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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., (Copyright © 2017 John Wiley & Sons, Ltd.)

Extravascular extracellular space (v e ) 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 v e from a time trace of the longitudinal relaxation rate, ΔR 1 (R 1  = 1/T 1 ), in DCE-MRI studies. Using the extended Tofts equation, a set of ΔR 1 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 ΔR 1 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 v e at a resolution of 10% (error of ±5%) was 82%. The ANN was applied on DCE-MRI data of 26 glioblastoma patients to estimate v e in tumor regions. Its results were compared with the maximum likelihood estimation (MLE) of v e . 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 v e ., (Copyright © 2017 John Wiley & Sons, Ltd.)

Glioblastoma (GBM) is a hypervascular primary brain tumor with poor prognosis. HET0016 is a selective CYP450 inhibitor, which has been shown to inhibit angiogenesis and tumor growth. Therefore, to explore novel treatments, we have generated an improved intravenous (IV) formulation of HET0016 with HPßCD and tested in animal models of human and syngeneic GBM. Administration of a single IV dose resulted in 7-fold higher levels of HET0016 in plasma and 3.6-fold higher levels in tumor at 60 min than that in IP route. IV treatment with HPßCD-HET0016 decreased tumor growth, and altered vascular kinetics in early and late treatment groups (p < 0.05). Similar growth inhibition was observed in syngeneic GL261 GBM (p < 0.05). Survival studies using patient derived xenografts of GBM811, showed prolonged survival to 26 weeks in animals treated with focal radiation, in combination with HET0016 and TMZ (p < 0.05). We observed reduced expression of markers of cell proliferation (Ki-67), decreased neovascularization (laminin and αSMA), in addition to inflammation and angiogenesis markers in the treatment group (p < 0.05). Our results indicate that HPßCD-HET0016 is effective in inhibiting tumor growth through decreasing proliferation, and neovascularization. Furthermore, HPßCD-HET0016 significantly prolonged survival in PDX GBM811 model., Competing Interests: The authors declare no competing financial interests.

In this study we used magnetic resonance imaging (MRI) biomarkers to monitor the acute temporal changes in tumor vascular physiology with the aim of identifying the vascular signatures that predict response to combined anti-angiogenic and radiation treatments. Forty-three athymic rats implanted with orthotopic U-251 glioma cells were studied for approximately 21 days after implantation. Two MRI studies were performed on each animal, pre- and post-treatment, to measure tumor vascular parameters. Two animal groups received treatment comprised of Cilengitide, an anti-angiogenic agent and radiation. The first group received a subcurative regimen of Cilengitide 1 h before irradiation, while the second group received a curative regimen of Cilengitide 8 h before irradiation. Cilengitide was given as a single dose (4 mg/kg; intraperitoneal) after the pretreatment MRI study and before receiving a 20 Gy radiation dose. After irradiation, the post-treatment MRI study was performed at selected time points: 2, 4, 8 and 12 h (n = ≥5 per time point). Significant changes in vascular parameters were observed at early time points after combined treatments in both treatment groups (1 and 8 h). The temporal changes in vascular parameters in the first group (treated 1 h before exposure) resembled a previously reported pattern associated with radiation exposure alone. Conversely, in the second group (treated 8 h before exposure), all vascular parameters showed an initial response at 2-4 h postirradiation, followed by an apparent lack of response at later time points. The signature time point to define the "synergy" of Cilengitide and radiation was 4 h postirradiation. For example, 4 h after combined treatments using a 1 h separation (which followed the subcurative regimen), tumor blood flow was significantly decreased, nearly 50% below baseline (P = 0.007), whereas 4 h after combined treatments using an 8 h separation (which followed the curative regimen), tumor blood flow was only 10% less than baseline. Comparison between the first and second groups further revealed that most other vascular parameters were maximally different 4 h after combined treatments. In conclusion, the data are consistent with the assertion that the delivery of radiation at the vascular normalization time window of Cilengitide improves radiation treatment outcome. The different vascular responses after the different delivery times of combined treatments in light of the known tumor responses under similar conditions would indicate that timing has a crucial influence on treatment outcome and long-term survival. Tracking acute changes in tumor physiology after monotherapy or combined treatments appears to aid in identifying the beneficial timing for administration, and perhaps has predictive value. Therefore, judicial timing of treatments may result in optimal treatment response.

The distribution of dynamic contrast-enhanced MRI (DCE-MRI) parametric estimates in a rat U251 glioma model was analyzed. Using Magnevist as contrast agent (CA), 17 nude rats implanted with U251 cerebral glioma were studied by DCE-MRI twice in a 24 h interval. A data-driven analysis selected one of three models to estimate either (1) plasma volume (vp), (2) vp and forward volume transfer constant (K(trans)) or (3) vp, K(trans) and interstitial volume fraction (ve), constituting Models 1, 2 and 3, respectively. CA distribution volume (VD) was estimated in Model 3 regions by Logan plots. Regions of interest (ROIs) were selected by model. In the Model 3 ROI, descriptors of parameter distributions--mean, median, variance and skewness--were calculated and compared between the two time points for repeatability. All distributions of parametric estimates in Model 3 ROIs were positively skewed. Test-retest differences between population summaries for any parameter were not significant (p ≥ 0.10; Wilcoxon signed-rank and paired t tests). These and similar measures of parametric distribution and test-retest variance from other tumor models can be used to inform the choice of biomarkers that best summarize tumor status and treatment effects., (Copyright © 2014 John Wiley & Sons, Ltd.)

Dynamic contrast enhanced T(1)-weighted MRI using the contrast agent gadopentetate dimeglumine (Gd-DTPA) was performed on 10 patients with glioblastoma. Nested models with as many as three parameters were used to estimate plasma volume or plasma volume and forward vascular transfer constant (K(trans)) and the reverse vascular transfer constant (k(ep)). These constituted models 1, 2, and 3, respectively. Model 1 predominated in normal nonleaky brain tissue, showing little or no leakage of contrast agent. Model 3 predominated in regions associated with aggressive portions of the tumor, and model 2 bordered model 3 regions, showing leakage at reduced rates. In the patient sample, v(p) was about four times that of white matter in the enhancing part of the tumor. K(trans) varied by a factor of 10 between the model 2 (1.9 ↔ 10(-3) min(-1)) and model 3 regions (1.9 ↔ 10(-2) min(-1)). The mean calculated interstitial space (model 3) was 5.5%. In model 3 regions, excellent curve fits were obtained to summarize concentration-time data (mean R(2) = 0.99). We conclude that the three parameters of the standard model are sufficient to fit dynamic contrast enhanced T(1) data in glioblastoma under the conditions of the experiment., (Copyright © 2011 Wiley Periodicals, Inc.)

The apparent forward transfer constant, K transa, for albumin was measured in 9L cerebral tumors in 15 rats. An MRI study using gadolinium-labeled bovine serum albumin was followed by terminal quantitative autoradiography (QAR) using radioiodinated serum albumin. Look-Locker MRI estimates of T(1) followed gadolinium-labeled bovine serum albumin blood and tissue concentration. QAR and MRI maps of K transa were coregistered, a region of interest (ROI) that included the tumor and its surround was selected, and the two estimates of K transa from the ROI on QAR and MRI maps were compared by either mean per animal ROI or on pixel-by-pixel data using a generalized estimating equation. An ROI analysis showed a moderate correlation between the two measures (r = 0.57, P = 0.026); pixel-by-pixel generalized estimating equation analysis concurred (r = 0.54, P < 0.0001). The estimates of QAR with MRI of last time points (e.g., 25 min) showed a moderate correlation (ROI r = 0.55, P < 0.035; generalized estimating equation r = 0.58, P < 0.0001). Differences between the QAR and MRI estimates of K transa did not differ from zero, but the MRI 25-min estimate was significantly lower than the QAR estimate. Thus, noninvasive MRI estimates of vascular permeability can serve as a surrogate for QAR measures., (Copyright © 2011 Wiley Periodicals, Inc.)

Background: Due to the hypervascular nature of glioblastoma (GBM), antiangiogenic treatments, such as vatalanib, have been added as an adjuvant to control angiogenesis and tumor growth. However, evidence of progressive tumor growth and resistance to antiangiogenic treatment has been observed. To counter the unwanted effect of vatalanib on GBM growth, we have added a new agent known as N-hydroxy-N'-(4-butyl-2 methylphenyl)formamidine (HET0016), which is a selective inhibitor of 20-hydroxyeicosatetraenoic acid (20-HETE) synthesis. The aims of the studies were to determine 1) whether the addition of HET0016 can attenuate the unwanted effect of vatalanib on tumor growth and 2) whether the treatment schedule would have a crucial impact on controlling GBM. Methods: U251 human glioma cells (4×105) were implanted orthotopically. Two different treatment schedules were investigated. Treatment starting on day 8 (8-21 days treatment) of the tumor implantation was to mimic treatment following detection of tumor, where tumor would have hypoxic microenvironment and well-developed neovascularization. Drug treatment starting on the same day of tumor implantation (0-21 days treatment) was to mimic cases following radiation therapy or surgery. There were four different treatment groups: vehicle, vatalanib (oral treatment 50 mg/kg/d), HET0016 (intraperitoneal treatment 10 mg/kg/d), and combined (vatalanib and HET0016). Following scheduled treatments, all animals underwent magnetic resonance imaging on day 22, followed by euthanasia. Brain specimens were equally divided for immunohistochemistry and protein array analysis. Results: Our results demonstrated a trend that HET0016, alone or in combination with vatalanib, is capable of controlling the tumor growth compared with that of vatalanib alone, indicating attenuation of the unwanted effect of vatalanib. When both vatalanib and HET0016 were administered together on the day of the tumor implantation (0-21 days treatment), tumor volume, tumor blood volume, permeability, extravascular and extracellular space volume, tumor cell proliferation, and cell migration were decreased compared with that of the vehicle-treated group. Conclusion: HET0016 is capable of controlling tumor growth and migration, but these effects are dependent on the timing of drug administration. The addition of HET0016 to vatalanib may attenuate the unwanted effect of vatalanib. [ABSTRACT FROM AUTHOR]