Impact of contrast agent injection duration on dynamic contrast‐enhanced MRI quantification in prostate cancer

The volume transfer constant K^trans, which describes the leakage of contrast agent (CA) from vasculature into tissue, is the most commonly reported quantitative parameter for dynamic contrast‐enhanced (DCE‐) MRI. However, the variation in reported K^trans values between studies from different institutes is large. One of the primary sources of uncertainty is quantification of the arterial input function (AIF). The aim of this study is to determine the influence of the CA injection duration on the AIF and tracer kinetic analysis (TKA) parameters (i.e. K^trans, k_ep and v_e). Thirty‐one patients with prostate cancer received two DCE‐MRI examinations with an injection duration of 5 s in the first examination and a prolonged injection duration in the second examination, varying between 7.5 s and 30 s. The DCE examination was carried out on a 3.0 T MRI scanner using a transversal T₁‐weighted 3D spoiled gradient echo sequence (300 s duration, dynamic scan time of 2.5 s). Data of 29 of the 31 were further analysed. AIFs were determined from the phase signal in the left and right femoral arteries. K^trans, k_ep and v_e were estimated with the standard Tofts model for regions of healthy peripheral zone and tumour tissue. We observed a significantly smaller peak height and increased width in the AIF for injection durations of 15 s and longer. However, we did not find significant differences in K^trans, k_ep or v_e for the studied injection durations. The study demonstrates that the TKA parameters K^trans, k_ep and v_e, measured in the prostate, do not show a significant change as a function of injection duration.     

DCE‐MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro‐fuzzy‐based model and nested model selection technique

This pilot study investigates the construction of an Adaptive Neuro‐Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimated by the model selection (MS) technique in dynamic contrast enhanced‐magnetic resonance imaging (DCE‐MRI) data analysis, and patient age. DCE‐MRI investigations of 33 treatment‐naïve patients with GBM were studied. Using the modified Tofts model and MS technique, the following physiologically nested models were constructed: Model 1, no vascular leakage (normal tissue); Model 2, leakage without efflux; Model 3, leakage with bidirectional exchange (influx and efflux). For each patient, the PK parameters of the three models were estimated as follows: blood plasma volume (v_p) for Model 1; v_p and volume transfer constant (K^trans) for Model 2; v_p, K^trans and rate constant (k_ep) for Model 3. Using Cox regression analysis, the best combination of the estimated PK parameters, together with patient age, was identified for the design and training of ANFIS. A K‐fold cross‐validation (K = 33) technique was employed for training, testing and optimization of ANFIS. Given the survival time distribution, three classes of survival were determined and a confusion matrix for the correct classification fraction (CCF) of the trained ANFIS was estimated as an accuracy index of ANFIS's performance. Patient age, k_ep and v_e (K^trans/k_ep) of Model 3, and K^trans of Model 2, were found to be the most effective parameters for training ANFIS. The CCF of the trained ANFIS was 84.8%. High diagonal elements of the confusion matrix (81.8%, 90.1% and 81.8% for Class 1, Class 2 and Class 3, respectively), with low off‐diagonal elements, strongly confirmed the robustness and high performance of the trained ANFIS for predicting the three survival classes. This study confirms that DCE‐MRI PK analysis, combined with the MS technique and ANFIS, allows the construction of a DCE‐MRI‐based fuzzy integrated predictor for the prediction of the survival of patients with GBM.     

Cluster analysis of DCE‐MRI data identifies regional tracer‐kinetic changes after tumor treatment with high intensity focused ultrasound

Evaluation of high intensity focused ultrasound (HIFU) treatment with MRI is generally based on assessment of the non‐perfused volume from contrast‐enhanced T₁‐weighted images. However, the vascular status of tissue surrounding the non‐perfused volume has not been extensively investigated with MRI. In this study, cluster analysis of the transfer constant K^trans and extravascular extracellular volume fraction v_e, derived from dynamic contrast‐enhanced MRI (DCE‐MRI) data, was performed in tumor tissue surrounding the non‐perfused volume to identify tumor subregions with distinct contrast agent uptake kinetics. DCE‐MRI was performed in CT26.WT colon carcinoma‐bearing BALB/c mice before (n = 12), directly after (n = 12) and 3 days after (n = 6) partial tumor treatment with HIFU. In addition, a non‐treated control group (n = 6) was included. The non‐perfused volume was identified based on the level of contrast enhancement. Quantitative comparison between non‐perfused tumor fractions and non‐viable tumor fractions derived from NADH‐diaphorase histology showed a stronger agreement between these fractions 3 days after treatment (R² to line of identity = 0.91) compared with directly after treatment (R² = 0.74). Next, k‐means clustering with four clusters was applied to K^trans and v_e parameter values of all significantly enhanced pixels. The fraction of pixels within two clusters, characterized by a low K^trans and either a low or high v_e, significantly increased after HIFU. Changes in composition of these clusters were considered to be HIFU induced. Qualitative H&E histology showed that HIFU‐induced alterations in these clusters may be associated with hemorrhage and structural tissue disruption. Combined microvasculature and hypoxia staining suggested that these tissue changes may affect blood vessel functionality and thereby tumor oxygenation. In conclusion, it was demonstrated that, in addition to assessment of the non‐perfused tumor volume, the presented methodology gives further insight into HIFU‐induced effects on tumor vascular status. This method may aid in assessment of the consequences of vascular alterations for the fate of the tissue. Copyright © 2015 John Wiley & Sons, Ltd.     

Dynamic contrast‐enhanced MRI model selection for predicting tumor aggressiveness in papillary thyroid cancers

The purpose of this study was to identify the optimal tracer kinetic model from T₁‐weighted dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) data and evaluate whether parameters estimated from the optimal model predict tumor aggressiveness determined from histopathology in patients with papillary thyroid carcinoma (PTC) prior to surgery. In this prospective study, 18 PTC patients underwent pretreatment DCE‐MRI on a 3 T MR scanner prior to thyroidectomy. This study was approved by the institutional review board and informed consent was obtained from all patients. The two‐compartment exchange model, compartmental tissue uptake model, extended Tofts model (ETM) and standard Tofts model were compared on a voxel‐wise basis to determine the optimal model using the corrected Akaike information criterion (AICc) for PTC. The optimal model is the one with the lowest AICc. Statistical analysis included paired and unpaired t‐tests and a one‐way analysis of variance. Bonferroni correction was applied for multiple comparisons. Receiver operating characteristic (ROC) curves were generated from the optimal model parameters to differentiate PTC with and without aggressive features, and AUCs were compared. ETM performed best with the lowest AICc and the highest Akaike weight (0.44) among the four models. ETM was preferred in 44% of all 3419 voxels. The ETM estimates of K^trans in PTCs with the aggressive feature extrathyroidal extension (ETE) were significantly higher than those without ETE (0.78 ± 0.29 vs. 0.34 ± 0.18 min^?1, P = 0.005). From ROC analysis, cut‐off values of K^trans, v_e and v_p, which discriminated between PTCs with and without ETE, were determined at 0.45 min^?1, 0.28 and 0.014 respectively. The sensitivities and specificities were 86 and 82% (K^trans), 71 and 82% (v_e), and 86 and 55% (v_p), respectively. Their respective AUCs were 0.90, 0.71 and 0.71. We conclude that ETM K^trans has shown potential to classify tumors with and without aggressive ETE in patients with PTC.     

Simultaneous measurement of T1/B1 and pharmacokinetic model parameters using active contrast encoding (ACE)‐MRI

The aim of this study was to assess the feasibility of combining dynamic contrast enhanced‐magnetic resonance imaging (DCE‐MRI) with the measurement of the radiofrequency (RF) transmit field B ₁ and pre‐contrast longitudinal relaxation time T ₁₀. A novel approach has been proposed to simultaneously estimate B ₁ and T ₁₀ from a modified DCE‐MRI scan that actively encodes the washout phase of the curve with different amounts of T ₁ and B ₁ weighting using multiple flip angles and repetition times, hence referred to as active contrast encoding (ACE)‐MRI. ACE‐MRI aims to simultaneously measure B ₁ and T ₁₀, together with contrast kinetic parameters, such as the transfer constant K ^trans, interstitial space volume fraction v _e and vascular space volume fraction v _p. The proposed method was tested using numerical simulations and in vivo studies with mouse models of breast cancer implanted in the flank and mammary fat pad, and glioma in the brain. In the numerical simulation study with a signal‐to‐noise ratio of 10, both B ₁ and T ₁₀ were estimated accurately with errors of 5.1 ± 3.5% and 12.3 ± 8.8% and coefficients of variation (CV) of 14.9 ± 8.6% and 15.0 ± 5.0%, respectively. Using the same ACE‐MRI data, the kinetic parameters K ^trans, v _e and v _p were also estimated with errors of 14.2 ± 8.3% (CV = 13.5 ± 4.6%), 14.7 ± 9.9% (CV = 13.3 ± 4.5%) and 14.0 ± 9.3% (CV = 14.0 ± 4.5%), respectively. For the in vivo tumor data from 11 mice, voxel‐wise comparisons between ACE‐MRI and DCE‐MRI methods showed that the mean differences for the five parameters were as follows: ΔK ^trans = 0.006 (/min), Δv _e = 0.016, Δv _p = 0.000, ΔB ₁ = ?0.014 and ΔT ₁ = ?0.085 (s), which suggests a good agreement between the two methods. When compared with separately measured B ₁ and T ₁₀, and DCE‐MRI estimated kinetic parameters as a reference, the mean relative errors of ACE‐MRI estimation were B ₁ = ?0.3%, T ₁₀ = ?8.5%, K ^trans = 11.4%, v _e = 14.5% and v _p = 4.5%. This proof‐of‐concept study demonstrates that the proposed ACE‐MRI method can be used to estimate B ₁ and T ₁₀, together with contrast kinetic model parameters.     

Correlation of tumor characteristics derived from DCE‐MRI and DW‐MRI with histology in murine models of breast cancer

The purpose of this work was to determine the relationship between the apparent diffusion coefficient (ADC, from diffusion‐weighted (DW) MRI), the extravascular, extracellular volume fraction (v_e, from dynamic contrast‐enhanced (DCE) MRI), and histological measurement of the extracellular space fraction. Athymic nude mice were injected with either human epidermal growth factor receptor 2 positive (HER2+) BT474 (n = 15) or triple negative MDA‐MB‐231 (n = 20) breast cancer cells, treated with either Herceptin (n = 8), Abraxane (low dose n = 7, high dose n = 6), or saline (n = 7 for each cell line), and imaged using DW‐ and DCE‐MRI before, during, and after treatment. After the final imaging acquisition, the tissue was resected and evaluated by histological analysis. H&E‐stained central slices were scanned using a digital brightfield microscope and evaluated with thresholding techniques to calculate the extracellular space. For both BT474 and MDA‐MB‐231, the median ADC of the central slice exhibited a significantly positive correlation with the corresponding central slice extracellular space as measured by H&E (p = 0.03, p < 0.01, respectively). Median v_e calculated from the central slice showed differing results between the two cell lines. For BT474, a significant correlation between v_e and extracellular space was calculated (p = 0.02), while MDA‐MB‐231 tumors did not demonstrate a significant correlation (p = 0.64). Additionally, there was no correlation discovered between ADC and v_e with either whole tumor analysis or central slice analysis (p > 0.05). While ADC correlates well with the histologically determined fraction of extracellular space, these data add to the growing body of literature that suggests that v_e derived from DCE‐MRI is not a reliable biomarker of extracellular space for a range of physiological conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessment of early docetaxel response in an experimental model of human breast cancer using DCE‐MRI,ex vivo HR MAS,and in vivo 1H MRS

The purpose of this study was to evaluate the use of dynamic contrast‐enhanced (DCE) MRI, in vivo ¹H MRS and ex vivo high resolution magic angle spinning (HR MAS) MRS of tissue samples as methods to detect early treatment effects of docetaxel in a breast cancer xenograft model (MCF‐7) in mice. MCF‐7 cells were implanted subcutaneously in athymic mice and treated with docetaxel (20, 30, and 40 mg/kg) or saline six weeks later. DCE‐MRI and in vivo ¹H MRS were performed on a 7 T MR system three days after treatment. The dynamic images were used as input for a two‐compartment model, yielding the vascular parameters K^trans and v_e. HR MAS MRS, histology, and immunohistochemical staining for proliferation (Ki‐67), apoptosis (M30 cytodeath), and vascular/endothelial cells (CD31) were performed on excised tumor tissue. Both in vivo spectra and HR MAS spectra were used as input for multivariate analysis (principal component analysis (PCA) and partial least squares regression analysis (PLS)) to compare controls to treated tumors. Tumor growth was suppressed in docetaxel‐treated mice compared to the controls. The anti‐tumor effect led to an increase in K^trans and v_e values in all the treated groups. Furthermore, in vivo MRS and HR MAS MRS revealed a significant decrease in choline metabolite levels for the treated groups, in accordance with reduced proliferative index as seen on Ki‐67 stained sections. In this study DCE‐MRI, in vivo MRS and ex vivo HR MAS MRS have been used to demonstrate that docetaxel treatment of a human breast cancer xenograft model results in changes in the vascular dynamics and metabolic profile of the tumors. This indicates that these MR methods could be used to monitor intra‐tumoral treatment effects. Copyright © 2009 John Wiley & Sons, Ltd.     

Intratumor mapping of intracellular water lifetime: metabolic images of breast cancer?

Shutter‐speed pharmacokinetic analysis of dynamic‐contrast‐enhanced (DCE)‐MRI data allows evaluation of equilibrium inter‐compartmental water interchange kinetics. The process measured here – transcytolemmal water exchange – is characterized by the mean intracellular water molecule lifetime (τ_i). The τ_i biomarker is a true intensive property not accessible by any formulation of the tracer pharmacokinetic paradigm, which inherently assumes it is effectively zero when applied to DCE‐MRI. We present population‐averaged in vivo human breast whole tumor τ_i changes induced by therapy, along with those of other pharmacokinetic parameters. In responding patients, the DCE parameters change significantly after only one neoadjuvant chemotherapy cycle: while K^trans (measuring mostly contrast agent (CA) extravasation) and k_ep (CA intravasation rate constant) decrease, τ_i increases. However, high‐resolution, (1 mm)², parametric maps exhibit significant intratumor heterogeneity, which is lost by averaging. A typical 400 ms τ_i value means a trans‐membrane water cycling flux of 10¹³ H₂O molecules s^?1/cell for a 12 µm diameter cell. Analyses of intratumor variations (and therapy‐induced changes) of τ_i in combination with concomitant changes of v_e (extracellular volume fraction) indicate that the former are dominated by alterations of the equilibrium cell membrane water permeability coefficient, P_W, not of cell size. These can be interpreted in light of literature results showing that τ_i changes are dominated by a P_W(active) component that reciprocally reflects the membrane driving P‐type ATPase ion pump turnover. For mammalian cells, this is the Na⁺,K⁺‐ATPase pump. These results promise the potential to discriminate metabolic and microenvironmental states of regions within tumors in vivo, and their changes with therapy. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.     

Dynamic contrast‐enhanced MRI in mouse tumors at 11.7 T: comparison of three contrast agents with different molecular weights to assess the early effects of combretastatin A4

Dynamic contrast‐enhanced (DCE)‐MRI is useful to assess the early effects of drugs acting on tumor vasculature, namely anti‐angiogenic and vascular disrupting agents. Ultra‐high‐field MRI allows higher‐resolution scanning for DCE‐MRI while maintaining an adequate signal‐to‐noise ratio. However, increases in susceptibility effects, combined with decreases in longitudinal relaxivity of gadolinium‐based contrast agents (GdCAs), make DCE‐MRI more challenging at high field. The aim of this work was to explore the feasibility of using DCE‐MRI at 11.7 T to assess the tumor hemodynamics of mice. Three GdCAs possessing different molecular weights (gadoterate: 560 Da, 0.29 mmol Gd/kg; p846: 3.5 kDa, 0.10 mmol Gd/kg; and p792: 6.47 kDa, 0.15 mmol Gd/kg) were compared to see the influence of the molecular weight in the highlight of the biologic effects induced by combretastatin A4 (CA4). Mice bearing transplantable liver tumor (TLT) hepatocarcinoma were divided into two groups (n = 5–6 per group and per GdCA): a treated group receiving 100 mg/kg CA4, and a control group receiving vehicle. The mice were imaged at 11.7 T with a T₁‐weighted FLASH sequence 2 h after the treatment. Individual arterial input functions (AIFs) were computed using phase imaging. These AIFs were used in the Extended Tofts Model to determine K^trans and v_p values. A separate immunohistochemistry study was performed to assess the vascular perfusion and the vascular density. Phase imaging was used successfully to measure the AIF for the three GdCAs. In control groups, an inverse relationship between the molecular weight of the GdCA and K^trans and v_p values was observed. K^trans was significantly decreased in the treated group compared with the control group for each GdCA. DCE‐MRI at 11.7 T is feasible to assess tumor hemodynamics in mice. With K^trans, the three GdCAs were able to track the early vascular effects induced by CA4 treatment. Copyright © 2014 John Wiley & Sons, Ltd.     

Dynamic contrast-enhanced MRI parametric mapping using high spatiotemporal resolution Golden-angle RAdial Sparse Parallel MRI and iterative joint estimation of the arterial input function and pharmacokinetic parameters

The aim of this work is to develop a data-driven quantitative dynamic contrast-enhanced (DCE) MRI technique using Golden-angle RAdial Sparse Parallel (GRASP) MRI with high spatial resolution and high flexible temporal resolution and pharmacokinetic (PK) analysis with an arterial input function (AIF) estimated directly from the data obtained from each patient. DCE-MRI was performed on 13 patients with gynecological malignancy using a 3-T MRI scanner with a single continuous golden-angle stack-of-stars acquisition and image reconstruction with two temporal resolutions, by exploiting a unique feature in GRASP that reconstructs acquired data with user-defined temporal resolution. Joint estimation of the AIF (both AIF shape and delay) and PK parameters was performed with an iterative algorithm that alternates between AIF and PK estimation. Computer simulations were performed to determine the accuracy (expressed as percentage error [PE]) and precision of the estimated parameters. PK parameters (volume transfer constant [K^trans], fractional volume of the extravascular extracellular space [v_e], and blood plasma volume fraction [v_p]) and normalized root-mean-square error [nRMSE] (%) of the fitting errors for the tumor contrast kinetic data were measured both with population-averaged and data-driven AIFs. On patient data, the Wilcoxon signed-rank test was performed to compare nRMSE. Simulations demonstrated that GRASP image reconstruction with a temporal resolution of 1 s/frame for AIF estimation and 5 s/frame for PK analysis resulted in an absolute PE of less than 5% in the estimation of K^trans and v_e, and less than 11% in the estimation of v_p. The nRMSE (mean ± SD) for the dual temporal resolution image reconstruction and data-driven AIF was 0.16 ± 0.04 compared with 0.27 ± 0.10 (p < 0.001) with 1 s/frame using population-averaged AIF, and 0.23 ± 0.07 with 5 s/frame using population-averaged AIF (p < 0.001). We conclude that DCE-MRI data acquired and reconstructed with the GRASP technique at dual temporal resolution can successfully be applied to jointly estimate the AIF and PK parameters from a single acquisition resulting in data-driven AIFs and voxelwise PK parametric maps.     

DCE and DW-MRI monitoring of vascular disruption following VEGF-Trap treatment of a rat glioma model

Vascular‐targeted therapies have shown promise as adjuvant cancer treatment. As these agents undergo clinical evaluation, sensitive imaging biomarkers are needed to assess drug target interaction and treatment response. In this study, dynamic contrast enhanced MRI (DCE‐MRI) and diffusion‐weighted MRI (DW‐MRI) were evaluated for detecting response of intracerebral 9 L gliosarcomas to the antivascular agent VEGF‐Trap, a fusion protein designed to bind all forms of Vascular Endothelial Growth Factor‐A (VEGF‐A) and Placental Growth Factor (PGF). Rats with 9 L tumors were treated twice weekly for two weeks with vehicle or VEGF‐Trap. DCE‐ and DW‐MRI were performed one day prior to treatment initiation and one day following each administered dose. Kinetic parameters (K^trans, volume transfer constant; k_ep, efflux rate constant from extravascular/extracellular space to plasma; and v_p, blood plasma volume fraction) and the apparent diffusion coefficient (ADC) over the tumor volumes were compared between groups. A significant decrease in kinetic parameters was observed 24 hours following the first dose of VEGF‐Trap in treated versus control animals (p < 0.05) and was accompanied by a decline in ADC values. In addition to the significant hemodynamic effect, VEGF‐Trap treated animals exhibited significantly longer tumor doubling times (p < 0.05) compared to the controls. Histological findings were found to support imaging response metrics. In conclusion, kinetic MRI parameters and change in ADC have been found to serve as sensitive and early biomarkers of VEGF‐Trap anti‐vascular targeted therapy. Copyright © 2011 John Wiley & Sons, Ltd.     

Correlative assessment of tumor microcirculation using contrast‐enhanced perfusion MRI and intravoxel incoherent motion diffusion‐weighted MRI: is there a link between them?

The purpose of this study was to correlate intravoxel incoherent motion (IVIM) imaging with classical perfusion‐weighted MRI metrics in human gliomas. Parametric images for slow diffusion coefficient (D), fast diffusion coefficient (D*), and fractional perfusion‐related volume (f) in patients with high‐grade gliomas were generated. Maps of F_p (plasma flow), v_p (vascular plasma volume), PS (permeability surface–area product), v_e (extravascular, extracellular volume), E (extraction ratio), k_e (influx ratio into the interstitium), and t_c (vascular transit time) from dynamic contrast‐enhanced (DCE) and dynamic susceptibility contrast‐enhanced (DSC) MRI were also generated. A region‐of‐interest analysis on the contralateral healthy white matter and on the tumor areas was performed and the extracted parameter values were tested for any significant differences among tumor grades or any correlations. Only f could be significantly correlated to DSC‐derived v_p and t_c in healthy brain tissue. Concerning the tumor regions, F_p was significantly positively correlated with D* and inversely correlated with f in DSC measurements. The D*, f, and f × D* values in the WHO grade III gliomas were non‐significantly different from those in the grade IV gliomas. There was a trend to significant negative correlations between f and PS as well as between f × D* and k_e in DCE experiments. Presumably due to different theoretical background, tracer properties and modeling of the tumor vasculature in the IVIM theory, there is no clearly evident link between D*, f and DSC‐ and DCE‐derived metrics. Copyright © 2014 John Wiley & Sons, Ltd.     

Gaussian mixture model‐based classification of dynamic contrast enhanced MRI data for identifying diverse tumor microenvironments: preliminary results

Tumor hypoxia develops heterogeneously, affects radiation sensitivity and the development of metastases. Prognostic information derived from the in vivo characterization of the spatial distribution of hypoxic areas in solid tumors can be of value for radiation therapy planning and for monitoring the early treatment response. Tumor hypoxia is caused by an imbalance between the supply and consumption of oxygen. The tumor oxygen supply is inherently linked to its vasculature and perfusion which can be evaluated by dynamic contrast enhanced (DCE‐) MRI using the contrast agent Gd‐DTPA. Thus, we hypothesize that DCE‐MRI data may provide surrogate information regarding tumor hypoxia. In this study, DCE‐MRI data from a rat prostate tumor model were analysed with a Gaussian mixture model (GMM)‐based classification to identify perfused, hypoxic and necrotic areas for a total of ten tumor slices from six rats, of which one slice was used as training data for GMM classifications. The results of pattern recognition analyzes were validated by comparison to corresponding Ak_ep maps defining the perfused area (0.84 ± 0.09 overlap), hematoxylin and eosin (H&E)‐stained tissue sections defining necrosis (0.64 ± 0.15 overlap) and pimonidazole‐stained sections defining hypoxia (0.72 ± 0.17 overlap), respectively. Our preliminary data indicate the feasibility of a GMM‐based classification to identify tumor hypoxia, necrosis and perfusion/permeability from non‐invasively acquired, in vivo DCE‐MRI data alone, possibly obviating the need for invasive procedures, such as biopsies, or exposure to radioactivity, such as positron emission tomography (PET) exams. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimization of saturation‐recovery dynamic contrast‐enhanced MRI acquisition protocol: monte carlo simulation approach demonstrated with gadolinium MR renography

Dynamic contrast‐enhanced (DCE) MRI is widely used for the measurement of tissue perfusion and to assess organ function. MR renography, which is acquired using a DCE sequence, can measure renal perfusion, filtration and concentrating ability. Optimization of the DCE acquisition protocol is important for the minimization of the error propagation from the acquired signals to the estimated parameters, thus improving the precision of the parameters. Critical to the optimization of contrast‐enhanced T₁‐weighted protocols is the balance of the T₁‐shortening effect across the range of gadolinium (Gd) contrast concentration in the tissue of interest. In this study, we demonstrate a Monte Carlo simulation approach for the optimization of DCE MRI, in which a saturation‐recovery T₁‐weighted gradient echo sequence is simulated and the impact of injected dose (D) and time delay (TD, for saturation recovery) is tested. The results show that high D and/or high TD cause saturation of the peak arterial signals and lead to an overestimation of renal plasma flow (RPF) and glomerular filtration rate (GFR). However, the use of low TD (e.g. 100 ms) and low D leads to similar errors in RPF and GFR, because of the Rician bias in the pre‐contrast arterial signals. Our patient study including 22 human subjects compared TD values of 100 and 300 ms after the injection of 4 mL of Gd contrast for MR renography. At TD = 100 ms, we computed an RPF value of 157.2 ± 51.7 mL/min and a GFR of 33.3 ± 11.6 mL/min. These results were all significantly higher than the parameter estimates at TD = 300 ms: RPF = 143.4 ± 48.8 mL/min (p = 0.0006) and GFR = 30.2 ± 11.5 mL/min (p = 0.0015). In conclusion, appropriate optimization of the DCE MRI protocol using simulation can effectively improve the precision and, potentially, the accuracy of the measured parameters. Copyright © 2016 John Wiley & Sons, Ltd.     

An adaptive model for rapid and direct estimation of extravascular extracellular space in dynamic contrast enhanced MRI studies

Extravascular extracellular space (v_e) is a key parameter to characterize the tissue of cerebral tumors. This study introduces an artificial neural network (ANN) as a fast, direct, and accurate estimator of v_e from a time trace of the longitudinal relaxation rate, ΔR₁ (R₁ = 1/T₁), in DCE‐MRI studies. Using the extended Tofts equation, a set of ΔR₁ profiles was simulated in the presence of eight different signal to noise ratios. A set of gain‐ and noise‐insensitive features was generated from the simulated ΔR₁ profiles and used as the ANN training set. A K‐fold cross‐validation method was employed for training, testing, and optimization of the ANN. The performance of the optimal ANN (12:6:1, 12 features as input vector, six neurons in hidden layer, and one output) in estimating v_e at a resolution of 10% (error of ±5%) was 82%. The ANN was applied on DCE‐MRI data of 26 glioblastoma patients to estimate v_e in tumor regions. Its results were compared with the maximum likelihood estimation (MLE) of v_e. The two techniques showed a strong agreement (r = 0.82, p < 0.0001). Results implied that the perfected ANN was less sensitive to noise and outperformed the MLE method in estimation of v_e.     

39K and 23Na relaxation times and MRI of rat head at 21.1 T

At ultrahigh magnetic field strengths (B₀ ≥ 7.0 T), potassium (³⁹K) MRI might evolve into an interesting tool for biomedical research. However, ³⁹K MRI is still challenging because of the low NMR sensitivity and short relaxation times. In this work, we demonstrated the feasibility of ³⁹K MRI at 21.1 T, determined in vivo relaxation times of the rat head at 21.1 T, and compared ³⁹K and sodium (²³Na) relaxation times of model solutions containing different agarose gel concentrations at 7.0 and 21.1 T. ³⁹K relaxation times were markedly shorter than those of ²³Na. Compared with the lower field strength, ³⁹K relaxation times were up to 1.9‐ (T₁), 1.4‐ (T_2S) and 1.9‐fold (T_2L) longer at 21.1 T. The increase in the ²³Na relaxation times was less pronounced (up to 1.2‐fold). Mono‐exponential fits of the ³⁹K longitudinal relaxation time at 21.1 T revealed T₁ = 14.2 ± 0.1 ms for the healthy rat head. The ³⁹K transverse relaxation times were 1.8 ± 0.2 ms and 14.3 ± 0.3 ms for the short (T_2S) and long (T_2L) components, respectively. ²³Na relaxation times were markedly longer (T₁ = 41.6 ± 0.4 ms; T_2S = 4.9 ± 0.2 ms; T_2L = 33.2 ± 0.2 ms). ³⁹K MRI of the healthy rat head could be performed with a nominal spatial resolution of 1 × 1 × 1 mm³ within an acquisition time of 75 min. The increase in the relaxation times with magnetic field strength is beneficial for ²³Na and ³⁹K MRI at ultrahigh magnetic field strength. Our results demonstrate that ³⁹K MRI at 21.1 T enables acceptable image quality for preclinical research. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessment of vessel permeability by combining dynamic contrast‐enhanced and arterial spin labeling MRI

The forward volumetric transfer constant (K^trans), a physiological parameter extracted from dynamic contrast‐enhanced (DCE) MRI, is weighted by vessel permeability and tissue blood flow. The permeability × surface area product per unit mass of tissue (PS) in brain tumors was estimated in this study by combining the blood flow obtained through pseudo‐continuous arterial spin labeling (PCASL) and K^trans obtained through DCE MRI. An analytical analysis and a numerical simulation were conducted to understand how errors in the flow and K^trans estimates would propagate to the resulting PS. Fourteen pediatric patients with brain tumors were scanned on a clinical 3‐T MRI scanner. PCASL perfusion imaging was performed using a three‐dimensional (3D) fast‐spin‐echo readout module to determine blood flow. DCE imaging was performed using a 3D spoiled gradient‐echo sequence, and the K^trans map was obtained with the extended Tofts model. The numerical analysis demonstrated that the uncertainty of PS was predominantly dependent on that of K^trans and was relatively insensitive to the flow. The average PS values of the whole tumors ranged from 0.006 to 0.217 min^?1, with a mean of 0.050 min^?1 among the patients. The mean K^trans value was 18% lower than the PS value, with a maximum discrepancy of 25%. When the parametric maps were compared on a voxel‐by‐voxel basis, the discrepancies between PS and K^trans appeared to be heterogeneous within the tumors. The PS values could be more than two‐fold higher than the K^trans values for voxels with high K^trans levels. This study proposes a method that is easy to implement in clinical practice and has the potential to improve the quantification of the microvascular properties of brain tumors. Copyright © 2015 John Wiley & Sons, Ltd.     

Reduced respiratory motion artifacts using structural similarity in fast 2D dynamic contrast enhanced MRI of liver lesions

The purpose of this work was to improve dynamic contrast enhanced MRI (DCE‐MRI) of liver lesions by removing motion corrupted images as identified by a structural similarity (SSIM) algorithm, and to assess the effect of this correction on the pharmacokinetic parameter K^trans using automatically determined arterial input functions (AIFs). Fifteen patients with colorectal liver metastases were measured twice with a T₁ weighted multislice 2D FLASH sequence for DCE‐MRI (time resolution 1.2 s). AIFs were automatically derived from contrast inflow in the aorta of each patient. Thereafter, SSIM identified motion corrupted images of the liver were removed from the DCE dataset. From this corrected data set K^trans and its reproducibility were determined. Using the SSIM algorithm a median fraction of 46% (range 37–50%) of the liver images in DCE time series was labeled as motion distorted. Rejection of these images resulted in a significantly lower median K^trans (p < 0.05) and lower coefficient of repeatability of K^trans in liver metastases compared with an analysis without correction. SSIM correction improves the reproducibility of the DCE‐MRI parameter K^trans in liver metastasis and reduces contamination of K^trans values of lesions by that of surrounding normal liver tissue.     

Evaluation of segmented 3D acquisition schemes for whole‐brain high‐resolution arterial spin labeling at 3 T

Recent technical developments have significantly increased the signal‐to‐noise ratio (SNR) of arterial spin labeled (ASL) perfusion MRI. Despite this, typical ASL acquisitions still employ large voxel sizes. The purpose of this work was to implement and evaluate two ASL sequences optimized for whole‐brain high‐resolution perfusion imaging, combining pseudo‐continuous ASL (pCASL), background suppression (BS) and 3D segmented readouts, with different in‐plane k‐space trajectories. Identical labeling and BS pulses were implemented for both sequences. Two segmented 3D readout schemes with different in‐plane trajectories were compared: Cartesian (3D GRASE) and spiral (3D RARE Stack‐Of‐Spirals). High‐resolution perfusion images (2 × 2 × 4 mm³) were acquired in 15 young healthy volunteers with the two ASL sequences at 3 T. The quality of the perfusion maps was evaluated in terms of SNR and gray‐to‐white matter contrast. Point‐spread‐function simulations were carried out to assess the impact of readout differences on the effective resolution. The combination of pCASL, in‐plane segmented 3D readouts and BS provided high‐SNR high‐resolution ASL perfusion images of the whole brain. Although both sequences produced excellent image quality, the 3D RARE Stack‐Of‐Spirals readout yielded higher temporal and spatial SNR than 3D GRASE (spatial SNR = 8.5 ± 2.8 and 3.7 ± 1.4; temporal SNR = 27.4 ± 12.5 and 15.6 ± 7.6, respectively) and decreased through‐plane blurring due to its inherent oversampling of the central k‐space region, its reduced effective T_E and shorter total readout time, at the expense of a slight increase in the effective in‐plane voxel size. Copyright © 2014 John Wiley & Sons, Ltd.