board approved this retrospective study and waived the requirement to obtain informed consent. Reports of breast magnetic resonance (MR) examinations (n = 9453) that described NME were reviewed from examinations performed at the study institution from January 2008 to December 2011. NME with linear distribution was allocated to one of two subtypes: linear pattern (arrayed in a line) or branching pattern (with branches). The x 2 test, Fisher exact test, or Student t test was performed for univariate analyses. Factors that showed a significant association with outcome at univariate analyses were assessed with multivariate analyses by using a logistic regression model. Interobserver agreement of the two subtypes between initial interpretation and the interpretation by two additional radiologists who were blinded to any clinical or pathologic information was evaluated with k analysis. Results:Within the 156 linearly distributed NME lesions, the PPV of the branching pattern (71 of 95 lesions [75%]; 95% confidence interval [CI]: 66%, 84%) was significantly higher than that of the linear pattern (five of 61 lesions [8%]; 95% CI: 1%, 15%) (P , .0001). The PPV of linear pattern lesions smaller than 1 cm was 0% (0 of 30 lesions; 95% CI: 0%, 0%). At multivariate analysis, branching pattern and NME lesion size of 1 cm or greater were significant predictors of malignancy (P , .0001 [odds ratio: 21.6; 95% CI: 7.5, 62.2] and P = .015 [odds ratio: 5.8; 95% CI: 1.4, 24.0], respectively). Substantial interobserver agreement was obtained for differentiating the two subtypes, with k values of 0.64 (95% CI: 0.51, 0.76), 0.70 (95% CI: 0.59, 0.82), and 0.64 (95% CI: 0.51, 0.76) between the initial interpreter and reviewer 1, the initial interpreter and reviewer 2, and reviewer 1 and reviewer 2, respectively. Conclusion:The branching pattern was a significantly stronger predictor of malignancy than was the linear pattern. NME lesions with a linear pattern that are smaller than 1 cm can be managed with follow-up.q RSNA, 2015

Changes of FDG uptake are useful for evaluating individual bone metastases in cases of breast cancer during therapy. Lytic change on CT images suggests progression of bone metastasis. The lysis-progression/sclerosis-improvement pattern was observed in the majority of subjects, but a sclerosis-progression pattern was also observed. The hybrid pattern of increase of FDG uptake on PET/lytic change on CT is most accurate to show progression of bone metastases. Assessments of these processes during therapy are necessary for the precise evaluation of bone metastases.

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