We compared vertebral fracture assessment by semi-automated quantitative vertebral morphometry measurements with the conventional semi-quantitative (SQ) grading using lateral CT scout views. The semi-automated morphometry method showed good to excellent agreement with the visual SQ grading by radiologists for identification of vertebral fractures.
Introduction: Semi-automated quantitative vertebral morphometry (QM) measurements may enhance management of osteoporosis patients by providing an efficient means to identify vertebral fractures (VFx). We compared identification of prevalent VFx by semi-automated QM to SQ grading.
Methods: A non-radiologist performed semi-automated QM from CT lateral scout views in 200 subjects (102 men, 98 women, 65.8 ± 8.9 years) selected from the Framingham Heart Study Multidetector CT Study. VFx were classified in the QM approach based on using Genant's criteria for deformities, and compared with conventional SQ grading performed by experienced radiologists as the gold standard. The kappa (k) statistics, percent agreement (% Agree), sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) were computed.
Results: Among 200 subjects, 57 had mild and 41 had moderate or severe VFx by visual SQ grading. Per-person analyses showed excellent agreement between the two methods, with k = 0.780. The % Agree ranged from 86.7% to 91.2%, the SE was 81.3%-96%, and the SP was 86.5%-92%. Among 2,588 vertebrae analyzed, 107 had mild and 49 had moderate or severe VFx by visual SQ grading. Per-vertebra analyses revealed good agreement, with k = 0.580. Agreement between the methods tended to be highest in L1-L4 region. Agreement and validity measures were higher when only moderate and severe fractures were included.
Conclusion: The semi-automated quantitative vertebral morphometry measurements from CT lateral scout views provided good to excellent agreement with the standard SQ grading for assessment of prevalent vertebral fractures.