Reconstruction of high-quality CTA from noisy cerebral CT perfusion data

Purpose: Current techniques for reconstructing CT angiography (CTA) from CT perfusion (CTP) data use single arterial phase (aCTP) or the temporal MIP (tMIP) but such images suffer from the increased image noise in thin-section CTP data. We developed and tested a technique that allows for reconstruction of high-quality CTA from noisy cerebral CTP data. Methods and Materials: We developed a novel method for reconstructing CTA from CTP data that combines the advantages of tMIP (high vascular contrast) and temporal mean (low image noise). This perfusion-derived CTA (pCTA) was tested on 17 patients with suspected subarachnoid haemorrhage who underwent CTP (80 kV, 150 mAs, 30 scans every 2s) and standard CTA with 64x0.625mm collimation. Standard CTA, aCTP, tMIP and pCTA were randomized and blindly presented to an expert who was unaware of the techniques. All scans were scored on a 5-point scale for arterial contrast, detail visibility, vascular noise and overall image quality. Image noise was determined over a 100mm2 homogenous ROI. Results: pCTA yielded significantly superior visual scores for overall image quality and vascular noise (p<0.05). Overall image quality with tMIP was significantly superior to both CTA and aCTP. Detail visibility was similar to tMIP but significantly better than CTA and aCTA. Arterial contrast was significantly higher than for standard CTA and similar to tMIP and aCTA. Image noise was significantly lowest on pCTA and highest for aCTA. Conclusion: Our CTA reconstruction algorithm appears superior to conventional CTA of the brain and existing techniques for reconstructing CTA from CTP data.