Parametric perfusion imaging with single-pixel resolution and high signal to clutter ratio

Abstract

Parametric perfusion imaging (PPI) based on time-intensity-curves (TICs) can quantify and depict the spatial distribution of tumor perfusion information in liver cancer research. However, accurate diagnosis of PPI is seriously disturbed by the fluctuations of TICs and decreases of coded threshold induced by no-microbubble (MB) regions. Such disturbances, particularly the decrease of signal-to-clutter ratio (SCR) of TICs, are further exacerbated during selecting single-pixel region-of-interest (ROI) to obtain PPI with highest resolution. The objective of this study was to accurately obtain PPI with single-pixel resolution at the smallest ROI by the valid TICs filtration and the SCR enhancement of TICs. First, single-pixel TICs were obtained from the dynamic contrast images of a patient with gallbladder carcinoma liver metastasis. Next, these TICs in no-MB regions were then eliminated due to their low correlation with MB regions. Whereas the valid reserved TICs were filtered by the detrended fluctuation analysis to improve their SCR. Color-coded images were finally obtained based on the perfusion parameters extracted from the reserved TICs. After TICs filtration and denoising, the disturbances from no-MB regions were effectively removed; SCR of TICs was enhanced by 5.49 ± 0.34 dB; and operation time of PPI decreased 50.4 ± 0.1% because lots of invalid data were eliminated. Hot spots distribution and perfusion characteristic of neovascularization in the liver metastases were accurately distinguished and depicted by combining PPI with single-pixel resolution, especially the wash in time and wash out time. Besides, edge features of the invasion area and liver were clearly described without extra segmentation algorithm. It can contribute to accurately make a clinical decision in the liver cancer diagnoses by the single-pixel resolution PPI with comprehensive functional perfusion information.