Signal intensity in T2' magnetic resonance imaging is related to brain glioma grade

The value of Synthetic MRI in discriminating metastatic and non-metastatic lymph nodes in head and neck squamous cell carcinoma, compared with DWI and subjective experience

OBJECTIVES

To explore the role of Synthetic MRI (SyMRI) histogram parameters in differentiating metastatic from non-metastatic cervical lymph nodes (LNs) in head and neck squamous cell carcinoma (HNSCC) patients, and construct a practical model.

METHODS

A total of 149 pathologically confirmed LNs (metastatic LNs: 58, non-metastatic LNs: 91) were included in the study. LNs were stratified and randomly divided into a training set and an independent validation set in a ratio of 7:3. Histogram parameters derived from SyMRI, ADC values, and the short and long diameters of each LN were obtained. Significantly different parameters between metastatic and non-metastatic LNs were selected in the training set, and logistic regression analysis was adopted to construct different models. ROC analysis and AUC were performed to assess the diagnostic performance of different models and subjective analysis.

RESULTS

The AUCs of the three models were 0.882 (SyMRI_model), 0.755 (DWI), and 0.952 (Combined_model) in the validation set. The Combined_model, constructed based on SyMRI, ADC values, and size, had the highest diagnostic potency in both training and validation sets, with an accuracy of 0.905 and 0.864 in the two sets, respectively. The diagnostic performance of the Combined_model was superior to multi-radiologists' subjective experience, not only in LNs from validation set (AUC: 0.952 vs. 0.705 ∼ 0.845) but also in the cohort of sub-centimeter LNs (AUC: 0.878 vs. 0.429 ∼ 0.628) (all P < 0.001).

CONCLUSION

Histogram parameters derived from SyMRI are feasible in discriminating metastatic from non-metastatic cervical LNs in HNSCC, and the diagnostic efficacy is optimal when combined with DWI and size.

Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review

PURPOSE

There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated.

METHODS

Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author.

RESULTS

A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease.

CONCLUSION

A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.

Magnetic resonance relaxometry in quantitative imaging of brain gliomas: A literature review

Magnetic resonance (MR) relaxometry is a quantitative imaging method that measures tissue relaxation properties. This review discusses the state of the art of clinical proton MR relaxometry for glial brain tumors. Current MR relaxometry technology also includes MR fingerprinting and synthetic MRI, which solve the inefficiencies and challenges of earlier techniques. Despite mixed results regarding its capability for brain tumor differential diagnosis, there is growing evidence that MR relaxometry can differentiate between gliomas and metastases and between glioma grades. Studies of the peritumoral zones have demonstrated their heterogeneity and possible directions of tumor infiltration. In addition, relaxometry offers T2* mapping that can define areas of tissue hypoxia not discriminated by perfusion assessment. Studies of tumor therapy response have demonstrated an association between survival and progression terms and dynamics of native and contrast-enhanced tumor relaxometric profiles. In conclusion, MR relaxometry is a promising technique for glial tumor diagnosis, particularly in association with neuropathological studies and other imaging techniques.

Radiomic profiling for insular diffuse glioma stratification with distinct biologic pathway activities

Current literature emphasizes surgical complexities and customized resection for managing insular gliomas; however, radiogenomic investigations into prognostic radiomic traits remain limited. We aimed to develop and validate a radiomic model using multiparametric magnetic resonance imaging (MRI) for prognostic prediction and to reveal the underlying biological mechanisms. Radiomic features from preoperative MRI were utilized to develop and validate a radiomic risk signature (RRS) for insular gliomas, validated through paired MRI and RNA-seq data (N = 39), to identify core pathways underlying the RRS and individual prognostic radiomic features. An 18-feature-based RRS was established for overall survival (OS) prediction. Gene set enrichment analysis (GSEA) and weighted gene coexpression network analysis (WGCNA) were used to identify intersectional pathways. In total, 364 patients with insular gliomas (training set, N = 295; validation set, N = 69) were enrolled. RRS was significantly associated with insular glioma OS (log-rank p = 0.00058; HR = 3.595, 95% CI:1.636-7.898) in the validation set. The radiomic-pathological-clinical model (R-P-CM) displayed enhanced reliability and accuracy in prognostic prediction. The radiogenomic analysis revealed 322 intersectional pathways through GSEA and WGCNA fusion; 13 prognostic radiomic features were significantly correlated with these intersectional pathways. The RRS demonstrated independent predictive value for insular glioma prognosis compared with established clinical and pathological profiles. The biological basis for prognostic radiomic indicators includes immune, proliferative, migratory, metabolic, and cellular biological function-related pathways.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Joint radial trajectory correction for accelerated T2 * mapping on an MR-Linac

BACKGROUND

T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes.

PURPOSE

The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac).

MATERIALS AND METHODS

The proposed method was validated in a numerical phantom, where two T2 * mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2 * maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T2 * maps reconstructed, with and without trajectory corrections were compared.

RESULTS

Numerical simulations demonstrated that, for all noise levels, T2 * maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32 ms, respectively, which reduced to 10.92 and 5.89 ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90 ms, respectively, which reduced to 9.10 and 5.40 ms for gradient delay [1, 2]. For in vivo data, T2 * maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV).

CONCLUSION

Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2 * maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.

T 2 ' mapping of the brain from water-unsuppressed 1 H-MRSI and turbo spin-echo data

PURPOSE

To obtain high-quality T 2 ' $$ {\mathrm{T}}_2^{\prime } $$ maps of brain tissues from water-unsuppressed magnetic resonance spectroscopic imaging (MRSI) and turbo spin-echo (TSE) data.

METHODS

T 2 ' $$ {\mathrm{T}}_2^{\prime } $$ mapping can be achieved using T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping from water-unsuppressed MRSI data and T 2 $$ {\mathrm{T}}_2 $$ mapping from TSE data. However, T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping often suffers from signal dephasing and distortions caused by B 0 $$ {\mathrm{B}}_0 $$ field inhomogeneity; T 2 $$ {\mathrm{T}}_2 $$ measurements may be biased due to system imperfections, especially for T 2 $$ {\mathrm{T}}_2 $$ -weighted image with small number of TEs. In this work, we corrected the B 0 $$ {\mathrm{B}}_0 $$ field inhomogeneity effect on T 2 * $$ {\mathrm{T}}_2^{\ast } $$ mapping using a subspace model-based method, incorporating pre-learned spectral basis functions of the water signals. T 2 $$ {\mathrm{T}}_2 $$ estimation bias was corrected using a TE-adjustment method, which modeled the deviation between measured and reference T 2 $$ {\mathrm{T}}_2 $$ decays as TE shifts.

RESULTS

In vivo experiments were performed to evaluate the performance of the proposed method. High-quality T 2 * $$ {\mathrm{T}}_2^{\ast } $$ maps were obtained in the presence of large field inhomogeneity in the prefrontal cortex. Bias in T 2 $$ {\mathrm{T}}_2 $$ measurements obtained from TSE data was effectively reduced. Based on the T 2 * $$ {\mathrm{T}}_2^{\ast } $$ and T 2 $$ {\mathrm{T}}_2 $$ measurements produced by the proposed method, high-quality T 2 ' $$ {\mathrm{T}}_2^{\prime } $$ maps were obtained, along with neurometabolite maps, from MRSI and TSE data that were acquired in about 9 min. The results obtained from acute stroke and glioma patients demonstrated the feasibility of the proposed method in the clinical setting.

CONCLUSIONS

High-quality T 2 ' $$ {\mathrm{T}}_2^{\prime } $$ maps can be obtained from water-unsuppressed ¹ H-MRSI and TSE data using the proposed method. With further development, this method may lay a foundation for simultaneously imaging oxygenation and neurometabolic alterations of brain disorders.

Cerebral oxygen extraction fraction MRI: Techniques and applications

The human brain constitutes 2% of the body's total mass but uses 20% of the oxygen. The rate of the brain's oxygen utilization can be derived from a knowledge of cerebral blood flow and the oxygen extraction fraction (OEF). Therefore, OEF is a key physiological parameter of the brain's function and metabolism. OEF has been suggested to be a useful biomarker in a number of brain diseases. With recent advances in MRI techniques, several MRI-based methods have been developed to measure OEF in the human brain. These MRI OEF techniques are based on the T₂ of blood, the blood signal phase, the magnetic susceptibility of blood-containing voxels, the effect of deoxyhemoglobin on signal behavior in extravascular tissue, and the calibration of the BOLD signal using gas inhalation. Compared to ¹⁵ O PET, which is considered the "gold standard" for OEF measurement, MRI-based techniques are non-invasive, radiation-free, and are more widely available. This article provides a review of these emerging MRI-based OEF techniques. We first briefly introduce the role of OEF in brain oxygen homeostasis. We then review the methodological aspects of different categories of MRI OEF techniques, including their signal mechanisms, acquisition methods, and data analyses. The strengths and limitations of the techniques are discussed. Finally, we review key applications of these techniques in physiological and pathological conditions.

Investigated diagnostic value of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling and diffusion-weighted imaging in the grading of glioma

BACKGROUND

To investigate the performance of synthetic relaxometry, three-dimensional pseudo-continuous arterial spin labelling (pCASL) and diffusion-weighted imaging (DWI) in differentiating high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and to compare with the conventional MRI.

METHODS

Seventy-two patients with gliomas (including 27 LGGs and 45 HGGs) were studied using synthetic magnetic resonance imaging (sy-MRI), pCASL, and DWI with a 3.0 T MR scanner. T1 relaxometry (T1), T2 relaxometry (T2), as well as proton density (PD) from sy-MRI, cerebral blood flow (CBF) from pCASL, apparent diffusion coefficient (ADC) from DWI and enhancement quality (EQ), proportion enhancing (PE) from conventional contrast enhanced image based Visually-Accessible-Rembrandt-Images (VASARI) scoring system, were all analyzed by two radiologists. The Student's t-test, Mann-Whitney U test or Fisher's exact test was used to compare the parameters between LGGs and HGGs. The diagnostic performance of each parameter and their combination for glioma grading were analyzed.

RESULTS

Significant statistical differences in T1, PD, CBF, ADC, EQ and PE are observed between LGGs and HGGs (all P < 0.001). The ADC values have higher discrimination abilities compared with other univariable parameters, with the AUC of 0.905. AUC values for conventional contrast-enhanced method, EQ and PE from VASARI, and conventional contrast-free method, CBF + ADC, are 0.873 and 0.912 respectively. The combined T1, PD, CBF and ADC model had the best performance for differentiating LGGs and HGGs with AUC, sensitivity and specificity of 0.993, 95.5%, 100%, respectively.

CONCLUSIONS

Relaxometry parameters derived from synthetic MRI contributed to the discrimination of low-grade gliomas from high-grade gliomas. Proposed contrast-free approach combining T1, PD, CBF and ADC showed a strong discriminative power, and outperformed conventional approaches.

Gadolinium is not necessary for surveillance MR imaging in children with chiasmatic-hypothalamic low-grade glioma

BACKGROUND

Patients with chiasmatic-hypothalamic low-grade glioma (CHLGG) have frequent MRIs with gadolinium-based contrast agents (GBCA) for disease monitoring. Cumulative gadolinium deposition in the brains of children is a potential concern. The purpose of this study is to evaluate whether MRI with GBCA is necessary for determining radiographic tumor progression in children with CHLGG.

METHODS

Children who were treated for progressive CHLGG from 2005 to 2019 at Texas Children's Cancer Center were identified. Pre- and post-contrast MRI sequences were separately reviewed by one neuroradiologist who was blinded to the clinical course. Three dimensional measurements and tumor characteristics were evaluated. Radiographic progression was defined as a 25% increase in size (product of two largest dimensions) compared with baseline or best response after initiation of therapy.

RESULTS

A total of 28 patients with progressive CHLGG were identified with a total of 683 MRIs with GBCA reviewed (mean 24 MRIs/patient; range, 11-43 MRIs). Radiographic progression was observed 92 times, 91 (99%) on noncontrast and 90 (98%) on contrast imaging. Sixty-seven progressions necessitating management changes were identified in all (100%) noncontrast sequences and 66 (99%) contrast sequences. Tumor growth > 2 mm in any dimension was identified in 184/187 (98%) noncontrast and 181/187 (97%) with contrast imaging. Metastatic tumors were better visualized on contrast imaging in 4/7 (57%).

CONCLUSION

MRI without GBCA effectively identifies patients with progressive disease. When imaging children with CHLGG, eliminating GBCA should be considered unless monitoring patients with metastatic disease.

Can R2 ' mapping evaluate hypoxia in renal ischemia reperfusion injury quantitatively? An experimental study

PURPOSE

To explore if R₂ ' mapping can assess renal hypoxia in rabbits with ischemia reperfusion injury (IRI).

METHODS

Forty rabbits were randomly divided into 4 groups according to the clipping time: the sham group and 45 min, 60 min, and 75 min for the mild, moderate, and severe groups (with n = 10 each group), respectively. Intravenous furosemide (FU) was administered 24 h after IRI. All rabbits were performed 5 times (IRI_pre , IRI_24h , FU_5min , FU_12min , and FU_24min ) with a 3.0 Tesla MR. The R₂ ' values and the hypoxic scores were then recorded. The repeated measurement analysis of variance and Spearman correlation analysis was used for statistical analysis.

RESULTS

Compared to the baseline, the medullary R₂ ' values increased significantly 24 h after the IRI (baseline 19.31 ± 1.21 s^-1 , mild group 20.05 ± 1.26 s^-1 , moderate group 25.38 ± 1.38 s^-1 , and severe group 25.79 ± 1.10 s^-1 ; each P < .001). FU led to a significant decrease in the medullary R₂ ' value (sham group 11.17 ± 4.33 s^-1 , mild group 7.80 ± 0.74 s^-1 , moderate group 3.92 ± 0.28 s^-1 , and severe group 3.82 ± 0.23 s^-1 ; each P < .05). Quantitative hypoxic scores revealed significant differences among the 4 groups in the outer medulla (P < .001 each). The medullary R₂ ' differences (before and after intravenous FU) were significantly correlated with the hypoxic scores, respectively (P < .001).

CONCLUSION

R₂ ' mapping can evaluate the renal hypoxia in the procession of IRI in rabbits and might serve as a quantitative biomarker for IRI.

Quantitative MRI for analysis of peritumoral edema in malignant gliomas

Background and purpose

Damage to the blood-brain barrier with subsequent contrast enhancement is a hallmark of glioblastoma. Non-enhancing tumor invasion into the peritumoral edema is, however, not usually visible on conventional magnetic resonance imaging. New quantitative techniques using relaxometry offer additional information about tissue properties. The aim of this study was to evaluate longitudinal relaxation R₁, transverse relaxation R₂, and proton density in the peritumoral edema in a group of patients with malignant glioma before surgery to assess whether relaxometry can detect changes not visible on conventional images.

Methods

In a prospective study, 24 patients with suspected malignant glioma were examined before surgery. A standard MRI protocol was used with the addition of a quantitative MR method (MAGIC), which measured R₁, R₂, and proton density. The diagnosis of malignant glioma was confirmed after biopsy/surgery. In 19 patients synthetic MR images were then created from the MAGIC scan, and ROIs were placed in the peritumoral edema to obtain the quantitative values. Dynamic susceptibility contrast perfusion was used to obtain cerebral blood volume (rCBV) data of the peritumoral edema. Voxel-based statistical analysis was performed using a mixed linear model.

Results

R₁, R₂, and rCBV decrease with increasing distance from the contrast-enhancing part of the tumor. There is a significant increase in R₁ gradient after contrast agent injection (P < .0001). There is a heterogeneous pattern of relaxation values in the peritumoral edema adjacent to the contrast-enhancing part of the tumor.

Conclusion

Quantitative analysis with relaxometry of peritumoral edema in malignant gliomas detects tissue changes not visualized on conventional MR images. The finding of decreasing R₁ and R₂ means shorter relaxation times closer to the tumor, which could reflect tumor invasion into the peritumoral edema. However, these findings need to be validated in the future.

Improved visibility of brain tumors in synthetic MP-RAGE anatomies with pure T1 weighting

Conventional MRI for brain tumor diagnosis employs T2 -weighted and contrast-enhanced T1 -weighted sequences. Non-enhanced T1 -weighted images provide improved anatomical details for precise tumor location, but reduced tumor-to-background contrast as elevated T1 and proton density (PD) values in tumor tissue affect the signal inversely. Radiofrequency (RF) coil inhomogeneities may further mask tumor and edema outlines. To overcome this problem, the aims of this work were to employ quantitative MRI techniques to create purely T1 -weighted synthetic anatomies which can be expected to yield improved tissue and tumor-to-background contrasts, to compare the quality of conventional and synthetic anatomies, and to investigate optical contrast and visibility of brain tumors and edema in synthetic anatomies. Conventional magnetization-prepared rapid acquisition of gradient echoes (MP-RAGE) anatomies and maps of T1 , PD and RF coil profiles were acquired in comparable and clinically feasible times. Three synthetic MP-RAGE anatomies (PD T1 weighting both with and without RF bias; pure T1 weighting) were calculated for healthy subjects and 32 patients with brain tumors. In healthy subjects, the PD T1 -weighted synthetic anatomies with RF bias precisely matched the conventional anatomies, yielding high signal-to-noise (SNR) and contrast-to-noise (CNR) ratios. Pure T1 weighting yielded lower SNR, but high CNR, because of increased optical contrasts. In patients with brain tumors, synthetic anatomies with pure T1 weighting yielded significant increases in optical contrast and improved visibility of tumor and edema in comparison with anatomies reflecting conventional T1 contrasts. In summary, the optimized purely T1 -weighted synthetic anatomy with an isotropic resolution of 1 mm, as proposed in this work, considerably enhances optical contrast and visibility of brain tumors and edema.

Quantitative T2 mapping of recurrent glioblastoma under bevacizumab improves monitoring for non-enhancing tumor progression and predicts overall survival

BACKGROUND

Anti-angiogenic treatment in recurrent glioblastoma patients suppresses contrast enhancement and reduces vasogenic edema while non-enhancing tumor progression is common. Thus, the importance of T2-weighted imaging is increasing. We therefore quantified T2 relaxation times, which are the basis for the image contrast on T2-weighted images.

METHODS

Conventional and quantitative MRI procedures were performed on 18 patients with recurrent glioblastoma before treatment with bevacizumab and every 8 weeks thereafter until further tumor progression. We segmented the tumor on conventional MRI into 3 subvolumes: enhancing tumor, non-enhancing tumor, and edema. Using coregistered quantitative maps, we followed changes in T2 relaxation time in each subvolume. Moreover, we generated differential T2 maps by a voxelwise subtraction using the first T2 map under bevacizumab as reference.

RESULTS

Visually segmented areas of tumor and edema did not differ in T2 relaxation times. Non-enhancing tumor volume did not decrease after commencement of bevacizumab treatment but strikingly increased at progression. Differential T2 maps clearly showed non-enhancing tumor progression in previously normal brain. T2 relaxation times decreased under bevacizumab without re-increasing at tumor progression. A decrease of <26 ms in the enhancing tumor following exposure to bevacizumab was associated with longer overall survival.

CONCLUSIONS

Combining quantitative MRI and tumor segmentation improves monitoring of glioblastoma patients under bevacizumab. The degree of change in T2 relaxation time under bevacizumab may be an early response parameter predictive of overall survival. The sustained decrease in T2 relaxation times toward values of healthy tissue masks progressive tumor on conventional T2-weighted images. Therefore, quantitative T2 relaxation times may detect non-enhancing progression better than conventional T2-weighted imaging.

MR-based hypoxia measures in human glioma

Hypoxia plays a central role in tumor stem cell genesis and is related to a more malignant tumor phenotype, therapy resistance (e.g. in anti-angiogenic therapies) and radio-insensitivity. Reliable hypoxia imaging would provide crucial metabolic information in the diagnostic work-up of brain tumors. In this study, we applied a novel BOLD-based MRI method for the measurement of relative oxygen extraction fraction (rOEF) in glioma patients and investigated potential benefits and drawbacks. Forty-five glioma patients were examined preoperatively in a pilot study on a 3T MR scanner. rOEF was calculated from quantitative transverse relaxation rates (T2, T2*) and cerebral blood volume (CBV) using a quantitative BOLD approach. rOEF maps were assessed visually and by means of a volume of interest (VOI) analysis. In six cases, MRI-targeted biopsy samples were analyzed using HIF-1α-immunohistochemistry. rOEF maps could be obtained with a diagnostic quality. Focal spots with high rOEF values were observed in the majority of high-grade tumors but in none of the low-grade tumors. VOI analysis revealed potentially hypoxic tumor regions with high rOEF in contrast-enhancing tumor regions as well as in the non-enhancing infiltration zone. Systematic bias was found as a result of non-BOLD susceptibility effects (T2*) and contrast agent leakage affecting CBV. Histological samples demonstrated reasonable correspondence between MRI characteristics and HIF-1α-staining. The presented method of rOEF imaging is a promising tool for the metabolic characterization of human glioma. For the interpretation of rOEF maps, confounding factors must be considered, with a special focus on CBV measurements in the presence of contrast agent leakage. Further validation involving a bigger cohort and extended immuno-histochemical correlation is required.

Is T2* enough to assess oxygenation? Quantitative blood oxygen level-dependent analysis in brain tumor

PURPOSE

To analyze the contribution of the transverse relaxation parameter (T2), macroscopic field inhomogeneities (B0), and blood volume fraction (BVf) to blood oxygen level-dependent (BOLD)-based magnetic resonance (MR) measurements of blood oxygen saturation (SO2) obtained in a brain tumor model.

MATERIALS AND METHODS

This study was approved by the local committee for animal care and use. Experiments were performed in accordance with permit 380 820 from the French Ministry of Agriculture. The 9L gliosarcoma cells were implanted in the brain of eight rats. Fifteen days later, 4.7-T MR examinations were performed to estimate T2*, T2, BVf, and T2*ΔB0corrected in the tumor and contralateral regions. MR estimates of SO2 were derived by combining T2, BVf, and T2*ΔB0corrected according to a recently described quantitative BOLD approach. Scatterplots and linear regression analysis were used to identify correlation between parameters. Paired Student t tests were used to compare the tumor region with the contralateral region.

RESULTS

No significant correlations were found between T2* and any parameter in either tumor tissue or healthy tissue. T2* in the tumor and T2* in the uninvolved contralateral brain were the same (36 msec±4 [standard deviation] vs 36 msec±5, respectively), which might suggest similar oxygenation. Adding T2 information (98 msec±7 vs 68 msec±2, respectively) alone yields results that suggest apparent hypo-oxygenation of the tumor, while incorporating BVf (5.3%±0.6 vs 2.6%±0.3, respectively) alone yields results that suggest apparent hyperoxygenation. MR estimates of SO2 obtained with a complete quantitative BOLD analysis, although not correlated with T2* values, suggest normal oxygenation (68%±3 vs 65%±4, respectively). MR estimates of SO2 obtained in the contralateral tissue agree with previously reported values.

CONCLUSION

Additional measurements, such as BVf, T2, and B0, are needed to obtain reliable information on oxygenation with BOLD MR imaging. The proposed quantitative BOLD approach, which includes these measurements, appears to be a promising tool with which to map tumor oxygenation.

Bevacizumab impairs oxidative energy metabolism and shows antitumoral effects in recurrent glioblastomas: a 31P/1H MRSI and quantitative magnetic resonance imaging study

Bevacizumab shows unprecedented rates of response in recurrent glioblastomas (GBM), but the detailed mechanisms are still unclear. We employed in vivo magnetic resonance spectroscopic imaging (MRSI) and quantitative magnetic resonance imaging to investigate whether bevacizumab alters oxygen and energy metabolism and whether this effect has antitumoral activity in recurrent GBM. (31)P and (1)H MRSI, apparent diffusion coefficient (ADC), and high-resolution T2 and T2' mapping (indirect marker of oxygen extraction) were investigated in 16 patients with recurrent GBM at 3 Tesla before and 1.5-2 months after initiation of therapy with bevacizumab. Changes of metabolite concentrations and of the quantitative values in the tumor and normal appearing brain tissue were calculated. The Wilcoxon signed-ranks test was used to evaluate differences for tumor/edema versus control as well as changes before versus after commencement of therapy. Survival analyses were performed for significant parameters. Tumor T2', pH, ADC, and T2 decreased significantly in patients responding to bevacizumab therapy (n = 10). Patients with at least 25% T2' decrease during treatment showed longer progression-free and overall survival durations. Levels of high-energy metabolites were lower at baseline; these persisted under therapy. Glycerophosphoethanolamine as catabolic phospholipid metabolite increased in responders. The MRSI data support the hypothesis that bevacizumab induces relative tumor hypoxia (T2' decrease) and affects energy homeostasis in recurrent GBM, suggesting that bevacizumab impairs vascular function. The antiangiogenic effect of bevacizumab is predictive of better outcome and seems to induce antitumoral activity in the responding GBMs.

Multimodality assessment of brain tumors and tumor recurrence

Neuroimaging plays a significant role in the diagnosis of intracranial tumors, especially brain gliomas, and must consist of an assessment of location and extent of the tumor and of its biologic activity. Therefore, morphologic imaging modalities and functional, metabolic, or molecular imaging modalities should be combined for primary diagnosis and for following the course and evaluating therapeutic effects. MRI is the gold standard for providing detailed morphologic information and can supply some additional insights into metabolism (MR spectroscopy) and perfusion (perfusion-weighted imaging) but still has limitations in identifying tumor grade, invasive growth into neighboring tissue, and treatment-induced changes, as well as recurrences. These insights can be obtained by various PET modalities, including imaging of glucose metabolism, amino acid uptake, nucleoside uptake, and hypoxia. Diagnostic accuracy can benefit from coregistration of PET results and MRI, combining the high-resolution morphologic images with the biologic information. These procedures are optimized by the newly developed combination of PET and MRI modalities, permitting the simultaneous assessment of morphologic, functional, metabolic, and molecular information on the human brain.