ABSTRACT
Duchenne muscular dystrophy (DMD) is an X-linked genetic disease characterized by progressive weakness and wasting of skeletal and cardiac muscle; boys present with weakness by the age of 5 years and, if left untreated, are unable to walk without assistance by the age of 10 years. Therapy for DMD has been primarily palliative, with oral steroids emerging as a first-line approach even though this treatment has serious side-effects. Consequently, low-cost imaging technology suitable for improved diagnosis and treatment monitoring of DMD would be of great value, especially in remote and underserved areas. Previously, we reported use of the logarithm of the signal energy, log [E(f)], and a new method for ultrasound signal characterization using entropy, H(f), to monitor prednisolone treatment of skeletal muscle in a dystrophin-deficient mouse model. Three groups were studied: mdx mice treated with prednisolone, a control group of mdx mice treated with saline, and a control group of wild-type mice treated with saline. It was found that both log [E(f)] and H(f) were required to statistically differentiate the three groups. In the current study, we show that preprocessing of the raw ultrasound using optimal smoothing splines before computation of either log [E(f)] or a rapidly computable variant of Hf, denoted I(f,∞), permits delineation of all three groups by either metric alone. This opens the way to the ultimate goal of this study, which is identification and implementation of new diagnostically sensitive algorithms on the new generation of low-cost hand-held clinical ultrasonic imaging systems.
Subject(s)
Algorithms , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Muscular Dystrophy, Duchenne/diagnostic imaging , Muscular Dystrophy, Duchenne/drug therapy , Steroids/therapeutic use , Ultrasonography/methods , Animals , Anti-Inflammatory Agents/therapeutic use , Mice , Mice, Inbred mdx , Prognosis , Reproducibility of Results , Sensitivity and Specificity , Treatment OutcomeABSTRACT
In several investigations of molecular imaging of angiogenic neovasculature using a targeted contrast agent, Renyi entropy [I(f)(r)] and a limiting form of Renyi entropy (I(f,∞)) exhibited significantly more sensitivity to subtle changes in scattering architecture than energy-based methods. Many of these studies required the fitting of a cubic spline to backscattered waveforms prior to calculation of entropy [either I(f)(r) or I(f,∞)]. In this study, it is shown that the robustness of I(f,∞) may be improved by using a smoothing spline. Results are presented showing the impact of different smoothing parameters. In addition, if smoothing is preceded by low-pass filtering of the waveforms, further improvements may be obtained.
Subject(s)
Contrast Media , Models, Theoretical , Molecular Imaging/methods , Nanoparticles , Neoplasms/blood supply , Neovascularization, Pathologic/diagnostic imaging , Signal Processing, Computer-Assisted , Algorithms , Animals , Cell Line, Tumor , Computer Simulation , Humans , Integrin alphaVbeta3/metabolism , Mice , Mice, Nude , Neoplasm Transplantation , Neovascularization, Pathologic/metabolism , Numerical Analysis, Computer-Assisted , Predictive Value of Tests , Scattering, Radiation , Time Factors , UltrasonographyABSTRACT
Previously, we reported new methods for ultrasound signal characterization using entropy, H(f); a generalized entropy, the Renyi entropy, I(f)(r); and a limiting form of Renyi entropy suitable for real-time calculation, I(f),(infinity). All of these quantities demonstrated significantly more sensitivity to subtle changes in scattering architecture than energy-based methods in certain settings. In this study, the real-time calculable limit of the Renyi entropy, I(f),(infinity), is applied for the imaging of angiogenic murine neovasculature in a breast cancer xenograft using a targeted contrast agent. It is shown that this approach may be used to reliably detect the accumulation of targeted nanoparticles at five minutes post-injection in this in vivo model.
