Predictive value of flat-panel CT for haemorrhagic transformations in patients with acute stroke treated with thrombectomy.

INTRODUCTION: Haemorrhagic transformations are pejorative for patients with acute ischaemic stroke (AIS). We estimated flat-panel CT performances to detect brain parenchymal hyperdense lesions immediately after mechanical thrombectomy directly on the angiography table in patients with AIS, and its ability to predict haemorrhagic transformation. We also evaluated an easy-reading protocol for post-procedure flat-panel CT evaluation by clinicians to enable them to determine the potential risk of haemorrhage.

METHODS: Two neuroradiologists retrospectively reviewed post-procedural flat-panel CT and 24 h follow-up imaging. We evaluated hyperdense lesions on flat-panel CT to predict the occurrence of haemorrhagic transformation within 24 h detected with conventional imaging.

RESULTS: Of 63 patients, 60.3% presented post-procedural parenchymal hyperdensity and 54.0% had haemorrhagic transformation. Significantly more patients with hyperdense lesions on post-thrombectomy flat-panel CT presented haemorrhagic transformation (84.2% vs 8.0%; p<0.0001). No significant haemorrhagic transformations were detected for patients without parenchymal hyperdensity. Sensitivity and specificity of hyperdense lesions on flat-panel CT for the prediction of haemorrhagic transformation were 94.1% (80.3-99.3%) and 79.3% (60.3-92.0%), respectively. The positive and negative predictive values for the occurrence of haemorrhage were 84.2% (68.8-94.0%) and 92.0% (74.0-99.0%), respectively. For significant parenchymal haemorrhage type 2, sensitivity and negative predictive values were 100%. We observed good homogeneity between the different readers. Hyperdensity on post-procedural flat-panel CT was associated with a tendency for higher risk of death and lower risk of good clinical outcome.

CONCLUSIONS: Flat-panel CT appears to be a good tool to detect brain parenchymal hyperdensities after mechanical thrombectomy in patients with AIS and to predict haemorrhagic transformation.