Digital mammography, cancer screening: Factors important for image compression

The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers

Biomarkers characterization of circulating tumour cells in breast cancer patients

Introduction: Increasing evidence supports the view that the detection of circulating tumor cells (CTCs) predicts outcomes of nonmetastatic breast cancer patients. CTCs differ genetically from the primary tumor and may contribute to variations in prognosis and response to therapy. As we start to understand more about the biology of CTCs, we can begin to address how best to treat this form of disease. Methods: Ninety-eight nonmetastatic breast cancer patients were included in this study. CTCs were isolated by immunomagnetic techniques using magnetic beads labelled with a multi-CK-specific antibody (CK3-11D5) and CTC detection through immunocytochemical methods. Estrogen receptor, progesterone receptor and epidermal growth factor receptor (EGFR) were evaluated by immunofluorescence experiments and HER2 and TOP2A by fluorescence in situ hybridization. We aimed to characterize this set of biomarkers in CTCs and correlate it with clinical-pathological characteristics. Results: Baseline detection rate was 46.9% ≥ 1 CTC/30 ml threshold. CTC-positive cells were more frequent in HER2-negative tumors (p = 0.046). In patients younger than 50 years old, HER2-amplified and G1-G2 tumors had a higher possibility of being nondetectable CTCs. Heterogeneous expression of hormonal receptors (HRs) in samples from the same patients was found. Discordances between HR expression, HER2 and TOP2A status in CTCs and their primary tumor were found in the sequential blood samples. Less that 35% of patients switched their CTC status after receiving chemotherapy. EGFR-positive CTCs were associated with Luminal tumors (p = 0.03). Conclusions: This is the largest exploratory CTC biomarker analysis in nonmetastatic BC patients. Our study suggests that CTC biomarkers profiles might be useful as a surrogate marker for therapeutic selection and monitoring since heterogeneity of the biomarker distribution in CTCs and the lack of correlation with the primary tumor biomarker status were found. Further exploration of the association between EGFR-positive CTCs and Luminal tumors is warranted

Nanobiopolymer for Direct Targeting and Inhibition of EGFR Expression in Triple Negative Breast Cancer

Treatment options for triple negative breast cancer (TNBC) are generally limited to cytotoxic chemotherapy. Recently, anti-epidermal growth factor receptor (EGFR) therapy has been introduced for TNBC patients. We engineered a novel nanobioconjugate based on a poly(β-L-malic acid) (PMLA) nanoplatform for TNBC treatment. The nanobioconjugate carries anti-tumor nucleosome-specific monoclonal antibody (mAb) 2C5 to target breast cancer cells, anti-mouse transferrin receptor (TfR) antibody for drug delivery through the host endothelial system, and Morpholino antisense oligonucleotide (AON) to inhibit EGFR synthesis. The nanobioconjugates variants were: (1) P (BioPolymer) with AON, 2C5 and anti-TfR for tumor endothelial and cancer cell targeting, and EGFR suppression (P/AON/2C5/TfR), and (2) P with AON and 2C5 (P/AON/2C5). Controls included (3) P with 2C5 but without AON (P/2C5), (4) PBS, and (5) P with PEG and leucine ester (LOEt) for endosomal escape (P/mPEG/LOEt). Drugs were injected intravenously to MDA-MB-468 TNBC bearing mice. Tissue accumulation of injected nanobioconjugates labeled with Alexa Fluor 680 was examined by Xenogen IVIS 200 (live imaging) and confocal microscopy of tissue sections. Levels of EGFR, phosphorylated and total Akt in tumor samples were detected by western blotting

Computer aided diagnosis of mammographic microcalcification clusters

Computer aided diagnosis techniques in medical imaging are developed for the automated differentiation between benign and malignant lesions and go beyond computer aided detection by providing cancer likelihood for a detected lesion given image and/or patient characteristics. A computer aided detection and diagnosis algorithm for mammographic calcification clusters is developed and evaluated. The emphasis is on the diagnostic component although the algorithm includes automated detection, segmentation, and classification steps based on wavelet filters and artificial neural networks. Classification features are selected primarily from descriptors of the morphology of the individual calcifications and the distribution of the cluster as well as patient\u27s demographics as input to the network. Te selected features are robust morphological and distributional descriptors, relatively insensitive to segmentation and detection errors such as false positive signals and variations among imaging sources or imaging equipment

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Stereoscopic representation of the breast from two mammographi