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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