Fast kilovoltage (KV)-switching dual-energy CT virtual noncalcium technique using different reconstruction kernels for identifying acute and chronic vertebral compression fractures.

UNLABELLED

The vertebral compression fractures (VCFs) represent an incidental finding on thoracic and abdominal dual-energy CT examinations (which use STND reconstruction kernel), which are associated with increased mortality. While the BONE reconstruction kernel shows a superior diagnostic accuracy to find fractures. This study showed STND and BONE reconstruction kernel both had excellent diagnostic performance to detect abnormal edema in acute VCFs.

PURPOSE

To investigate whether different reconstruction kernels (STND V.S. BONE) affect the diagnostic performance of dual-energy CT virtual noncalcium technique (VNCa) for identifying acute and chronic vertebral compression fractures (VCFs).

METHODS

This retrospective study included 31 consecutive patients with 79 VCFs who underwent both a dual-energy CT and a 3-T MR examination of the spine between August 2018 and March 2019. MR images served as the reference standard. Two independent and blinded radiologists evaluated all vertebral bodies for the presence of abnormal edema on color-coded overlay VNCa images. Two additional radiologists performed a quantitative analysis on VNCa images by calculating water content of vertebral bodies. Receiver operating characteristic curve (ROC) analysis was conducted. Area under the curve (AUC) was calculated.

RESULTS

MR imaging depicted 44 edematous and 35 nonedematous VCFs. In visual analysis, the AUC and AUC were 0.932 and 0.943. In quantitative analysis, water content results were significantly different between vertebrae with and without bone marrow edema on MR (P < 0.001). And the AUC and AUC were 0.851 and 0.850 respectively.

CONCLUSION

Visual and quantitative analysis of dual-energy CT VNCa technique had excellent diagnostic performance for identifying acute and chronic compression fractures; different reconstruction kernels did not matter.