Quantitative dynamic contrast-enhanced MRI for mouse models using automatic detection of the arterial input function

Noninvasive ROS imaging and drug delivery monitoring in the tumor microenvironment

Reactive oxygen species (ROS) that are overproduced in certain tumors can be considered an indicator of oxidative stress levels in the tissue. Here, we report a magnetic resonance imaging (MRI)-based probe capable of detecting ROS levels in the tumor microenvironment (TME) using ROS-responsive manganese ion (Mn2+)-chelated, biotinylated bilirubin nanoparticles (Mn@bt-BRNPs). These nanoparticles are disrupted in the presence of ROS, resulting in the release of free Mn2+, which induces T1-weighted MRI signal enhancement. Mn@BRNPs show more rapid and greater MRI signal enhancement in high ROS-producing A549 lung carcinoma cells compared with low ROS-producing DU145 prostate cancer cells. A pseudo three-compartment model devised for the ROS-reactive MRI probe enables mapping of the distribution and concentration of ROS within the tumor. Furthermore, doxorubicin-loaded, cancer-targeting ligand biotin-conjugated Dox/Mn@bt-BRNPs show considerable accumulation in A549 tumors and also effectively inhibit tumor growth without causing body weight loss, suggesting their usefulness as a new theranostic agent. Collectively, these findings suggest that Mn@bt-BRNPs could be used as an imaging probe capable of detecting ROS levels and monitoring drug delivery in the TME with potential applicability to other inflammatory diseases.

A Multi-Layer Perceptron Network for Perfusion Parameter Estimation in DCE-MRI Studies of the Healthy Kidney

Background: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an imaging technique which helps in visualizing and quantifying perfusion—one of the most important indicators of an organ’s state. This paper focuses on perfusion and filtration in the kidney, whose performance directly influences versatile functions of the body. In clinical practice, kidney function is assessed by measuring glomerular filtration rate (GFR). Estimating GFR based on DCE-MRI data requires the application of an organ-specific pharmacokinetic (PK) model. However, determination of the model parameters, and thus the characterization of GFR, is sensitive to determination of the arterial input function (AIF) and the initial choice of parameter values. Methods: This paper proposes a multi-layer perceptron network for PK model parameter determination, in order to overcome the limitations of the traditional model’s optimization techniques based on non-linear least-squares curve-fitting. As a reference method, we applied the trust-region reflective algorithm to numerically optimize the model. The effectiveness of the proposed approach was tested for 20 data sets, collected for 10 healthy volunteers whose image-derived GFR scores were compared with ground-truth blood test values. Results: The achieved mean difference between the image-derived and ground-truth GFR values was 2.35 mL/min/1.73 m2, which is comparable to the result obtained for the reference estimation method (−5.80 mL/min/1.73 m2). Conclusions: Neural networks are a feasible alternative to the least-squares curve-fitting algorithm, ensuring agreement with ground-truth measurements at a comparable level. The advantages of using a neural network are twofold. Firstly, it can estimate a GFR value without the need to determine the AIF for each individual patient. Secondly, a reliable estimate can be obtained, without the need to manually set up either the initial parameter values or the constraints thereof.

Toward precise arterial input functions derived from DCE-MRI through a novel extracorporeal circulation approach in mice

PURPOSE

Dynamic contrast-enhanced MRI can be used in pharmacokinetic models to quantify functional parameters such as perfusion and permeability. However, precise quantification in preclinical models is challenged by the difficulties to dynamically measure the true arterial blood contrast agent concentration. We propose a novel approach toward a precise and experimentally feasible method to derive the arterial input function from DCE-MRI in mice.

METHODS

Arterial blood was surgically shunted from the femoral artery to the tail vein and led through an extracorporeal circulation that resided on the head of brain tumor-bearing mice inside the FOV of a 9.4T MRI scanner. Dynamic 3D-FLASH scanning was performed after injection of gadobutrol with an effective resolution of 0.175 × 0.175 × 1 mm and a temporal resolution of 4 seconds. Pharmacokinetic modeling was performed using the extended Tofts and two-compartment exchange model.

RESULTS

Arterial input functions measured inside the extracorporeal circulation showed little noise, small interindividual variance, and typical curve shapes. Ex vivo and mass spectrometry validation measurements documented the influence of shunt flow velocity and hematocrit on estimation of contrast agent concentrations. Modeling of tumors and muscles allowed fitting of the recorded dynamic concentrations, resulting in quantitative plausible parameters.

CONCLUSION

The extracorporeal circulation allows deriving the contrast agent dynamics in arterial blood with high robustness and at acceptable experimental effort from DCE-MRI, previously not achievable in mice. It sets the basis for quantitative precise pharmacokinetic modeling in small animals to enhance the translatability of preclinical DCE-MRI measurements to patients.

Response-Derived Input Function Estimation for Dynamic Contrast-Enhanced MRI Demonstrated by Anti-DLL4 Treatment in a Murine U87 Xenograft Model

PURPOSE

Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) is an accepted method to evaluate tumor perfusion and permeability and anti-vascular cancer therapies. However, there is no consensus on the vascular input function estimation method, which is critical to kinetic modeling and K ^trans estimation. This work proposes a response-derived input function (RDIF) estimated from the response of the tumor, modeled as a linear, time-invariant (LTI) system.

PROCEDURES

In an LTI system, an unknown input can be estimated from the system response. If applied to DCE MRI, this method would eliminate need of distal image-derived inputs, model inputs, or reference regions. The RDIF method first determines each tumor pixel's best-fit input function, and then combines the individual fits into a single input function for the entire tumor. The method was tested with simulations and a xenograft study with anti-vascular drug treatment.

RESULTS

Simulations showed successful estimation of input function expected values and good performance in the presence of noise. In vivo, significant reductions in K ^trans and AUC occurred 2 days following anti-delta-like ligand 4 treatment. The in vivo study results yielded K ^trans consistent with published data in xenograft models.

CONCLUSION

The RDIF method for DCE analysis offers an alternative, easy-to-implement method for estimating the input function in tumors. The method assumes that during the DCE experiment, the changes observed by MRI result solely from vascular perfusion and permeability kinetics, and that information can be used to model the input function. Importantly, the method is demonstrated in a murine xenograft study to yield K ^trans results consistent with literature values and suitable for compound studies.

Characterization of Continuous and Pulsed Emission modes of a Hybrid Micro Focus X-ray Source for Medical Imaging Applications

The aim of this study was to quantitatively characterize a micro focus x-ray tube that can operate in both continuous and pulsed emission modes. The micro focus x-ray source (Model L9181-06, Hamamatsu Photonics, Japan) has a varying focal spot size ranging from 16-50 μm as the source output power changes from 10-39 W. We measured the source output, beam quality, focal spot sizes, kV accuracy, spectra shapes and spatial resolution. Source output was measured using an ionization chamber for various tube voltages (kVs) with varying current (μA) and distances. The beam quality was measured in terms of half value layer (HVL), kV accuracy was measured with a non-invasive kV meter, and the spectra was measured using a compact integrated spectrometer system. The focal spot sizes were measured using a slit method with a CCD detector with a pixel pitch of 22 μm. The spatial resolution was quantitatively measured using the slit method with a CMOS flat panel detector with a 50 μm pixel pitch, and compared to the qualitative results obtained by imaging a contrast bar pattern. The focal spot sizes in the vertical direction were smaller than that of the horizontal direction, the impact of which was visible when comparing the spatial resolution values. Our analyses revealed that both emission modes yield comparable imaging performances in terms of beam quality, spectra shape and spatial resolution effects. There were no significantly large differences, thus providing the motivation for future studies to design and develop stable and robust cone beam imaging systems for various diagnostic applications.

Nanoagonist-mediated endothelial tight junction opening: A strategy for safely increasing brain drug delivery in mice

Even though opening endothelial tight junctions is an efficient way to up-regulate brain drug delivery, the extravasation of blood-borne components from the compromised tight junctions can result in adverse consequences such as edema and neuronal injuries. In this work, we developed a nanoagonist that temporarily opened tight junctions by signaling adenosine 2A receptor, a type of G protein-coupled receptor expressed on brain capillary endothelial cells. Magnetic resonance imaging demonstrated remarkable blood-brain barrier permeability enhancements and significantly increased brain uptakes of both small molecular and macromolecular paramagnetic agents after nanoagonist administration. Gamma ray imaging and transmission electron microscope observed tight junction opening followed by spontaneous recovery after nanoagonist treatment. Immunofluorescence staining showed the unspoiled basal membrane, pericytes and astrocyte endfeet that enwrapped the vascular endothelium. Importantly, edema, apoptosis and neuronal injuries observed after hypertonic agent mediated tight junction-opening were not observed after nanoagonist intervention. The uncompromised neurovascular units may prevent the leakage of blood-borne constituents into brain parenchyma and accelerate tight junction recovery. Considering blood-brain barrier impermeability is a major obstacle in the treatment of central nervous system diseases, nanoagonist-mediated tight junction opening provides a promising strategy to enhance brain drug delivery with minimized adverse effects.

Intravoxel Incoherent Motion Diffusion Weighted Magnetic Resonance Imaging for Differentiation Between Nasopharyngeal Carcinoma and Lymphoma at the Primary Site

OBJECTIVE

The aim of the study was to investigate the utility of intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (DWI) for differentiating nasopharyngeal carcinoma (NPC) from lymphoma.

METHODS

Intravoxel incoherent motion-based parameters including the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), and fD* (the product of D* and f) were retrospectively compared between 102 patients (82 with NPC, 20 with lymphoma) who received pretreatment IVIM DWI.

RESULTS

Compared with lymphoma, NPC exhibited higher ADC, D, D*, fD* values (P < 0.001) and f value (P = 0.047). The optimal cutoff values (area under the curve, sensitivity, and specificity, respectively) for distinguishing the 2 tumors were as follows: ADC value of 0.761 × 10 mm/s (0.781, 93.90%, 55.00%); D, 0.66 × 10 mm/s (0.802, 54.88%, 100.00%); D*, 7.89 × 10 mm/s (0.898, 82.93%, 85.00%); f, 0.29 (0.644, 41.46%, 95.00%); and fD*, 1.99 × 10 mm/s (0.960, 85.37%, 100.00%).

CONCLUSIONS

Nasopharyngeal carcinoma exhibits different IVIM-based imaging features from lymphoma. Intravoxel incoherent motion DWI is useful for differentiating lymphoma from NPC.

Evaluation of an automated method for arterial input function detection for first-pass myocardial perfusion cardiovascular magnetic resonance

BACKGROUND

Quantitative assessment of myocardial blood flow (MBF) with first-pass perfusion cardiovascular magnetic resonance (CMR) requires a measurement of the arterial input function (AIF). This study presents an automated method to improve the objectivity and reduce processing time for measuring the AIF from first-pass perfusion CMR images. This automated method is used to compare the impact of different AIF measurements on MBF quantification.

METHODS

Gadolinium-enhanced perfusion CMR was performed on a 1.5 T scanner using a saturation recovery dual-sequence technique. Rest and stress perfusion series from 270 clinical studies were analyzed. Automated image processing steps included motion correction, intensity correction, detection of the left ventricle (LV), independent component analysis, and LV pixel thresholding to calculate the AIF signal. The results were compared with manual reference measurements using several quality metrics based on the contrast enhancement and timing characteristics of the AIF. The median and 95% confidence interval (CI) of the median were reported. Finally, MBF was calculated and compared in a subset of 21 clinical studies using the automated and manual AIF measurements.

RESULTS

Two clinical studies were excluded from the comparison due to a congenital heart defect present in one and a contrast administration issue in the other. The proposed method successfully processed 99.63% of the remaining image series. Manual and automatic AIF time-signal intensity curves were strongly correlated with median correlation coefficient of 0.999 (95% CI [0.999, 0.999]). The automated method effectively selected bright LV pixels, excluded papillary muscles, and required less processing time than the manual approach. There was no significant difference in MBF estimates between manually and automatically measured AIFs (p = NS). However, different sizes of regions of interest selection in the LV cavity could change the AIF measurement and affect MBF calculation (p = NS to p = 0.03).

CONCLUSION

The proposed automatic method produced AIFs similar to the reference manual method but required less processing time and was more objective. The automated algorithm may improve AIF measurement from the first-pass perfusion CMR images and make quantitative myocardial perfusion analysis more robust and readily available.

Discrimination between Metastatic and Nonmetastatic Mesorectal Lymph Nodes in Rectal Cancer Using Intravoxel Incoherent Motion Diffusion-weighted Magnetic Resonance Imaging

RATIONALE AND OBJECTIVES

The aim of the study was to investigate the diagnostic value of intravoxel incoherent motion diffusion-weighted magnetic resonance imaging (IVIM DWI) for discriminating nonmetastatic from metastatic mesorectal lymph nodes in rectal cancer.

MATERIALS AND METHODS

IVIM DWI was performed preoperatively on 50 patients with rectal carcinoma. The short-axis diameter, short- to long-axis diameter ratio, and IVIM-based parameter (pure diffusion coefficient [D], pseudo-diffusion coefficient [D*] and perfusion fraction [f]) values were compared between the metastatic and nonmetastatic lymph node groups.

RESULTS

The short-axis diameter; short- to long-axis diameter ratio; and D, D*, and f values for the nonmetastatic lymph node group (n = 28) were 6.446 ± 1.201 mm, 0.815 ± 0.099, 1.071 ± 0.234 × 10(-3) mm(2)/s, 15.443 ± 5.946 mm(2)/s and 0.261 ± 0.128, respectively, and were 9.045 ± 3.185 mm, 0.809 ± 0.099, 0.816 ± 0.121 × 10(-3) mm(2)/s, 11.679 ± 7.521 × 10(-3) mm(2)/s, and 0.190 ± 0.064, respectively, for the metastatic lymph node group (n = 31). The short-axis diameter for the metastatic group was significantly higher than for the nonmetastatic group (P <0.001). The metastatic group exhibited significantly lower D and D* values than the nonmetastatic group (P <0.01). The short- to long-axis diameter ratio and f values did not differ significantly between the two groups. Optimal cutoff values (area under the curve, sensitivity, and specificity) for distinguishing metastatic from nonmetastatic lymph nodes were as follows: short-axis diameter = 5.563 mm (0.783, 74.2%, 82.1%); D = 0.667 × 10(-3) mm(2)/s (0.885, 77.4%, 89.3%); and D* = 0.485 × 10(-3) mm(2)/s (0.727, 80.6%, 67.9%).

CONCLUSION

IVIM DWI is useful to differentiate between metastatic and nonmetastatic mesorectal lymph nodes in rectal cancer.

Quantitative dynamic contrast-enhanced and diffusion-weighted MRI for differentiation between nasopharyngeal carcinoma and lymphoma at the primary site

OBJECTIVES

To investigate the value of quantitative dynamic contrast-enhanced MRI (QDCE-MRI) and diffusion-weighted MRI (DW-MRI) in differentiating nasopharyngeal carcinoma (NPC) from lymphoma.

METHODS

We retrospectively analysed the data from 102 patients (82 with NPC and 20 with lymphoma) who underwent pre-treatment QDCE-MRI and DW-MRI on a 1.5-T MR unit. QDEC-MRI parameters [influx transfer constant (K(trans)), efflux rate constant (Kep), fractional volume of extravascular extracellular space (Ve) and fractional volume of plasma (fPV)] based on pharmacokinetic model and apparent diffusion coefficient (ADC) were compared between the two nasopharyngeal malignancies.

RESULTS

The K(trans), Kep, Ve, fPV and ADC values (mean ± standard deviation) for NPC were 0.366 ± 0.155 min(-1), 1.353 ± 0.468 min(-1), 0.292 ± 0.117, 0.027 ± 0.024 and 0.981 ± 0.184 × 10(-3) mm(2) s(-1), respectively. The K(trans), Kep, Ve, fPV and ADC values (mean ± standard deviation) for lymphoma were 0.212 ± 0.059 min(-1), 1.073 ± 0.238 min(-1), 0.213 ± 0.104, 0.008 ± 0.007 and 0.760 ± 0.182 × 10(-3) mm(2) s(-1), respectively. Optimal cut-off values (area under the curve, sensitivity, specificity) for distinguishing the two tumours were as follows: K(trans) = 0.262 min(-1) (0.866, 80.49%, 85.00%), Kep = 1.401 min(-1) (0.681, 43.90%, 100.00%), Ve = 0.211 (0.784, 76.83%, 85.00%), fPV = 0.012 (0.779, 60.98%, 85.00%), ADC = 0.761 × 10(-3) mm(2) s(-1) (0.781, 93.90%, 55.00%).

CONCLUSIONS

QDCE-MRI together with DW-MRI is useful for differentiation between NPC and lymphoma.

Dynamic contrast-enhanced MRI in mice at high field: estimation of the arterial input function can be achieved by phase imaging

PURPOSE

Quantitative dynamic contrast-enhanced MRI requires an accurate arterial input function (AIF). At high field, increased susceptibility effects and decreased longitudinal relaxivity of contrast agents lead to predominant T2* effects in blood vessels, producing a dip in signal during passage of the contrast agent bolus. This study determined phase-derived AIFs in mice at 11.7 T.

METHODS

AIFs were measured in aorta/vena cava for five FBV/N mice and in iliac arteries/veins for five NMRI mice with a fast low angle shot sequence, simultaneously with tumor imaging (temporal resolution: 1.19 s). Gadoterate was injected into the tail vein as a bolus (0.286 mmol Gd/kg). An in vitro study was also performed to calculate the relationship between ΔΦ and gadolinium concentration.

RESULTS

The phantom system confirmed the linear relationship between measured ΔΦ and gadolinium concentration. In vivo, a dip in arterial magnitude signal made it impossible to quantify the AIF. With phase imaging, a clear quantifiable bolus peak was obtained; peak measured concentration in plasma was 4.9 ± 0.9 mM for FBV/N mice and 8.0 ± 0.6 mM for NMRI mice, close to the expected concentration of 6.8 mM.

CONCLUSION

Phase imaging seems to be an appropriate means to measure the AIF of mice at high field.

Salvaging brain ischemia by increasing neuroprotectant uptake via nanoagonist mediated blood brain barrier permeability enhancement

Ischemic stroke is a leading cause of adult disability and cognitive impairment worldwide. Neuroprotective therapy aims to save neurons by impeding the deleterious ischemic insults. However, the low efficiency of the neuroprotectants crossing blood brain barrier (BBB) prevents their clinical translation. In this work, a nanoagonist (NA) was developed to enhance neuroprotectant uptake by specifically increasing BBB permeability in brain ischemia. This NA first targeted ischemic brain vasculatures, temporarily opened local BBB by activating adenosine 2A receptors, and up-regulated the neuroprotectant uptake in brain ischemia. This NA significantly increased the delivery of superoxide dismutase (SOD), a free radical scavenger, into mouse brain ischemia. The combined treatment of NA/SOD achieved a five-fold ischemic volume reduction rate compared to the animal models treated with SOD alone. Non-invasive magnetic resonance imaging (MRI) confirmed the ischemia targeted BBB opening, increased brain drug delivery efficiency and up-regulated therapeutic response during the combined NA/SOD treatment. Since the inefficient brain drug delivery is a general problem for the treatment of central nervous system (CNS) diseases, this work provides a novel strategy to deliver therapeutics by crossing BBB with high efficiency and targeting specificity.

Assessment of early therapeutic response to sorafenib in renal cell carcinoma xenografts by dynamic contrast-enhanced and diffusion-weighted MR imaging

OBJECTIVE

To investigate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted MRI (DWI) in monitoring early therapeutic response to sorafenib in renal cell carcinoma (RCC) xenograft models.

METHODS

Sorafenib (40 mg kg(-1)) was administered orally to BALB/c nude mice (n = 9) bearing subcutaneous tumours of human RCC ACHN xenografts. DCE-MRI and DWI were obtained 0, 1, 3 and 7 days after therapy, and DCE-MRI parameters (K(trans) and ve) and apparent diffusion coefficient (ADC) values were calculated. Tumour size and volume changes were correlated with changes in DCE-MRI parameters or ADC values after therapy.

RESULTS

Following therapy, K(trans) showed a significant decrease over time (p = 0.005), whereas ve did not demonstrate significant changes between time points (p = 0.97). ADC values showed a progressive increase over time (p = 0.004). Compared with pre-therapy, K(trans) showed a significant decrease after 3 days of therapy (p = 0.039), and ADC values increased significantly after 7 days (p = 0.039). Tumour size and volume did not show significant changes during 7 days. Tumour size and volume changes were not associated with changes in DCE-MRI parameters or ADC values.

CONCLUSION

DCE-MRI and DWI may show early physiological changes within 1 week after initiating sorafenib treatment on human RCC xenografts.

ADVANCES IN KNOWLEDGE

The quantitative parameters of DCE-MRI and DWI may offer the potential for assessing early therapeutic response to sorafenib in clinical trials.

Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images

BACKGROUND

To introduce a segmentation method to calculate an automatic arterial input function (AIF) based on principal component analysis (PCA) of dynamic contrast enhanced MR (DCE-MR) imaging and compare it with individual manually selected and population-averaged AIFs using calculated pharmacokinetic parameters.

METHODS

The study included 65 individuals with prostate examinations (27 tumors and 38 controls). Manual AIFs were individually extracted and also averaged to obtain a population AIF. Automatic AIFs were individually obtained by applying PCA to volumetric DCE-MR imaging data and finding the highest correlation of the PCs with a reference AIF. Variability was assessed using coefficients of variation and repeated measures tests. The different AIFs were used as inputs to the pharmacokinetic model and correlation coefficients, Bland-Altman plots and analysis of variance tests were obtained to compare the results.

RESULTS

Automatic PCA-based AIFs were successfully extracted in all cases. The manual and PCA-based AIFs showed good correlation (r between pharmacokinetic parameters ranging from 0.74 to 0.95), with differences below the manual individual variability (RMSCV up to 27.3%). The population-averaged AIF showed larger differences (r from 0.30 to 0.61).

CONCLUSION

The automatic PCA-based approach minimizes the variability associated to obtaining individual volume-based AIFs in DCE-MR studies of the prostate.

Evaluation of tumor microvascular response to brivanib by dynamic contrast-enhanced 7-T MRI in an orthotopic xenograft model of hepatocellular carcinoma

OBJECTIVE

The purpose of this article is to evaluate the antiangiogenic effects of brivanib using dynamic contrast-enhanced MRI (DCE-MRI) in an orthotopic mouse model of human hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

With human HCC (HepG2 cell line) orthotopic nude mouse xenografts, brivanib was administered orally to the treatment group, and the vehicle was administered to the control group for 14 days. DCE-MRI was performed before the start of the therapy and 7 and 14 days after the start of therapy. Treatment-induced changes in tumor volume and microvessel density (MVD) assessed by CD31 immunohistochemistry were analyzed. Perfusion parameters, including volume transfer constant between blood plasma and extravascular extracellular space (K(trans)), fractional extravascular extracellular space per unit volume of tissue (ve), and rate constant between extravascular extracellular space and blood plasma (Kep), were calculated using the two-compartment model.

RESULTS

Brivanib shows potent antitumor activity in tumor volume. The mean (± SD) MVD of the tumors was statistically significantly lower in the brivanib-treated group (40.8 ± 17.3 vessels/field) than in the control group (55.2 ± 9.05 vessels/field) (p < 0.05). In the control group, the K(trans) value increased statistically significantly between the baseline and 14 days after treatment (p = 0.048). In the brivanib-treated group, the K(trans) and ve values decreased statistically significantly between baseline and 7 days after treatment (p = 0.024 and p = 0.031, respectively) and between baseline and 14 days after treatment (p = 0.043 and p = 0.018, respectively). The difference between the K(trans) and ve values between baseline and 14 days after treatment showed a statistically significant difference between the two groups (p = 0.004 and p = 0.034, respectively).

CONCLUSION

DCE-MRI is feasible in the orthotopic mouse model of human HCC, and it can noninvasively monitor brivanib-induced changes in tumor microvasculature.

Comparison of K-means and fuzzy c-means algorithm performance for automated determination of the arterial input function

The arterial input function (AIF) plays a crucial role in the quantification of cerebral perfusion parameters. The traditional method for AIF detection is based on manual operation, which is time-consuming and subjective. Two automatic methods have been reported that are based on two frequently used clustering algorithms: fuzzy c-means (FCM) and K-means. However, it is still not clear which is better for AIF detection. Hence, we compared the performance of these two clustering methods using both simulated and clinical data. The results demonstrate that K-means analysis can yield more accurate and robust AIF results, although it takes longer to execute than the FCM method. We consider that this longer execution time is trivial relative to the total time required for image manipulation in a PACS setting, and is acceptable if an ideal AIF is obtained. Therefore, the K-means method is preferable to FCM in AIF detection.

High-field small animal magnetic resonance oncology studies

This review focuses on the applications of high magnetic field magnetic resonance imaging (MRI) and spectroscopy (MRS) to cancer studies in small animals. High-field MRI can provide information about tumor physiology, the microenvironment, metabolism, vascularity and cellularity. Such studies are invaluable for understanding tumor growth and proliferation, response to treatment and drug development. The MR techniques reviewed here include (1)H, (31)P, chemical exchange saturation transfer imaging and hyperpolarized (13)C MRS as well as diffusion-weighted, blood oxygen level dependent contrast imaging and dynamic contrast-enhanced MRI. These methods have been proven effective in animal studies and are highly relevant to human clinical studies.

Practical dynamic contrast enhanced MRI in small animal models of cancer: data acquisition, data analysis, and interpretation

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) consists of the continuous acquisition of images before, during, and after the injection of a contrast agent. DCE-MRI allows for noninvasive evaluation of tumor parameters related to vascular perfusion and permeability and tissue volume fractions, and is frequently employed in both preclinical and clinical investigations. However, the experimental and analytical subtleties of the technique are not frequently discussed in the literature, nor are its relationships to other commonly used quantitative imaging techniques. This review aims to provide practical information on the development, implementation, and validation of a DCE-MRI study in the context of a preclinical study (though we do frequently refer to clinical studies that are related to these topics).

DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data

Background

DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity.

Results

Pixel-wise model-based quantitative parameters are estimated by fitting DCE-MRI data to several pharmacokinetic models using the Levenberg-Marquardt algorithm (LMA). DCE@urLAB also includes the semi-quantitative parametric and heuristic analysis approaches commonly used in practice. This software application has been programmed in the Interactive Data Language (IDL) and tested both with publicly available simulated data and preclinical studies from tumor-bearing mouse brains.

Conclusions

A user-friendly solution for applying pharmacokinetic and non-quantitative analysis DCE-MRI in preclinical studies has been implemented and tested. The proposed tool has been specially designed for easy selection of multi-pixel ROIs. A public release of DCE@urLAB, together with the open source code and sample datasets, is available at http://www.die.upm.es/im/archives/DCEurLAB/.

Tumor perfusion-related parameter of diffusion-weighted magnetic resonance imaging: correlation with histological microvessel density

PURPOSE

We obtained intravoxel incoherent motion (IVIM) parameters through biexponential analysis on diffusion-weighted MR imaging (DWI) using multiple b values. Correlation was evaluated between these parameters and histological microvessel density (MVD) for the possibility of noninvasive evaluation of MVD with DWI.

METHODS

Twenty-five nude mice with the HT29 colorectal cancer cells implanted were analyzed after undergoing DWI with multiple b values (0, 50, 100, 300, 500, 700, and 1000 s/mm(2)). Tissue diffusivity (D(t)), pseudo-diffusion coefficient (D(p)), and perfusion fraction (f(p)) were calculated using a biexponential analysis, and these parameters were correlated with MVD. The MVD was determined with the CD31 stain. For statistical analysis, Spearman's rank correlation was applied.

RESULTS

The mean value and correlation coefficient with MVD for each IVIM parameter were as follows: D(t)  = 0.98 ± 0.06 × 10(-3) mm(2)/s with r = 0.139 (P = 0.508); D(p) = 23.70 ± 7.94 × 10(-3) mm(2)/s with r = 0.782 (P < 0.001); and f(p) = 15.58 ± 5.7% with r = 0.749 (P < 0.001). D(p) and f(p) showed significant correlation with MVD, but D(t) did not.

CONCLUSION

The IVIM parameters, D(p) and f(p), on DWI might be used in the noninvasive evaluation of MVD.