Niesen Wolf-Dirk, Schläger Axel, Reinhard Matthias, Fuhrer Hannah
Department of Neurology, University of Freiburg, Freiburg, Germany.
Department of Neurology, Medical Center Esslingen, Teaching Hospital of the University of Tuebingen, Esslingen, Germany.
J Neuroimaging. 2018 Jul;28(4):370-373. doi: 10.1111/jon.12510. Epub 2018 Mar 25.
The differentiation of primary intracerebral hemorrhage (ICH) from parenchymal hemorrhagic transformation within an ischemic infarction (PHI) is crucial in order to adapt therapeutic measures. We hypothesized that a distinction of ICH and PHI can be made at bedside via transcranial gray-scale and perfusion sonography.
We prospectively included 14 patients with intracranial hemorrhage on admission imaging in this pilot study. Differentiation between ICH and PHI was made either by cerebral magnetic resonance imaging or follow-up computed tomography scan. All patients were examined via gray-scale and perfusion sonography.
Eight patients were diagnosed with ICH, and 6 patients with PHI. Volumes of ICH did not differ between the two groups. However, PHI patients showed a significantly larger perfusion deficit compared to ICH patients (P < .01). At a cutoff value of 1.41 of the mismatch index of perfusion deficit and hyperechogenic lesion, the PHI diagnosis can be made with a 100%-sensitivity and 100%-specificity.
Differentiation of ICH and PHI via multimodal transcranial sonography with mismatch imaging is possible. Since sonographic imaging as a bedside-method is cost- as well as time-efficient, it may be a helpful tool for differentiation between these two entities particularly in critically ill patients with unclear ICH.
为了采取合适的治疗措施,区分原发性脑出血(ICH)与缺血性梗死灶内的实质出血性转化(PHI)至关重要。我们假设通过经颅灰阶和灌注超声检查可在床边区分ICH和PHI。
在这项前瞻性初步研究中,我们纳入了14例入院时影像学检查发现颅内出血的患者。通过脑磁共振成像或后续计算机断层扫描来区分ICH和PHI。所有患者均接受灰阶和灌注超声检查。
8例患者被诊断为ICH,6例患者被诊断为PHI。两组间ICH的体积无差异。然而,与ICH患者相比,PHI患者的灌注缺损明显更大(P <.01)。当灌注缺损与高回声病变的不匹配指数截断值为1.41时,诊断PHI的敏感性和特异性均为100%。
通过多模态经颅超声检查及不匹配成像区分ICH和PHI是可行的。由于超声成像作为一种床边检查方法既经济又省时,它可能是区分这两种情况的有用工具,尤其是对于ICH情况不明的重症患者。