17 research outputs found

    Perceived Sufficiency of Full-Field Digital Mammograms With and Without Irreversible Image Data Compression for Comparison with Next-Year Mammograms

    Get PDF
    Problems associated with the large file sizes of digital mammograms have impeded the integration of digital mammography with picture archiving and communications systems. Digital mammograms irreversibly compressed by the novel wavelet Access Over Network (AON) compression algorithm were compared with lossless-compressed digital mammograms in a blinded reader study to evaluate the perceived sufficiency of irreversibly compressed images for comparison with next-year mammograms. Fifteen radiologists compared the same 100 digital mammograms in three different comparison modes: lossless-compressed vs 20:1 irreversibly compressed images (mode 1), lossless-compressed vs 40:1 irreversibly compressed images (mode 2), and 20:1 irreversibly compressed images vs 40:1 irreversibly compressed images (mode 3). Compression levels were randomly assigned between monitors. For each mode, the less compressed of the two images was correctly identified no more frequently than would occur by chance if all images were identical in compression. Perceived sufficiency for comparison with next-year mammograms was achieved by 97.37% of the lossless-compressed images and 97.37% of the 20:1 irreversibly compressed images in mode 1, 97.67% of the lossless-compressed images and 97.67% of the 40:1 irreversibly compressed images in mode 2, and 99.33% of the 20:1 irreversibly compressed images and 99.19% of the 40:1 irreversibly compressed images in mode 3. In a random-effect analysis, the irreversibly compressed images were found to be noninferior to the lossless-compressed images. Digital mammograms irreversibly compressed by the wavelet AON compression algorithm were as frequently judged sufficient for comparison with next-year mammograms as lossless-compressed digital mammograms

    Radiologist-Patient Communication: Current Practices and Barriers to Communication in Breast Imaging.

    No full text
    © 2018 American College of Radiology Purpose: The aim of this study was to assess variability in radiologist-patient communication practices and barriers to communication among members of the Society of Breast Imaging (SBI). Methods: A 36-item questionnaire developed by the SBI Patient Care and Delivery Task Force was distributed electronically to SBI members to evaluate patient communication, education, and screening practices. Data from 14 items investigating patient communication (eg, practices, comfort, barriers to communication) were analyzed and compared with demographic variables using χ 2 or independent t tests as appropriate. Results: Ninety-three percent of radiologists reported that they directly communicate abnormal results of diagnostic mammographic examinations that require biopsy and malignant or high-risk biopsy results that require surgery. Radiologists (66%) and technologists (57%) often provide normal or negative diagnostic mammographic results. Most respondents were completely comfortable discussing the need for additional imaging, recommending biopsy, and discussing biopsy results directly with patients, and 71% rated their communication skills as excellent. Radiologists who spend less time in breast imaging reported only average communication skills. The most frequent barriers to communication were that practices were not set up for direct communication (loss of revenue) and discomfort with angry patients. Conclusions: Although variation in breast imaging communication practices exists among radiologists and practice types, the majority of radiologists directly communicate the most distressing results to patients, such as those regarding abnormal diagnostic mammographic findings requiring biopsies and abnormal biopsy results leading to cancer diagnoses and surgery. The majority of radiologists are completely comfortable with these conversations, but all feel that enhancing communication with patients will lead to greater patient satisfaction
    corecore