Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for breast cancer diagnosis and treatment planning. Nevertheless, due to the multi-temporal nature of DCE-MRI data, the assessment of early stage breast cancer is a challenging task. In this study, we applied an unsupervised clustering approach and cluster validation technique to the analysis of malignant intral-tumoral kinetic curves in DCE-MRI. K-means cluster analysis was performed from real world malignant tumor cases and the data were transformed into an optimal number of reference patterns representative each cluster. The optimal number of clusters was estimated by a cluster validation index, which was calculated with the ratio of inter-class scatter to intra-class scatter. This technique then classifies tumor specific patterns from a given MRI data by measuring the vector distances from the reference pattern set, and compared the result from the k-means clustering with that from three-time-points (3TP) method, which represents a clinical standard protocol for analysis of tumor kinetics. The evaluation of twenty five cases indicates that optimal k-means clustering reflects partitioning intra-tumoral kinetic patterns better than the 3TP technique. This method will greatly enhance the capability of radiologists to identify and characterize internal kinetic heterogeneity and vascular change of a tumor in breast DCE-MRI.

BackgroundExosomes are small membrane vesicles (40–150 nm) of endocytic origin secreted by many types of cells and engage in cell-to-cell communication by transferring proteins, microRNAs, mRNA, and lipid to recipient cells. Exosomes are also identified in various biological fluids including blood, urine, amniotic fluid, saliva, malignant ascites, and synovial fluid. Until now, the role of exosomes from synovial fluid (SF) on human osteoclastogenesis is unknown.ObjectivesWe aimed to identify the characteristics of synovial exosomes and evaluate the effects on human osteoclastogenesis.MethodsSynovial exosomes were isolated from SF of rheumatoid arthritis (RA), osteoarthritis (OA), ankylosing spondylitis (AS), and gout patients using ExoQuick (System Biosciences, USA). Monocytes were isolated from human peripheral blood mononuclear cell and were differentiated into macrophages by treatment of 20 ng/ml recombinant human macrophage colony-stimulating factor (M-CSF) for 3–4 days. Then, macrophages were incubated with synovial exosomes in alpha-MEM supplemented with 10% FBS and 1% penicillin/streptomycin for 9–10 days. Osteoclast differentiation was evaluated by tartrate resistant acid phosphatase stain. Exosomes from RA (n=11), OA (n=5), AS (n=6), and gout (n=6) patients were quantified by measuring acetylcholinesterase activity in colorimetric assay.ResultsThe number of synovial exosomes isolated from same volume of SF from RA, OA, AS, and gout patients was assessed. We found that exosomes are abundant in SF of RA, AS, and gout patients compared to OA patients. (mean ± SEM 7.36×107±1.35×107, 9.91×107±2.50×107, 7.50×107±2.17×107 vs. 2.66×107±0.42×107). Interestingly, the number of exosomes from AS SF was significantly higher (by 3.72 fold, p=0.0476) than exosomes from OA SF. Exosomes from RA, OA, AS, and gout patients induced proliferation and osteoclast formation without M-CSF and receptor activator of nuclear factor kappa-B ligand (RANKL) (Figure 1), which is essential to proliferation and differentiation of osteoclast. Noticeably, exosomes from RA SF had higher potential on osteoclast differentiation than other three diseases. (20.28±14.28 fold vs. 2.38±0.42 fold).ConclusionsOur results suggest that exosomes from SF of various inflammatory diseases might have differential functional roles in osteoclast differentiation and the number of exosomes may be associated with inflammatory conditions.ReferencesL. Raimondi et al. Oncotarget 2015 May 30; 6(15): 13772–13789C Théry et al. Nat Rev Immunol 2002 Aug; 2(8): 569–579RJ Simpson J et al. Proteomics 2008 Oct; 8(19): 4083–4099Disclosure of InterestNone declared

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