Dark Diffusion Sign: A Novel MRI Predictor of Hemorrhagic Transformation in Patients with Stroke Treated with...

Intracerebral hemorrhagic transformation (HT) is associated with poor outcome after reperfusion therapies in patients with stroke but is difficult to anticipate. Some patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) can exhibit a lenticular heterogeneous signal on their baseline diffusion-weighted imaging that we called the dark diffusion sign (DDS). Our aim was to evaluate whether the presence of the DDS on pretreatment MRI of patients with LVO-AIS is associated with increased risk of HT after endovascular therapy (EVT).

Participants from the French Acute Multimodal Imaging Study to Select Patients for Mechanical Thrombectomy (FRAME) who had LVO-AIS treated with EVT were included. Association of DDS on pretreatment MRI with posttreatment lenticular nucleus hemorrhagic transformation (LNHT) 24 hours postreperfusion as well as the association with the 3-month functional outcome were evaluated by using univariable and multivariable analyses. The same statistical methods were used to evaluate the determinants of the DDS.

One hundred twenty-seven patients were included (mean age 70 years old, 47% women). DDS was present in the baseline MRI of 57 patients (44.9%) and 55 (43.3%) had lenticular hemorrhagic transformation on posttreatment imaging. DDS was present in 36 patients (65.5%) who experienced posttreatment LNHT compared with 21 (29.2%) in those without HT (P = .0001). In multivariable analysis, DDS was independently associated with HT in LN at 24 hours (OR: 4.52; 95% CI, 1.89-11.37; P = .0009) but not with the 3-month functional outcome. NIHSS severity at baseline was the only determinant of the DDS.

DDS on pretreatment imaging could be an independent predictor of HT but was not associated with the functional outcome. Pathophysiologic mechanisms underlying DDS remain to be investigated. The results must be confirmed by further studies, given the small sample size and the population characteristics.