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
Keywords : analysis,Baltimore,Decision Support Systems,Clinical,diagnosis,Diagnosis,Computer-Assisted,Diagnosis,Differential,etiology,Evidence-Based Medicine,Fractures,Compression,Humans,Magnetic Resonance Imaging,methods,Online Systems,pathology,Radiology,Spinal Fractures,Spinal Neoplasms,Thoracic Vertebrae,, Online,Evidencebased,Decision,Support,System, pain consultants
Date of Publication : 2011 Jun
Authors : Wang KC;Jeanmenne A;Weber GM;Thawait SK;Carrino JA;
Organisation : Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Hospital, 601 North Caroline Street, Baltimore, MD 21287, USA. kenwang@stanfordalumni.org
Journal of Publication : J Digit Imaging
Pubmed Link : https://www.ncbi.nlm.nih.gov/pubmed/20680384
The London Spine Unit : Harley Street UK. Specialists in Cutting Edge Technologies for Spinal Surgery
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