To evaluate whether K_trans can be reliably estimated in dynamic contrast enhanced (DCE) MRI, with reduced contrast agent concentration, by the lengthening of pre-injection baseline time.DCE-MRI gives quantitative and semi-quantitative information about the integrity of the vascular system. It has been applied to the study of pathologies ranging from cancer to mild cognitive impairment. Recent studies have also shown the value of DCE-MRI in the screening of breast ¹ and prostate cancer ². In these populations, the availability of reliable and quantitative DCE-MRI parameters, especially K_trans, would likely contribute to the efficacy of the exam. However, the promise of contrast-enhance imaging is offset by the toxicity of the infused gadolinium contrast agents, which can cause nephrogenic systemic fibrosis ³ and accumulate in the brain ⁴. Thus, DCE-MRI protocols that maximize the extractable quantitative information while minimizing the amount of infused contrast agent are imperative. In a prior study ⁵, we developed a metric, K-CNR (an estimated K_trans contrast to noise ratio (CNR), which takes into account both the accuracy and precision of K_trans estimation), to evaluate the effects of DCE-MRI acquisition parameters and kinetic model choice upon K_trans estimation. Using simulations, we demonstrated that lengthening of the pre-injection baseline aids the precision and accuracy of K_trans measurement. In this study, we evaluated whether the benefits of a lengthened baseline can offset the decreased image signal intensities obtained with reduced contrast agent concentration ([CA]). DCE-MRI simulations were generated using the 2-compartment exchange model (2CXM) in MATLAB and fitted to extended-Tofts and Patlak models using ROCKETSHIP software ⁶. These simulations have been shown to reflect real-life clinical data ⁵. The arterial input function developed by Parker et al. ⁷ was modified to mimic the behavior of our clinical datasets, which uses Multihance CA. K_trans estimation (K_trans: 0.0005 to 0.02 min-1; v_p = 0.01; v_e = 0.1; SNR = 15, 30, 100; sampling time = 3.75, 15.4 s, total duration = 15 min) was performed using varying pre-injection baselines (30, 60, 300, 500 s) and at different [CA] (0.05, 0.025, 0.0125 mmol/kg or standard dose,½ dose,¼ dose, respectively). Each set of parameter combinations were simulated and fitted 100 times. The ability to reliably estimate Ktrans at differing baselines and [CA] was then evaluated using K-CNR.As expected, DCE-MRI using the highest [CA] and longest pre-injection baseline (and at shortest sampling time/highest SNR) estimated K_trans best. Standard dose [CA]/30s baseline, ½ dose [CA]/ 60 or 300s baseline and ¼ dose [CA]/500s baseline were directly compared to examine the interplay of these two variables. Graphs comparing K_trans(simulated) vs. K_trans(estimated) at a sampling time of 3.75s are shown in Fig 1, and demonstrates that K_trans were estimated well at all three conditions with both Patlak and extended-Tofts models, albeit with different variances. K-CNR vs. K_trans plots are shown in Fig 2, highlighting the wider variance of K_trans estimation using ¼ dose [CA]/500s compared to the standard dose [CA]/30s. For the extended-Tofts model, the ½ dose [CA]/300s achieved similar K-CNR as the standard dose [CA]/30s baseline condition, while the ½ dose [CA]/300s exhibited a higher K-CNR using the Patlak model. Other acquisition parameters can also influence the K-CNR. For example, upon decreasing the sampling time, the ½ dose [CA]/60s performs similarly to the standard dose [CA]/30s condition (Fig 3).In the ideal imaging situation, an adequate [CA] (high but not enough to cause dephasing effects) is desirable for accurate K_trans estimation. However, results from this simulation study suggest that lower [CA] (up to 1/2 dose) can achieve similar K_trans accuracy and reliability by increasing the pre-injection baseline time. This is likely secondary to the fact that concentration time curves are partially calculated as the ratio of pre-injection and post-injection signal intensities; thus reducing the variance of the baseline can reduce the variance of the post-injection time curve. This effect is also dependent on other imaging parameters, such as the sampling time, as well intrinsic variables such as v_e or v_p. The appropriate choice of [CA], baseline time and other acquisition variables will likely be project and site specific. K-CNR and simulations provide a framework to tailor protocols to suit individual studies. Simulations demonstrate that [CA] can be reduced in DCE-MRI studies while achieving robust K_trans estimation with appropriate adjustment of acquisition variables, such as the pre-injection baseline duration. This should be taken into account when designing protocols where nephro- or neurotoxicity due to gadolinium is a concern.