0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      CT image-based biomarkers for opportunistic screening of osteoporotic fractures: a systematic review and meta-analysis

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The use of opportunistic computed tomography (CT) image-based biomarkers may be a low-cost strategy for screening older individuals at high risk for osteoporotic fractures and populations that are not sufficiently targeted. This review aimed to assess the discriminative ability of image-based biomarkers derived from existing clinical routine CT scans for hip, vertebral, and major osteoporotic fracture prediction. A systematic search in PubMed MEDLINE, Embase, Cochrane, and Web of Science was conducted from the earliest indexing date until July 2023. The evaluation of study quality was carried out using a modified Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. The primary outcome of interest was the area under the curve (AUC) and its corresponding 95% confidence intervals (CIs) obtained for four main categories of biomarkers: areal bone mineral density (BMD), image attenuation, volumetric BMD, and finite element (FE)-derived biomarkers. The meta-analyses were performed using random effects models. Sixty-one studies were included in this review, among which 35 were synthesized in a meta-analysis and the remaining articles were qualitatively synthesized. In comparison to the pooled AUC of areal BMD (0.73 [95% CI 0.71–0.75]), the pooled AUC values for predicting osteoporotic fractures for FE-derived parameters (0.77 [95% CI 0.72–0.81]; p < 0.01) and volumetric BMD (0.76 [95% CI 0.71–0.81]; p < 0.01) were significantly higher, but there was no significant difference with the pooled AUC for image attenuation (0.73 [95% CI 0.66–0.79]; p = 0.93). Compared to areal BMD, volumetric BMD and FE-derived parameters may provide a significant improvement in the discrimination of osteoporotic fractures using opportunistic CT assessments.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00198-024-07029-0.

          Related collections

          Most cited references91

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Rayyan—a web and mobile app for systematic reviews

          Background Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan (http://rayyan.qcri.org), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Results Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Conclusions Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The meaning and use of the area under a receiver operating characteristic (ROC) curve.

            A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented. It is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a randomly chosen non-diseased subject. Moreover, this probability of a correct ranking is the same quantity that is estimated by the already well-studied nonparametric Wilcoxon statistic. These two relationships are exploited to (a) provide rapid closed-form expressions for the approximate magnitude of the sampling variability, i.e., standard error that one uses to accompany the area under a smoothed ROC curve, (b) guide in determining the size of the sample required to provide a sufficiently reliable estimate of this area, and (c) determine how large sample sizes should be to ensure that one can statistically detect differences in the accuracy of diagnostic techniques.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies.

              In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias, and the first 3 domains are also assessed in terms of concerns regarding applicability. Signalling questions are included to help judge risk of bias. The QUADAS-2 tool is applied in 4 phases: summarize the review question, tailor the tool and produce review-specific guidance, construct a flow diagram for the primary study, and judge bias and applicability. This tool will allow for more transparent rating of bias and applicability of primary diagnostic accuracy studies.
                Bookmark

                Author and article information

                Contributors
                anitha.dpraveen@sec.ethz.ch
                Journal
                Osteoporos Int
                Osteoporos Int
                Osteoporosis International
                Springer London (London )
                0937-941X
                1433-2965
                14 February 2024
                14 February 2024
                2024
                : 35
                : 6
                : 971-996
                Affiliations
                [1 ]GRID grid.514054.1, ISNI 0000 0004 9450 5164, Early Detection of Health Risks and Prevention, , Future Health Technologies, Singapore-ETH Centre (SEC), Campus for Research Excellence and Technological Enterprise (CREATE), ; 1 Create Way, CREATE Tower, #06-01, Singapore, 138602 Singapore
                [2 ]Department of Diagnostic and Interventional Radiology, University Hospital Ulm, ( https://ror.org/05emabm63) Ulm, Germany
                [3 ]GRID grid.6936.a, ISNI 0000000123222966, Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, , Technical University of Munich, ; Munich, Germany
                [4 ]GRID grid.6936.a, ISNI 0000000123222966, TUM-Neuroimaging Center, Klinikum rechts der Isar, , Technical University of Munich, ; Munich, Germany
                [5 ]Institute for Biomechanics, ETH-Zurich, ( https://ror.org/05a28rw58) Zurich, Switzerland
                Author information
                http://orcid.org/0000-0001-7174-139X
                http://orcid.org/0000-0002-8120-2223
                Article
                7029
                10.1007/s00198-024-07029-0
                11136833
                38353706
                148facc9-fc28-4b6f-8ca2-e23fdc52c4a3
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 17 September 2023
                : 19 January 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001381, National Research Foundation Singapore;
                Categories
                Review
                Custom metadata
                © International Osteoporosis Foundation and Bone Health and Osteoporosis Foundation 2024

                Orthopedics
                fractures,osteoporosis,bone mineral density,computed tomography,finite-element analysis,systematic review,meta-analysis

                Comments

                Comment on this article