title: Quantitative assessment of myositis in thigh muscles using magnetic resonance imaging.
abstract: Magnetic resonance (MR) imaging has been suggested as a technique for diagnosing and monitoring myositis, an inflammatory muscle disease. To date, the assessment of disease from MR images has been by subjective visual analysis. We describe here an objective, semi-automatic, computer-based method for quantifying the degree of disease from MR images, without the need for a radiologist or physician trained in the visual assessment of the MR images. The method is based on analysis of the histogram of intensity values produced from the MR images. The analysis yielded measures of the intensity and extent of disease. These two measures were combined to produce a calculated myositis index (CMI) which described the degree of disease evident from the MR images. This index was compared with a clinical assessment of the patient's condition, based on currently accepted, invasive and non-invasive, non-imaging criteria. Receiver operating characteristic (ROC) curve analysis showed that calculated myositis index agreed at least as well with clinical assessment as did visual analysis (receiver operating characteristic area = 0.93 and 0.94, p = not significant (NS), respectively, for separating remission from disease). Even using only two central MR slices for each patient, the receiver operating characteristic area for calculated myositis index was 0.92, implying that very short acquisition times are possible. We conclude that quantitative histogram analysis of MR images can be successfully performed with minimal operator input and using few MR slices. Agreement with more invasive clinical assessment is good and the method has the advantages of repeatability, objectivity, and decreased scan and analysis time.
authors.affiliation: Department of Nuclear Medicine, CC, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, MD 20892-1180, USA.
authors.forename: M L
authors.initials: ML
authors.lastname: Bartlett
authors.forename: L
authors.initials: L
authors.lastname: Ginn
authors.forename: L
authors.initials: L
authors.lastname: Beitz
authors.forename: M L
authors.initials: ML
authors.lastname: Villalba
authors.forename: P
authors.initials: P
authors.lastname: Plotz
authors.forename: S L
authors.initials: SL
authors.lastname: Bacharach
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000473:pathology*; D009220:Myositis / Q000473:pathology*; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D013848:Thigh