Dynamic Contrast-enhanced MRI Acquisition Research Articles

A four-dimensional computational model of dynamic contrast-enhanced magnetic resonance imaging measurement of subtle blood-brain barrier leakage

Dynamic contrast-enhanced MRI (DCE-MRI) is increasingly used to quantify and map the spatial distribution of blood-brain barrier (BBB) leakage in neurodegenerative disease, including cerebral small vessel disease and dementia. However, the subtle nature of leakage and resulting small signal changes make quantification challenging. While simplified one-dimensional simulations have probed the impact of noise, scanner drift, and model assumptions, the impact of spatio-temporal effects such as gross motion, k-space sampling and motion artefacts on parametric leakage maps has been overlooked. Moreover, evidence on which to base the design of imaging protocols is lacking due to practical difficulties and the lack of a reference method. To address these problems, we present an open-source computational model of the DCE-MRI acquisition process for generating four dimensional Digital Reference Objects (DROs), using a high-resolution brain atlas and incorporating realistic patient motion, extra-cerebral signals, noise and k-space sampling. Simulations using the DROs demonstrated a dominant influence of spatio-temporal effects on both the visual appearance of parameter maps and on measured tissue leakage rates. The computational model permits greater understanding of the sensitivity and limitations of subtle BBB leakage measurement and provides a non-invasive means of testing and optimising imaging protocols for future studies.

Cortical bone vessel identification and quantification on contrast-enhanced MR images

Cortical bone porosity is a major determinant of bone strength. Despite the biomechanical importance of cortical bone porosity, the biological drivers of cortical porosity are unknown. The content of cortical pore space can indicate pore expansion mechanisms; both of the primary components of pore space, vessels and adipocytes, have been implicated in pore expansion. Dynamic contrast-enhanced MRI (DCE-MRI) is widely used in vessel detection in cardiovascular studies, but has not been applied to visualize vessels within cortical bone. In this study, we have developed a multimodal DCE-MRI and high resolution peripheral QCT (HR-pQCT) acquisition and image processing pipeline to detect vessel-filled cortical bone pores. For this in vivo human study, 19 volunteers (10 males and 9 females; mean age =63±5) were recruited. Both distal and ultra-distal regions of the non-dominant tibia were imaged by HR-pQCT (82 µm nominal resolution) for bone structure segmentation and by 3T DCE-MRI (Gadavist; 9 min scan time; temporal resolution =30 sec; voxel size 230×230×500 µm3) for vessel visualization. The DCE-MRI was registered to the HR-pQCT volume and the voxels within the MRI cortical bone region were extracted. Features of the DCE data were calculated and voxels were categorized by a 2-stage hierarchical kmeans clustering algorithm to determine which voxels represent vessels. Vessel volume fraction (volume ratio of vessels to cortical bone), vessel density (average vessel count per cortical bone volume), and average vessel volume (mean volume of vessels) were calculated to quantify the status of vessel-filled pores in cortical bone. To examine spatial resolution and perform validation, a virtual phantom with 5 channel sizes and an applied pseudo enhancement curve was processed through the proposed image processing pipeline. Overlap volume ratio and Dice coefficient was calculated to measure the similarity between the detected vessel map and ground truth. In the human study, mean vessel volume fraction was 2.2%±1.0%, mean vessel density was 0.68±0.27 vessel/mm3, and mean average vessel volume was 0.032±0.012 mm3/vessel. Signal intensity for detected vessel voxels increased during the scan, while signal for non-vessel voxels within pores did not enhance. In the validation phantom, channels with diameter 250 µm or greater were detected successfully, with volume ratio equal to 1 and Dice coefficient above 0.6. Both statistics decreased dramatically for channel sizes less than 250 µm. We have a developed a multi-modal image acquisition and processing pipeline that successfully detects vessels within cortical bone pores. The performance of this technique degrades for vessel diameters below the in-plane spatial resolution of the DCE-MRI acquisition. This approach can be applied to investigate the biological systems associated with cortical pore expansion.

DCE-MRI for Early Prediction of Response in Hepatocellular Carcinoma after TACE and Sorafenib Therapy: A Pilot Study

Objective:Dynamic contrast-enhanced MRI (DCE-MRI) can measure the changes in tumor blood flow, vascular permeability and interstitial and intravascular volume. The objective was to evaluate the efficacy of DCE-MRI in prediction of Barcelona Clinic Liver Cancer (BCLC) staging B or C hepatocellular carcinoma (HCC) response after treatment with transcatheter arterial chemoembolization (TACE) followed by sorafenib therapy.Methods:Sorafenib was administered four days after TACE of BCLC staging B or C HCC in 11 patients (21 lesions). DCE-MRI was performed with Gd-EOB-DTPA contrast before TACE and three and 10 days after TACE. DCE-MRI acquisitions were taken pre-contrast, hepatic arterial-dominant phase and 60, 120, 180, 240, 330, 420, 510 and 600 seconds post-contrast. Distribution volume of contrast agent (DV) and transfer constant Ktrans were calculated. Patients were grouped by mRECIST after one month or more post-TACE into responders (complete response, partial response) and non-responders (stable disease, progressive disease).Results:DV was reduced in responders at three and 10 days post-TACE (p = 0.008 and p = 0.008 respectively). DV fell in non-responders at three days (p = 0.025) but was not significantly changed from pre-TACE values after sorafenib. Sensitivity and specificity for DV 10 days post-TACE were 88% and 77% respectively.Conclusion:DV may be a useful biomarker for early prediction of therapeutic outcome in intermediate HCC.

Radial multigradient-echo DCE-MRI for 3DKtransmapping with individual arterial input function measurement in mouse tumor models

The purpose of this study was to provide proof of concept for a new three-dimensional (3D) radial dynamic contrast enhanced MRI acquisition technique, called "Radial Entire Tumor with Individual Arterial input function dynamic contrast-enhanced MRI" (RETIA dynamic contrast-enhanced MRI), which allows for the simultaneous measurement of an arterial input function in the mouse heart at 2 s temporal resolution and coverage of the whole tumor. Alternating 2D and 3D projections contribute to the 2D heart image or 3D tumor data with a 3-cm field of view. Sixty-four 2D images of the heart are obtained during acquisition of each 3D tumor dataset. In a pilot study, global K(trans) and ve values were measured in four mice, in a respiratory motion-animated subcutaneously implanted breast tumor model. This technique is expected to be most useful for the characterization of microvasculature in motion-animated orthotopic tumors.

Extended graphical model for analysis of dynamic contrast‐enhanced MRI

Kinetic analysis with mathematical models has become increasingly important to quantify physiological parameters in computed tomography (CT), positron emission tomography (PET), and dynamic contrast-enhanced MRI (DCE-MRI). The modified Kety/Tofts model and the graphical (Patlak) model have been widely applied to DCE-MRI results in disease processes such as cancer, inflammation, and ischemia. In this article, an intermediate model between the modified Kety/Tofts and Patlak models is derived from a mathematical expansion of the modified Kety/Tofts model. Simulations and an in vivo experiment involving DCE-MRI of carotid atherosclerosis were used to compare the new extended graphical model with the modified Kety/Tofts model and the Patlak model. In our simulated circumstances and the carotid artery application, we found that the extended graphical model exhibited lower noise sensitivity and provided more accurate estimates of the volume transfer constant (K(trans)) and fractional plasma volume (v(p)) than the modified Kety/Tofts model for DCE-MRI acquisitions of total duration less than 100-300 s, depending on kinetic parameters. In comparison with the Patlak model, we found that the extended graphical model exhibited 74.4-99.8% less bias in estimates of K(trans). Thus, the extended graphical model may allow kinetic modeling of DCE-MRI results with shortened data acquisition periods, without sacrificing accuracy in estimates of K(trans) and v(p).

Kinetic Curves of Malignant Lesions Are Not Consistent Across MRI Systems: Need for Improved Standardization of Breast Dynamic Contrast-Enhanced MRI Acquisition

Kinetic Curves of Malignant Lesions Are Not Consistent Across MRI Systems: Need for Improved Standardization of Breast Dynamic Contrast-Enhanced MRI Acquisition

Temporal sampling requirements for reference region modeling of DCE‐MRI data in human breast cancer

To assess the temporal sampling requirements needed for quantitative analysis of dynamic contrast-enhanced MRI (DCE-MRI) data with a reference region (RR) model in human breast cancer. Simulations were used to study errors in pharmacokinetic parameters (K(trans) and v(e)) estimated by the RR model using six DCE-MRI acquisitions over a range of pharmacokinetic parameter values, arterial input functions, and temporal samplings. DCE-MRI data were acquired on 12 breast cancer patients and parameters were estimated using the native resolution data (16.4 seconds) and compared to downsampled 32.8-second and 65.6-second data. Simulations show that, in the majority of parameter combinations, the RR model results in an error less than 20% in the extracted parameters with temporal sampling as poor as 35.6 seconds. The experimental results show a high correlation between K(trans) and v(e) estimates from data acquired at 16.4-second temporal resolution compared to the downsampled 32.8-second data: the slope of the regression line was 1.025 (95% confidence interval [CI]: 1.021, 1.029), Pearson's correlation r = 0.943 (95% CI: 0.940, 0.945) for K(trans), and 1.023 (95% CI: 1.021. 1.025), r = 0.979 (95% CI: 0.978, 0.980) for v(e). For the 64-second temporal resolution data the results were: 0.890 (95% CI: 0.894, 0.905), r = 0.8645, (95% CI: 0.858, 0.871) for K(trans), and 1.041 (95% CI: 1.039, 1.043), r = 0.970 (95% CI: 0.968, 0.971) for v(e). RR analysis allows for a significant reduction in temporal sampling requirements and this lends itself to analyze DCE-MRI data acquired in practical situations.

Fluctuations in tumor blood perfusion assessed by dynamic contrast‐enhanced MRI

Temporal heterogeneity in blood perfusion is a common phenomenon in tumors, but data characterizing the nature of the blood flow fluctuations are sparse. This study investigated the occurrence of blood flow fluctuations in A-07 melanoma xenografts by using gadopentetate dimeglumine (Gd-DTPA)-based dynamic contrast-enhanced MRI (DCE-MRI). Each tumor was subjected to two DCE-MRI acquisitions separated by 1 hour. The data were processed by Kety analysis and resulted in two E.F images (E is the initial extraction fraction of Gd-DTPA and F is the perfusion) and two lambda images (lambda is the partition coefficient of Gd-DTPA) for each tumor. The E . F images were used to determine the changes in blood perfusion arising in the time between the two imaging sequences. The lambda images were used to control the reproducibility of the experimental procedure. The study showed that DCE-MRI with subsequent Kety analysis is a useful method for detection of blood flow fluctuations in A-07 tumors, and strongly suggested that the peripheral regions of A-07 tumors are more exposed to temporal changes in blood perfusion than are the central regions.

A method for pharmacokinetic modelling of dynamic contrast enhanced MRI studies of rapidly enhancing lesions acquired in a clinical setting

Abnormal microcirculation is a feature of many neoplastic and non-neoplastic diseases. Physiological variables that characterize tissue microcirculation (capillary permeability and the volume of the extravascular extracellular fluid) are altered in pathological states. Pharmacokinetic analysis of dynamic contrast enhanced MRI (DCE-MRI) has found a widespread use in the assessment of abnormal microcirculation due to the direct link between the contrast agent kinetics and underlying microcirculatory properties. A representation of temporal variation of contrast agent concentration in blood plasma (Cp(t)) is central to this analysis. In clinical applications of DCE-MRI, signal intensity curves derived from rapidly enhancing lesions often display a sigmoid shape during the initial phase of contrast uptake and rapid arrival at the equilibrium phase. In this work, the features of two principal methods for pharmacokinetic analysis of DCE-MRI which allow for theoretical representation of Cp(t) are examined and combined to improve analysis of this particular class of DCE-MRI curves. The proposed method allows the representation of the initial sigmoid part of the enhancement profiles whilst retaining a realistic representation of Cp(t) based on previously published measurements obtained in healthy volunteers. The results of the computer simulations indicate that in rapidly enhancing lesions, with the transfer constant Ktrans greater than 0.1 min−1, the DCE-MRI acquisition can be restricted to 5 min post-injection and a mono-exponential representation of Cp(t) decay is sufficient. Furthermore, non-ideal bolus delivery can be represented as a short constant rate infusion when the tissue under investigation exhibits a sigmoid pattern of contrast uptake.