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Biomedical subjects

Jeff L Zhang

Publications and source records attributed to Jeff L Zhang.

3 recordsLinked to original sources

A biphasic parameter estimation method for quantitative analysis of dynamic renal scintigraphic data.

Dynamic renal scintigraphy is an established method in nuclear medicine, commonly used for the assessment of renal function. In this paper, a biphasic model fitting method is proposed for simultaneous estimation of both vascular and parenchymal parameters from renal scintigraphic data. These parameters include the renal plasma flow, vascular and parenchymal mean transit times, and the glomerular extraction rate. Monte Carlo simulation was used to evaluate the stability and confidence of the parameter estimates obtained by the proposed biphasic method, before applying the method on actual patient study cases to compare with the conventional fitting approach and other established renal indices. The various parameter estimates obtained using the proposed method were found to be consistent with the respective pathologies of the study cases. The renal plasma flow and extraction rate estimated by the proposed method were in good agreement with those previously obtained using dynamic computed tomography and magnetic resonance imaging.

Computer Simulation↗

On the selection of optimal flip angles for T1 mapping of breast tumors with dynamic contrast-enhanced magnetic resonance imaging.

We present a method for selecting optimal flip angles for both precontrast and postcontrast T1 mapping of breast tumors using dynamic contrast-enhanced magnetic resonance imaging; and with the aim of improving accuracy in the estimation of contrast medium concentration. The proposed method can appropriately account for the different ranges of precontrst and postcontrast T1 values by the use of weighting functions, which also allow the flexibility to enhance the accuracy of certain T1 values, corresponding to the tissues of interest. Results of Monte Carlo simulations show that the proposed method could yield significantly lower errors in the estimation of contrast concentration, as compared with an existing approach.

Algorithms↗

Estimation of renal scintigraphy parameters using a linear piecewise-continuous model.

Instead of performing a numerical deconvolution, we propose to use a linear piecewise-continuous model of the renal impulse response function for parametric fitting of renal scintigraphy data, to obtain clinically useful renal parameters. The strengths of the present model are its simplicity and speed of computation, while not compromising on accuracy. Preliminary patient case studies show that the estimated parameters are in good agreement with a more elaborate model.

Algorithms↗