ABSTRACT
PURPOSE: To determine the precision for in vivo applications of model and non-model-based bootstrap algorithms for estimating the measurement uncertainty of diffusion parameters derived from diffusion tensor imaging data. MATERIALS AND METHODS: Four different bootstrap methods were applied to diffusion datasets acquired during 10 repeated imaging sessions. Measurement uncertainty was derived in eight manually selected regions of interest and in the entire brain white matter and gray matter. The precision of the bootstrap methods was analyzed using coefficients of variation and intra-class correlation coefficients. Comprehensive simulations were performed to validate the results. RESULTS: All bootstrap algorithms showed similar precision which slightly varied in dependence of the selected region of interest. The averaged coefficient of variation in the selected regions of interest was 13.81%, 12.35%, and 17.93% with respect to the apparent diffusion coefficient, the fractional anisotropy value, and the cone of uncertainty, respectively. The repeated measurements showed a very high similarity with intraclass-correlation coefficients larger than 0.96. The simulations confirmed most of the in vivo findings. CONCLUSION: All investigated bootstrap methods perform with a similar, high precision in deriving the measurement uncertainty of diffusion parameters. Thus, the time-efficient model-based bootstrap approaches should be the method of choice in clinical practice.
Subject(s)
Algorithms , Brain/anatomy & histology , Diffusion Magnetic Resonance Imaging/methods , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Pattern Recognition, Automated/methods , Humans , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
The high sensitivity of fluorescence imaging enables the detection of molecular processes in living organisms. However, diffuse light propagation in tissue prevents accurate recovery of tomographic information on fluorophore distribution for structures embedded deeper than 0.5 mm. Combining optical with magnetic resonance imaging (MRI) provides an accurate anatomical reference for fluorescence imaging data and thereby enables the correlation of molecular with high quality structural/functional information. We describe an integrated system for small animal imaging incorporating a noncontact fluorescence molecular tomography (FMT) system into an MRI detector. By adopting a free laser beam design geometrical constraints imposed by the use of optical fibers could be avoided allowing for flexible fluorescence excitation schemes. Photon detection based on a single-photon avalanche diode array enabled simultaneous FMT/MRI measurements without interference between modalities. In vitro characterization revealed good spatial accuracy of FMT data and accurate quantification of dye concentrations. Feasibility of FMT/MRI was demonstrated in vivo by simultaneous assessment of protease activity and tumor morphology in murine colon cancer xenografts.