Quantitative MR Estimation of Interstitial Fluid Pressure in a Pre-Clinical Rat Model of Glioblastoma Tumors Using an Adaptive Model and Principle Component Analysis

Purpose: In many solid tumors, an elevated Interstitial Fluid Pressure (IFP) results in inefficient uptake of therapeutic agents. This study investigates the feasibility of constructing an Artificial Neural Network (ANN) for prediction of IFP in a rat-based model of glioblastoma (U251n) tumors. Methods: Dynamic-Contrast-Enhanced (DCE)-MRI data was studied in 35 athymic rats with orthotopic-U251-glioma. Tumor IFP was measured by the Wick-in-needle technique. Using a Model-Selection (MS) technique applied on Toftsmodel, three physiologically-nested models with the following PK parameters were constructed for the tumors: Model-1 with one parameter (vp: plasma volume), Model-2 with two parameters (vp and Ktrans: forward transfer constant), and Model-3 with three parameters (vp and Ktrans and kep: reverse transfer constant). A principle component analysis (PCA) technique was recruited to identify and construct three major components with the most discriminative power from PK parameters. The PCA features were used to train an ANN. A K-fold-Cross-Validation technique and an Area-Under-Correct- Classification-Fraction (AUCCF) were employed for training, structure optimization, and evaluation of the ANN. Results: Three discriminant features were identified and constructed by the PCA as follows: X1 = 0.95 × vp (Model-1) + 0.869vp (Model-3) + 0.76 × Ktrans (Model-2) + 0.68×Ktrans (Model-3) + 0.94×ve (Model-3), X2 = 0.69×Ktrans (Model-2) + 0.99×kep (Model-3), and X3 = 0.98×vp (Model-1). The performance of the trained-ANN at the optimum epoch was 79%. The cumulative variance of the three PCA-components was 89%. The optimal architecture (3, 6 and 1 neuron in its input, hidden and output layers) of the ANN was found at the epoch number of 1200 with AUCCF of 0.79. The generalization error of the trained- ANN for estimating the IFP was 20%. Conclusion: This pilot study confirmed the feasibility of constructing an adaptive model (ANN-PCA) for prediction of IFP of U251n tumors using DCE-MRI and MS technique. The proposed methodology can be used for predicting the IFP of glioblastoma in human

Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24h in a rat 9L gliosarcoma model

PURPOSE: The objective was to study temporal changes in tumor vascular physiological indices in a period of 24h in a 9L gliosarcoma rat model. METHODS: Fischer-344 rats (N=14) were orthotopically implanted with 9L cells. At 2weeks post-implantation, they were imaged twice in a 24h interval using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Data-driven model-selection-based analysis was used to segment tumor regions with varying vascular permeability characteristics. The region with the maximum number of estimable parameters of vascular kinetics was chosen for comparison across the two time points. It provided estimates of three parameters for an MR contrast agent (MRCA): i) plasma volume (v RESULTS: Test-retest differences between population summaries for any parameter were not significant (paired t and Wilcoxon signed rank tests). Bland-Altman plots showed no apparent trends between the differences and averages of the test-retest measures for all indices. The intraclass correlation coefficients showed moderate to almost perfect reproducibility for all of the parameters, except v CONCLUSION: The data suggest the relative stability of these MR indices of tumor microenvironment over a 24h duration in this gliosarcoma model

Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24h in a rat 9L gliosarcoma model

PURPOSE: The objective was to study temporal changes in tumor vascular physiological indices in a period of 24h in a 9L gliosarcoma rat model. METHODS: Fischer-344 rats (N=14) were orthotopically implanted with 9L cells. At 2weeks post-implantation, they were imaged twice in a 24h interval using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Data-driven model-selection-based analysis was used to segment tumor regions with varying vascular permeability characteristics. The region with the maximum number of estimable parameters of vascular kinetics was chosen for comparison across the two time points. It provided estimates of three parameters for an MR contrast agent (MRCA): i) plasma volume (vp), ii) forward volumetric transfer constant (Ktrans) and interstitial volume fraction (ve, ratio of Ktrans to reverse transfer constant, kep). In addition, MRCA extracellular distribution volume (VD) was estimated in the tumor and its borders, along with tumor blood flow (TBF) and peritumoral MRCA flux. Descriptors of parametric distributions were compared between the two times. Tumor extent was examined by hematoxylin and eosin (H&E) staining. Picrosirus red staining of secreted collagen was performed as an additional index for 9L cells. RESULTS: Test-retest differences between population summaries for any parameter were not significant (paired t and Wilcoxon signed rank tests). Bland-Altman plots showed no apparent trends between the differences and averages of the test-retest measures for all indices. The intraclass correlation coefficients showed moderate to almost perfect reproducibility for all of the parameters, except vp. H&E staining showed tumor infiltration in parenchyma, perivascular space and white matter tracts. Collagen staining was observed along the outer edges of main tumor mass. CONCLUSION: The data suggest the relative stability of these MR indices of tumor microenvironment over a 24h duration in this gliosarcoma model

Stellaria media (L.) Vill. (BR0000010100714)

Belgium Herbarium image of Meise Botanic Garden

Reproducibility and relative stability in magnetic resonance imaging indices of tumor vascular physiology over a period of 24h in a rat 9L gliosarcoma model

PURPOSE: The objective was to study temporal changes in tumor vascular physiological indices in a period of 24h in a 9L gliosarcoma rat model. METHODS: Fischer-344 rats (N=14) were orthotopically implanted with 9L cells. At 2weeks post-implantation, they were imaged twice in a 24h interval using dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). Data-driven model-selection-based analysis was used to segment tumor regions with varying vascular permeability characteristics. The region with the maximum number of estimable parameters of vascular kinetics was chosen for comparison across the two time points. It provided estimates of three parameters for an MR contrast agent (MRCA): i) plasma volume (vp), ii) forward volumetric transfer constant (Ktrans) and interstitial volume fraction (ve, ratio of Ktrans to reverse transfer constant, kep). In addition, MRCA extracellular distribution volume (VD) was estimated in the tumor and its borders, along with tumor blood flow (TBF) and peritumoral MRCA flux. Descriptors of parametric distributions were compared between the two times. Tumor extent was examined by hematoxylin and eosin (H&E) staining. Picrosirus red staining of secreted collagen was performed as an additional index for 9L cells. RESULTS: Test-retest differences between population summaries for any parameter were not significant (paired t and Wilcoxon signed rank tests). Bland-Altman plots showed no apparent trends between the differences and averages of the test-retest measures for all indices. The intraclass correlation coefficients showed moderate to almost perfect reproducibility for all of the parameters, except vp. H&E staining showed tumor infiltration in parenchyma, perivascular space and white matter tracts. Collagen staining was observed along the outer edges of main tumor mass. CONCLUSION: The data suggest the relative stability of these MR indices of tumor microenvironment over a 24h duration in this gliosarcoma model

Toward a noninvasive estimate of interstitial fluid pressure by dynamic contrast-enhanced MRI in a rat model of cerebral tumor

PURPOSE: This study demonstrates a DCE-MRI estimate of tumor interstitial fluid pressure (TIFP) and hydraulic conductivity in a rat model of glioblastoma, with validation against an invasive wick-in-needle (WIN) technique. An elevated TIFP is considered a mark of aggressiveness, and a decreased TIFP a predictor of response to therapy. METHODS: The DCE-MRI studies were conducted in 36 athymic rats (controls and posttreatment animals) with implanted U251 cerebral tumors, and with TIFP measured using a WIN method. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the MRI parameters required for estimating TIFP noninvasively were estimated. Two models, a fluid-mechanical model and a multivariate empirical model, were used for estimating TIFP, as verified against WIN-TIFP. RESULTS: Using DCE-MRI, the mean estimated hydraulic conductivity (MRI-K) in U251 tumors was (2.3 ± 3.1) × 10 CONCLUSION: This research suggests that MRI dynamic studies contain enough information to noninvasively estimate TIFP in this, and possibly other, tumor models, and thus might be used to assess tumor aggressiveness and response to therapy

Thuja occidentalis L. (BR0000025055764)

Belgium Herbarium image of Meise Botanic Garden

Magnetization transfer and T2-weighted MRI studies are useful for visualizing phenotypic presentations of orthotopic, patientderived xenograft mouse models of glioblastoma

Introduction: Patient-derived xenograft (PDX) models for glioblastoma (GBM) from resected tumor tissues replicate several features of the original tumor. They are considered to be representative models to study tumor progression, and to test responses to putative therapies. Longitudinal noninvasive imaging can be useful in such investigations. To that end, we employed magnetic resonance imaging (MRI) to visualize and measure tumor burden in four different PDX models of GBM. Experimental procedures: Four orthotopic mouse PDX models, HF2587, HF2927, HF3077 and HF3253, developed from neurosphere cultures of four different human glioblastoma samples were used in the study. The neurosphere cells were implanted into the right striatum in immunocompromised nude mice (n=5-8 per model) and allowed to grow for 2-8 weeks, depending on their known growth rates from previous studies. They were imaged in a Varian 7T MRI system with the following weightings: T2 , T1 , magnetization transfer (MT), and contrast enhanced MRI (CE-MRI) with Magnevist as the contrast agent (CA). Following imaging, all the mice were sacrificed and their brains processed for hematoxylin and eosin (H&E) histology and human major histocompatibility complex (MHC) immunohistochemistry. Results: Tumor masses were visible as hyperintense regions on MT and T2-weighted images. The extent of such masses matched the H&E and MHC staining patterns. Ventricle enlargements seen on MRI in several mice were also confirmed by histology. Necrotic cores, when present, were observed on both imaging and on histopathology with good spatial correlations. Surprisingly, post-contrast T1 imaging did not enhance in the tumor mass or peritumorally, except in one mouse in which some intratumoral enhancement was observed. In all other instances from the four PDX models tested, enhancement was observed only when the tumor tissue or parts of it were contiguous with pial or dural vasculature. Conclusions: At 7 Tesla, MT-MRI and T2-weighted imaging, rather than CE-MRI, appear to be of better utility in visualizing these PDX models of GBM if MRI is chosen as the imaging modality. Since the parent tumors imaged at lower field strengths showed contrast enhancement, absence of a similar feature in these models needs additional studies to understand their vascular characteristics. Such properties may include low level of vascularization and/or relatively less leaky tumor vasculature. Another possible reason may be that the models tested represent the invasive features of GBM better than the vascular features, e.g. peritumoral ring enhancement, of larger clinical tumors with increased exposure to hypoxia

Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma

The effect of a human vascular endothelial growth factor antibody on the vasculature of human tumor grown in rat brain was studied. Using dynamic contrast-enhanced magnetic resonance imaging, the effects of intravenous bevacizumab (Avastin; 10 mg/kg) were examined before and at postadministration times of 1, 2, 4, 8, 12 and 24 h (N = 26; 4–5 per time point) in a rat model of orthotopic, U251 glioblastoma (GBM). The commonly estimated vascular parameters for an MR contrast agent were: (i) plasma distribution volume (v(p)), (ii) forward volumetric transfer constant (K(trans)) and (iii) reverse transfer constant (k(ep)). In addition, extracellular distribution volume (V(D)) was estimated in the tumor (V(D-tumor)), tumor edge (V(D-edge)) and the mostly normal tumor periphery (V(D-peri)), along with tumor blood flow (TBF), peri-tumoral hydraulic conductivity (K) and interstitial flow (Flux) and tumor interstitial fluid pressure (TIFP). Studied as % changes from baseline, the 2-h post-treatment time point began showing significant decreases in v(p), V(D-tumor,) V(D-edge) and V(D-peri), as well as K, with these changes persisting at 4 and 8 h in v(p), K, V(D-tumor, -edge) and (-peri) (t-tests; p < 0.05–0.01). Decreases in K(trans) were observed at the 2- and 4-h time points (p < 0.05), while interstitial volume fraction (v(e); = K(trans)/k(ep)) showed a significant decrease only at the 2-h time point (p < 0.05). Sustained decreases in Flux were observed from 2 to 24 h (p < 0.01) while TBF and TIFP showed delayed responses, increases in the former at 12 and 24 h and a decrease in the latter only at 12 h. These imaging biomarkers of tumor vascular kinetics describe the short-term temporal changes in physical spaces and fluid flows in a model of GBM after Avastin administration