Assessment of Non-permeability of Gd-DTPA for Dynamic Susceptibility Contrast in Human Brain: A Preliminary Study Using Non-linear Curve Fitting

To develop an advanced non-linear curve fitting (NLCF) algorithm for performing dynamic susceptibility contrast study of the brain. The first pass effects give rise to spuriously high estimates of Ktrans for the voxels that represent the large vascular components. An explicit threshold value was used to reject voxels. The blood perfusion and volume estimation were accurately evaluated in the T2*-weighted dynamic contrast enhanced (DCE)-MR images. From each of the recalculated parameters, a perfusion weighted image was outlined by using the modified non-linear curve fitting algorithm. The present study demonstrated an improvement of an estimation of the kinetic parameters from the DCE T2*-weighted magnetic resonance imaging data with using contrast agents.

Reducing the Scan Time in Gastric Emptying Scintigraphy by Using Mathematical Models / 대한핵의학회잡지

PURPOSE: Gastric emptying scan (GES) is usually acquired up to 2 hours. Our study investigated whether a fraction of meal-retention in the stomach at 120 minutes (FR120) was predicted from the data measured for 90 minutes by using non-linear curve fitting. We aimed at saving the delayed imaging by utilizing mathematical models. MATERIALS AND METHODS: Ninety-six patients underwent GES immediately after taking a boiled egg with 74 MBq (2 mCi) Tc-99m DTPA. The patients were divided into Group I (T1/2 < or=90 min) and Group II (90 min< T1/2< or=120 min). Group I (n=51) had 21 men and 30 women, and Group II (n=45) 15 men and 30 women. There was no significant difference in age and sex between the two groups. Simple exponential, power exponential, and modified power exponential curves were acquired from the measured fraction of meal-retention at each time (0, 15, 30, 45, 60, 75, and 90 min) by non-linear curve fitting (MATLAB (R) 5.3) and another simple exponential fitting was performed on the fractions at late times (60, 75, and 90 min). A predicted FR120 was calculated from the acquired functional formulas. A correlation coefficient between the measured FR120 and the predicted FR120 was computed (MedCalc (R) 6.0). RESULTS: Correlation coefficients (r) between the measured FR120 and the predicted FR120 of each mathematical functions were as follows: simple exponential function (Group I: 0.8858, Group II: 0.5982, p< 0.0001), power exponential function (Group I: 0.8755, Group II: 0.6008, p< 0.0001), modified power exponential function (Group I: 0.8892, Group II: 0.5882, p< 0.0001), and simple exponential function at the late times (Group I: 0.9085, Group II: 0.6832, p< 0.0001). In all the fitting models, the predicted FR120 were significantly correlated with the measured FR120 in Group I but not in Group II. There was no statistically significant difference in correlation among the 4 mathematical models. CONCLUSION: In the cases with T1/2 < or=90 min, the predicted FR120 is significantly correlated with the measured FR120. Therefore, FR120 can be predicted from the data measured for 90 minutes by using non-linear curve fitting, saving the delayed imaging after 90 minutes when T1/2 < or=90 min is ascertained.