Three-dimensional susceptibility-weighted imaging at 3 T using various image analysis methods in the estimation of grading intracranial gliomas

Object

Although three-dimensional (3D), high-spatial resolution susceptibility-weighted imaging (SWI) appears to be valuable in the evaluation of central nervous system gliomas, several evaluation methods are proposed in the literature. The purpose of this study was to evaluate the use of 3D SWI for grading intracranial gliomas with various analysis methods.

Materials and Methods

Twenty-three patients suspected of having gliomas participated in this study. SWI was performed in addition to conventional MR sequences. In 15 cases, post-gadolinium enhanced SWI was also obtained. Imaging evaluation criteria were conventional grade, hypointensity ratio in the tumor-dominant structure of hypointensity on SWI (hemorrhage or vascular structure) and presence of abnormal enhancement surrounding the tumor.

Results

Mean grading scores of conventional grade showed no statistically significant difference among WHO grades. Mean grading scores of hypointensity ratios in the tumor were higher for WHO Grades 3 and 4 than for lower grade tumors (P=.05, Mann–Whitney U test). Hemorrhagic foci were more frequently seen in the higher grade tumor. Post-contrast susceptibility-weighted images of five of 11 WHO Grade 3 and 4 cases showed bright enhancement surrounding the tumor, suggesting a breakdown of the blood–brain barrier.

Conclusions

SWI at 3 T may be a useful method to analyze the structural characteristics of gliomas and to evaluate pathology in vivo. Assessment of hypointensity ratios in the glioma was the most preferable method in grading glioma. However, more studies, specifically concerning a suitable method for image analysis, are needed to establish SWI at 3 T as a useful tool in clinical routine.     

Characterize the interaction between naringenin and bovine serum albumin using spectroscopic approach

Naringenin, a flavanone compound highly enriched in grapefruits, has been identified as a possible inhibitor of cell proliferation; and thus has the potential to act as an antitumorigenic agent. In this study, the binding of naringenin to bovine serum albumin (BSA) was studied at the physiological conditions (pH=7.40) by fluorescence and UV-vis spectroscopy. Naringenin strongly quenches the intrinsic fluorescence of BSA, and a decrease in the fluorescence quenching constant was observed together with an increase in temperature, which indicates that the fluorescence quenching of BSA by naringenin is a result of the formation of naringenin-BSA complex. Binding parameters calculating from Stern-Volmer method and Scatchard method showed that naringenin bind to BSA with the binding affinities of the order 10⁴ L mol⁻¹. Thermodynamic parameters such as ΔG, ΔH and ΔS, were calculated at different temperatures, showing that electrostatic interactions were mostly responsible for the binding of naringenin to BSA. Site marker competitive displacement experiments demonstrating that naringenin bind with high affinity to site I (subdomain IIA) of BSA. Furthermore, the effect of metal ions to naringenin-BSA system was studied, and the specific binding distance r (3.30 nm) between donor (Trp-212) and acceptor (naringenin) was obtained according to fluorescence resonance energy transfer (FRET).     

Unsupervised Learning With Random Forest Predictors

A random forest (RF) predictor is an ensemble of individual tree predictors. As part of their construction, RF predictors naturally lead to a dissimilarity measure between the observations. One can also define an RF dissimilarity measure between unlabeled data: the idea is to construct an RF predictor that distinguishes the “observed” data from suitably generated synthetic data. The observed data are the original unlabeled data and the synthetic data are drawn from a reference distribution. Here we describe the properties of the RF dissimilarity and make recommendations on how to use it in practice.

An RF dissimilarity can be attractive because it handles mixed variable types well, is invariant to monotonic transformations of the input variables, and is robust to outlying observations. The RF dissimilarity easily deals with a large number of variables due to its intrinsic variable selection; for example, the Addcl 1 RF dissimilarity weighs the contribution of each variable according to how dependent it is on other variables.

We find that the RF dissimilarity is useful for detecting tumor sample clusters on the basis of tumor marker expressions. In this application, biologically meaningful clusters can often be described with simple thresholding rules.     

Asymptotic Behaviour of Solutions of a Multidimensional Moving Boundary Problem Modeling Tumor Growth

We study a moving boundary problem modeling the growth of multicellular spheroids or in vitro tumors. This model consists of two elliptic equations describing the concentration of a nutrient and the distribution of the internal pressure in the tumor's body, respectively. The driving mechanism of the evolution of the tumor surface is governed by Darcy's law. Finally surface tension effects on the moving boundary are taken into account which are considered to counterbalance the internal pressure. To put our analysis on a solid basis, we first state a local well-posedness result for general initial data. However, the main purpose of our study is the investigation of the asymptotic behaviour of solutions as time goes to infinity. As a result of a centre manifold analysis, we prove that if the initial domain is sufficiently close to a Euclidean ball in the C ^m+μ-norm with m ≥ 3 and μ ∈ (0,1), then the solution exists globally and the corresponding domains converge exponentially fast to some (possibly shifted) ball, provided the surface tension coefficient γ is larger than a positive threshold value γ_*. In the case 0 < γ < γ_* the radially symmetric equilibrium is unstable.     

Computing steady-state solutions for a free boundary problem modeling tumor growth by Stokes equation

We consider a free boundary problem modeling tumor growth where the model equations include a diffusion equation for the nutrient concentration and the Stokes equation for the proliferation of tumor cells. For any positive radius R$R$, it is known that there exists a unique radially symmetric stationary solution. The proliferation rate μ$\mu$ and the cell-to-cell adhesiveness γ$\gamma$ are two parameters for characterizing “aggressiveness” of the tumor. We compute symmetry-breaking bifurcation branches of solutions by studying a polynomial discretization of the system. By tracking the discretized system, we numerically verified a sequence of μ/γ$\mu /\gamma$ symmetry breaking bifurcation branches. Furthermore, we study the stability of both radially symmetric and radially asymmetric stationary solutions.     

Ultrasound exposure in the presence of hematoporphyrin induced loss of membrane integral proteins and inactivity of cell proliferation associated enzymes in sarcoma 180 cells in vitro

Ultrasonically induced effects of hematoporphyrin (HPD) on cell damage and membrane protein alteration of S180 isolated tumor cells in vitro were investigated, and the potential mechanisms of sonodynamic therapy (SDT) inhibiting tumor growth were discussed. Tumor cells suspended in air-saturated PBS (pH 7.2) were exposed to ultrasound at 1.8 MHz for up to 180 s in the presence and absence of HPD. The viability of cells was determined by a trypan blue exclusion test. To estimate the damage effects of SDT on plasma membrane of tumor cells primarily, membrane integral proteins (EGFR, Ras, Fas, FasL) and cell proliferation associated enzymes (adenylate cyclase and guanylate cyclase) were checked with immunochemical methods. The results indicated that the intensity threshold for ultrasonically induced cell damage at 1.8 MHz was 3 W/cm². At this condition, the expression of the integral proteins was obviously inhibited and the activity of the enzymes was decreased post ultrasound treatment in the presence of 20 μg/ml HPD. Loss of the membrane proteins and inactivity of AC and GC post SDT was time-dependent. This paper reveals SDT can cause the loss of tumor cell membrane integral proteins and inactivity of the enzymes associated with cell proliferation which might be attributed to a sonochemical activation mechanism. The mechanisms by that tumor growth is inhibited by SDT can be understood as that the growth signaling pathway is partially interdicted and the resistance of tumor cells to the specifically activated immune cells is weakened.     

Versatile Nitro-Fluorophore as Highly Effective Sensor for Hypoxic Tumor Cells: Design, Imaging and Evaluation

Based on the characteristics of a nitro-group, which can be partially or totally reduced to an amino-group in hypoxic cells, two series of hypoxic sensors containing 7H-Benzimidazole [2,1-a]benz[de]isoquinolin-7-one cores with nitro groups in different positions were designed, synthesized and evaluated. The target compounds exhibited significantly different fluorescence characteristics (fluorescence enhancement or quenching). The strong fluorescences of some partially reduced compounds could be explained through the examination of their infrared spectra, which showed a restriction of the nitro-group vibration. These compounds exhibited significant hypoxic–oxic fluorescence differences not only in numerical values but also in their fluorescent imaging properties as reported for the first time.      

Comparison of tumor histology to dynamic contrast enhanced magnetic resonance imaging-based physiological estimates

Purpose

The purpose of this study was to compare histologically determined cellularity and extracellular space to dynamic contrast-enhanced magnetic resonance imaging (DCE MRI)-based maps of a two-compartment model's parameters describing tumor contrast agent extravasation, specifically tumor extravascular extracellular space (EES) volume fraction (v_e), tumor plasma volume fraction (v_p) and volume-normalized contrast agent transfer rate between tumor plasma and interstitium (K_TRANS/V_T).

Materials and Methods

Obtained v_e, v_p and K_TRANS/V_T maps were estimated from gadolinium diethylenetriamine penta-acetic acid DCE T₁-weighted gradient-echo images at resolutions of 469, 938 and 2500 μm. These parameter maps were compared at each resolution to histologically determined tumor type, and the high-resolution 469-μm maps were compared with automated cell counting using Otsu's method and a color-thresholding method for estimated intracellular (V_{intracellular}) and extracellular (V_{extracellular}) space fractions.

Results

The top five K_TRANS/V_T values obtained from each tumor at 469 and 938 μm resolutions are significantly different from those obtained at 2500 μm (P<.0001) and from one another (P=.0014). Using these top five K_TRANS/V_T values and the corresponding tumor EES volume fractions v_e, we can statistically differentiate invasive ductal carcinomas from noninvasive papillary carcinomas for the 469- and 938-μm resolutions (P=.0017 and P=.0047, respectively), but not for the 2500-μm resolution (P=.9008). The color-thresholding method demonstrated that v_e measured by DCE MRI is statistically similar to histologically determined EES. The V_{extracellular} obtained from the color-thresholding method was statistically similar to the v_e measured with DCE MRI for the top 10 K_TRANS/V_T values (P>.05). DCE MRI-based K_TRANS/V_T estimates are not statistically correlated with histologically determined cellularity.

Conclusion

DCE MRI estimates of tumor physiology are a limited representation of tumor histological features. Extracellular spaces measured by both DCE MRI and microscopic analysis are statistically similar. Tumor typing by DCE MRI is spatial resolution dependent, as lower resolutions average out contributions to voxel-based estimates of K_TRANS/V_T. Thus, an appropriate resolution window is essential for DCE MRI tumor diagnosis. Within this resolution window, the top K_TRANS/V_T values with corresponding v_e are diagnostic for the tumor types analyzed in this study.     

Analysis of a new multispecies tumor growth model coupling 3D phase-fields with a 1D vascular network

In this work, we present and analyze a mathematical model for tumor growth incorporating ECM erosion, interstitial flow, and the effect of vascular flow and nutrient transport. The model is of phase-field or diffused-interface type in which multiple phases of cell species and other constituents are separated by smooth evolving interfaces. The model involves a mesoscale version of Darcy’s law to capture the flow mechanism in the tissue matrix. Modeling flow and transport processes in the vasculature supplying the healthy and cancerous tissue, one-dimensional (1D) equations are considered. Since the models governing the transport and flow processes are defined together with cell species models on a three-dimensional (3D) domain, we obtain a 3D–1D coupled model.