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Cerebral microbleeds (CMBs) are findings in patients with neurological disorders such as cerebral amyloid angiopathy and Alzheimer's disease, and are indicative of an underlying vascular pathology. A diagnosis of CMBs requires an imaging method that is capable of detecting iron-containing lesions with high sensitivity and spatial accuracy in the presence of potentially confounding tissue abnormalities. In this study, we investigated the feasibility of quantitative magnetic susceptibility mapping (QSM), a novel technique based on gradient-recalled echo (GRE) phase data, for the detection of CMBs in the arcAβ mouse, a mouse model of cerebral amyloidosis. Quantitative susceptibility maps were generated from phase data acquired with a high-resolution T(2)(*)-weighted GRE sequence at 9.4 T. We examined the influence of different regularization parameters on susceptibility computation; a proper adjustment of the regularization parameter minimizes streaking artifacts and preserves fine structures. In the present study, it is shown that QSM provides increased detection sensitivity of CMBs and improved contrast when compared with GRE magnitude imaging. Furthermore, QSM corrects for the blooming effect observed in magnitude and phase images and depicts both the localization and spatial extent of CMBs with high accuracy. Therefore, QSM may become an important tool for diagnosing CMBs in neurological diseases.

Detection of Cerebral Microbleeds with Quantitative Susceptibility Mapping in the Arcabeta Mouse Model of Cerebral Amyloidosis