Towards reduced-preparation Spectral-CT-colonography utilizing local covariance

In CT colonography (CTC), residual stool is a possible confounder in the detection of colonic polyps. While there is a clear clinical need for reduced or minimal bowel preparation for CT colonography, residual stool that is poorly tagged by oral contrast agent prevents satisfactory electronic cleansing (EC) by standard methods on conventional CT. Our study aims to answer quantitatively whether dual-layer spectral-CT allows superior discrimination of residual stool. 60 spectral CT colonography scans were obtained in clinical practice, and careful exhaustive ground truth was established by consensus reading. Results indicate that spectral CT adds significant discrimination power, in particular when utilizing local spectral variances and covariances, which can be computed efficiently by standard Gaussian filter operations. Simple linear spectral material separation, however, is sufficient only in extended homogeneous regions. In subtle finely structured transition areas, non-linear classifiers or convolutional neural networks are required because of non-linear local multi material superposition effects.