英文摘要 |
This study uses Philips IQon Spectral CT imaging parameters including conventional CT, monoenergetic CT (40 keV), iodine density, iodine-no-water, and Z effective images to conduct a quantitative analysis on bone metastasis lesions. The feasibility of using various spectral CT imaging parameters to diagnose bone metastasis was discussed. Thirty patients with vertebral bone metastasis were selected and manually segmented. Deep learning was used to segment the normal vertebrae. The optimal threshold for identifying bone metastasis lesions was found by ROC analysis. Bone metastasis lesions and normal vertebrae showed significant differences in spectral CT, which were suitable for using a threshold to distinguish. The AUC of each parameter of the spectral CT images was greater than 0.9. The classification results showed that the effective Z image had the best AUC (0.942), while the image of the iodine density had the worst performance (0.905). The effective Z image also had the highest sensitivity (89.19%), and the iodine-no-water image had the highest specificity (93.32%). Different spectral CT imaging parameters can effectively identify bone metastases. |