Quantitative analysis of glioma cell invasion by diffusion tensor imaging

Current Knowledge about the Peritumoral Microenvironment in Glioblastoma

Glioblastoma is a deadly disease, with a mean overall survival of less than 2 years from diagnosis. Recurrence after gross total surgical resection and adjuvant chemo-radiotherapy almost invariably occurs within the so-called peritumoral brain zone (PBZ). The aim of this narrative review is to summarize the most relevant findings about the biological characteristics of the PBZ currently available in the medical literature. The PBZ presents several peculiar biological characteristics. The cellular landscape of this area is different from that of healthy brain tissue and is characterized by a mixture of cell types, including tumor cells (seen in about 30% of cases), angiogenesis-related endothelial cells, reactive astrocytes, glioma-associated microglia/macrophages (GAMs) with anti-inflammatory polarization, tumor-infiltrating lymphocytes (TILs) with an "exhausted" phenotype, and glioma-associated stromal cells (GASCs). From a genomic and transcriptomic point of view, compared with the tumor core and healthy brain tissue, the PBZ presents a "half-way" pattern with upregulation of genes related to angiogenesis, the extracellular matrix, and cellular senescence and with stemness features and downregulation in tumor suppressor genes. This review illustrates that the PBZ is a transition zone with a pre-malignant microenvironment that constitutes the base for GBM progression/recurrence. Understanding of the PBZ could be relevant to developing more effective treatments to prevent GBM development and recurrence.

Perifocal Zone of Brain Gliomas: Application of Diffusion Kurtosis and Perfusion MRI Values for Tumor Invasion Border Determination

(1) Purpose: To determine the borders of malignant gliomas with diffusion kurtosis and perfusion MRI biomarkers. (2) Methods: In 50 high-grade glioma patients, diffusion kurtosis and pseudo-continuous arterial spin labeling (pCASL) cerebral blood flow (CBF) values were determined in contrast-enhancing area, in perifocal infiltrative edema zone, in the normal-appearing peritumoral white matter of the affected cerebral hemisphere, and in the unaffected contralateral hemisphere. Neuronavigation-guided biopsy was performed from all affected hemisphere regions. (3) Results: We showed significant differences between the DKI values in normal-appearing peritumoral white matter and unaffected contralateral hemisphere white matter. We also established significant (p < 0.05) correlations of DKI with Ki-67 labeling index and Bcl-2 expression activity in highly perfused enhancing tumor core and in perifocal infiltrative edema zone. CBF correlated with Ki-67 LI in highly perfused enhancing tumor core. One hundred percent of perifocal infiltrative edema tissue samples contained tumor cells. All glioblastoma samples expressed CD133. In the glioblastoma group, several normal-appearing white matter specimens were infiltrated by tumor cells and expressed CD133. (4) Conclusions: DKI parameters reveal changes in brain microstructure invisible on conventional MRI, e.g., possible infiltration of normal-appearing peritumoral white matter by glioma cells. Our results may be useful for plotting individual tumor invasion maps for brain glioma surgery or radiotherapy planning.

Associating IDH and TERT Mutations in Glioma with Diffusion Anisotropy in Normal-Appearing White Matter

BACKGROUND AND PURPOSE

IDH and TERT mutations might infiltratively manifest within normal-appearing white matter with specific phenotypes such as microstructural changes undetectable by standard MR imaging contrasts but potentially associable with DTI variables. The aim of this retrospective glioma study was to statistically investigate IDH and TERT associations and classifications with DTI reported microstructure in normal-appearing white matter.

MATERIALS AND METHODS

Retrospective data from patients imaged between March 2012 and February 2016 were analyzed by grouping them as IDH-TERT subgroups and by IDH and TERT mutation status. DTI variables in the IDH-TERT subgroups were first identified by the Kruskal-Wallis test, followed by Dunn-Šidák multiple comparisons with Bonferroni correction. IDH and TERT mutations were compared with the Mann-Whitney U test. Classification by thresholding was tested using receiver operating characteristic analysis.

RESULTS

Of 170 patients, 70 patients (mean age, 43.73 [SD, 15.32] years; 40 men) were included. Whole-brain normal-appearing white matter fractional anisotropy (FA) and relative anisotropy (RA) (P = .002) were significantly higher and the contralateral-ipsilateral hemispheric differences, ΔFA and ΔRA, (P < .001) were significantly lower in IDHonly patients compared with TERTonly, with a higher whole-brain normal-appearing white matter FA and RA (P = .01) and ΔFA and ΔRA (P = .002) compared to double positive patients. Whole-brain normal-appearing white matter ADC (P = .02), RD (P = .001), λ2 (P = .001), and λ3 (P = .001) were higher in IDH wild-type. Whole-brain normal-appearing white matter λ1 (AD) (P = .003), FA (P < .001), and RA (P = .003) were higher, but Δλ1 (P = .002), ΔFA, and ΔRA (P < .001) were lower in IDH mutant versus IDH wild-type. ΔFA (P = .01) and ΔRA (P = .02) were significantly higher in TERT mutant versus TERT wild-type.

CONCLUSIONS

Axial and nonaxial diffusivities, anisotropy indices in the normal-appearing white matter and their interhemispheric differences demonstrated microstructural differences between IDH and TERT mutations, with the potential for classification methods.

The peritumoral brain zone in glioblastoma: where we are and where we are going

Glioblastoma (GBM) is the most aggressive and invasive primary brain tumor. Current therapies are not curative, and patients' outcomes remain poor with an overall survival of 20.9 months after surgery. The typical growing pattern of GBM develops by infiltrating the surrounding apparent normal brain tissue within which the recurrence is expected to appear in the majority of cases. Thus, in the last decades, an increased interest has developed to investigate the cellular and molecular interactions between GBM and the peritumoral brain zone (PBZ) bordering the tumor tissue. The aim of this review is to provide up-to-date knowledge about the oncogenic properties of the PBZ to highlight possible druggable targets for more effective treatment of GBM by limiting the formation of recurrence, which is almost inevitable in the majority of patients. Starting from the description of the cellular components, passing through the illustration of the molecular profiles, we finally focused on more clinical aspects, represented by imaging and radiological details. The complete picture that emerges from this review could provide new input for future investigations aimed at identifying new effective strategies to eradicate this still incurable tumor.

DTI Abnormalities Related to Glioblastoma: A Prospective Comparative Study with Metastasis and Healthy Subjects

(1) Background: Glioblastoma multiforme (GBM) shows complex mechanisms of spreading of the tumor cells, up to remote areas, and little is still known of these mechanisms, thus we focused on MRI abnormalities observable in the tumor and the brain adjacent to the lesion, up to the contralateral hemisphere, with a special interest on tensor diffusion imaging informing on white matter architecture; (2) Material and Methods: volumes, macroscopic volume (MV), brain-adjacent-tumor (BAT) volume and abnormal color-coded DTI volume (aCCV), and region-of-interest samples (probe volumes, ipsi, and contra lateral to the lesion), with their MRI characteristics, apparent diffusion coefficient (ADC), fractional anisotropy (FA) values, and number of fibers (DTI fiber tracking) were analyzed in patients suffering GBM (n = 15) and metastasis (n = 9), and healthy subjects (n = 15), using ad hoc statistical methods (type I error = 5%) (3) Results: GBM volumes were larger than metastasis volumes, aCCV being larger in GBM and BAT ADC was higher in metastasis, ADC decreased centripetally in metastasis, FA increased centripetally either in GBM or metastasis, MV and BAT FA values were higher in GBM, ipsi FA values of GBM ROIs were higher than those of metastasis, and the GBM ipsi number of fibers was higher than the GBM contra number of fibers; (4) Conclusions: The MV, BAT and especially the aCCV, as well as their related water diffusion characteristics, could be useful biomarkers in oncology and functional oncology.

Diffusion tensor imaging derived metrics in high grade glioma and brain metastasis differentiation

Background: Pretreatment differentiation between glioblastoma and metastasis is a frequently encountered dilemma in neurosurgical practice. Distinction is required for precise planning of resection or radiotherapy, and also for defining further diagnostic procedures. Morphology and spectroscopy imaging features are not specific and frequently overlap. This limitation of magnetic resonance imaging and magnetic resonance spectroscopy was the reason to initiate this study. The aim of the present study was to determine whether the dataset of diffusion tensor imaging metrics contains information which may be used for the distinction between primary and secondary intra-axial neoplasms. Methods: Two diffusion tensor imaging parameters were measured in 81 patients with an expansive, ring-enhancing, intra-axial lesion on standard magnetic resonance imaging (1.5 T system). All tumors were histologically verified glioblastoma or secondary deposit. For qualitative analysis, two regions of interest were defined: intratumoral and immediate peritumoral region (locations 1 and 2, respectively). Fractional anisotropy and mean difusivity values of both groups were compared. Additional test was performed to determine if there was a significant difference in mean values between two locations. Results: A statistically significant difference was found in fractional anisotropy values among two locations, with decreasing values in the direction of neoplastic infiltration, although such difference was not observed in fractional anisotropy values in the group with secondary tumors. Mean difusivity values did not appear helpful in differentiation between these two entities. In both groups there was no significant difference in mean difusivity values, neither in intratumoral nor in peritumoral location. Conclusion: The results of our study justify associating the diffusion tensor imaging technique to conventional morphologic magnetic resonance imaging as an additional diagnostic tool for the distinction between primary and secondary intra-axial lesions. Quantitative analysis of diffusion tensor imaging metric, in particular measurement of fractional anisotropy in peritumoral edema facilitates accurate diagnosis.

Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography

Intraoperative ultrasound elastography (IOUS-E) is a novel image modality applied in brain tumor assessment. However, the potential links between elastographic findings and other histological and neuroimaging features are unknown. This study aims to find associations between brain tumor elasticity, diffusion tensor imaging (DTI) metrics, and cell proliferation. A retrospective study was conducted to analyze consecutively admitted patients who underwent craniotomy for supratentorial brain tumors between March 2018 and February 2020. Patients evaluated by IOUS-E and preoperative DTI were included. A semi-quantitative analysis was performed to calculate the mean tissue elasticity (MTE). Diffusion coefficients and the tumor proliferation index by Ki-67 were registered. Relationships between the continuous variables were determined using the Spearman ρ test. A predictive model was developed based on non-linear regression using the MTE as the dependent variable. Forty patients were evaluated. The pathologic diagnoses were as follows: 21 high-grade gliomas (HGG); 9 low-grade gliomas (LGG); and 10 meningiomas. Cases with a proliferation index of less than 10% had significantly higher medians of MTE (110.34 vs. 79.99, p < 0.001) and fractional anisotropy (FA) (0.24 vs. 0.19, p = 0.020). We found a strong positive correlation between MTE and FA (r_s (38) = 0.91, p < 0.001). A cubic spline non-linear regression model was obtained to predict tumoral MTE from FA (R² = 0.78, p < 0.001). According to our results, tumor elasticity is associated with histopathological and DTI-derived metrics. These findings support the usefulness of IOUS-E as a complementary tool in brain tumor surgery.

A Neural Network Approach to Identify the Peritumoral Invasive Areas in Glioblastoma Patients by Using MR Radiomics

The challenge in the treatment of glioblastoma is the failure to identify the cancer invasive area outside the contrast-enhancing tumour which leads to the high local progression rate. Our study aims to identify its progression from the preoperative MR radiomics. 57 newly diagnosed cerebral glioblastoma patients were included. All patients received 5-aminolevulinic acid (5-ALA) fluorescence guidance surgery and postoperative temozolomide concomitant chemoradiotherapy. Preoperative 3 T MRI data including structure MR, perfusion MR, and DTI were obtained. Voxel-based radiomics features extracted from 37 patients were used in the convolutional neural network to train and as internal validation. Another 20 patients of the cohort were tested blindly as external validation. Our results showed that the peritumoural progression areas had higher signal intensity in FLAIR (p = 0.02), rCBV (p = 0.038), and T1C (p = 0.0004), and lower intensity in ADC (p = 0.029) and DTI-p (p = 0.001) compared to non-progression area. The identification of the peritumoural progression area was done by using a supervised convolutional neural network. There was an overall accuracy of 92.6% in the training set and 78.5% in the validation set. Multimodal MR radiomics can demonstrate distinct characteristics in areas of potential progression on preoperative MRI.

Early assessment of recurrent glioblastoma response to bevacizumab treatment by diffusional kurtosis imaging: a preliminary report

PURPOSE

The purpose of this preliminary study is to apply diffusional kurtosis imaging to assess the early response of recurrent glioblastoma to bevacizumab treatment.

METHODS

This prospective cohort study included 10 patients who had been diagnosed with recurrent glioblastoma and scheduled to receive bevacizumab treatment. Diffusional kurtosis images were obtained from all the patients 0-7 days before (pre-bevacizumab) and 28 days after (post-bevacizumab) initiating bevacizumab treatment. The mean, 10th, and 90th percentile values were derived from the histogram of diffusional kurtosis imaging metrics in enhancing and non-enhancing lesions, selected on post-contrast T1-weighted and fluid-attenuated inversion recovery images. Correlations of imaging measures with progression-free survival and overall survival were evaluated using Spearman's rank correlation coefficient. The significance level was set at P < 0.05.

RESULTS

Higher pre-bevacizumab non-enhancing lesion volume was correlated with poor overall survival (r = -0.65, P = 0.049). Higher post-bevacizumab mean diffusivity and axial diffusivity (D_∥, D_∥10% and D_∥90%) in non-enhancing lesions were correlated with poor progression-free survival (r = -0.73, -0.83, -0.71 and -0.85; P < 0.05). Lower post-bevacizumab axial kurtosis (K_∥10%) in non-enhancing lesions was correlated with poor progression-free survival (r = 0.81, P = 0.008).

CONCLUSIONS

This preliminary study demonstrates that diffusional kurtosis imaging metrics allow the detection of tissue changes 28 days after initiating bevacizumab treatment and that they may provide information about tumor progression.

Multimodal MRI characteristics of the glioblastoma infiltration beyond contrast enhancement

Our inability to identify the invasive margin of glioblastomas hampers attempts to achieve local control. Diffusion tensor imaging (DTI) has been implemented clinically to delineate the margin of the tumor infiltration, its derived anisotropic (q) values can extend beyond the contrast-enhanced area and correlates closely with the tumor. However, its correlation with tumor infiltration shown on multivoxel proton magnetic resonance spectroscopy¹ (MRS) and perfusion magnetic resonance imaging (MRI) should be investigated. In this study, we aimed to show tissue characteristics of the q-defined peritumoral invasion on MRS and perfusion MRI. Patients with a primary glioblastoma were included (n = 51). Four regions of interest were analyzed; the contrast-enhanced lesion, peritumoral abnormal q region, peritumoral normal q region, and contralateral normal-appearing white matter. MRS, including choline (Cho)/creatinine (Cr), Cho/N-acetyl-aspartate (NAA) and NAA/Cr ratios, and the relative cerebral blood volume (rCBV) were analyzed. Our results showed an increase in the Cho/NAA (p = 0.0346) and Cho/Cr (p = 0.0219) ratios in the peritumoral abnormal q region, suggestive of tumor invasion. The rCBV was marginally elevated (p = 0.0798). Furthermore, the size of the abnormal q regions was correlated with survival; patients with larger abnormal q regions showed better progression-free survival (median 287 versus 53 days, p = 0.001) and overall survival (median 464 versus 274 days, p = 0.006) than those with smaller peritumoral abnormal q regions of interest. These results support how the DTI q abnormal area identifies tumor activity beyond the contrast-enhanced area, especially correlating with MRS.

Highly accelerated, model-free diffusion tensor MRI reconstruction using neural networks

PURPOSE

The purpose of this study was to develop a neural network that accurately performs diffusion tensor imaging (DTI) reconstruction from highly accelerated scans.

MATERIALS AND METHODS

This retrospective study was conducted using data acquired between 2013 and 2018 and was approved by the local institutional review board. DTI acquired in healthy volunteers (N = 10) was used to train a neural network, DiffNet, to reconstruct fractional anisotropy (FA) and mean diffusivity (MD) maps from small subsets of acquired DTI data with between 3 and 20 diffusion-encoding directions. FA and MD maps were then reconstructed in volunteers and in patients with glioblastoma multiforme (GBM, N = 12) using both DiffNet and conventional reconstructions. Accuracy and precision were quantified in volunteer scans and compared between reconstructions. The accuracy of tumor delineation was compared between reconstructed patient data by evaluating agreement between DTI-derived tumor volumes and volumes defined by contrast-enhanced T1-weighted MRI. Comparisons were performed using areas under the receiver operating characteristic curves (AUC).

RESULTS

DiffNet FA reconstructions were more accurate and precise compared with conventional reconstructions for all acceleration factors. DiffNet permitted reconstruction with only three diffusion-encoding directions with significantly lower bias than the conventional method using six directions (0.01 ± 0.01 vs 0.06 ± 0.01, P < 0.001). While MD-based tumor delineation was not substantially different with DiffNet (AUC range: 0.888-0.902), DiffNet FA had higher AUC than conventional reconstructions for fixed scan time and achieved similar performance with shorter scans (conventional, six directions: AUC = 0.926, DiffNet, three directions: AUC = 0.920).

CONCLUSION

DiffNet improved DTI reconstruction accuracy, precision, and tumor delineation performance in GBM while permitting reconstruction from only three diffusion-encoding directions.&!#6.

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.

Diffusion Kurtosis Imaging in the Assessment of Peritumoral Brain Edema in Glioblastomas and Brain Metastases

Aim: to explore the opportunities of application of diffusionkurtosis imaging (DKI) for assessment and estimation of diffusion scalar metrics in different locations of peritumoral edema for extra- and intracerebral tumors and in contralateral normal tissue.

Materials and methods. 38 patients with supratentorial brain tumors were investigated: 24 (63%) patients with primarily revealed glioblastomas (GB) and 14 (37%) patients with solitary cancer brain metastasis (MTS). MRI was performed on 3.0 T MR-scanner (Signa HDxt, General Electric, USA) with the standard protocols for brain tumor and additional protocol for DKI. The standard protocol for brain tumor included: T1-, T2-weighted images, T2-FLAIR, DWI,  T1 with contrast enhancement. Diffusion kurtosis MRI based on SE  EPI with TR = 10000 ms, TE = 102 ms, FOV = 240 mm, isotropic voxel size 3 × 3 × 3 mm3, 60 noncoplanar diffusion directions. We  used three b-values: 0, 1000 and 2500 s/mm2. Аcquisition time was 22 min. Total acquisition time was near 40 min. This study was approved by Ethical committee of Burdenko National Scientific  and Practical Center for Neurosurgery. Parametric maps were  constructed for the following diffusion coefficients: mean (MK),  transverse / radial (RK), longitudinal / axial (AK) kurtozis; medium  (MD), transverse / radial (RD) and longitudinal / axial (AD) diffusion; fractional anisotropy (FA) and a bi-exponential diffusion model  coefficients: axonal water fractions (AWF), axial (AxEAD) and radial  (RadEAD) extra-axonal water diffusion and the water molecules  trajectory tortuosity index (TORT). Normative quantitative indicators  were obtained for the six regions of the peritumoral zone as they  moved away from the tumor (region 2) to the edema periphery  (regions 4–5), as well as in the normal brain on the contralateral  hemisphere (C/L) (zone 7). A comparative analysis of these  indicators was conducted for cases with GB and MTS. DKI scalar metrics were estimated using Explore DTI (http://www.exploredti.com/).

Results. Anatomic MRI (T1 without/with contrast enhancement) for  all cases with GB and MTS visualized a contrast enhancement tumor.  The peritumoral edema, spreading mainly over the brain white  matter, was well visualized on T2-FLAIR. Diffusion kurtosis  coefficients decreased in the near peritumoral edema (regions 2–3)  and a gradually increased to the edema periphery (regions 5–6). In Region 2, MK in both GB and MTS groups were MKGB(2) = 0.637 ±  0.140 and MKMTS(2) = 0.550 ± 0.046; RK in this region were  RKGB(2) = 0.690 ± 0.154 and RKMTS (2) = 0.584 ± 0.051.  Differences both MK and RK coefficients in patients with GB and MTS of region 2 were significant (p < 0.001). There were no differences in AK values for GB and MTS in region 2 (p > 0.05), but in regions 3  and 4 differences were observed (p < 0.01). The minimum value of  AK in the central edema (regions 3–4) was AKMTS(3–4) = 0.433 ± 0.063 in patients with MTS. The values of MK and RK on the  contralateral side in patients with MTS were significantly higher than  in the GB group (p < 0.02); MKC/LMTC = 0.954 ± 0.140, RKC/LMTC  = 1.257 ± 0.308 and MKC/LGB = 0.829 ± 0.146, RKc/LGB = 0.989  ± 0.282. There was no significant difference for contralateral AK between the groups.

Conclusions. We found that DKI scalar metrics are the sensitive  tumor biomarkers. It allows us to perform a robust differentiation  between the infiltrating GB tumor and purely vasogenic edema of  МТS. The obtained results will allow further differential diagnosis of  extra- and intracerebral tumors and can be used to plan surgical /  radiosurgical treatment for brain tumors.

MR Fingerprinting of Adult Brain Tumors: Initial Experience

BACKGROUND AND PURPOSE

MR fingerprinting allows rapid simultaneous quantification of T1 and T2 relaxation times. This study assessed the utility of MR fingerprinting in differentiating common types of adult intra-axial brain tumors.

MATERIALS AND METHODS

MR fingerprinting acquisition was performed in 31 patients with untreated intra-axial brain tumors: 17 glioblastomas, 6 World Health Organization grade II lower grade gliomas, and 8 metastases. T1, T2 of the solid tumor, immediate peritumoral white matter, and contralateral white matter were summarized within each ROI. Statistical comparisons on mean, SD, skewness, and kurtosis were performed by using the univariate Wilcoxon rank sum test across various tumor types. Bonferroni correction was used to correct for multiple-comparison testing. Multivariable logistic regression analysis was performed for discrimination between glioblastomas and metastases, and area under the receiver operator curve was calculated.

RESULTS

Mean T2 values could differentiate solid tumor regions of lower grade gliomas from metastases (mean, 172 ± 53 ms, and 105 ± 27 ms, respectively; P = .004, significant after Bonferroni correction). The mean T1 of peritumoral white matter surrounding lower grade gliomas differed from peritumoral white matter around glioblastomas (mean, 1066 ± 218 ms, and 1578 ± 331 ms, respectively; P = .004, significant after Bonferroni correction). Logistic regression analysis revealed that the mean T2 of solid tumor offered the best separation between glioblastomas and metastases with an area under the curve of 0.86 (95% CI, 0.69-1.00; P < .0001).

CONCLUSIONS

MR fingerprinting allows rapid simultaneous T1 and T2 measurement in brain tumors and surrounding tissues. MR fingerprinting-based relaxometry can identify quantitative differences between solid tumor regions of lower grade gliomas and metastases and between peritumoral regions of glioblastomas and lower grade gliomas.

Mesoscopic imaging of glioblastomas: Are diffusion, perfusion and spectroscopic measures influenced by the radiogenetic phenotype?

The purpose of this study was to identify markers from perfusion, diffusion, and chemical shift imaging in glioblastomas (GBMs) and to correlate them with genetically determined and previously published patterns of structural magnetic resonance (MR) imaging. Twenty-six patients (mean age 60 years, 13 female) with GBM were investigated. Imaging consisted of native and contrast-enhanced 3D data, perfusion, diffusion, and spectroscopic imaging. In the presence of minor necrosis, cerebral blood volume (CBV) was higher (median ± SD, 2.23% ± 0.93) than in pronounced necrosis (1.02% ± 0.71), p_corr = 0.0003. CBV adjacent to peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity was lower in edema (1.72% ± 0.31) than in infiltration (1.91% ± 0.35), p_corr = 0.039. Axial diffusivity adjacent to peritumoral FLAIR hyperintensity was lower in severe mass effect (1.08*10^-3 mm²/s ± 0.08) than in mild mass effect (1.14*10^-3 mm²/s ± 0.06), p_corr = 0.048. Myo-inositol was positively correlated with a marker for mitosis (Ki-67) in contrast-enhancing tumor, r = 0.5, p_corr = 0.0002. Changed CBV and axial diffusivity, even outside FLAIR hyperintensity, in adjacent normal-appearing matter can be discussed as to be related to angiogenesis pathways and to activated proliferation genes. The correlation between myo-inositol and Ki-67 might be attributed to its binding to cell surface receptors regulating tumorous proliferation of astrocytic cells.

Microscopic DTI accurately identifies early glioma cell migration: correlation with multimodal imaging in a new glioma stem cell model

Monitoring glioma cell infiltration in the brain is critical for diagnosis and therapy. Using a new glioma Glio6 mouse model derived from human stem cells we show how diffusion tensor imaging (DTI) may predict glioma cell migration/invasion. In vivo multiparametric MRI was performed at one, two and three months of Glio6 glioma growth (Glio6 (n = 6), sham (n = 3)). This longitudinal study reveals the existence of a time window to study glioma cell/migration/invasion selectively. Indeed, at two months only Glio6 cell invasion was detected, while tumor mass formation, edema, blood-brain barrier leakage and tumor angiogenesis were detected later, at three months. To robustly confirm the potential of DTI for detecting glioma cell migration/invasion, a microscopic 3D-DTI (80 μm isotropic spatial resolution) technique was developed and applied to fixed mouse brains (Glio6 (n = 6), sham (n = 3)). DTI changes were predominant in the corpus callosum (CC), a known path of cell migration. Fractional anisotropy (FA) and perpendicular diffusivity (D_⊥ ) changes derived from ex vivo microscopic 3D-DTI were significant at two months of tumor growth. In the caudate putamen an FA increase of +38% (p < 0.001) was observed, while in the CC a - 28% decrease in FA (p < 0.005) and a + 95% increase in D_⊥ (p < 0.005) were observed. In the CC, DTI changes and fluorescent Glio6 cell density obtained by two-photon microscopy in the same brains were correlated (p < 0.001, r = 0.69), validating FA and D_⊥ as early quantitative biomarkers to detect glioma cell migration/invasion. The origin of DTI changes was assessed by electron microscopy of the same tract, showing axon bundle disorganization. During the first two months, Glio6 cells display a migratory phenotype without being associated with the constitution of a brain tumor mass. This offers a unique opportunity to apply microscopic 3D-DTI and to validate DTI parameters FA and D_⊥ as biomarkers for glioma cell invasion.

Interhemispheric Difference Images from Postoperative Diffusion Tensor Imaging of Gliomas

Introduction

Determining the full extent of gliomas during radiotherapy planning can be challenging with conventional T1 and T2 magnetic resonance imaging (MRI). The purpose of this study was to develop a method to automatically calculate differences in the fractional anisotropy (FA) and mean diffusivity (MD) values in target volumes obtained with diffusion tensor imaging (DTI) by comparing with values from anatomically homologous voxels on the contralateral side of the brain.

Methods

Seven patients with a histologically confirmed glioma underwent postoperative radiotherapy planning with 1.5 T MRI and computed tomography. DTI was acquired using echo planar imaging for 20 noncolinear directions with b = 1000 s/mm² and one additional image with b = 0, repeated four times for signal averaging. The distribution of FA and MD was calculated in the gross tumor volume (GTV), shells 0-5 mm, 5-10 mm, 10-15 mm, 15-20 mm, and 20-25 mm outside the GTV, and the GTV mirrored in the left-right direction (mirGTV). All images were aligned to a template image, and FA and MD interhemispheric difference images were calculated. The difference in mean FA and MD between the regions of interest was statistically tested using two-sided paired t-tests with α = 0.05.

Results

The mean FA in mirGTV was 0.20 ± 0.04, which was larger than the FA in the GTV (0.12 ± 0.03) and shells 0-5 mm (0.15 ± 0.03) and 5-10 mm (0.17 ± 0.03) outside the GTV. The mean MD (×10^-3 mm²/s) in mirGTV was 0.93 ± 0.09, which was smaller than the MD in the GTV (1.48 ± 0.19) and the peritumoral shells. The distribution of FA and MD interhemispheric differences followed the same trends as FA and MD values.

Conclusions

This study successfully implemented a method for calculation of FA and MD differences by comparison of voxel values with anatomically homologous voxels on the contralateral side of the brain. Further research is warranted to determine if radiotherapy planning using these images can be used to improve target delineation.

Fractional Anisotropy Correlates with Overall Survival in Glioblastoma

OBJECTIVE

Glioblastoma (GB) is an infiltrative disease that results in microstructural damage on a cellular level. Fractional anisotropy (FA) is an important estimate of diffusion tensor imaging (DTI) that can be used to assess microstructural integrity. The aim of this study was to examine the correlation between FA values and overall survival (OS) in patients with GB.

METHODS

This retrospective single-center study included 122 consecutive patients with GB (50 women; median age, 63 years) with preoperative MRI including fluid attenuated inversion recovery (FLAIR), contrast-enhanced T1-weighted sequences, and DTI. FA and apparent diffusion coefficient (ADC) values in contrast-enhancing lesions (FA-CEL, FA-ADC), nonenhancing lesions, and central tumor regions were correlated to histopathologic and clinical parameters. Univariate and multivariate survival analyses were performed.

RESULTS

Patients with low FA-CEL (median <0.31) showed significantly improved OS in univariate analysis (P = 0.028). FA-CEL also showed a positive correlation with Ki-67 proliferation index (P = 0.003). However, in a multivariate survival model, FA values could not be identified as independent prognostic parameters beside established factors such as age and Karnofsky performance scale score. FA values in nonenhancing lesions and central tumor regions and mean ADC values had no distinct influence on OS.

CONCLUSIONS

FA values can provide prognostic information regarding OS in patients with GB. There is a correlation between FA-CEL values and Ki-67 proliferation index, a marker for malignancy. Noninvasive identification of more aggressive GB growth patterns might be beneficial for preoperative risk evaluation and estimation of prognosis.

Diffusion tensor imaging suggests extrapontine extension of pediatric diffuse intrinsic pontine gliomas

PURPOSE

To apply DTI to detect early extrapontine extension of pediatric diffuse intrinsic pontine glioma along the corticospinal tracts.

METHODS

In children with diffuse intrinsic pontine glioma, low-grade brainstem glioma, and age-matched controls, DTI metrics were measured in the posterior limb of the internal capsule and posterior centrum semiovale. Histological examination was available in one patient.

RESULTS

6 diffuse intrinsic pontine glioma, 8 low-grade brainstem glioma, and two groups of 25 controls were included. In diffuse intrinsic pontine glioma compared to controls, fractional anisotropy was lower in the bilateral posterior limb of the internal capsule, axial diffusivity was lower in the bilateral posterior centrum semiovale and posterior limb of the internal capsule, while radial diffusivity was higher in the bilateral posterior limb of the internal capsule. No significant differences were found between low-grade brainstem glioma and controls. In diffuse intrinsic pontine glioma compared to low-grade brainstem glioma, axial diffusivity was lower in the bilateral posterior limb of the internal capsule. Histological examination in one child showed tumor cells in the posterior limb of the internal capsule.

CONCLUSION

Reduction in fractional anisotropy and axial diffusivity and increase in radial diffusivity in diffuse intrinsic pontine glioma may reflect tumor extension along the corticospinal tracts as shown by histology. DTI may detect early extrapontine tumor extension in diffuse intrinsic pontine glioma before it becomes apparent on conventional MRI sequences.

Brain maturation in neonatal rodents is impeded by sevoflurane anesthesia

BACKGROUND

A wealth of data shows neuronal demise after general anesthesia in the very young rodent brain. Herein, the authors apply proton magnetic resonance spectroscopy (1HMRS), testing the hypothesis that neurotoxic exposure during peak synaptogenesis can be tracked via changes in neuronal metabolites.

METHODS

1HMRS spectra were acquired in the brain (thalamus) of neonatal rat pups 24 and 48 h after sevoflurane exposure on postnatal day (PND) 7 and 15 and in unexposed, sham controls. A repeated measure ANOVA was performed to examine whether changes in metabolites were different between exposed and unexposed groups. Sevoflurane-induced neurotoxicity on PND7 was confirmed by immunohistochemistry.

RESULTS

In unexposed PND7 pups (N = 21), concentration of N-acetylaspartate (NAA; [NAA]) increased by 16% from PND8 to PND9, whereas in exposed PND7 pups (N = 19), [NAA] did not change and concentration of glycerophosphorylcholine and phosphorylcholine ([GPC + PCh]) decreased by 25%. In PND15 rats, [NAA] increased from PND16 to PND17 for both the exposed (N = 14) and the unexposed (N = 16) groups. Two-way ANOVA for PND7 pups demonstrated that changes over time observed in [NAA] (P = 0.031) and [GPC + PCh] (P = 0.024) were different between those two groups.

CONCLUSIONS

The authors demonstrated that normal [NAA] increase from PND8 to PND9 was impeded in sevoflurane-exposed rats when exposed at PND7; however, not impeded when exposed on PND15. Furthermore, the authors showed that noninvasive 1HMRS is sufficiently sensitive to detect subtle differences in developmental time trajectory of [NAA]. This is potentially clinically relevant because 1HMRS can be applied across species and may be useful in providing evidence of neurotoxicity in the human neonatal brain.

Intratumoral heterogeneity in glioblastoma: don't forget the peritumoral brain zone

Glioblastoma (GB) is the most frequent and aggressive primary tumor of the central nervous system. Prognosis remains poor despite ongoing progress. In cases where the gadolinium-enhanced portion of the GB is completely resected, 90% of recurrences occur at the margin of surgical resection in the macroscopically normal peritumoral brain zone (PBZ). Intratumoral heterogeneity in GB is currently a hot topic in neuro-oncology, and the GB PBZ may be involved in this phenomenon. Indeed, this region, which possesses specific properties, has been less studied than the core of the GB tumor. The high rate of local recurrence in the PBZ and the limited success of targeted therapies against GB demonstrate the need for a better understanding of the PBZ. We present here a review of the literature on the GB PBZ, focusing on its radiological, cellular, and molecular characteristics. We discuss how intraoperative analysis of the PBZ is important for the optimization of surgical resection and the development of targeted therapies against GB.

Evaluating the Possibility of Defining Cut-Off Points for ΔFA% in Order to Differentiate Four Major Types of Peri-Tumoral White Matter Tract Involvement

BACKGROUND

Diffusion tensor imaging (DTI) and its different scalar values such as fractional anisotropy (FA) have recently been used for evaluation of peri-tumoral white matter (WM) involvement to help define safer surgical excision margins.

OBJECTIVES

The purpose of this study is to evaluate the possibility of defining diagnostic cut-off points for differentiating four major types of peri-tumoral WM involvement using FA.

PATIENTS AND METHODS

DTI was performed in 12 patients with high presumption of having brain tumors, on a 1.5 T MRI scanner. DTI data was processed by MedINRIA software. Two-hundred region of interests (ROI) were evaluated: 100 in the lesion zone and the rest in the normal WM in the contralateral hemisphere. FA value related to each ROI was measured, and the percentage of FA decrement (ΔFAs%) was calculated.

RESULTS

Of the 100 ROIs on the lesion side, 74 were related to high-grade lesions, 23 to low-grade ones, and three to "gliosis". There were 54 "infiltrated", 22 "displaced", 15 "disrupted", and 9 "edematous" tracts. The major type of fiber involvement, both in low-grade and high-grade tumors was "infiltrated, whereas "edematous" fibers comprised the minority. ΔFA% was more than -35 for "displaced" and "edematous" fibers, and less than -35 for the majority of "disrupted" ones, but "infiltrated" fibers had scattered distribution. Mean ΔFA% was the least for "disrupted", followed by "infiltrated", "edematous" and "displaced" parts.

CONCLUSION

Introducing definite diagnostic cut-points was not possible, due to overlap. Based on the fact that "disruption" is the most aggressive process, a sensitivity analysis was carried out for "disrupted" fibers for several presumptive cut-off points.

[Towards more precision in the therapy of brain tumors. Possibilities and limits of MRI]

Due to the introduction of advanced functional and spectroscopic magnetic resonance (MR) sequences, MR imaging has gained significant importance in neuro-oncology. In contrast to recent years when neuro-oncological imaging was mostly limited to contrast-enhanced T1-weighted images, advanced MR methods provide direct visualization and assessment of tumor pathophysiology. This article summarizes the most relevant MR methods for neuro-oncological imaging and highlights the pathophysiological background as well as potential clinical applications. Ultimately, this article gives a glimpse into the future and introduces potential applications of ultra-high field MRI.

Diffusion-weighted MRI as a biomarker for treatment response in glioma

Diffusion-weighted imaging (DWI) is a powerful MRI method, which probes abnormalities of tissue structure by detecting microscopic changes in water mobility at a cellular level beyond what is available with other imaging techniques. Accordingly, DWI has the potential to identify pathology before gross anatomic changes are evident on standard anatomical brain images. These features of tissue characterization and earlier detection are what make DWI particularly appealing for the evaluation of gliomas and the newer therapies where standard anatomical imaging is proving insufficient. This article focuses on the basic principles and applications of DWI, and its derived parameter, the apparent diffusion coefficient, for the purposes of diagnosis and evaluation of glioma, especially in the context of monitoring response to therapy.

Meta-analysis of diffusion metrics for the prediction of tumor grade in gliomas

BACKGROUND AND PURPOSE

Diffusion tensor metrics are potential in vivo quantitative neuroimaging biomarkers for the characterization of brain tumor subtype. This meta-analysis analyzes the ability of mean diffusivity and fractional anisotropy to distinguish low-grade from high-grade gliomas in the identifiable tumor core and the region of peripheral edema.

MATERIALS AND METHODS

A meta-analysis of articles with mean diffusivity and fractional anisotropy data for World Health Organization low-grade (I, II) and high-grade (III, IV) gliomas, between 2000 and 2013, was performed. Pooled data were analyzed by using the odds ratio and mean difference. Receiver operating characteristic analysis was performed for patient-level data.

RESULTS

The minimum mean diffusivity of high-grade gliomas was decreased compared with low-grade gliomas. High-grade gliomas had decreased average mean diffusivity values compared with low-grade gliomas in the tumor core and increased average mean diffusivity values in the peripheral region. High-grade gliomas had increased FA values compared with low-grade gliomas in the tumor core, decreased values in the peripheral region, and a decreased fractional anisotropy difference between the tumor core and peripheral region.

CONCLUSIONS

The minimum mean diffusivity differs significantly with respect to the World Health Organization grade of gliomas. Statistically significant effects of tumor grade on average mean diffusivity and fractional anisotropy were observed, supporting the concept that high-grade tumors are more destructive and infiltrative than low-grade tumors. Considerable heterogeneity within the literature may be due to systematic factors in addition to underlying lesion heterogeneity.

Clinical use of diffusion tensor image-merged functional neuronavigation for brain tumor surgeries: review of preoperative, intraoperative, and postoperative data for 123 cases

PURPOSE

To achieve maximal safe resection during brain tumor surgery, functional image-merged neuronavigation is widely used. We retrospectively reviewed our cases in which diffusion tensor image (DTI)-merged functional neuronavigation was performed during surgery.

MATERIALS AND METHODS

Between November 2008 and May 2010, 123 patients underwent surgery utilizing DTI-merged neuronavigation. Anatomical magnetic resonance images (MRI) were obtained preoperatively and fused with DTI of major white matter tracts, such as the corticospinal tract, optic radiation, or arcuate fasciculus. We used this fused image for functional neuronavigation during brain tumor surgery of eloquent areas. We checked the DTI images together with postoperative MRI images and evaluated the integrity of white matter tracts.

RESULTS

A single white matter tract was inspected in 78 patients, and two or more white matter tracts were checked in 45 patients. Among the 123 patients, a grossly total resection was achieved in 90 patients (73.2%), subtotal resection in 29 patients (23.6%), and partial resection in 4 patients (3.3%). Postoperative neurologic outcomes, compared with preoperative function, included the following: 100 patients (81.3%) displayed improvement of neurologic symptoms or no change, 7 patients (5.7%) experienced postoperative permanent neurologic deterioration (additional or aggravated neurologic symptoms), and 16 patients (13.0%) demonstrated transient worsening.

CONCLUSION

DTI-merged functional neuronavigation could be a useful tool in brain tumor surgery for maximal safe resection. However, there are still limitations, including white matter tract shift, during surgery and in DTI itself. Further studies should be conducted to overcome these limitations.

Characterizing invading glioma cells based on IDH1-R132H and Ki-67 immunofluorescence

Glioma, the most common primary brain tumor, is characterized by proliferative-invasive growth. However, the detailed biological characteristics of invading glioma cells remain to be elucidated. A monoclonal antibody (clone HMab-1) that specifically and sensitively recognizes the isocitrate dehydrogenase-1 (IDH1) protein carrying the R132H mutation can identify invading glioma cells by immunostaining. To investigate the degree of invasion in gliomas of distinct grades and the proliferative capacity of the invading cells, immunofluorescent staining was conducted using antibodies against IDH1-R132H and Ki-67 on 11 surgical and autopsy specimens of the tumor core and the invading area. Higher numbers of IDH1-R132H-positive cells in the invading area correlated with a higher tumor grade. Double staining for IDH1-R132H and Ki-67 demonstrated that most invading cells that expressed IDH1-R132H were not stained by the Ki-67 antibody, and the ratio of Ki-67-positive cells among IDH1-R132H-positive cells was significantly lower in the invasion area than in the tumor core in all grades of glioma. These data suggest that higher grade gliomas have a greater invasive potential and that invading cells possess low proliferative capacity.

Nonlinear distortion correction of diffusion MR images improves quantitative DTI measurements in glioblastoma

The purpose of this study was to use a retrospective nonlinear distortion correction technique and evaluate the changes in DTI metrics in areas of interest in and around GBM tumors. A total of 24 histologically confirmed GBM patients with pre-operative 20-direction DTI scans were examined. Variability in apparent diffusion coefficient (ADC) and fractional anisotropy (FA) in normal tissue before and after distortion correction were examined. Changes in mean, median and variance of ADC and FA in contrast enhancing and T2/FLAIR ROIs were also examined with and without distortion correction. Results suggest the intra-subject SDs of ADC and FA decreased in normal tissue after the application of distortion correction (P < 0.0001). FA mean and median values decreased after distortion correction in both T1+C and T2 ROIs (P < 0.017), while ADC mean and median values did not significantly change except for the median ADC in T1+C ROIs (P = 0.0054). The intra-subject SD of ADC and FA values in tumor ROIs changed significantly with distortion correction, and Bland-Altman analysis indicated that the bias and the SD of the bias of these intra-subject SDs were larger than those of the mean and median terms. Additionally, the means of the two curves of a double Gaussian fit to the histogram of ADC values from T1+C ROIs, ADCL (mean of lower Gaussian) as well as ADCH (mean of the higher Gaussian) were found to change significantly with distortion correction (P = 0.0045 for ADCL and P = 0.0370 for ADCH). Nonlinear distortion correction better aligns neuro-anatomical structures between DTI and anatomical scans, and significantly alters the measurement of values within tumor ROIs for GBM patients.

Utility of diffusion tensor imaging in evaluation of the peritumoral region in patients with primary and metastatic brain tumors

In the brain, diffusion tensor imaging is a useful tool for defining white matter anatomy, planning a surgical approach to space-occupying lesions, and characterizing tumors, including distinguishing primary tumors from metastases. Recent studies have attempted, with varying success, to use DTI to define the extent of tumor microinfiltration beyond the apparent borders on T2-weighted imaging. In the present review, we discuss the current state of research on the utility of DTI for evaluating the peritumoral region of brain tumors.

Visualizing non-Gaussian diffusion: clinical application of q-space imaging and diffusional kurtosis imaging of the brain and spine

Recently, non-Gaussian diffusion-weighted imaging (DWI) techniques, including q-space imaging (QSI) and diffusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diffusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., specific diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diffusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diffusion coefficient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diffusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting differences from conventional diffusional metrics.

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.

High level of miR-221/222 confers increased cell invasion and poor prognosis in glioma

Background

MiR-221 and miR-222 (miR-221/222), upregulated in gliomas, can regulate glioma cell cycle progression and apoptosis, respectively. However, the association of miR-221/222 with glioma cell invasion and survival remains unknown.

Methods

Invasion capability of miR-221/222 was detected by mutiple analyses, including diffusion tensor imaging (DTI), transwell, wound healing and nude mouse tumor xenograft model assay. Further, the target of miR-221/222 was determined by luciferase reporter, western blot and gene rescue assay. The association of miR-221/222 with outcome was examined in fifty glioma patients.

Results

MiR-221/222 expression was significantly increased in high-grade gliomas compared with low-grade gliomas, and positively correlated with the degree of glioma infiltration. Over-expression of miR-221/222 increased cell invasion, whereas knockdown of miR-221/222 decreased cell invasion via modulating the levels of the target, TIMP3. Introduction of a TIMP3 cDNA lacking 3’ UTR abrogated miR-221/222-induced cell invasion. In addition, knockdown of miR-221/222 increased TIMP3 expression and considerably inhibited tumor growth in a xenograft model. Finally, the increased level of miR-221/222 expression in high-grade gliomas confers poorer overall survival.

Conclusions

The present data indicate that miR-221 and miR-222 directly regulate cell invasion by targeting TIMP3 and act as prognostic factors for glioma patients.

[Imaging of lateral ventricle tumors]

Lateral ventricular neoplasms are rare, and account for 50% of all intraventricular tumors in adults and 25% in children. Although these neoplasms are easily detected with computed tomography (CT) and magnetic resonance imaging (MRI), both techniques are relatively unspecific in identifying the type of tumor. However, few imaging patterns are specific for a particular pathological process and useful conclusions can be made from the morphological appearance of the lesion, its location and enhancement pattern. The aim of this article was to review and illustrate the CT and MRI findings of a wide spectrum of tumors of the lateral ventricle. We reviewed choroid plexus tumors, meningioma, subependymal giant cell astrocytoma, central neurocytoma, and less frequent lesion such as lymphoma and metastases.