Whole-body MRI-based multivariate prediction model in the assessment of bone metastasis in prostate cancer.

PURPOSE

A whole-body MRI (WB-MRI) including T1, short time inversion recovery (STIR), diffusion-weighted imaging (high b value) was applied in our center for the detection of bone metastasis in prostate cancer (PCa) patients. We intended to assess the diagnostic performance of this examination.

METHODS

547 cases of PCa patients with higher risk of metastasis were referred to bone scintigraphy with SPECT/CT (BS + SPECT/CT) and whole-body MRI in Shanghai Changhai Hospital. Best valuable comparator (BVC) was applied for the final diagnosis of metastasis. A panel of radiologists interpreted the results. Decision curve analysis (DCA) and receiver operating characteristic curve (ROC) analysis were applied.

RESULTS

Bone metastasis was diagnosed in 110 cases, and others were non-metastatic by BVC. The area under the receiver operating characteristic curve (AUC) was higher in WB-MRI (0.778) than BS + SPECT/CT (0.634, p < 0.001). A WB-MRI-based prediction model was established with AUC of 0.877. Internal validation showed that the predictive model was well-calibrated. The DCA demonstrated that the model had higher net benefit than the BS + SPECT/CT-based model.

CONCLUSION

WB-MRI is more effective in identifying metastasis in PCa patients than BS + SPECT/CT. The prediction model combined WB-MRI with clinical parameters may be a promising approach to the assessment of metastasis.