Objectives: Calcific and hemorrhagic intracranial lesions with attenuation levels of less than 100 Hounsfield units (HUs) cannot currently be reliably differentiated by single-energy computed tomography (SECT). The proper differentiation of these lesion types would have a multitude of clinical applications. A phantom model was used to test the ability of dual-energy CT (DECT) to differentiate such lesions.
Materials and methods: Agar gel-bound ferric oxide and hydroxyapatite were used to model hemorrhage and calcification, respectively. Gel models were scanned using SECT and DECT and organized into SECT attenuation-matched pairs at 16 attenuation levels between 0 and 100 HU. Dual-energy CT data were analyzed using 3-dimensional (3D) Gaussian mixture models (GMMs), as well as a simplified threshold plane metric derived from the 3D GMM, to assign voxels to hemorrhagic or calcific categories. Accuracy was calculated by comparing predicted voxel assignments with actual voxel identities.
Results: We measured 6032 voxels from each gel model, for a total of 193,024 data points (16 matched model pairs). Both the 3D GMM and its more clinically implementable threshold plane derivative yielded similar results, with higher than 90% accuracy at matched SECT attenuation levels of 50 HU and greater.
Conclusions: Hemorrhagic and calcific lesions with attenuation levels between 50 and 100 HU were differentiable using DECT in a clinically relevant phantom system with higher than 90% accuracy. This method warrants further testing for potential clinical applications.