Deconvolution of Tc99m-mercaptoacetyltriglycine (MAG3) renograms with the concomitant use of a sparse Legendre polynomial representation and the Moore-Penrose pseudo-inverse.

INTRODUCTION: The purpose of this study is to introduce an improved deconvolution technique for MAG3 renograms based on the combination of a sparse Legendre polynomial representation and the Moore-Penrose inversion matrix (LG). This method reduces the impact of noise on the renal retention function transit time measurement.
METHODS: The stability and the accuracy of the proposed method were tested using a renal database containing Monte-Carlo simulated studies and real adult patient data. The two clinical parameters, split function and mean transit time (meanTT), obtained with LG were compared to values calculated with the established method that combines matrix deconvolution and a 3-point linear smoothing (F121) as recommended by the 2008 International Scientific Committee of Radionuclides in Nephrourology consensus on renal transit time measurements.
RESULTS: For simulated data, the root mean square error (RMSE) between the theoretical non-noisy renal retention curve (RRC) and the results of the deconvolution methods applied to the noisy RRC were up to 2 times lower with LG (P <0.001). The RMSE of the reconvoluted renogram and the theoretical one was also lower for LG (P <0.001), and showed better preservation of the original signal. The split function was neither improved nor degraded by the proposed method. For patient data, there was no statistical difference between the split function for the LG method compared to the database values, and the meanTT better agreed with the physician’s diagnosis than the matrix or clinical software (Hermes) outputs. A visual improvement of the RRC was also clearly observed.
DISCUSSION AND CONCLUSION: By combining the sparse Legendre representation of the renogram curves and the Moore-Penrose matrix inverse techniques, we obtained improved noise reduction in the deconvoluted data, leading to better elimination of non-physiological signals as negative values and the avoidance of the smear effect of conventional smoothing on the vascular peak, which both influenced the meanTT measurement.