Identification of prevalent vertebral fractures using CT lateral scout views: a comparison of semi-automated quantitative vertebral morphometry and radiologist semi-quantitative grading

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.

Intra-and inter-reader reliability of semi-automated quantitative morphometry measurements and vertebral fracture assessment using lateral scout views from computed tomography

Intra-and inter-reader reliability of semi-automated quantitative vertebral morphometry measurements was determined using lateral computed tomography (CT) scout views. The method requires less time than conventional morphometry. Reliability was excellent for vertebral height measurements, good for height ratios, and comparable to semi-quantitative grading by radiologists for identification of vertebral fractures.

INTRODUCTION

Underdiagnosis and undertreatment of vertebral fracture (VFx) is a well-known problem worldwide. Thus, new methods are needed to facilitate identification of VFx. This study aimed to determine intra- and inter-reader reliability of semi-automated quantitative vertebral morphometry based on shape-based statistical modeling (SpineAnalyzer, Optasia Medical, Cheadle, UK).

METHODS

Two non-radiologists independently assessed vertebral morphometry from CT lateral scout views at two time points in 96 subjects (50 men, 46 women, 70.3 ± 8.9 years) selected from the Framingham Heart Study Offspring and Third Generation Multi-Detector CT Study. VFxs were classified based solely on morphometry measurements using Genant's criteria. Intraclass correlation coefficients (ICCs), root mean squared coefficient of variation (RMS CV) and kappa (k) statistics were used to assess reliability.

RESULTS

We analyzed 1,246 vertebrae in 96 subjects. The analysis time averaged 5.4 ± 1.7 min per subject (range, 3.2-9.1 min). Intra-and inter-reader ICCs for vertebral heights were excellent (>0.95) for all vertebral levels combined. Intra-and inter-reader RMS CV for height measurements ranged from 2.5% to 3.9% and 3.3% to 4.4%, respectively. Reliability of vertebral height ratios was good to fair. Based on morphometry measurements alone, readers A and B identified 51-52 and 46-59 subjects with at least one prevalent VFx, respectively, and there was a good intra-and inter-reader agreement (k = 0.59-0.69) for VFx identification.

CONCLUSIONS

Semi-automated quantitative vertebral morphometry measurements from CT lateral scout views are convenient and reproducible, and may facilitate assessment of VFx.