6 research outputs found

    Histopathology Slide Indexing and Search: Are We There Yet?

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    The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-of-the-art histopathology slide search engines, Yottixel, SISH, and RetCCL, on three patients with solid tumors. We provide a qualitative assessment of each model's performance in providing retrieval results that are reliable and useful to pathologists. We found that all three image search engines fail to produce consistently reliable results and have difficulties in capturing granular and subtle features of malignancy, limiting their diagnostic accuracy. Based on our findings, we also propose a minimal set of requirements to further advance the development of accurate and reliable histopathology image search engines for successful clinical adoption

    Cardiovascular disease training for community health workers serving native Hawaiians and pacific people

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    M.S. University of Hawaii at Manoa 2013.Includes bibliographical references.It has been well documented that Native Hawaiians and other Pacific Peoples (NHPP) are disproportionately affected by cardiovascular disease (CVD) in the United States, and particularly in Hawaiʻi. Nationally, community health workers (CHW) have been shown to be effective in delivering CVD self-management education. They are utilized by clinics and health agencies for individual and group education, as well as in case management and outreach; however, they are often hired with no formal health education and with limited clinical experience. In Hawaiʻi, CHW are used extensively in community health centers (CHC) and throughout the Native Hawaiian Healthcare System (NHHS). A 2008 needs assessment of 19 CHC and the NHHS identified the training of CHW in CVD as a top priority. The focus of this thesis was to further develop and evaluate a CVD training program tailored specifically for CHW serving NHPP. A community-based participatory research (CBPR) framework was utilized to both identify this priority and guide the development of a training program. Our efforts were motivated by the hypothesis that CHW knowledge in CVD could be increased, and subsequently retained, through training that is both culturally competent and interactive. Specific aspects of culture-based education (CBE) were systematically incorporated throughout the development of the training. The resulting product, "Heart 101," is a 5-hour long training seminar that is taught by a multidisciplinary team and balances a PowerPoint guided lecture with interactive class games, group discussions, and role-play scenarios. To date, Heart 101 has been delivered nine times, reaching 162 individuals, primarily CHW. For our evaluations we examined participants from three training seminars held during 2010. Identical pre-, post-, and 6-month post-training CVD knowledge tests were administered to seminar participants to assess gain and retention of CVD knowledge. Additionally, participants were also asked to complete a satisfaction survey. The results of our analyses of changes in mean test scores revealed both significant gains in CVD knowledge from pre-to post-seminar, as well as retention of that knowledge measured at 6-months post-training. Participant feedback about their experience in Heart 101 was overwhelmingly positive. A subsequent analysis to investigate knowledge change by CVD subtopics compared the frequency of correct answers by question from pre-to post-seminar. Although there were clear increases in knowledge for all subtopics reviewed, we also found baseline understanding among participants to be stronger in clinical knowledge as opposed to that of the basic sciences. This finding provides us with a basis to strengthen the Heart 101 curriculum and may serve as a guide for the development of future CHW training programs. The demonstrated success of Heart 101 has positive implications for the standardization of CHW education and their professional development. Our findings show that a CHW training program like Heart 101 can be effective in providing the necessary tools for the further development of this important and growing segment of the healthcare workforce. As the utilization of CHW in efforts to ameliorate health disparities increases, so will the importance of their ability to assist in the delivery of chronic disease management directives

    Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis

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    To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future

    Plus Disease in Retinopathy of Prematurity: Diagnostic Trends in 2016 Versus 2007

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    To identify any temporal trends in the diagnosis of plus disease in retinopathy of prematurity (ROP) by experts. Reliability analysis. ROP experts were recruited in 2007 and 2016 to classify 34 wide-field fundus images of ROP as plus, pre-plus, or normal, coded as “3,” “2,” and “1,” respectively, in the database. The main outcome was the average calculated score for each image in each cohort. Secondary outcomes included correlation on the relative ordering of the images in 2016 vs 2007, interexpert agreement, and intraexpert agreement. The average score for each image was higher for 30 of 34 (88%) images in 2016 compared with 2007, influenced by fewer images classified as normal (P < .01), a similar number of pre-plus (P = .52), and more classified as plus (P < .01). The mean weighted kappa values in 2006 were 0.36 (range 0.21–0.60), compared with 0.22 (range 0–0.40) in 2016. There was good correlation between rankings of disease severity between the 2 cohorts (Spearman rank correlation ρ = 0.94), indicating near-perfect agreement on relative disease severity. Despite good agreement between cohorts on relative disease severity ranking, the higher average score and classifications for each image demonstrate that experts are diagnosing pre-plus and plus disease at earlier stages of disease severity in 2016, compared with 2007. This has implications for patient care, research, and teaching, and additional studies are needed to better understand this temporal trend in image-based plus disease diagnosis

    Plus Disease in Retinopathy of Prematurity

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    To identify patterns of interexpert discrepancy in plus disease diagnosis in retinopathy of prematurity (ROP). We developed 2 datasets of clinical images as part of the Imaging and Informatics in ROP study and determined a consensus reference standard diagnosis (RSD) for each image based on 3 independent image graders and the clinical examination results. We recruited 8 expert ROP clinicians to classify these images and compared the distribution of classifications between experts and the RSD. Eight participating experts with more than 10 years of clinical ROP experience and more than 5 peer-reviewed ROP publications who analyzed images obtained during routine ROP screening in neonatal intensive care units. Expert classification of images of plus disease in ROP. Interexpert agreement (weighted κ statistic) and agreement and bias on ordinal classification between experts (analysis of variance [ANOVA]) and the RSD (percent agreement). There was variable interexpert agreement on diagnostic classifications between the 8 experts and the RSD (weighted κ, 0–0.75; mean, 0.30). The RSD agreement ranged from 80% to 94% for the dataset of 100 images and from 29% to 79% for the dataset of 34 images. However, when images were ranked in order of disease severity (by average expert classification), the pattern of expert classification revealed a consistent systematic bias for each expert consistent with unique cut points for the diagnosis of plus disease and preplus disease. The 2-way ANOVA model suggested a highly significant effect of both image and user on the average score (dataset A: P < 0.05 and adjusted R2 = 0.82; and dataset B: P < 0.05 and adjusted R2 = 0.6615). There is wide variability in the classification of plus disease by ROP experts, which occurs because experts have different cut points for the amounts of vascular abnormality required for presence of plus and preplus disease. This has important implications for research, teaching, and patient care for ROP and suggests that a continuous ROP plus disease severity score may reflect more accurately the behavior of expert ROP clinicians and may better standardize classification in the future
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