Diffusion tensor magnetic resonance imaging of rat glioma models: a correlation study of MR imaging and histology

Functional magnetic resonance imaging study on anxiety and depression disorders induced by chronic restraint stress in rats

Persistent and negative stress stimulation is one of the most important factors leading to anxiety and depression in individuals, and it can negatively affect the normal function and structure of brain-related regions. However, the maladaptive changes of brain neural networks in anxiety and depression induced by chronic stress have not been explored in detail. In this study, we analyzed the changes in global information transfer efficiency, stress related blood oxygen level dependent (BOLD)- and diffusion tensor imaging (DTI)- signals and functional connectivity (FC) in rat models based on resting-state functional magnetic resonance imaging (rs-fMRI). The results showed that compared to control group, rats treated with chronic restraint stress (CRS) for 5 weeks had reconstructed the small-world network properties. In addition, CRS group had increased coherence and activity in bilateral Striatum (ST_R & L), but decreased coherence and activity in unilateral (left) Frontal Association Cortex (FrA_L) and unilateral (left) Medial Entorhinal Cortex (MEC_L). DTI analysis and correlation analysis confirmed the disrupted integrity of MEC_L and ST_R & L and their correlation to anxiety- and depressive-liked behaviors. Functional connectivity further showed these regions of interest (ROI) had decreased positive correlations with several brain areas, respectively. Our study comprehensively revealed the adaptive changes of brain neural networks induced by chronic stress and emphasized the abnormal activity and functional connectivity of ST_R & L and MEC_L in the pathological condition.

Magnetic resonance imaging to assess the brain response to fasting in glioblastoma-bearing rats as a model of cancer anorexia

BACKGROUND

Global energy balance is a vital process tightly regulated by the brain that frequently becomes dysregulated during the development of cancer. Glioblastoma (GBM) is one of the most investigated malignancies, but its appetite-related disorders, like anorexia/cachexia symptoms, remain poorly understood.

METHODS

We performed manganese enhanced magnetic resonance imaging (MEMRI) and subsequent diffusion tensor imaging (DTI), in adult male GBM-bearing (n = 13) or control Wistar rats (n = 12). A generalized linear model approach was used to assess the effects of fasting in different brain regions involved in the regulation of the global energy metabolism: cortex, hippocampus, hypothalamus and thalamus. The regions were selected on the contralateral side in tumor-bearing animals, and on the left hemisphere in control rats. An additional DTI-only experiment was completed in two additional GBM (n = 5) or healthy cohorts (n = 6) to assess the effects of manganese infusion on diffusion measurements.

RESULTS

MEMRI results showed lower T₁ values in the cortex (p-value < 0.001) and thalamus (p-value < 0.05) of the fed ad libitum GBM animals, as compared to the control cohort, consistent with increased Mn²⁺ accumulation. No MEMRI-detectable differences were reported between fed or fasting rats, either in control or in the GBM group. In the MnCl₂-infused cohorts, DTI studies showed no mean diffusivity (MD) variations from the fed to the fasted state in any animal cohort. However, the DTI-only set of acquisitions yielded remarkably decreased MD values after fasting only in the healthy control rats (p-value < 0.001), and in all regions, but thalamus, of GBM compared to control animals in the fed state (p-value < 0.01). Fractional anisotropy (FA) decreased in tumor-bearing rats due to the infiltrate nature of the tumor, which was detected in both diffusion sets, with (p-value < 0.01) and without Mn²⁺ administration (p-value < 0.001).

CONCLUSIONS

Our results revealed that an altered physiological brain response to fasting occurred in hunger related regions in GBM animals, detectable with DTI, but not with MEMRI acquisitions. Furthermore, the present results showed that Mn²⁺ induces neurotoxic inflammation, which interferes with diffusion MRI to detect appetite-induced responses through MD changes.

White Matter Tracts and Diffuse Lower-Grade Gliomas: The Pivotal Role of Myelin Plasticity in the Tumor Pathogenesis, Infiltration Patterns, Functional Consequences and Therapeutic Management

For many decades, interactions between diffuse lower-grade glioma (LGG) and brain connectome were neglected. However, the neoplasm progression is intimately linked to its environment, especially the white matter (WM) tracts and their myelin status. First, while the etiopathogenesis of LGG is unclear, this tumor seems to appear during the adolescence, and it is mostly located within anterior and associative cerebral areas. Because these structures correspond to those which were myelinated later in the brain maturation process, WM myelination could play a role in the development of LGG. Second, WM fibers and the myelin characteristics also participate in LGG diffusion, since glioma cells migrate along the subcortical pathways, especially when exhibiting a demyelinated phenotype, which may result in a large invasion of the parenchyma. Third, such a migratory pattern can induce functional (neurological, cognitive and behavioral) disturbances, because myelinated WM tracts represent the main limitation of neuroplastic potential. These parameters are critical for tailoring an individualized therapeutic strategy, both (i) regarding the timing of active treatment(s) which must be proposed earlier, before a too wide glioma infiltration along the WM bundles, (ii) and regarding the anatomic extent of surgical resection and irradiation, which should take account of the subcortical connectivity. Therefore, the new science of connectomics must be integrated in LGG management, based upon an improved understanding of the interplay across glioma dissemination within WM and reactional neural networks reconfiguration, in order to optimize long-term oncological and functional outcomes. To this end, mechanisms of activity-dependent myelin plasticity should be better investigated.

Machine Learning-Based Analysis of Magnetic Resonance Radiomics for the Classification of Gliosarcoma and Glioblastoma

Objective

To identify optimal machine-learning methods for the radiomics-based differentiation of gliosarcoma (GSM) from glioblastoma (GBM).

Materials and Methods

This retrospective study analyzed cerebral magnetic resonance imaging (MRI) data of 83 patients with pathologically diagnosed GSM (58 men, 25 women; mean age, 50.5 ± 12.9 years; range, 16-77 years) and 100 patients with GBM (58 men, 42 women; mean age, 53.4 ± 14.1 years; range, 12-77 years) and divided them into a training and validation set randomly. Radiomics features were extracted from the tumor mass and peritumoral edema. Three feature selection and classification methods were evaluated in terms of their performance in distinguishing GSM and GBM: the least absolute shrinkage and selection operator (LASSO), Relief, and Random Forest (RF); and adaboost classifier (Ada), support vector machine (SVM), and RF; respectively. The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) of each method were analyzed.

Results

Based on tumor mass features, the selection method LASSO + classifier SVM was found to feature the highest AUC (0.85) and ACC (0.77) in the validation set, followed by Relief + RF (AUC = 0.84, ACC = 0.72) and LASSO + RF (AUC = 0.82, ACC = 0.75). Based on peritumoral edema features, Relief + SVM was found to have the highest AUC (0.78) and ACC (0.73) in the validation set. Regardless of the method, tumor mass features significantly outperformed peritumoral edema features in the differentiation of GSM from GBM (P < 0.05). Furthermore, the sensitivity, specificity, and accuracy of the best radiomics model were superior to those obtained by the neuroradiologists.

Conclusion

Our radiomics study identified the selection method LASSO combined with the classifier SVM as the optimal method for differentiating GSM from GBM based on tumor mass features.

Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions

Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.

High-frequency electrical properties tomography at 9.4T as a novel contrast mechanism for brain tumors

PURPOSE

To establish high-frequency magnetic resonance electrical properties tomography (MREPT) as a novel contrast mechanism for the assessment of glioblastomas using a rat brain tumor model.

METHODS

Six F98 intracranial tumor bearing rats were imaged longitudinally 8, 11 and 14 days after tumor cell inoculation. Conductivity and mean diffusivity maps were generated using MREPT and Diffusion Tensor Imaging. These maps were co-registered with T2 -weighted images and volumes of interests (VOIs) were segmented from the normal brain, ventricles, edema, viable tumor, tumor rim, and tumor core regions. Longitudinal changes in conductivity and mean diffusivity (MD) values were compared in these regions. A correlation analysis was also performed between conductivity and mean diffusivity values.

RESULTS

The conductivity of ventricles, edematous area and tumor regions (tumor rim, viable tumor, tumor core) was significantly higher (P < .01) compared to the contralateral cortex. The conductivity of the tumor increased over time while MD from the tumor did not change. A marginal positive correlation was noted between conductivity and MD values for tumor rim and viable tumor, whereas this correlation was negative for the tumor core.

CONCLUSION

We demonstrate a novel contrast mechanism based on ionic concentration and mobility, which may aid in providing complementary information to water diffusion in probing the microenvironment of brain tumors.

Diffusion kurtosis imaging for characterizing tumor heterogeneity in an intracranial rat glioblastoma model

The utility of diffusion kurtosis imaging (DKI) for assessing intra-tumor heterogeneity was evaluated in a rat model of glioblastoma multiforme. Longitudinal MRI including T₂ -weighted and diffusion-weighted MRI (DWI) was performed on six female Fischer rats 8, 11 and 14 days after intracranial transplantation of F98 cells. T₂ -weighted images were used to measure the tumor volumes and DWI images were used to compute diffusion tensor imaging (DTI) and DWI based parametric maps including mean diffusivity (MD), mean kurtosis (MK), axial diffusivity (AD), axial kurtosis, radial diffusivity, radial kurtosis, fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA). Median values from the segmented normal contralateral cortex, tumor and edema from the diffusion parameters were compared at the three imaging time points to assess any changes in tumor heterogeneity over time. ex vivo DKI was also performed in a representative sample and compared with histology. Significant differences were observed between normal cortex, tumor and edema in both the DTI and DKI parameters. Notably, at the earliest time point MK and KFA were significantly different between normal cortex and tumor in comparison with MD or FA. Although a decreasing trend in MD, AD and FA values of the tumor were observed as the tumor grew, no significant changes in any of the DTI or DKI parameters were observed longitudinally. While DKI was equally sensitive to DTI in differentiating tumor from edema and normal brain, it was unable to detect longitudinal increases in intra-tumoral heterogeneity in the F98 model of glioblastoma multiforme.

The value of diffusion tensor tractography delineating corticospinal tract in glioma in rat: validation via correlation histology

Background

An assessment of the degree of white matter tract injury is important in neurosurgical planning for patients with gliomas. The main objective of this study was to assess the injury grade of the corticospinal tract (CST) in rats with glioma using diffusion tensor imaging (DTI).

Methods

A total 17 rats underwent 7.0T MRI on day 10 after tumor implantation. The apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were acquired in the tumor, peritumoral and contralateral areas, and the ADC ratio (ipsilateral ADC/contralateral ADC) and rFA (relative FA = ipsilateral FA/contralateral FA) in the peritumoral areas were measured. The CST injury was divided into three grades and delineated by diffusion tensor tractography reconstruction imaging. The fiber density index (FDi) of the ipsilateral and contralateral CST and rFDi (relative FDi = ipsilateral FDi/contralateral FDi) in the peritumoral areas were measured. After the mice were sacrificed, the invasion of glioma cells and fraction of proliferating cells were observed by hematoxylin-eosin and Ki67 staining in the tumor and peritumoral areas. The correlations among the pathology results, CST injury grade and DTI parameter values were calculated using a Spearman correlation analysis. One-way analysis of variance was performed to compare the different CST injury grade by the rFA, rFDi and ADC ratio values.

Results

The tumor cells and proliferation index were positively correlated with the CST injury grade (r = 0.8857, 0.9233, P < 0.001). A negative correlation was demonstrated between the tumor cells and the rFA and rFDi values in the peritumoral areas (r = −0.8571, −0.5588), and the proliferation index was negatively correlated with the rFA and rFDi values (r = −0.8571, −0.5588), while the ADC ratio was not correlated with the tumor cells or proliferation index. The rFA values between the CST injury grades (1 and 3, 2 and 3) and the rFDi values in grades 1 and 3 significantly differed (P < 0.05).

Conclusions

Diffusion tensor imaging may be used to quantify the injury degrees of CST involving brain glioma in rats. Our data suggest that these quantitative parameters may be used to enhance the efficiency of delineating the relationship between fiber tracts and malignant tumor.

A combined diffusion tensor imaging and Ki-67 labeling index study for evaluating the extent of tumor infiltration using the F98 rat glioma model

Diffusion tensor imaging (DTI) has been proven to be a sophisticated and useful tool for the delineation of tumors. In the present study, we investigated the predictive role of DTI compared to other magnetic resonance imaging (MRI) techniques in combination with Ki-67 labeling index in defining tumor cell infiltration in the peritumoral regions of F98 glioma-bearing rats. A total of 29 tumor-bearing Fischer rats underwent T2-weighted imaging, contrast-enhanced T1-weighted imaging, and DTI of their brain using a 7.0-T MRI scanner. The fractional anisotropy (FA) ratios were correlated to the Ki-67 labeling index using the Spearman correlation analysis. A receiver operating characteristic curve (ROC) analysis was established to evaluate parameters with sensitivity and specificity in order to identify the threshold values for predicting tumor infiltration. Significant correlations were observed between the FA ratios and Ki-67 labeling index (r = - 0.865, p < 0.001). The ROC analysis demonstrated that the apparent diffusion coefficient (ADC) and FA ratios could predict 50% of the proliferating cells in the regions of interest (ROI), with a sensitivity of 88.1 and 81.3%, and a specificity of 86.2 and 90.2%, respectively (p < 0.001). Meanwhile, the two ratios could also predict 10% of the proliferating cells in the ROI, with a sensitivity of 82.5 and 94.9%, and a specificity of 100 and 88.9%, respectively (p < 0.001). The present study demonstrated that the FA ratios are closely correlated with the Ki-67 labeling index. Furthermore, both ADC and FA ratios, derived from DTI, were useful for quantitatively predicting the Ki-67 labeling of glioma cells.

MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.

Diffusion Kurtosis Imaging of Gliomas Grades II and III - A Study of Perilesional Tumor Infiltration, Tumor Grades and Subtypes at Clinical Presentation

BACKGROUND

Diffusion kurtosis imaging (DKI) allows for assessment of diffusion influenced by microcellular structures. We analyzed DKI in suspected low-grade gliomas prior to histopathological diagnosis. The aim was to investigate if diffusion parameters in the perilesional normal-appearing white matter (NAWM) differed from contralesional white matter, and to investigate differences between glioma malignancy grades II and III and glioma subtypes (astrocytomas and oligodendrogliomas).

PATIENTS AND METHODS

Forty-eight patients with suspected low-grade glioma were prospectively recruited to this institutional review board-approved study and investigated with preoperative DKI at 3T after written informed consent. Patients with histologically proven glioma grades II or III were further analyzed (n=35). Regions of interest (ROIs) were delineated on T2FLAIR images and co-registered to diffusion MRI parameter maps. Mean DKI data were compared between perilesional and contralesional NAWM (student's t-test for dependent samples, Wilcoxon matched pairs test). Histogram DKI data were compared between glioma types and glioma grades (multiple comparisons of mean ranks for all groups). The discriminating potential for DKI in assessing glioma type and grade was assessed with receiver operating characteristics (ROC) curves.

RESULTS

There were significant differences in all mean DKI variables between perilesional and contralesional NAWM (p=<0.000), except for axial kurtosis (p=0.099). Forty-four histogram variables differed significantly between glioma grades II (n=23) and III (n=12) (p=0.003-0.048) and 10 variables differed significantly between ACs (n=18) and ODs (n=17) (p=0.011-0.050). ROC curves of the best discriminating variables had an area under the curve (AUC) of 0.657-0.815.

CONCLUSIONS

Mean DKI variables in perilesional NAWM differ significantly from contralesional NAWM, suggesting altered microstructure by tumor infiltration not depicted on morphological MRI. Histogram analysis of DKI data identifies differences between glioma grades and subtypes.

Early detection of human glioma sphere xenografts in mouse brain using diffusion MRI at 14.1 T

Glioma models have provided important insights into human brain cancers. Among the investigative tools, MRI has allowed their characterization and diagnosis. In this study, we investigated whether diffusion MRI might be a useful technique for early detection and characterization of slow-growing and diffuse infiltrative gliomas, such as the proposed new models, LN-2669GS and LN-2540GS glioma sphere xenografts. Tumours grown in these models are not visible in conventional T₂ -weighted or contrast-enhanced T₁ -weighted MRI at 14.1 T. Diffusion-weighted imaging and diffusion tensor imaging protocols were optimized for contrast by exploring long diffusion times sensitive for probing the microstructural alterations induced in the normal brain by the slow infiltration of glioma sphere cells. Compared with T₂ -weighted images, tumours were properly identified in their early stage of growth using diffusion MRI, and confirmed by localized proton MR spectroscopy as well as immunohistochemistry. The first evidence of tumour presence was revealed for both glioma sphere xenograft models three months after tumour implantation, while no necrosis, oedema or haemorrhage were detected either by MRI or by histology. Moreover, different values of diffusion indices, such as mean diffusivity and fractional anisotropy, were obtained in tumours grown from LN-2669GS and LN-2540GS glioma sphere lines. These observations highlighted diverse tumour microstructures for both xenograft models, which were reflected in histology. This study demonstrates the ability of diffusion MRI techniques to identify and investigate early stages of slow-growing, invasive tumours in the mouse brain, thus providing a potential imaging biomarker for early detection of tumours in humans.

Preoperative Quantitative MR Tractography Compared with Visual Tract Evaluation in Patients with Neuropathologically Confirmed Gliomas Grades II and III: A Prospective Cohort Study

Background and Purpose. Low-grade gliomas show infiltrative growth in white matter tracts. Diffusion tensor tractography can noninvasively assess white matter tracts. The aim was to preoperatively assess tumor growth in white matter tracts using quantitative MR tractography (3T). The hypothesis was that suspected infiltrated tracts would have altered diffusional properties in infiltrated tract segments compared to noninfiltrated tracts. Materials and Methods. Forty-eight patients with suspected low-grade glioma were included after written informed consent and underwent preoperative diffusion tensor imaging in this prospective review-board approved study. Major white matter tracts in both hemispheres were tracked, segmented, and visually assessed for tumor involvement in thirty-four patients with gliomas grade II or III (astrocytomas or oligodendrogliomas) on postoperative neuropathological evaluation. Relative fractional anisotropy (rFA) and mean diffusivity (rMD) in tract segments were calculated and compared with visual evaluation and neuropathological diagnosis. Results. Tract segment infiltration on visual evaluation was associated with a lower rFA and high rMD in a majority of evaluated tract segments (89% and 78%, resp.). Grade II and grade III gliomas had similar infiltrating behavior. Conclusion. Quantitative MR tractography corresponds to visual evaluation of suspected tract infiltration. It may be useful for an objective preoperative evaluation of tract segment involvement.

Prognostic value of combined visualization of MR diffusion and perfusion maps in glioblastoma

We analyzed whether the combined visualization of decreased apparent diffusion coefficient (ADC) values and increased cerebral blood volume (CBV) in perfusion imaging can identify prognosis-related growth patterns in patients with newly diagnosed glioblastoma. Sixty-five consecutive patients were examined with diffusion and dynamic susceptibility-weighted contrast-enhanced perfusion weighted MRI. ADC and CBV maps were co-registered on the T1-w image and a region of interest (ROI) was manually delineated encompassing the enhancing lesion. Within this ROI pixels with ADC values <the 30th percentile (ADCmin), pixels with CBV values >the 70th percentile (CBVmax) and the intersection of pixels with ADCmin and CBVmax were automatically calculated and visualized. Initially, all tumors with a mean intersection greater than the upper quartile of the normally distributed mean intersection of all patients were subsumed to the first growth pattern termed big intersection (BI). Subsequently, the remaining tumors' growth patterns were categorized depending on the qualitative representation of ADCmin, CBVmax and their intersection. Log-rank test exposed a significantly longer overall survival of BI (n = 16) compared to non-BI group (n = 49) (p = 0.0057). Thirty-one, four and 14 patients of the non-BI group were classified as predominant ADC-, CBV- and mixed growth group, respectively. In a multivariate Cox regression model, the BI-, CBV- and mixed groups had significantly lower adjusted hazard ratios (p-value, α(Bonferroni) < 0.006) when compared to the reference group ADC: 0.29 (0.0027), 0.11 (0.038) and 0.33 (0.0059). Our study provides evidence that the combination of diffusion and perfusion imaging allows visualization of different glioblastoma growth patterns that are associated with prognosis. A possible biological hypothesis for this finding could be the interpretation of the ADCmin fraction as the invasion-front of tumor cells while the CBVmax fraction might represent the vascular rich tumor border that is "trailing behind" the invasion-front in the ADC group.

Nuclear Overhauser Enhancement imaging of glioblastoma at 7 Tesla: region specific correlation with apparent diffusion coefficient and histology

OBJECTIVE

To explore the correlation between Nuclear Overhauser Enhancement (NOE)-mediated signals and tumor cellularity in glioblastoma utilizing the apparent diffusion coefficient (ADC) and cell density from histologic specimens. NOE is one type of chemical exchange saturation transfer (CEST) that originates from mobile macromolecules such as proteins and might be associated with tumor cellularity via altered protein synthesis in proliferating cells.

PATIENTS AND METHODS

For 15 patients with newly diagnosed glioblastoma, NOE-mediated CEST-contrast was acquired at 7 Tesla (asymmetric magnetization transfer ratio (MTRasym) at 3.3ppm, B1 = 0.7 μT). Contrast enhanced T1 (CE-T1), T2 and diffusion-weighted MRI (DWI) were acquired at 3 Tesla and coregistered. The T2 edema and the CE-T1 tumor were segmented. ADC and MTRasym values within both regions of interest were correlated voxelwise yielding the correlation coefficient rSpearman (rSp). In three patients who underwent stereotactic biopsy, cell density of 12 specimens per patient was correlated with corresponding MTRasym and ADC values of the biopsy site.

RESULTS

Eight of 15 patients showed a weak or moderate positive correlation of MTRasym and ADC within the T2 edema (0.16≤rSp≤0.53, p<0.05). Seven correlations were statistically insignificant (p>0.05, n = 4) or yielded rSp≈0 (p<0.05, n = 3). No trend towards a correlation between MTRasym and ADC was found in CE-T1 tumor (-0.31<rSp<0.28, p<0.05, n = 9; p>0.05, n = 6). The biopsy-analysis within CE-T1 tumor revealed a strong positive correlation between tumor cellularity and MTRasym values in two of the three patients (rSppatient3 = 0.69 and rSppatient15 = 0.87, p<0.05), while the correlation of ADC and cellularity was heterogeneous (rSppatient3 = 0.545 (p = 0.067), rSppatient4 = -0.021 (p = 0.948), rSppatient15 = -0.755 (p = 0.005)).

DISCUSSION

NOE-imaging is a new contrast promising insight into pathophysiologic processes in glioblastoma regarding cell density and protein content, setting itself apart from DWI. Future studies might be based on the assumption that NOE-mediated CEST visualizes cellularity more accurately than ADC, especially in the CE-T1 tumor region.

Translation of the ecological trap concept to glioma therapy: the cancer cell trap concept

Viewing tumors as ecosystems offers the opportunity to consider how ecological concepts can be translated to novel therapeutic perspectives. The ecological trap concept emerged approximately half a century ago when it was observed that animals can prefer an environment of low quality for survival over other available environments of higher quality. The presence of such a trap can drive a local population to extinction. The cancer cell trap concept is the translation of the ecological trap into glioma therapy. It exploits and diverts the invasive potential of glioma cells by guiding their migration towards specific locations where a local therapy can be delivered efficiently. This illustrates how an ecological concept can change therapeutic obstacles into therapeutic tools.

Differentiation of pure vasogenic edema and tumor-infiltrated edema in patients with peritumoral edema by analyzing the relationship of axial and radial diffusivities on 3.0T MRI

OBJECT

The purpose of this study was to analyze the relationship of axial diffusivity (AD) and radial diffusivity (RD) in peritumoral edema of high grade glioma, metastasis, and meningioma, and to differentiate tumor-infiltrated edema from pure vasogenic edema.

MATERIALS AND METHODS

Twenty patients with high-grade glioma and 16 with meningioma or metastatic tumor were enrolled in our study. All cases were confirmed by histopathological study. Diffusion tensor imaging (DTI) was performed in all patients. Peritumoral edema of high-grade glioma was considered tumor-infiltrated edema, and edema of meningioma or metastasis was considered pure vasogenic edema. Fractional anisotropy (FA), mean diffusivity (MD), AD, RD, regression coefficient of RD to AD (RCRD-AD), and tumor infiltration index (TII) in tumor-infiltrated edema and pure vasogenic edema were analyzed and compared. Receiver operating characteristic (ROC) curve analysis was conducted to demonstrate their differential effectiveness.

RESULTS

RCRD-AD in tumor-infiltrated edema (0.724±0.125) was significantly higher than that in pure vasogenic edema (0.571±0.111) (P=0.001). FA of tumor-infiltrated edema (0.175±0.025) was significantly lower than that of pure vasogenic edema (0.203±0.035) (P=0.007). Other parameters showed no significant difference between the 2 types of edema. ROC curve analysis showed RCRD-AD was the most effective parameter in distinguishing tumor-infiltrated edema from pure vasogenic edema. Using a threshold of 0.6, a sensitivity of 0.85 and specificity of 0.69 can be achieved with RCRD-AD.

CONCLUSION

Analysis of the AD and RD relationship may reflect differences in diffusion characteristics of edema surrounding high-grade glioma and meningioma or metastasis, and may be helpful in detecting peritumoral infiltration in high-grade glioma.

Radiation induced brain injury: assessment of white matter tracts in a pre-clinical animal model using diffusion tensor MR imaging

We aim to study radiation induced white matter injury in a pre-clinical model using Diffusion tensor MR imaging (DTI). Nineteen 12-week old Sprague-Dawley rats were irradiated to the right hemisphere using a linear accelerator. The dose distribution map was coregistered to the DTI map to generate the actual radiation dose to each white matter tract. Rats underwent longitudinal DTI scans at five time points from 4 to 48 weeks post-radiation with histological evaluations. Fractional anisotropy (FA) of the external capsule, fornix, cerebral peduncle, anterior commissure, optic tract and optic nerve was evaluated. Radiation dose was highest at the ipsilateral external capsule and fornix (29.4 ± 1.3 and 29.8 ± 1.1 Gy, respectively). Optic nerve received 50 % dose to the external capsule and other white matter tracts received 80 % dose. Significantly lower FA was firstly found in the ipsilateral external capsule at 4 weeks post-radiation and in the ipsilateral fornix at 40 weeks post-radiation compared to the contralateral side. Significantly lower FA was found in contralateral optic nerve compared to ipsilateral optic nerve at 48 weeks post-radiation despite ipsilateral optic nerves receiving higher radiation dose than contralateral optic nerve (p = 0.021). No differences were found in other white matter regions until 48 weeks. Histology indicated demyelination, axonal degeneration and coagulative necrosis in all injured white matter. DTI can serve as a promising tool for assessment of radiation induced white matter injury and regional radiosensitivity of white matter tracts.