Wavelet-based calculation of cerebral angiographic data from time-resolved CT perfusion acquisitions.

Objectives: To evaluate a new approach for reconstructing angiographic images by application of wavelet transforms on CT perfusion data.Methods: Fifteen consecutive patients with suspected stroke were examined with a multi-detector CT acquiring 32 dynamic phases (∆t = 1.5s) of 99 slices (total slab...

Descripción completa

Detalles Bibliográficos
Publicado en:European Radiology Vol. 25; no. 8; pp. 2354 - 2362
Autores principales: Havla, Lukas, Thierfelder, Kolja M, Beyer, Sebastian E, Sommer, Wieland H, Dietrich, Olaf
Formato: Journal Article
Publicado: Springer Nature Aug2015
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:Objectives: To evaluate a new approach for reconstructing angiographic images by application of wavelet transforms on CT perfusion data.Methods: Fifteen consecutive patients with suspected stroke were examined with a multi-detector CT acquiring 32 dynamic phases (∆t = 1.5s) of 99 slices (total slab thickness 99mm) at 80kV/200mAs. Thirty-five mL of iomeprol-350 was injected (flow rate = 4.5mL/s). Angiographic datasets were calculated after initial rigid-body motion correction using (a) temporally filtered maximum intensity projections (tMIP) and (b) the wavelet transform (Paul wavelet, order 1) of each voxel time course. The maximum of the wavelet-power-spectrum was defined as the angiographic signal intensity. The contrast-to-noise ratio (CNR) of 18 different vessel segments was quantified and two blinded readers rated the images qualitatively using 5pt Likert scales.Results: The CNR for the wavelet angiography (501.8 ± 433.0) was significantly higher than for the tMIP approach (55.7 ± 29.7, Wilcoxon test p < 0.00001). Image quality was rated to be significantly higher (p < 0.001) for the wavelet angiography with median scores of 4/4 (reader 1/reader 2) than the tMIP (scores of 3/3).Conclusions: The proposed calculation approach for angiography data using temporal wavelet transforms of intracranial CT perfusion datasets provides higher vascular contrast and intrinsic removal of non-enhancing structures such as bone.Key Points: • Angiographic images calculated with the proposed wavelet-based approach show significantly improved contrast-to-noise ratio. • CT perfusion-based wavelet angiography is an alternative method for vessel visualization. • Provides intrinsic removal of non-enhancing structures such as bone.