Predictive value of thrombus susceptibility for cardioembolic stroke by quantitative susceptibility mapping.

BACKGROUND

The hypointense blooming signal of thrombi on susceptibility-weighted imaging (SWI), known as the susceptibility vessel sign (SVS), is predictive of cardioembolic stroke. The SVS originates from the local magnetic susceptibility effect; thus, the susceptibility value of thrombi may provide useful information in discriminating stroke etiology. We aim to utilize quantitative susceptibility mapping (QSM) to assess thrombus's susceptibility value in acute ischemic stroke patients and explore the relationship of thrombus susceptibility with cardioembolic stroke.

METHODS

From 2018 to 2020, 132 consecutive acute ischemic stroke patients with middle cerebral artery occlusion were recruited within 48 hours of onset. All patients underwent a three-dimensional multi-echo SWI scan using a 3 Tesla magnetic resonance imaging scanner. The SVS presence and the diameter of the SVS-related hypointense signal were assessed on SWI. QSM was applied to compute the susceptibility value of the thrombus. The receiver operating characteristic (ROC) methodology was used to define the optimal cutoff value of the susceptibility in QSM and the diameter on SWI for predicting cardioembolic stroke.

RESULTS

The SVS was identified in 93 (70.5%) patients with symptomatic middle cerebral artery occlusion and was significantly associated with cardioembolism. The hyperintense signal on QSM in the corresponding middle cerebral artery occlusion was present in 116 (87.9%) patients. ROC analysis indicated that thrombus susceptibility had a greater area under the curve than that of the SVS diameter (0.88 0.70, P<0.001) and that the optimal cutoff value of thrombus susceptibility for cardioembolism was 0.35 ppm. Multivariate analysis demonstrated that thrombus susceptibility (≥0.35 ppm) was an independent predictor of cardioembolic stroke (odds ratio =20.75; 95% CI, 7.19-59.87; P<0.001), with sensitivity, specificity, a positive predictive value, and a negative predictive value of 85.2%, 80.8%, 75.4%, and 88.7%, respectively, while the SVS presence showed sensitivity, specificity, a positive predictive value, and a negative predictive value of 90.7%, 43.6%, 87.2%, and 52.7%, respectively.

CONCLUSIONS

Thrombus susceptibility provides superior diagnostic performance over the SVS for discriminating between cardioembolism and other stroke subtypes. Quantitative susceptibility measurements of thrombi may help predict cardioembolic stroke in patients with acute middle cerebral artery occlusion.