Monitoring angiogenesis in soft‐tissue engineered constructs for calvarium bone regeneration: an in vivo longitudinal DCE‐MRI study

Tissue engineering is a promising technique for bone repair and can overcome the major drawbacks of conventional autogenous bone grafting. In this in vivo longitudinal study, we proposed a new tissue‐engineering paradigm: inserting a biological soft‐tissue construct within the bone defect to enhance angiogenesis for improved bone regeneration. The construct acts as a resorbable scaffold to support desired angiogenesis and cellular activity and as a vector of vascular endothelial growth factor, known to promote both vessel and bone growth. Dynamic contrast‐ enhanced magnetic resonance imaging was performed to investigate and characterize angiogenesis necessary for bone formation following the proposed paradigm of inserting a VEGF‐impregnated tissue‐engineered construct within the critical‐sized calvarial defect in the membranous parietal bone of the rabbit. Results show that a model‐free quantitative approach, the normalized initial area under the curve metric, provides sensitive and reproducible measures of vascularity that is consistent with known temporal evolution of angiogenesis during bone regeneration. Copyright © 2009 John Wiley & Sons, Ltd.     

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.     

An extended reference region model for DCE‐MRI that accounts for plasma volume

The reference region model (RRM) for dynamic contrast‐enhanced magnetic resonance imaging (DCE‐MRI) provides pharmacokinetic parameters without requiring the arterial input function. A limitation of the RRM is that it assumes that the blood plasma volume in the tissue of interest is zero, but this is often not true in highly vascularized tissues, such as some tumours. This study proposes an extended reference region model (ERRM) to account for tissue plasma volume. Furthermore, ERRM was combined with a two‐fit approach to reduce the number of fitting parameters, and this was named the constrained ERRM (CERRM). The accuracy and precision of RRM, ERRM and CERRM were evaluated in simulations covering a range of parameters, noise and temporal resolutions. These models were also compared with the extended Tofts model (ETM) on in vivo glioblastoma multiforme data. In simulations, RRM overestimated K^trans by over 10% at v_p = 0.01 under noiseless conditions. In comparison, ERRM and CERRM were both accurate, with CERRM showing better precision when noise was included. On in vivo data, CERRM provided maps that had the highest agreement with ETM, whilst also being robust at temporal resolutions as poor as 30 s. ERRM can provide pharmacokinetic parameters without an arterial input function in tissues with non‐negligible v_p where RRM provides inaccurate estimates. The two‐fit approach, named CERRM, further improves on the accuracy and precision of ERRM.     

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.     

Characterization and stratification of prostate lesions based on comprehensive multiparametric MRI using detailed whole‐mount histopathology as a reference standard

The purpose of this study was to characterize prostate cancer (PCa) based on multiparametric MR (mpMR) measures derived from MRI, diffusion, spectroscopy, and dynamic contrast‐enhanced (DCE) MRI, and to validate mpMRI in detecting PCa and predicting PCa aggressiveness by correlating mpMRI findings with whole‐mount histopathology. Seventy‐eight men with untreated PCa received 3 T mpMR scans prior to radical prostatectomy. Cancerous regions were outlined, graded, and cancer amount estimated on whole‐mount histology. Regions of interest were manually drawn on T₂‐weighted images based on histopathology. Logistic regression was used to identify optimal combinations of parameters for the peripheral zone and transition zone to separate: (i) benign from malignant tissues; (ii) Gleason score (GS) ≤3 + 3 disease from ≥GS3 + 4; and (iii) ≤ GS3 + 4 from ≥GS4 + 3 cancers. The performance of the models was assessed using repeated fourfold cross‐validation. Additionally, the performance of the logistic regression models created under the assumption that one or more modality has not been acquired was evaluated. Logistic regression models yielded areas under the curve (AUCs) of 1.0 and 0.99 when separating benign from malignant tissues in the peripheral zone and the transition zone, respectively. Within the peripheral zone, combining choline, maximal enhancement slope, apparent diffusion coefficient (ADC), and citrate measures for separating ≤GS3 + 3 from ≥GS3 + 4 PCa yielded AUC = 0.84. Combining creatine, choline, and washout slope yielded AUC = 0.81 for discriminating ≤GS3 + 4 from ≥GS4 + 3 disease. Within the transition zone, combining washout slope, ADC, and creatine yielded AUC = 0.93 for discriminating ≤GS3 + 3 and ≥GS3 + 4 cancers. When separating ≤GS3 + 4 from ≥GS4 + 3 PCa, combining choline and washout slope yielded AUC = 0.92. MpMRI provides excellent separation between benign tissues and PCa, and across PCa tissues of different aggressiveness. The final models prominently feature spectroscopy and DCE‐derived metrics, underlining their value within a comprehensive mpMRI examination.     

Three‐dimensional dynamic contrast‐enhanced MRI for the accurate,extensive quantification of microvascular permeability in atherosclerotic plaques

Atherosclerotic plaques that cause stroke and myocardial infarction are characterized by increased microvascular permeability and inflammation. Dynamic contrast‐enhanced MRI (DCE‐MRI) has been proposed as a method to quantify vessel wall microvascular permeability in vivo. Until now, most DCE‐MRI studies of atherosclerosis have been limited to two‐dimensional (2D) multi‐slice imaging. Although providing the high spatial resolution required to image the arterial vessel wall, these approaches do not allow the quantification of plaque permeability with extensive anatomical coverage, an essential feature when imaging heterogeneous diseases, such as atherosclerosis. To our knowledge, we present the first systematic evaluation of three‐dimensional (3D), high‐resolution, DCE‐MRI for the extensive quantification of plaque permeability along an entire vascular bed, with validation in atherosclerotic rabbits. We compare two acquisitions: 3D turbo field echo (TFE) with motion‐sensitized‐driven equilibrium (MSDE) preparation and 3D turbo spin echo (TSE). We find 3D TFE DCE‐MRI to be superior to 3D TSE DCE‐MRI in terms of temporal stability metrics. Both sequences show good intra‐ and inter‐observer reliability, and significant correlation with ex vivo permeability measurements by Evans Blue near‐infrared fluorescence (NIRF). In addition, we explore the feasibility of using compressed sensing to accelerate 3D DCE‐MRI of atherosclerosis, to improve its temporal resolution and therefore the accuracy of permeability quantification. Using retrospective under‐sampling and reconstructions, we show that compressed sensing alone may allow the acceleration of 3D DCE‐MRI by up to four‐fold. We anticipate that the development of high‐spatial‐resolution 3D DCE‐MRI with prospective compressed sensing acceleration may allow for the more accurate and extensive quantification of atherosclerotic plaque permeability along an entire vascular bed. We foresee that this approach may allow for the comprehensive and accurate evaluation of plaque permeability in patients, and may be a useful tool to assess the therapeutic response to approved and novel drugs for cardiovascular disease. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Comparing diagnostic accuracy of luminal water imaging with diffusion‐weighted and dynamic contrast‐enhanced MRI in prostate cancer: A quantitative MRI study

Luminal water imaging (LWI) is a new MRI T₂ mapping technique that has been developed with the aim of diagnosis of prostate carcinoma (PCa). This technique measures the fractional amount of luminal water in prostate tissue, and has shown promising preliminary results in detection of PCa. To include LWI in clinical settings, further investigation on the accuracy of this technique is required. In this study, we compare the diagnostic accuracy of LWI with those of diffusion‐weighted imaging (DWI) and dynamic contrast‐enhanced (DCE) MRI in detection and grading of PCa. Fifteen patients with biopsy‐proven PCa consented to participate in this ethics‐board‐approved prospective study. Patients were examined with LWI, DWI, and DCE sequences at 3 T prior to radical prostatectomy. Maps of MRI parameters were generated and registered to whole‐mount histology. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic accuracy of individual and combined MR parameters. Correlation with Gleason score (GS) was evaluated using Spearman's rank correlation test. The results show that area under the ROC curve (AUC) obtained from LWI was equal to or higher than the AUC obtained from DWI, DCE, or their combination, in peripheral zone (0.98 versus 0.90, 0.89, and 0.91 respectively), transition zone (0.99 versus 0.98, n/a, and 0.98), and the entire prostate (0.85 versus 0.81, 0.75, and 0.84). The strongest correlation with GS was achieved from LWI (ρ = ?0.81 ± 0.09, P < 0.001). Results of this pilot study show that LWI performs equally well as, or better than, DWI and DCE in detection of PCa. LWI provides significantly higher correlation with GS than DWI and DCE. This technique can potentially be included in clinical MRI protocols to improve characterization of tumors. However, considering the small size of the patient population in this study, a further study with a larger cohort of patients and broader range of GS is required to confirm the findings and draw a firm conclusion on the applicability of LWI in clinical settings.     

An extended vascular model for less biased estimation of permeability parameters in DCE‐T1 images

One of the key elements in dynamic contrast enhanced (DCE) image analysis is the arterial input function (AIF). Traditionally, in DCE studies a global AIF sampled from a major artery or vein is used to estimate the vascular permeability parameters; however, not addressing dispersion and delay of the AIF at the tissue level can lead to biased estimates of these parameters. To find less biased estimates of vascular permeability parameters, a vascular model of the cerebral vascular system is proposed that considers effects of dispersion of the AIF in the vessel branches, as well as extravasation of the contrast agent (CA) to the extravascular‐extracellular space. Profiles of the CA concentration were simulated for different branching levels of the vascular structure, combined with the effects of vascular leakage. To estimate the permeability parameters, the extended model was applied to these simulated signals and also to DCE‐T1 (dynamic contrast enhanced T₁) images of patients with glioblastoma multiforme tumors. The simulation study showed that, compared with the case of solving the pharmacokinetic equation with a global AIF, using the local AIF that is corrected by the vascular model can give less biased estimates of the permeability parameters (K^trans, v_p and K_b). Applying the extended model to signals sampled from different areas of the DCE‐T1 image showed that it is able to explain the CA concentration profile in both the normal areas and the tumor area, where effects of vascular leakage exist. Differences in the values of the permeability parameters estimated in these images using the local and global AIFs followed the same trend as the simulation study. These results demonstrate that the vascular model can be a useful tool for obtaining more accurate estimation of parameters in DCE studies.     

Relationship between diffusion parameters derived from intravoxel incoherent motion MRI and perfusion measured by dynamic contrast‐enhanced MRI of soft tissue tumors

Our aim was to evaluate the link between diffusion parameters measured by intravoxel incoherent motion (IVIM) diffusion‐weighted imaging (DWI) and the perfusion metrics obtained with dynamic contrast‐enhanced (DCE) MRI in soft tissue tumors (STTs). Twenty‐eight patients affected by histopathologically confirmed STT were included in a prospective study. All patients underwent both DCE MRI and IVIM DWI. The perfusion fraction f, diffusion coefficient D and perfusion‐related diffusion coefficient D* were estimated using a bi‐exponential function to fit the DWI data. DCE MRI was acquired with a temporal resolution of 3–5 s. Maps of the initial area under the gadolinium concentration curve (IAUGC), time to peak (TTP) and maximum slope of increase (MSI) were derived using commercial software. The relationships between the DCE MRI and IVIM DWI measurements were assessed by Spearman's test. To exclude false positive results under multiple testing, the false discovery rate (FDR) procedure was applied. The Mann–Whitney test was used to evaluate the differences between all variables in patients with non‐myxoid and myxoid STT. No significant relationship was found between IVIM parameters and any DCE MRI parameters. Higher f and D*f values were found in non‐myxoid tumors compared with myxoid tumors (p = 0.004 and p = 0.003, respectively). MSI was significantly higher in non‐myxoid tumors than in myxoid tumors (p = 0.029). From the visual assessments of single clinical cases, both f and D*f maps were in satisfactory agreement with DCE maps in the extreme cases of an avascular mass and a highly vascularized mass, whereas, for tumors with slight vascularity or with a highly heterogeneous perfusion pattern, this association was not straightforward. Although IVIM DWI was demonstrated to be feasible in STT, our data did not support evident relationships between perfusion‐related IVIM parameters and perfusion measured by DCE MRI. 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.     

A comparison of arterial spin labeling perfusion MRI and DCE‐MRI in human prostate cancer

Perfusion MRI has the potential to provide pathophysiological biomarkers for the evaluating, staging and therapy monitoring of prostate cancer. The objective of this study was to explore the feasibility of noninvasive arterial spin labeling (ASL) to detect prostate cancer in the peripheral zone and to investigate the correlation between the blood flow (BF) measured by ASL and the pharmacokinetic parameters K^trans (forward volume transfer constant), k_ep (reverse reflux rate constant between extracellular space and plasma) and v_e (the fractional volume of extracellular space per unit volume of tissue) measured by dynamic contrast‐enhanced (DCE) MRI in patients with prostate cancer. Forty‐three consecutive patients (ages ranging from 49 to 86 years, with a median age of 74 years) with pathologically confirmed prostate cancer were recruited. An ASL scan with four different inversion times (TI = 1000, 1200, 1400 and 1600 ms) and a DCE‐MRI scan were performed on a clinical 3.0 T GE scanner. BF, K^trans, k_ep and v_e maps were calculated. In order to determine whether the BF values in the cancerous area were statistically different from those in the noncancerous area, an independent t‐test was performed. Spearman's bivariate correlation was used to assess the relationship between BF and the pharmacokinetic parameters K^trans, k_ep and v_e. The mean BF values in the cancerous areas (97.1 ± 30.7, 114.7 ± 28.7, 102.3 ± 22.5, 91.2 ± 24.2 ml/100 g/min, respectively, for TI = 1000, 1200, 1400, 1600 ms) were significantly higher (p < 0.01 for all cases) than those in the noncancerous regions (35.8 ± 12.5, 42.2 ± 13.7, 53.5 ± 19.1, 48.5 ± 13.5 ml/100 g/min, respectively). Significant positive correlations (p < 0.01 for all cases) between BF and the pharmacokinetic parameters K^trans, k_ep and v_e were also observed for all four TI values (r = 0.671, 0.407, 0.666 for TI = 1000 ms; 0.713, 0.424, 0.698 for TI = 1200 ms; 0.604, 0.402, 0.595 for TI = 1400 ms; 0.605, 0.422, 0.548 for TI = 1600 ms). It can be seen that the quantitative ASL measurements show significant differences between cancerous and benign tissues, and exhibit strong to moderate correlations with the parameters obtained using DCE‐MRI. These results show the promise of ASL as a noninvasive alternative to DCE‐MRI. Copyright © 2014 John Wiley & Sons, Ltd.     

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.     

Response of HT29 colorectal xenograft model to cediranib assessed with 18F‐fluoromisonidazole positron emission tomography,dynamic contrast‐enhanced and diffusion‐weighted MRI

Cediranib is a small‐molecule pan‐vascular endothelial growth factor receptor inhibitor. The tumor response to short‐term cediranib treatment was studied using dynamic contrast‐enhanced and diffusion‐weighted MRI at 7 T, as well as ¹⁸F‐fluoromisonidazole positron emission tomography and histological markers. Rats bearing subcutaneous HT29 human colorectal tumors were imaged at baseline; they then received three doses of cediranib (3 mg/kg per dose daily) or vehicle (dosed daily), with follow‐up imaging performed 2 h after the final cediranib or vehicle dose. Tumors were excised and evaluated for the perfusion marker Hoechst 33342, the endothelial cell marker CD31, smooth muscle actin, intercapillary distance and tumor necrosis. Dynamic contrast‐enhanced MRI‐derived parameters decreased significantly in cediranib‐treated tumors relative to pretreatment values [the muscle‐normalized initial area under the gadolinium concentration curve decreased by 48% (p = 0.002), the enhancing fraction by 43% (p = 0.003) and K^trans by 57% (p = 0.003)], but remained unchanged in controls. No change between the pre‐ and post‐treatment tumor apparent diffusion coefficients in either the cediranib‐ or vehicle‐treated group was observed over the course of this study. The ¹⁸F‐fluoromisonidazole mean standardized uptake value decreased by 33% (p = 0.008) in the cediranib group, but showed no significant change in the control group. Histological analysis showed that the number of CD31‐positive vessels (59 per mm²), the fraction of smooth muscle actin‐positive vessels (80–87%) and the intercapillary distance (0.17 mm) were similar in cediranib‐ and vehicle‐treated groups. The fraction of perfused blood vessels in cediranib‐treated tumors (81 ± 7%) was lower than that in vehicle controls (91 ± 3%, p = 0.02). The necrotic fraction was slightly higher in cediranib‐treated rats (34 ± 12%) than in controls (26 ± 10%, p = 0.23). These findings suggest that short‐term treatment with cediranib causes a decrease in tumor perfusion/permeability across the tumor cross‐section, but changes in vascular morphology, vessel density or tumor cellularity are not manifested at this early time point. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of the need for DCE MRI in the detection of dominant lesions in the whole gland: Correlation between histology and MRI of prostate cancer

The purpose of this study was to evaluate the utility of dynamic contrast‐enhanced magnetic resonance imaging (DCE MRI) in the detection of dominant prostate tumors with multi‐parametric MRI of the whole gland. Combined diffusion tensor imaging (DTI) and DCE MRI from 16 patients with biopsy‐proven prostate cancer and no previous treatment were acquired with a 3.0‐T MRI scanner prior to radical prostatectomy, and used to identify dominant tumors. MRI results were validated by whole‐mount histology. Paired t‐test and Wilcoxon test, logistic generalized linear mixed effect models and receiver operating characteristic (ROC) analyses were used for the estimation of the statistical significance of the results. In the peripheral zone (PZ), the areas under the ROC curve (ROC‐AUC) were 0.98 (sensitivity, 96%; specificity, 98%) for DTI, 0.96 (sensitivity, 92%; specificity, 97%) for DCE and 0.99 (sensitivity, 98%; specificity, 98%) for DTI + DCE. In the entire prostate, the ROC‐AUC values were 0.96 (sensitivity, 84%; specificity, 95%) for DTI, 0.87 (sensitivity, 45%; specificity, 94%) for DCE and 0.96 (sensitivity, 88%; specificity, 98%) for DTI + DCE. The increase in ROC‐AUC by the addition of DCE was not statistically significant in either PZ or the entire prostate. The results of this study have shown that DTI identified dominant tumors with high accuracy in both PZ and the entire prostate, whereas the inclusion of DCE MRI had no significant impact on the identification of either PZ or entire prostate dominant lesions. Our results suggest that the inclusion of DCE MRI may not increase the accuracy of dominant lesion detection, allowing for faster, better tolerated imaging studies.     

Prediction of chemotherapeutic response of colorectal liver metastases with dynamic gadolinium-DTPA-enhanced MRI and localized 19F MRS pharmacokinetic studies of 5-fluorouracil

Systemic chemotherapy is effective in only a subset of patients with metastasized colorectal cancer. Therefore, early selection of patients who are most likely to benefit from chemotherapy is desirable. Response to treatment may be determined by the delivery of the drug to the tumor, retention of the drug in the tumor and by the amount of intracellular uptake, metabolic activation and catabolism, as well as other factors. The first aim of this study was to investigate the predictive value of DCE-MRI with the contrast agent Gd-DTPA for tumor response to first-line chemotherapy in patients with liver metastases of colorectal cancer. The second aim was to investigate the predictive value of 5-fluorouracil (FU) uptake, retention and catabolism as measured by localized (19)F MRS for tumor response to FU therapy. Since FU uptake, retention and metabolism may depend on tumor vascularization, the relationship between (19)F MRS and the DCE-MRI parameters k(ep), K(trans) and v(e) was also examined (1). In this study, 37 patients were included. The kinetic parameters of DCE-MRI, k(ep), K(trans) and v(e), before start of treatment did not predict tumor response after 2 months, suggesting that the delivery of chemotherapy by tumor vasculature is not a major factor determining response in first-line treatment. No evident correlations between (19)F MRS parameters and tumor response were found. This suggests that in liver metastases that are not selected on the basis of their tumor diameter, FU uptake and catabolism are not limiting factors for response. The transfer constant K(trans), as measured by DCE-MRI before start of treatment, was negatively correlated with FU half-life in the liver metastases, which suggests that, in metastases with a larger tumor blood flow or permeability surface area product, FU is rapidly washed out from the tumor.     

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.     

High‐resolution MRI analysis of breast cancer xenograft on the chick chorioallantoic membrane

The chick chorioallantoic membrane (CAM) model has been successfully used to study angiogenesis, cancer progression and its pharmacological treatment, tumor pharmacokinetics, and properties of novel nanomaterials. MRI is an attractive technique for non‐invasive and longitudinal monitoring of physiological processes and tumor growth. This study proposes an age‐adapted cooling regime for immobilization of the chick embryo, enabling high‐resolution MRI of the embryo and the CAM tumor xenograft. 64 chick embryos were enrolled in this study. The novel immobilization and imaging protocol was optimized in 29 embryos. From d7 to d18 immobilization of the embryo up to 90 min was achieved by cooling at 4 °C pre‐imaging, with cooling times adapted to age. Its application to tumor growth monitoring was evaluated in 15 embryos after xenotransplantation of human MDA‐MB‐231 breast cancer cells on CAM. Tumor volumes were monitored from d4 to d9 after grafting (d11 to d16 after incubation) applying a T₂‐weighted multislice RARE sequence. At d9 after grafting, the tumors were collected and compared with the MRI‐derived data by histology and weight measurements. Additional imaging methods comprising DWI, T₂ mapping, and the bio‐distribution of contrast agents were tested at d9 after grafting in 20 further embryos. With the adaptive cooling regime, motion artifacts could be completely avoided for up to 90 min scan time, enabling high‐resolution in ovo imaging. Excellent anatomical details could be obtained in the embryo and tumors. Tumor volumes could be quantified over time. The results prove the feasibility of high‐resolution MRI for longitudinal tumor and organ growth monitoring. The suggested method is promising for future applications such as testing tailored and/or targeted treatment strategies, longitudinal monitoring of tumor development, analysis of therapeutic efficacies of drugs, or assessment of tumor pharmacokinetics. The method provides an alternative to animal experimentation. Copyright © 2015 John Wiley & Sons, Ltd.