Increased Glioma Collagen Is Associated with Greater Blood Flow and Peri-Tumoral Fluid Flux, but Less Infiltration

Introduction: Composition of the glioma microenvironment (TME) determines tumor growth rate, invasion, metastasis and resistance to treatment. Compared to normal brain, tumor extracellular matrix (ECM) has a higher concentration of structural proteins including collagen, laminin, tenascin, and vinculin. We compared collagen expression in two rat models of glioma, human U251 grown in immune-compromised rats and 9L in syngeneic Fischer-344 rats, representing primary and recurrent glioma features, respectively. Experimental procedures: The U251 and 9L cells were implanted in the right brain hemisphere of female RNU rats (n=10) and Fischer-344 rats (n=7), respectively. Rats were imaged 2 to 3 weeks after implantation by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Tumor size, blood flow, apparent diffusion coefficient (ADC), blood-to-tumor forward volumetric transfer constant (Ktrans) , peri-tumoral contrast flux (Flux), hydraulic conductivity (K), and extracellular volume fraction (VD ) in the tumor (VD-tumor), tumor rim (VD-rim) and its periphery (VD-peri) along with tumor interstitial fluid pressure (TIFP) were measured. Immediately after imaging, brains were processed for paraffin embedding and histopathology. Brain sections (6 |jm) containing the tumor were stained for collagen using Picrosirius red and adjacent brain sections with hematoxylin and eosin (H&E). MRI data were compared by t-tests and significance inferred at p≤0.05. Digital images of Picrosirius red staining were analyzed using ImageJ for collagen expression expressed as % fraction of total tumor area. It was compared to the MRI biomarkers, and to the patterns of tumor cell dispersion into normal brain observed on H&E stained images. Results: Tumor diameters averaged 4 mm for both models at the time of imaging. The U251 tumors showed greater Flux (p=0.03), higher blood flow (p=0.02), smaller VD-tumor (p=0.01) and VD r im (p=0.02) values than the 9L tumors. TIFP also tended to be higher in the U251 model (p=0.06). Collagen expression in U251 tumors was significantly higher than in 9L tumors (p=0.002). On H&E stained sections, the U251 tumors showed a well delineated tumor margin with very few cells invading the host tissue. In contrast, the 9L tumors showed cancer cells infiltrating singly and in clusters, along white matter tracts as well as in perivascular spaces. Conclusions: Increased collagen content was associated with elevated blood flow, Flux and TIFP, but less tumor cell infiltration in the U251 glioma. Observations of low collagen content in conjunction with increased tumor cell invasion in the 9L model suggest that treatment with collagenase, while increasing drug penetration may also make the tumors more infiltrative. A closer examination of TME to determine the composition of ECM proteins that regulate glioma aggressiveness and modulate its response to treatments is warranted

Noninvasive Estimation of Tumor Interstitial Fluid Pressure by DCE-MRI and Its Confirmation by Invasive Wick-In-Needle Technique in a Rat Glioblastoma Model

Objective: Dysfunctional blood-tumor barrier and elevated tumor interstitial fluid pressure (TIFP) limit perfusion and increase hypoxia. TIFP contributes to peri-tumoral exudate flow and edema. Peri-tumoral exudate flow and edema counter tumor penetration by chemotherapeutics. Increased TIFP is also a mark of tumor aggressiveness, and decreased TIFP, a predictor of response to therapy. However, non-invasive techniques are unavailable for measuring TIFP in cerebral tumors. This study employed dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to estimate TIFP and its confirmation by an invasive method using a rat glioblastoma model. Methods: Athymic rats (n = 22) were implanted intracerebrally with U251 glioblastoma. At 2 weeks post-implantation, DCE-MRI was conducted in control (n = 13) and bevacizumab-treated rats (n = 9), followed by invasive TIFP measurement in each animal using a \u27wick-in-needle\u27 (WIN) method. Applying model selection paradigm, Patlak- and Loganplots to DCE-MRI data, extracellular volume fraction (porosity) and velocity of exudate fluid flow at the tumor boundary were derived to estimate TIFP by Darcy\u27s law. Two models, a fluid-mechanical model and a multivariate empirical model, were used for TIFP estimations and verified against WIN-TIFP. WIN-TIFP and MRI-TIFP data were tested for correlation by linear regression and significance inferred at p \u3c 0.05. Results: Using DCE-MRI, the mean estimated hydraulic conductivity (MRI-K) was (2.3 ± 3.1) x 10-5 ( mm2/mm Hg-s) in control studies. Significant positive correlations were found between WIN-TIFP and MRI-TIFP in both mechanical and empirical models. For instance, in the control group of the fluid-mechanical model, MRI-TIFP was a strong predictor of WIN-TIFP (R = 0.76; p \u3c .01). Similar result was found in the bevacizumabtreated group in the empirical model (R = 0.87; p \u3c .01). In controls mean WIN-TIFP was 6.0 ± 3.7 and MRI-TIFP, 6.2 ± 3.7. Bevacizumab decreased the mean TIFP, albeit to slightly varying degrees by the two methods, 2.8 ± 1.6 (WIN) and 5.3 ± 3.3 (MRI). Both control and bevacizumab groups showed a high degree of inter-method correlation with R = 0.9 (p \u3c 0.01) between the WIN- and MRI-TIFP measurements. Conclusion: These data suggest that DCE-MRI studies contain enough information to noninvasively estimate TIFP in this, and possibly other, glioma models and, thus, might be useful to assess tumor aggressiveness and responses to therapies aiming to decrease TIFP and increase tumor drug delivery

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

Dynamic contrast enhanced MRI parameters and tumor cellularity in a rat model of cerebral glioma at 7 T

PURPOSE: To test the hypothesis that a noninvasive dynamic contrast enhanced MRI (DCE-MRI) derived interstitial volume fraction (ve ) and/or distribution volume (VD ) were correlated with tumor cellularity in cerebral tumor. METHODS: T1 -weighted DCE-MRI studies were performed in 18 athymic rats implanted with U251 xenografts. After DCE-MRI, sectioned brain tissues were stained with Hematoxylin and Eosin for cell counting. Using a Standard Model analysis and Logan graphical plot, DCE-MRI image sets during and after the injection of a gadolinium contrast agent were used to estimate the parameters plasma volume (vp ), forward transfer constant (K(trans) ), ve , and VD . RESULTS: Parameter values in regions where the standard model was selected as the best model were: (mean ± S.D.): vp = (0.81 ± 0.40)%, K(trans) = (2.09 ± 0.65) × 10(-2) min(-1) , ve = (6.65 ± 1.86)%, and VD = (7.21 ± 1.98)%. The Logan-estimated VD was strongly correlated with the standard model\u27s vp + ve (r = 0.91, P \u3c 0.001). The parameters, ve and/or VD , were significantly correlated with tumor cellularity (r ≥ -0.75, P \u3c 0.001 for both). CONCLUSION: These data suggest that tumor cellularity can be estimated noninvasively by DCE-MRI, thus supporting its utility in assessing tumor pathophysiology

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