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- W2893319681 abstract "To evaluate whether parameters from empirical mathematical model (EMM) for ultrafast dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) correlate with histological microvessel density (MVD) in invasive breast cancer.Ninety-eight consecutive patients with invasive breast cancer underwent an institutional review board-approved ultrafast DCE-MRI including a pre- and 18 postcontrast whole breast ultrafast scans (3 seconds) followed by four standard scans (60 seconds) using a 3T system. Region of interest was placed within each lesion where the highest signal increase was observed on ultrafast DCE-MRI, and the increase rate of enhancement was calculated as follows: ΔS = (SIpost - SIpre)/SIpre. The kinetic curve obtained from ultrafast DCE-MRI was analyzed using a truncated EMM: ΔS(t) = A(1 - e-αt), where A is the upper limit of the signal intensity, α (min-1) is the rate of signal increase. The initial slope of the kinetic curve is given by Aα. Initial area under curve (AUC30) and time of initial enhancement was calculated. From the standard DCE-MRI, the initial enhancement rate (IER) and the signal enhancement ratio (SER) were calculated as follows: IER = (SIearly - SIpre)/SIpre, SER = (SIearly - SIpre)/(SIdelayed - SIpre). The parameters were compared to MVD obtained from surgical specimens.A, α, Aα, AUC30, and time of initial enhancement significantly correlated with MVD (r = 0.29, 0.40, 0.51, 0.43, and -0.32 with p = 0.0027, p < 0.0001, p < 0.0001, p < 0.0001, and p = 0.0012, respectively), whereas IER and SER from standard DCE-MRI did not.The parameters of the EMM, especially the initial slope or Aα, for ultrafast DCE-MRI correlated with MVD in invasive breast cancer." @default.
- W2893319681 created "2018-10-05" @default.
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- W2893319681 date "2019-07-01" @default.
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- W2893319681 title "Ultrafast Dynamic Contrast-Enhanced Breast MRI: Kinetic Curve Assessment Using Empirical Mathematical Model Validated with Histological Microvessel Density" @default.
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- W2893319681 doi "https://doi.org/10.1016/j.acra.2018.08.016" @default.
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