Probabilistic Nested Model Selection in Pharmacokinetic Analysis of DCE-MRI Data in Animal Model of Cerebral Tumor.

Purpose: Best current practice in the analysis of dynamic contrast enhanced (DCE)-MRI is to employ a voxel-by-voxel model selection from a hierarchy of nested models. This nested model selection (NMS) assumes that the observed time-trace of contrast-agent (CA) concentration within a voxel, corresponds to a singular physiologically nested model. However, admixtures of different models may exist within a voxel's CA time-trace. This study introduces an unsupervised feature engineering technique (Kohonen-Self-Organizing-Map (K-SOM)) to estimate the voxel-wise probability of each nested model. Methods: Sixty-six immune-compromised-RNU rats were implanted with human U-251N cancer cells, and DCE-MRI data were acquired from all the rat brains. The time-trace of change in the longitudinalrelaxivity Δ R 1 for all animals' brain voxels was calculated. DCE-MRI pharmacokinetic (PK) analysis was performed using NMS to estimate three model regions: Model-1: normal vasculature without leakage, Model-2: tumor tissues with leakage without back-flux to the vasculature, Model-3: tumor vessels with leakage and back-flux. Approximately two hundred thirty thousand (229,314) normalized Δ R 1 profiles of animals' brain voxels along with their NMS results were used to build a K-SOM (topology-size: 8×8, with competitive-learning algorithm) and probability map of each model. K-fold nested-cross-validation (NCV, k=10) was used to evaluate the performance of the K-SOM probabilistic-NMS (PNMS) technique against the NMS technique. Results: The K-SOM PNMS's estimation for the leaky tumor regions were strongly similar (Dice-Similarity-Coefficient, DSC=0.774 [CI: 0.731-0.823], and 0.866 [CI: 0.828-0.912] for Models 2 and 3, respectively) to their respective NMS regions. The mean-percent-differences (MPDs, NCV, k=10) for the estimated permeability parameters by the two techniques were: -28%, +18%, and +24%, for v p , K trans , and v e , respectively. The KSOM-PNMS technique produced microvasculature parameters and NMS regions less impacted by the arterial-input-function dispersion effect. Conclusion: This study introduces an unsupervised model-averaging technique (K-SOM) to estimate the contribution of different nested-models in PK analysis and provides a faster estimate of permeability parameters.

Heterogeneous Mechanical Stress and Interstitial Fluid Flow Predictions Derived from DCE-MRI for Rat U251N Orthotopic Gliomas.

Mechanical stress and fluid flow influence glioma cell phenotype in vitro, but measuring these quantities in vivo continues to be challenging. The purpose of this study was to predict these quantities in vivo, thus providing insight into glioma physiology and potential mechanical biomarkers that may improve glioma detection, diagnosis, and treatment. Image-based finite element models of human U251N orthotopic glioma in athymic rats were developed to predict structural stress and interstitial flow in and around each animal's tumor. In addition to accounting for structural stress caused by tumor growth, our approach has the advantage of capturing fluid pressure-induced structural stress, which was informed by in vivo interstitial fluid pressure (IFP) measurements. Because gliomas and the brain are soft, elevated IFP contributed substantially to tumor structural stress, even inverting this stress from compressive to tensile in the most compliant cases. The combination of tumor growth and elevated IFP resulted in a concentration of structural stress near the tumor boundary where it has the greatest potential to influence cell proliferation and invasion. MRI-derived anatomical geometries and tissue property distributions resulted in heterogeneous interstitial fluid flow with local maxima near cerebrospinal fluid spaces, which may promote tumor invasion and hinder drug delivery. In addition, predicted structural stress and interstitial flow varied markedly between irradiated and radiation-naïve animals. Our modeling suggests that relative to tumors in stiffer tissues, gliomas experience unusual mechanical conditions with potentially important biological (e.g., proliferation and invasion) and clinical consequences (e.g., drug delivery and treatment monitoring).

Evaluating Debio 1347 in Patients with FGFR Fusion-Positive Advanced Solid Tumors from the FUZE Multicenter, Open-Label, Phase II Basket Trial.

PURPOSE: This multicenter phase II basket trial investigated the efficacy, safety, and pharmacokinetics of Debio 1347, an investigational, oral, highly selective, ATP-competitive, small molecule inhibitor of FGFR1-3, in patients with solid tumors harboring a functional FGFR1-3 fusion. PATIENTS AND METHODS: Eligible adults had a previously treated locally advanced (unresectable) or metastatic biliary tract (cohort 1), urothelial (cohort 2), or another histologic cancer type (cohort 3). Debio 1347 was administered at 80 mg once daily, continuously, in 28-day cycles. The primary endpoint was the objective response rate. Secondary endpoints included duration of response, progression-free survival, overall survival, pharmacokinetics, and incidence of adverse events. RESULTS: Between March 22, 2019, and January 8, 2020, 63 patients were enrolled and treated, 30 in cohort 1, 4 in cohort 2, and 29 in cohort 3. An unplanned preliminary statistical review showed that the efficacy of Debio 1347 was lower than predicted, and the trial was terminated. In total, 3 of 58 evaluable patients had partial responses, representing an objective response rate of 5%, with a further 26 (45%) having stable disease (≥6 weeks duration). Grade ≥3 treatment-related adverse events occurred in 22 (35%) of 63 patients, with the most common being hyperphosphatemia (13%) and stomatitis (5%). Two patients (3%) discontinued treatment due to adverse events. CONCLUSIONS: Debio 1347 had manageable toxicity; however, the efficacy in patients with tumors harboring FGFR fusions did not support further clinical evaluation in this setting. Our transcriptomic-based analysis characterized in detail the incidence and nature of FGFR fusions across solid tumors. See related commentary by Hage Chehade et al., p. 4549.

Radiomics characterization of tissues in an animal brain tumor model imaged using dynamic contrast enhanced (DCE) MRI.

Here, we investigate radiomics-based characterization of tumor vascular and microenvironmental properties in an orthotopic rat brain tumor model measured using dynamic-contrast-enhanced (DCE) MRI. Thirty-two immune compromised-RNU rats implanted with human U-251N cancer cells were imaged using DCE-MRI (7Tesla, Dual-Gradient-Echo). The aim was to perform pharmacokinetic analysis using a nested model (NM) selection technique to classify brain regions according to vasculature properties considered as the source of truth. A two-dimensional convolutional-based radiomics analysis was performed on the raw-DCE-MRI of the rat brains to generate dynamic radiomics maps. The raw-DCE-MRI and respective radiomics maps were used to build 28 unsupervised Kohonen self-organizing-maps (K-SOMs). A Silhouette-Coefficient (SC), k-fold Nested-Cross-Validation (k-fold-NCV), and feature engineering analyses were performed on the K-SOMs' feature spaces to quantify the distinction power of radiomics features compared to raw-DCE-MRI for classification of different Nested Models. Results showed that eight radiomics features outperformed respective raw-DCE-MRI in prediction of the three nested models. The average percent difference in SCs between radiomics features and raw-DCE-MRI was: 29.875% ± 12.922%, p < 0.001. This work establishes an important first step toward spatiotemporal characterization of brain regions using radiomics signatures, which is fundamental toward staging of tumors and evaluation of tumor response to different treatments.

Dynamic contrast enhanced (DCE) MRI estimation of vascular parameters using knowledge-based adaptive models.

We introduce and validate four adaptive models (AMs) to perform a physiologically based Nested-Model-Selection (NMS) estimation of such microvascular parameters as forward volumetric transfer constant, Ktrans, plasma volume fraction, vp, and extravascular, extracellular space, ve, directly from Dynamic Contrast-Enhanced (DCE) MRI raw information without the need for an Arterial-Input Function (AIF). In sixty-six immune-compromised-RNU rats implanted with human U-251 cancer cells, DCE-MRI studies estimated pharmacokinetic (PK) parameters using a group-averaged radiological AIF and an extended Patlak-based NMS paradigm. One-hundred-ninety features extracted from raw DCE-MRI information were used to construct and validate (nested-cross-validation, NCV) four AMs for estimation of model-based regions and their three PK parameters. An NMS-based a priori knowledge was used to fine-tune the AMs to improve their performance. Compared to the conventional analysis, AMs produced stable maps of vascular parameters and nested-model regions less impacted by AIF-dispersion. The performance (Correlation coefficient and Adjusted R-squared for NCV test cohorts) of the AMs were: 0.914/0.834, 0.825/0.720, 0.938/0.880, and 0.890/0.792 for predictions of nested model regions, vp, Ktrans, and ve, respectively. This study demonstrates an application of AMs that quickens and improves DCE-MRI based quantification of microvasculature properties of tumors and normal tissues relative to conventional approaches.

Persistent Peri-Ablation Blood-Brain Barrier Opening After Laser Interstitial Thermal Therapy for Brain Tumors.

Purpose Laser interstitial thermal therapy (LITT) is a minimally invasive, image-guided, cytoreductive procedure to treat recurrent glioblastoma. This study implemented dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) methods and employed a model selection paradigm to localize and quantify post-LITT blood-brain barrier (BBB) permeability in the ablation vicinity. Serum levels of neuron-specific enolase (NSE), a peripheral marker of increased BBB permeability, were measured. Methods Seventeen patients were enrolled in the study. Using an enzyme-linked immunosorbent assay, serum NSE was measured preoperatively, 24 hours postoperatively, and at two, eight, 12, and 16 weeks postoperatively, depending on postoperative adjuvant treatment. Of the 17 patients, four had longitudinal DCE-MRI data available, from which blood-to-brain forward volumetric transfer constant (Ktrans) data were assessed. Imaging was performed preoperatively, 24 hours postoperatively, and between two and eight weeks postoperatively. Results Serum NSE increased at 24 hours following ablation (p=0.04), peaked at two weeks, and returned to baseline by eight weeks postoperatively. Ktrans was found to be elevated in the peri-ablation periphery 24 hours after the procedure. This increase persisted for two weeks. Conclusion Following the LITT procedure, serum NSE levels and peri-ablation Ktrans estimated from DCE-MRI demonstrated increases during the first two weeks after ablation, suggesting transiently increased BBB permeability.

Profiles of COVID-19 vaccine hesitancy by race and ethnicity in eastern Pennsylvania.

BACKGROUND: Throughout US history, chronic and infectious diseases have severely impacted minority communities due to a lack of accessibility to quality healthcare and accurate information, as well as underlying racism. These fault lines in the care of minority communities in the US have been further exacerbated by the rise of the COVID-19 pandemic. This study examined the factors associated with COVID-19 vaccine hesitancy by race and ethnicity, particularly among African American and Latinx communities in Eastern Pennsylvania (PA). METHODS: Survey data was collected in July 2021 in Philadelphia, Scranton, Wilkes-Barre, and Hazleton, PA. The 203 participants (38.7% Black, 27.5% Latinx) completed the 28-question survey of COVID-19 vaccination attitudes in either English or Spanish. RESULT: Out of the 203 participants, 181 participants met all the inclusion criteria, including completed surveys; of these participants, over three-fifths (63.5%) were acceptant of the COVID-19 vaccine whereas the remainder (36.5%) were hesitant. Binary logistic regression results showed that age, concern for vaccine efficacy, race, knowledge on the vaccine, and belief that the COVID-19 virus is serious significantly influenced COVID-19 vaccine hesitancy. Minorities were more likely to be hesitant toward vaccination (OR: 2.8, 95% CI: 1.1, 6.8) than non-Hispanic whites. Those who believed the COVID-19 vaccine was ineffective (OR: 8.3, 95% CI: 3.8, 18.2), and that the virus is not serious (OR: 8.3, 95% CI: 1.1, 61.8) showed the greatest odds of hesitancy. CONCLUSIONS: Minority status, age less than 45 years, misinformation about seriousness of COVID-19 illness, and concern about vaccine efficacy were contributing factors of COVID-19 vaccine hesitancy. Therefore, understanding and addressing the barriers to COVID-19 vaccination in minority groups is essential to decreasing transmission and controlling this pandemic, and will provide lessons on how to implement public health measures in future pandemics.

Characterization of the Response of 9L and U-251N Orthotopic Brain Tumors to 3D Conformal Radiation Therapy.

In a study employing MRI-guided stereotactic radiotherapy (SRS) in two orthotopic rodent brain tumor models, the radiation dose yielding 50% survival (the TCD50) was sought. Syngeneic 9L cells, or human U-251N cells, were implanted stereotactically in 136 Fischer 344 rats or 98 RNU athymic rats, respectively. At approximately 7 days after implantation for 9L, and 18 days for U-251N, rats were imaged with contrast-enhanced MRI (CE-MRI) and then irradiated using a Small Animal Radiation Research Platform (SARRP) operating at 220 kV and 13 mA with an effective energy of ∼70 keV and dose rate of ∼2.5 Gy per min. Radiation doses were delivered as single fractions. Cone-beam CT images were acquired before irradiation, and tumor volumes were defined using co-registered CE-MRI images. Treatment planning using MuriPlan software defined four non-coplanar arcs with an identical isocenter, subsequently accomplished by the SARRP. Thus, the treatment workflow emulated that of current clinical practice. The study endpoint was animal survival to 200 days. The TCD50 inferred from Kaplan-Meier survival estimation was approximately 25 Gy for 9L tumors and below 20 Gy, but within the 95% confidence interval in U-251N tumors. Cox proportional-hazards modeling did not suggest an effect of sex, with the caveat of wide confidence intervals. Having identified the radiation dose at which approximately half of a group of animals was cured, the biological parameters that accompany radiation response can be examined.

Adaptation of laser interstitial thermal therapy for tumor ablation under MRI monitoring in a rat orthotopic model of glioblastoma.

BACKGROUND: Laser interstitial thermal therapy (LITT) under magnetic resonance imaging (MRI) monitoring is being increasingly used in cytoreductive surgery of recurrent brain tumors and tumors located in eloquent brain areas. The objective of this study was to adapt this technique to an animal glioma model. METHODS: A rat model of U251 glioblastoma (GBM) was employed. Tumor location and extent were determined by MRI and dynamic contrast-enhanced (DCE) MRI. A day after assessing tumor appearance, tumors were ablated during diffusion-weighted imaging (DWI)-MRI using a Visualase LITT system (n = 5). Brain images were obtained immediately after ablation and again at 24 h post-ablation to confirm the efficacy of tumor cytoablation. Untreated tumors served as controls (n = 3). Rats were injected with fluorescent isothiocyanate (FITC) dextran and Evans blue that circulated for 10 min after post-LITT MRI. The brains were then removed for fluorescence microscopy and histopathology evaluations using hematoxylin and eosin (H&E) and major histocompatibility complex (MHC) staining. RESULTS: All rats showed a space-occupying tumor with T2 and T1 contrast-enhancement at pre-LITT imaging. The rats that underwent the LITT procedure showed a well-demarcated ablation zone with near-complete ablation of tumor tissue and with peri-ablation contrast enhancement at 24 h post-ablation. Tumor cytoreduction by ablation as seen on MRI was confirmed by H&E and MHC staining. CONCLUSIONS: Data showed that tumor cytoablation using MRI-monitored LITT was possible in preclinical glioma models. Real-time MRI monitoring facilitated visualizing and controlling the area of ablation as it is otherwise performed in clinical applications.

A computational model of glioma reveals opposing, stiffness-sensitive effects of leaky vasculature and tumor growth on tissue mechanical stress and porosity.

A biphasic computational model of a growing, vascularized glioma within brain tissue was developed to account for unique features of gliomas, including soft surrounding brain tissue, their low stiffness relative to brain tissue, and a lack of draining lymphatics. This model is the first to couple nonlinear tissue deformation with porosity and tissue hydraulic conductivity to study the mechanical interaction of leaky vasculature and solid growth in an embedded glioma. The present model showed that leaky vasculature and elevated interstitial fluid pressure produce tensile stress within the tumor in opposition to the compressive stress produced by tumor growth. This tensile effect was more pronounced in softer tissue and resulted in a compressive stress concentration at the tumor rim that increased when tumor was softer than host. Aside from generating solid stress, fluid pressure-driven tissue deformation decreased the effective stiffness of the tumor while growth increased it, potentially leading to elevated stiffness in the tumor rim. A novel prediction of reduced porosity at the tumor rim was corroborated by direct comparison with estimates from our in vivo imaging studies. Antiangiogenic and radiation therapy were simulated by varying vascular leakiness and tissue hydraulic conductivity. These led to greater solid compression and interstitial pressure in the tumor, respectively, the former of which may promote tumor infiltration of the host. Our findings suggest that vascular leakiness has an important influence on in vivo solid stress, stiffness, and porosity fields in gliomas given their unique mechanical microenvironment.

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 (vp ), (ii) forward volumetric transfer constant (Ktrans ) and (iii) reverse transfer constant (kep ). In addition, extracellular distribution volume (VD ) was estimated in the tumor (VD-tumor ), tumor edge (VD-edge ) and the mostly normal tumor periphery (VD-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 vp , VD-tumor, VD-edge and VD-peri , as well as K, with these changes persisting at 4 and 8 h in vp , K, VD-tumor, -edge and -peri (t-tests; p < 0.05-0.01). Decreases in Ktrans were observed at the 2- and 4-h time points (p < 0.05), while interstitial volume fraction (ve ; = Ktrans /kep ) 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.

The impact of initial tumor microenvironment on imaging phenotype.

Models of human cancer, to be useful, must replicate human disease with high fidelity. Our focus in this study is rat xenograft brain tumors as a model of human embedded cerebral tumors. A distinguishing signature of such tumors in humans, that of contrast-enhancement on imaging, is often not present when the human cells grow in rodents, despite the xenografts having nearly identical DNA signatures to the original tumor specimen. Although contrast enhancement was uniformly evident in all the human tumors from which the xenografts' cells were derived, we show that long-term contrast enhancement in the model tumors may be determined conditionally by the tumor microenvironment at the time of cell implantation. We demonstrate this phenomenon in one of two patient-derived orthotopic xenograft (PDOX) models using cancer stem-like cell (CSC)-enriched neurospheres from human tumor resection specimens, transplanted to groups of immune-compromised rats in the presence or absence of a collagen/fibrin scaffolding matrix, Matrigel. The rats were imaged by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and their brains were examined by histopathology. Targeted proteomics of the PDOX tumor specimens grown from CSC implanted with and without Matrigel showed that while the levels of the majority of proteins and post-translational modifications were comparable between contrast-enhancing and non-enhancing tumors, phosphorylation of Fox038 showed a differential expression. The results suggest key proteins determine contrast enhancement and suggest a path toward the development of better animal models of human glioma. Future work is needed to elucidate fully the molecular determinants of contrast-enhancement.

Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Feasibility Analysis.

We developed and tested the feasibility of computational fluid modeling (CFM) based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for quantitative estimation of interstitial fluid pressure (IFP) and velocity (IFV) in patients with head and neck (HN) cancer with locoregional lymph node metastases. Twenty-two patients with HN cancer, with 38 lymph nodes, underwent pretreatment standard MRI, including DCE-MRI, on a 3-Tesla scanner. CFM simulation was performed with the finite element method in COMSOL Multiphysics software. The model consisted of a partial differential equation (PDE) module to generate 3D parametric IFP and IFV maps, using the Darcy equation and Ktrans values (min-1, estimated from the extended Tofts model) to reflect fluid influx into tissue from the capillary microvasculature. The Spearman correlation (ρ) was calculated between total tumor volumes and CFM estimates of mean tumor IFP and IFV. CFM-estimated tumor IFP and IFV mean ± standard deviation for the neck nodal metastases were 1.73 ± 0.39 (kPa) and 1.82 ± 0.9 × (10-7 m/s), respectively. High IFP estimates corresponds to very low IFV throughout the tumor core, but IFV rises rapidly near the tumor boundary where the drop in IFP is precipitous. A significant correlation was found between pretreatment total tumor volume and CFM estimates of mean tumor IFP (ρ = 0.50, P = 0.004). Future studies can validate these initial findings in larger patients with HN cancer cohorts using CFM of the tumor in concert with DCE characterization, which holds promise in radiation oncology and drug-therapy clinical trials.

Longitudinal evaluation of tumor microenvironment in rat focal brainstem glioma using diffusion and perfusion MRI.

BACKGROUND: Brainstem gliomas are aggressive and difficult to treat. Growth of these tumors may be characterized with MRI methods. PURPOSE: To visualize longitudinal changes in tumor volume, vascular leakiness, and tissue microstructure in an animal model of brainstem glioma. STUDY TYPE: Prospective animal model. ANIMAL MODEL: Male Sprague-Dawley rats (n = 9) were imaged with 9L gliosarcoma cells infused into the pontine reticular formation of the brainstem. The MRI tumor microenvironment was studied at 3 and 10 days postimplantation of tumor cells. FIELD STRENGTH/SEQUENCE: Diffusion tensor imaging (DTI) and dynamic contrast-enhanced (DCE)-MRI were performed at 4.7T using spin-echo multislice echo planar imaging and gradient echo multislice imaging, respectively. ASSESSMENT: Tumor leakiness was assessed by the forward volumetric transfer constant, Ktrans , estimated from DCE-MRI data. Tumor structure was evaluated with fractional anisotropy (FA) obtained from DTI. Tumor volumes, delineated by a T1 map, T2 -weighted image, FA, and DCE signal enhancement were compared. STATISTICAL TESTS: Changes in the assessed parameters within and across the groups (ie, rats 3 and 10 days post tumor cell implantation) were evaluated with Wilcoxon rank-sum tests. RESULTS: Day 3 tumors were visible mainly on contrast-enhanced images, while day 10 tumors were visible in both contrast-enhanced and diffusion-weighted images. Mean Ktrans at day 10 was 41% lower than at day 3 (P = 0.23). In day 10 tumors, FA was regionally lower in the tumor compared to normal tissue (P = 0.0004), and tumor volume, segmented based on FA map, was significantly smaller (P ≤ 0.05) than that obtained from other contrasts. DATA CONCLUSION: Contrast-enhanced MRI was found to be more sensitive in detecting early-stage tumor boundaries than other contrasts. Areas of the tumor outlined by DCE-MRI and DTI were significantly different. Over the observed period of tumor growth, average vessel leakiness decreased with tumor progression. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:1322-1332.

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) × 10-5 (mm2 /mmHg-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 (R2 = 0.76, p < .0001). A similar result was found in the bevacizumab-treated group of the empirical model (R2 = 0.93, p = .014). 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.

MRI Monitoring of Cerebral Blood Flow after the Delivery of Nanocombretastatin across the Blood Brain Tumor Barrier.

Introduction of polymeric nanoparticles in cancer therapeutics is widely investigated since nanomedicine often enables the intratumoral delivery of drugs with increased efficacy with minimal side effects. In this study MRI monitoring was employed to study the therapeutic effect of nanocombretastatin (G3-CA4) in an orthotopic glioma model. Water insoluble combretastatin (CA4) was conjugated to a small-sized water soluble G3-succinamic acid PAMAM dendrimer. Nanoconstruct sizes were determined by TEM to be 3 to 5 nm. Intravenous (i.v.) delivery of G3-CA4 in an orthotopic glioma model produced a long-lived ischemia accompanied by necrosis at the core of the tumor but leaving a rim of viable tissue. In contrast, delivery of CA4 alone has no therapeutic effect in an experimental rat model of glioma.

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.

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

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

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 (Ktrans , vp and Kb ). 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.