\n @ARTICLE{Turco2016,
\n author = {Turco, Simona AND Janssen, Augustus J.E.M. AND Lavini, Cristina AND de la Rosette, Jean J. AND Wijkstra, Hessel AND Mischi, Massimo},
\n title = {Time-efficient estimation of the magnetic resonance dispersion modelparameters for quantitative assessment of angiogenesis},
\n abstract = {The limitations of the available imaging modalities for prostate cancer (PCa) localization result in subop-timal protocols for management of the disease. In response, several dynamic contrast-enhanced imagingmodalities have been developed, which aim at cancer detection through the assessment of the changesoccurring in the tumor microenvironment due to angiogenesis. In this context, novel magnetic reso-nance dispersion imaging (MRDI) enables the estimation of parameters related to the microvasculararchitecture and leakage, by describing the contrast agent kinetics with a dispersion model. Although apreliminary validation of MRDI on PCa has shown promising results, parameter estimation can becomeburdensome due the convolution integral present in the dispersion model. To overcome this limitation,in this work we provide analytical solutions of the dispersion model in the time and frequency domains,and we implement three numerical methods to increase the time-efficiency of parameter estimation. Theproposed solutions are tested for PCa localization. A reduction by about 50% of computation time couldbe obtained, without significant changes in the estimation performance and in the clinical results. Withthe continuous development of new technological solutions to boost the spatiotemporal resolution ofDCE-MRI, solutions to improve the computational efficiency of parameter estimation are highly required.},
\n keywords = {Dynamic contrast enhanced magnetic resonance imaging, Physiological modeling, Parameter estimation, Cancer angiogenesis, Computational efficiency},
\n pages = {23–33},
\n bookTitle = {Biomedical Signal Processing and Control},
\n volume = {26},
year = {2016},
month = {Apr.}
}