An Online Evidence-Based Decision Support System for Distinguishing Benign from Malignant Vertebral Compression Fractures by Magnetic Resonance Imaging Feature Analysis.
Decision support systems have been used to promote the practice of evidence-based medicine. Computer-assisted diagnosis can serve as one element of evidence-based radiology. One area where such tools may provide benefit is analysis of vertebral compression fractures (VCFs), which can be a challenge...
| Publicado en: | Journal of Digital Imaging Vol. 24; no. 3; pp. 507 - 516 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2011
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104894845&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104894845 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2011 vid: 24 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104894845 60502972 10.1007/s10278-010-9316-3 NLM20680384 104894845 ppf: 507 ppct: 9 formats: fmt: @attributes: type: P tig: atl: An Online Evidence-Based Decision Support System for Distinguishing Benign from Malignant Vertebral Compression Fractures by Magnetic Resonance Imaging Feature Analysis. aug: au: Wang, Kenneth Jeanmenne, Anthony Weber, Griffin Thawait, Shrey Carrino, John affil: Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, 601 North Caroline Street, Room 5165 Baltimore 21287 USA sug: subj: Decision Support Systems, Clinical Decision Making, Computer Assisted Fractures, Vertebral Compression Diagnosis World Wide Web Applications Fractures, Vertebral Compression Etiology ab: Decision support systems have been used to promote the practice of evidence-based medicine. Computer-assisted diagnosis can serve as one element of evidence-based radiology. One area where such tools may provide benefit is analysis of vertebral compression fractures (VCFs), which can be a challenge in MRI interpretation. VCFs may be benign or malignant in etiology, and several MRI features may help to make this important distinction. We describe a web-based decision support system for discriminating benign from malignant VCFs as a prototype for a more general diagnostic decision support framework for radiologists. The system has three components: a feature checklist with an image gallery derived from proven reference cases, a prediction model, and a reporting mechanism. The website allows users to input the findings for a case to be interpreted using a structured feature checklist. The image gallery complements the checklist, for clarity and training purposes. The input from the checklist is then used to calculate the likelihood of malignancy by a logistic regression prediction model. Standardized report text is generated that summarizes pertinent positive and negative findings. This computer-assisted diagnosis system demonstrates the integration of three areas where diagnostic decision support can aid radiologists: first, in image interpretation, through feature checklists and illustrative image galleries; second, in feature-based prediction modeling; and third, in structured reporting. We present a diagnostic decision support tool that provides radiologists with evidence-based guidance for discriminating benign from malignant VCF. This model may be useful in other difficult-diagnosis situations and requires further clinical testing. pubtype: Academic Journal doctype: diagnostic images pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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