Differentiation of glioblastoma multiforme and single brain metastasis by peak height and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging

Neuro-oncological disorders of the cerebellum

This article provides an overview of the intra-axial tumors that affect the cerebellum, which can be categorized by location and age. For each tumor, we review conventional neuroimaging findings and discuss the value of more advanced neuroimaging techniques. Current management strategies are also briefly discussed. Finally, cerebellar paraneoplastic disorders and medication-induced cerebellar disorders are discussed.

Glioblastoma treated with concurrent radiation therapy and temozolomide chemotherapy: differentiation of true progression from pseudoprogression with quantitative dynamic contrast-enhanced MR imaging

PURPOSE

To explore the role of dynamic contrast material-enhanced magnetic resonance (MR) imaging in the differentiation of true progression from pseudoprogression in patients with glioblastoma on the basis of findings in entirely newly developed or enlarged enhancing lesions after concurrent radiation therapy and chemotherapy with temozolomide and to evaluate the diagnostic performance of the quantitative pharmacokinetic parameters obtained at dynamic contrast-enhanced MR imaging, such as the volume transfer constant (K(trans)), the extravascular extracellular space per unit volume of tissue(ve), and the blood plasma volume per unit volume of tissue(vp).

MATERIALS AND METHODS

This prospective study had institutional review board approval; written informed consent was obtained from all patients. Thirty-three patients with histopathologically proven glioblastoma who had undergone concurrent radiation therapy and chemotherapy with temozolomide were included. Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans), ve, and vp, were calculated for newly developed or enlarged enhancing lesions. Pharmacokinetic parameters were compared between the true progression (n = 17) and pseudoprogression (n = 16) groups by using unpaired t tests and then multivariable analysis.

RESULTS

The mean K(trans) and ve were higher in the true progression group than in the pseudoprogression group (mean K(trans), 0.44 min(-1) ± 0.25 [standard deviation] and 0.23 min(-1) ± 0.10 for true progression and pseudoprogression groups, respectively, P = .004; and mean ve, 1.26 ± 0.78 and 0.75 ± 0.49 for true progression and pseudoprogression groups, respectively, P = .034). Multivariable analysis showed that mean K(trans) was the only independently differentiating variable (P = .004).

CONCLUSION

Dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters, including K(trans) and ve, in the entire newly developed or enlarged enhancing lesion may be useful objective diagnostic tools in the differentiation of true progression from pseudoprogression in patients with glioblastoma who have undergone concurrent radiation therapy and chemotherapy with temozolomide.

Discrimination between glioblastoma multiforme and solitary metastasis using morphological features derived from the p:q tensor decomposition of diffusion tensor imaging

The management and treatment of high-grade glioblastoma multiforme (GBM) and solitary metastasis (MET) are very different and influence the prognosis and subsequent clinical outcomes. In the case of a solitary MET, diagnosis using conventional radiology can be equivocal. Currently, a definitive diagnosis is based on histopathological analysis on a biopsy sample. Here, we present a computerised decision support framework for discrimination between GBM and solitary MET using MRI, which includes: (i) a semi-automatic segmentation method based on diffusion tensor imaging; (ii) two-dimensional morphological feature extraction and selection; and (iii) a pattern recognition module for automated tumour classification. Ground truth was provided by histopathological analysis from pre-treatment stereotactic biopsy or at surgical resection. Our two-dimensional morphological analysis outperforms previous methods with high cross-validation accuracy of 97.9% and area under the receiver operating characteristic curve of 0.975 using a neural networks-based classifier.

Gradient of apparent diffusion coefficient values in peritumoral edema helps in differentiation of glioblastoma from solitary metastatic lesions

OBJECTIVE

Glioblastoma and solitary metastatic lesions can be difficult to differentiate with conventional MRI. The use of diffusion-weighted MRI to better characterize peritumoral edema has been explored for this purpose, but the results have been conflicting. The purpose of this study was to test the hypothesis that the gradient of apparent diffusion coefficient (ADC) values in peritumoral edema--that is, the difference in ADC values from the region closest to the enhancing tumor and the one closest to the normal-appearing white matter--may be a marker for differentiating glioblastoma from a metastatic lesion.

MATERIALS AND METHODS

Forty patients, 20 with glioblastoma and 20 with a solitary metastatic lesion, underwent diffusion-weighted brain MRI before surgical resection. The ADC values were retrospectively collected in the peritumoral edema in three positions: near, an intermediate distance from, and far from the core enhancing tumor (G1, G2, and G3). The ADC gradient in the peritumoral edema was calculated as the subtractions ADCG3 - ADCG1, ADCG3 - ADCG2, and ADCG2 - ADCG1. The ADC values in the enhancing tumor, peritumoral edema, ipsilateral normal-appearing white matter, contralateral healthy white matter, and CSF were also collected.

RESULTS

A gradient of ADC values was found in the peritumoral edema of glioblastoma. The ADC values increased from the region close to the enhancing tumor (1.36 ± 0.24 × 10(-3) mm(2)/s) to the area near the normal-appearing white matter (1.57 ± 0.34 × 10(-3) mm(2)/s). In metastatic lesions, however, those values were nearly homogeneous (p = 0.04).

CONCLUSION

The ADC gradient in peritumoral edema appears to be a promising tool for differentiating glioblastoma from a metastatic lesion.

Survival analysis in patients with newly diagnosed primary glioblastoma multiforme using pre- and post-treatment peritumoral perfusion imaging parameters

The objective of this study was to evaluate if peritumoral (PT) perfusion parameters obtained from dynamic susceptibility weighted contrast enhanced perfusion MRI can predict overall survival (OS) and progression free survival (PFS) in patients with newly diagnosed glioblastoma multiforme (GBM). Twenty-eight newly diagnosed GBM patients, who were treated with resection followed by concurrent chemoradiation and adjuvant chemotherapy, were included in this study. Evaluated perfusion parameters were pre- and post-treatment PT relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF). Proportional hazard analysis was used to assess the relationship OS, PFS and perfusion parameters. Kaplan-Meier survival estimates and log-rank test were used to characterize and compare the patient groups with high and low perfusion parameter values in terms of OS and PFS. Pretreatment PT rCBV and rCBF were not associated with OS and PFS whereas there was statistically significant association of both posttreatment PT rCBV and rCBF with OS and posttreatment rCBV with PFS (association of PFS and posttreatment rCBF was not statistically significant). Neither the Kaplan-Meier survival estimates nor the log-rank test demonstrated any differences in OS between high and low pretreatment PT rCBV values and rCBF values; however, high and low post-treatment PT rCBV and rCBF values did demonstrate statistically significant difference in OS and PFS. Our study found posttreatment, not pretreatment, PT perfusion parameters can be used to predict OS and PFS in patients with newly diagnosed GBM.

The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

Detection of glioma recurrence by ¹¹C-methionine positron emission tomography and dynamic susceptibility contrast-enhanced magnetic resonance imaging: a meta-analysis

PURPOSE

This study aimed to compare the diagnostic value of ¹¹C-methionine (¹¹C-MET) PET and dynamic susceptibility contrast-enhanced (DSCE) MRI in detecting glioma recurrence by meta-analysis.

MATERIALS AND METHODS

Databases such as PubMed (MEDLINE included), EMBASE, Science Direct, Springerlink, EBSCO, and Cochrane Database of Systematic Review were searched for relevant original articles on the detection of recurrent glioma using DSCE MRI or ¹¹C-MET PET with or without computed tomography. No restriction was imposed over the types and grades of glioma. The included studies were assessed for methodological quality. Results from histopathological analysis and/or close clinical and/or radiological follow-up for at least 3 months were used as the reference standard. The data were extracted by two reviewers independently to analyze the sensitivity, specificity, summary receiver-operating characteristic curve, area under the curve, and heterogeneity.

RESULTS

The present study analyzed a total of 17 selected articles including different types and grades of glioma and showed that ¹¹C-MET PET and DSCE MRI had comparable sensitivity (0.870 and 0.884, respectively), specificity (0.813 and 0.853, respectively), positive likelihood ratio (4.355 and 5.806, respectively), negative likelihood ratio (0.192 and 0.134, respectively), and diagnostic odds ratio (21.857 and 41.918, respectively) without statistically significant differences, except for the fact that DSCE MRI displayed higher area under the curve and Q* index compared with ¹¹C-MET PET (P<0.05).

CONCLUSION

Both ¹¹C-MET PET and DSCE MRI are accurate tools for detecting glioma recurrence. Although DSCE MRI seems to be superior to ¹¹C-MET PET, the latter can also be used to assess glioma recurrence when the former is not available.

DCE and DSC MR perfusion imaging in the differentiation of recurrent tumour from treatment-related changes in patients with glioma

AIM

To retrospectively compare the utility of perfusion magnetic resonance imaging (MRI) in distinguishing treatment-related changes from recurrent disease in glioma patients.

MATERIALS AND METHODS

Thirty-one patients with histologically diagnosed gliomas and increased enhancement after or during concurrent (chemo-) radiation therapy were enrolled. They underwent dynamic contrast-enhanced (DCE) permeability MRI followed by dynamic susceptibility contrast (DSC) perfusion MRI. The vascular transfer constant (rK(trans)) and initial areas under the concentration curve (riAUC) were obtained from DCE MRI, and cerebral blood volume (rCBV) was obtained from DSC MRI. Patients were classified as having treatment-related changes or recurrent tumours based on clinicoradiological results or pathological results from surgery.

RESULTS

Nineteen patients were diagnosed as having recurrences and 12 patients as having treatment-related changes. The rK(trans), riAUC, and rCBV values in the recurrent group were significantly higher than the values in the group with treatment-related changes (p < 0.05). For all 31 patients, there was no significant difference between DSC MRI and DCE MRI for the differentiating power between recurrence and treatment-related changes (p = 0.7227). However, when including only the 24 patients with concordant values of rK(trans) and riAUC, DCE MRI showed a significant AUC value of 0.786 in the receiver operating characteristic (ROC) curve analysis (p = 0.003), whereas DSC MRI did not (AUC = 0.643, p = 0.229).

CONCLUSION

MRI perfusion images appear to show promise in distinguishing treatment-related changes from recurrent tumours. When both rK(trans) and riAUC show concordant values, DCE MRI seems to be more powerful than DSC MRI in the differentiation of recurrence from treatment-related changes.

Advanced MR diffusion tensor imaging and perfusion weighted imaging of intramedullary tumors and tumor like lesions in the cervicomedullary junction region and the cervical spinal cord

Differential diagnosis between intramedullary tumors and tumor-like lesions (TLL) in the cervicomedullary junction region and cervical spinal cord is important, sometimes clinical dilemma on conventional MR imaging and empirical treatment. We evaluated advanced MR diffusion tensor imaging (DTI) and perfusion weighted imaging (PWI) in 25 patients, including 12 with intramedullary tumors and 13 with TLL in the cervicomedullary junction region and cervical spinal cord. We found that mean fractional anisotropy value of tumors was significantly lower than the value found in TLL, and the mean trace apparent diffusion coefficient and peak height values of tumors were significantly higher (P < 0.05). The receiver operating characteristic curve analysis showed that peak height was better than any of the other imaging parameters, with a sensitivity of 90.9% and specificity of 80% using a cutoff value of 4.523 to differentiate between tumors and TLL. In conclusion, the MR DTI and PWI could be useful in differentiating between intramedullary tumors and TLL in the cervicomedullary junction region and cervical spinal cord.

Perfusion MRI: the five most frequently asked clinical questions

OBJECTIVE

This article addresses questions that radiologists frequently ask when planning, performing, processing, and interpreting MRI perfusion studies in CNS imaging.

CONCLUSION

Perfusion MRI is a promising tool in assessing stroke, brain tumors, and neurodegenerative diseases. Most of the impediments that have limited the use of per-fusion MRI can be overcome to allow integration of these methods into modern neuroimaging protocols.

Measurements of tumor vascular leakiness using DCE in brain tumors: clinical applications

Various imaging techniques have been employed to evaluate blood-brain-barrier leakiness in brain tumors, as higher tumor vascular leakiness is known to be associated with higher grade and malignant potential of the tumor, and hence can help provide additional diagnostic and prognostic information. These imaging techniques range from routine post-contrast T1 -weighted images that highlight degree of contrast enhancement to absolute measurement of quantitative metrics of vascular leakiness employing complex pharmacokinetic modeling. The purpose of this article is to discuss the clinical applications of available imaging techniques, and in particular dynamic contrast-enhanced T1 -weighted MR imaging (DCE-MRI), to evaluate tumor vascular leakiness.

Perfusion imaging in brain disease

Perfusion CT or MRI have been extensively developed over the last years and are accessible on most imaging machines. Perfusion CT has taken a major place in the assessment of a stroke. Its role has to be specified for the diagnosis and treatment of the vasospasm, complicating a subarachnoid hemorrhage. Perfusion MRI should be included in the assessment of any brain tumor, both at the time of the diagnosis as well as in the post-treatment monitoring. It is included in the multimodal approach required for the optimum treatment of this disease. The applications in epilepsy and the neurodegenerative diseases are in the evaluation process.

The effect of pulse sequence parameters and contrast agent dose on percentage signal recovery in DSC-MRI: implications for clinical applications

BACKGROUND AND PURPOSE

Both technical and pathophysiologic factors affect PSR in DSC-MR imaging. We aimed to determine how TE, flip angle (α), and contrast dose impact PSR in high-grade gliomas.

MATERIALS AND METHODS

We retrospectively computed PSR maps for 22 patients with high-grade gliomas, comparing 3 DSC-MR imaging methods by using single-dose gadodiamide without preload administration: A (n = 7), α = 35°, TE = 54 ms; B (n = 5), α = 72°, TE = 30 ms; C (n = 10), α = 90°, TE = 30 ms. Methods A-C served as preload for subsequent dynamic imaging using method D (method C parameters but with double-dose contrast). We compared first- and second-injection tumor PSR for methods C and D (paired t test) and tumor PSR for both injections grouped by the first-injection acquisition method (3-group nonparametric 1-way ANOVA). We compared PSR in tumor and normal brain for each first- and second-injection method group (paired t test).

RESULTS

First-injection PSR in tumor and normal brain differed significantly for methods B (P = .01) and C (P = .05), but not A (P = .71). First-injection tumor PSR increased with T1 weighting with a significant main effect of method groupings (P = .0012), but there was no significant main effect for first-injection normal brain (P = .93), or second-injection tumor (P = .95) or normal brain (P = .13). In patients scanned with methods C and D, first-injection PSR significantly exceeded second-injection PSR for tumor (P = .037) and normal brain (P < .001).

CONCLUSIONS

PSR strongly depends on the T1 weighting of DSC-MR imaging, including pulse sequence (TE, α) and contrast agent (dose, preload) parameters, with implications for protocol design and the interpretation and comparison of PSR values across tumor types and imaging centers.

Differentiation of primary central nervous system lymphomas and glioblastomas: comparisons of diagnostic performance of dynamic susceptibility contrast-enhanced perfusion MR imaging without and with contrast-leakage correction

BACKGROUND AND PURPOSE

Contrast leakage results in underestimation of the CBV of brain tumors. Our aim was to compare the diagnostic performance of DSC perfusion MR imaging without and with mathematic contrast-leakage correction in differentiating PCNSLs and glioblastomas.

MATERIALS AND METHODS

Perfusion parameters-CBV, corrected CBV, and leakage coefficient-were measured in enhancing tumor portions and contralateral NAWM of 15 PCNSLs and 20 glioblastomas, respectively. The ratios of CBV and corrected CBV were calculated by dividing the tumor values by those obtained from contralateral NAWM. A paired t test was used to compare tumor K2 and NAWM K2, as well as tumor CBV ratios without and with leakage correction. Comparisons of CBV, corrected CBV, and K2 between PCNSLs and glioblastomas were done by using a 2-sample t test. The diagnostic performance of DSC perfusion MR imaging without and with contrast-leakage correction was assessed with receiver operating characteristic curve analysis.

RESULTS

PCNSLs and glioblastomas demonstrated higher K2 than those in their contralateral NAWM. Corrected CBV ratios were significantly higher than the uncorrected ones for both tumors. PCNSLs had lower CBV ratios (P < .001), lower corrected CBV ratios (P < .001), and higher K2 (P = .001) compared with glioblastomas. In differentiating between PCNSLs and glioblastomas, the area under the curve of the CBV ratio, corrected CBV ratio, and K2 were 0.984, 0.940, and 0.788, respectively.

CONCLUSIONS

PCNSL can be differentiated from glioblastoma with CBV ratios, corrected CBV ratios, and K2. CBV without contrast-leakage correction seems to have the best diagnostic performance in differentiating the 2 tumors.

Intraoperative Visualization of Residual Tumor: The Role of Perfusion-Weighted Imaging in a High-Field Intraoperative Magnetic Resonance Scanner

BACKGROUND:

High-field, intraoperative magnetic resonance imaging (iMRI) achieves free tumor margins in glioma surgery by involving anatomic neuronavigation and sophisticated functional imaging.

OBJECTIVE:

To evaluate the role of perfusion-weighted iMRI as an aid to detect residual tumor and to guide its resection.

METHODS:

Twenty-two patients undergoing intraoperative scanning (in a dual-room 1.5-T magnet setting) during the resection of high-grade gliomas were examined with perfusion-weighted iMRI. The generated relative cerebral blood volume (rCBV) maps were scrutinized for any hot spots indicative of tumor remnants, and region-of-interest analysis was performed. Differences among the rCBV region-of-interest estimates in residual tumor, free tumor margins, and normal white matter were analyzed. Histopathology of the tissue specimens and the neurosurgeon's intraoperative macroscopic estimations were considered the reference standards.

RESULTS:

In all cases, diagnostic rCBV perfusion maps were generated. Interpretation of perfusion maps demonstrated that gross total resection of gliomas was achieved in 4 of 22 cases (18%), which was macroscopically and histopathologically verified, whereas in 18 of 22 cases (82%), the perfusion-weighted iMRI revealed hot spots indicating subtotal tumor removal. The latter proved to be true in all but 1 case. The receiver-operating characteristic curves of the qualitative visual and quantitative analyses showed excellent sensitivity and specificity rates. Statistical analysis demonstrated statistically significant differences for the mean rCBV and maximum rCBV between residual disease and tumor-free margins (P = .002 for both).

CONCLUSION:

Perfusion-weighted iMRI may be implemented easily into imaging protocols and may assist the surgeon in detecting residual tumor volume.

Lesions masquerading as acute stroke

Rapid and accurate recognition of lesions masquerading as acute stroke is important. Any incorrect or delayed diagnosis of stroke mimics will not only increase the risk of being exposed to unnecessary and possibly dangerous interventional therapies, but will also delay proper treatment. In this article, written from a neuroradiologist's perspective, we classified these lesions masquerading as acute stroke into three groups: lesions that may have "normal imaging," lesions that are "symptom mimics" but on imaging clearly not a stroke, and lesions that are "symptom and imaging mimics" with imaging findings similar to stroke. We focused the review on neuroimaging findings of the latter two groups ending with a suggestion for a diagnostic approach in the form of an algorithm.

Lipid and macromolecules quantitation in differentiating glioblastoma from solitary metastasis: a short-echo time single-voxel magnetic resonance spectroscopy study at 3 T

OBJECTIVE

The differentiation between solitary metastasis (MET) and glioblastoma (GBM) is difficult using only magnetic resonance imaging techniques. Magnetic resonance spectroscopy (MRS) lipid signal indicates cellular necrosis both in GBMs and METs. The purpose of this prospective study was to determine whether a class of lipids and/or macromolecules (MMs), able to efficiently discriminate between these two types of lesions, exists.

METHODS

Forty-one patients with solitary brain tumor (23 GBMs and 18 METs) underwent magnetic resonance imaging and single-voxel MRS. Short-echo time point resolved spectroscopy sequence acquisition with water suppression technique was used. Spectra were analyzed using LCModel. Absolute quantification was performed with "water-scaling" procedure. The analysis was focused on sums of lipid and macromolecular (LM) components at 0.9 and 1.3 ppm.

RESULTS

The LM13 absolute concentration was statistically different (P < 0.0001) between GBMs and METs. With a cutoff of 81 mM in LM13 absolute concentration, METs and GBMs can be distinguished with a 78% of specificity and an 81% of sensitivity. The presence of the MM12 peak, related to the fucose II complex, in tumors harboring a K-ras gene mutation has been investigated.

CONCLUSIONS

We exploited the performance of a clinically easily implementable method, such as short-echo time single-voxel MRS, for the differentiation between brain metastasis and primary brain tumors. The study showed that MRS absolute lipid and macromolecular signals could be helpful in differentiating GBM from metastasis. LM13 class was found to be a discriminant parameter with an accuracy of 85%. Detection of the MM12-fucose peak may also have a role in understanding molecular biology of brain metastasis and should be further investigated to address specific metabolic phenotypes.

Controversies in the management of brain metastases

The multidisciplinary management of brain metastases has generated substantial controversy as treatment has diversified in recent years. Debate about the type, role, and timing of different diagnostic and therapeutic strategies has promoted rigorous scientific research into efficacy. However, much still remains unanswered in the treatment of this difficult disease process. This manuscript seeks to highlight some of the controversies identified in previous sections of this supplement, including prognosis, pathology, radiation and surgical treatment, neuroimaging, and the biochemical underpinnings of brain metastases. By recognizing what is yet unanswered, we hope to identify areas in which further research may yield promising results.

Imaging of brain metastases

Imaging plays a key role in the diagnosis of central nervous system (CNS) metastasis. Imaging is used to detect metastases in patients with known malignancies and new neurological signs or symptoms, as well as to screen for CNS involvement in patients with known cancer. Computed tomography (CT) and magnetic resonance imaging (MRI) are the key imaging modalities used in the diagnosis of brain metastases. In difficult cases, such as newly diagnosed solitary enhancing brain lesions in patients without known malignancy, advanced imaging techniques including proton magnetic resonance spectroscopy (MRS), contrast enhanced magnetic resonance perfusion (MRP), diffusion weighted imaging (DWI), and diffusion tensor imaging (DTI) may aid in arriving at the correct diagnosis. This image-rich review discusses the imaging evaluation of patients with suspected intracranial involvement and malignancy, describes typical imaging findings of parenchymal brain metastasis on CT and MRI, and provides clues to specific histological diagnoses such as the presence of hemorrhage. Additionally, the role of advanced imaging techniques is reviewed, specifically in the context of differentiating metastasis from high-grade glioma and other solitary enhancing brain lesions. Extra-axial CNS involvement by metastases, including pachymeningeal and leptomeningeal metastases is also briefly reviewed.

Comparison of the effectiveness of MRI perfusion and fluorine-18 FDG PET-CT for differentiating radiation injury from viable brain tumor: a preliminary retrospective analysis with pathologic correlation in all patients

OBJECTIVES

Differentiating radiation injury from viable tumor is important for optimizing patient care. Our aim was to directly compare the effectiveness of fluorine-18 fluorodeoxyglucose (FDG) positron emission tomography-computed tomography (PET-CT) and dynamic susceptibility-weighted contrast-enhanced (DSC) magnetic resonance (MR) perfusion in differentiating radiation effects from tumor growth in patients with increased enhancement following radiotherapy for primary or secondary brain tumors.

MATERIALS AND METHODS

We retrospectively identified 12 consecutive patients with primary and secondary brain tumors over a 1-year period that demonstrated indeterminate enhancing lesions after radiotherapy and that had undergone DSC MR perfusion, FDG PET-CT, and subsequent histopathologic diagnosis. The maximum standardized uptake value (SUV) of the lesion (SUVlesion max), SUVratio (SUVlesion max/SUVnormal brain), maximum relative cerebral blood volume, percentage of signal intensity recovery, and relative peak height were calculated from the positron emission tomography and MR perfusion studies. A prediction of tumor or radiation injury was made based on these variables while being blinded to the results of the surgical pathology.

RESULTS

SUVratio had the highest predictive value (area under the curve=0.943) for tumor progression, although this was not statistically better than any MR perfusion metric (area under the curve=0.757-0.829).

CONCLUSIONS

This preliminary study suggests that FDG PET-CT and DSC MR perfusion may demonstrate similar effectiveness for distinguishing tumor growth from radiation injury. Assessment of the SUVratio may increase the sensitivity and specificity of FDG PET-CT for differentiating tumor and radiation injury. Further analysis is needed to help define which modality has greater predictive capabilities.

3 Tesla magnetic resonance spectroscopy: cerebral gliomas vs. metastatic brain tumors. Our experience and review of the literature

The aim of the present study is to report about the value of magnetic resonance spectroscopy (MRS) in differentiating brain metastases, primary high-grade gliomas (HGG) and low-grade gliomas (LGG). MRI (magnetic resonance imaging) and MRS were performed in 60 patients with histologically verified brain tumors: 32 patients with HGG (28 glioblastomas multiforme [GBM] and 4 anaplastic astrocytomas), 14 patients with LGG (9 astrocytomas and 5 oligodendrogliomas) and 14 patients with metastatic brain tumors. The Cho/Cr (choline-containing compounds/creatine-phosphocreatine complex), Cho/NAA (N-acetyl aspartate) and NAA/Cr ratios were assessed from spectral maps in the tumoral core and peritumoral edema. The differences in the metabolite ratios between LGG, HGG and metastases were analyzed statistically. Lipids/lactate contents were also analyzed. Significant differences were noted in the tumoral and peritumoral Cho/Cr, Cho/NAA and NAA/Cr ratios between LGG, HGG and metastases. Lipids and lactate content revealed to be useful for discriminating gliomas and metastases. The results of this study demonstrate that MRS can differentiate LGG, HGG and metastases, therefore diagnosis could be allowed even in those patients who cannot undergo biopsy.

Usefulness of perfusion weighted magnetic resonance imaging with signal-intensity curves analysis in the differential diagnosis of sellar and parasellar tumors: preliminary report

PURPOSE

The most common pituitary tumors are adenomas, which however may be mimicked by other tumors that can show a very similar appearance in plain MRI. The aim of our study was to evaluate the usefulness of perfusion weighted MR imaging (PWI), including signal-intensity curves analysis in the differential diagnosis of sellar/parasellar tumors.

METHODS

Forty-one patients with sellar/parasellar tumors (23 macroadenomas, 10 meningiomas, 5 craniopharyngiomas, 1 intrasellar hemangioblastoma, 1 intrasellar prostate cancer metastasis, 1 suprasellar glioma), underwent plain MRI followed by PWI using a 1.5T unit. In each tumor, the mean and maximum values of relative cerebral blood volume (rCBV), as well as the relative peak height (rPH) and the relative percentage of signal intensity recovery (rPSR) were calculated.

RESULTS

The high perfusion tumors were: macroadenomas, meningiomas, squamous-papillary type of craniopharyngiomas, hemangioblastoma, glioma and metastasis. The low perfusion neoplasms included adamantinomatous type of craniopharyngiomas. By comparing adenomas and meningiomas, we found statistically significant differences in the mean and maximum rCBV values (p=0.026 and p=0.019, respectively), but not in rPH and rPSR. The maximum rCBV values >7.14 and the mean rCBV values >5.74 with the typical perfusion curve were very suggestive of the diagnosis of meningioma. There were differences between adenomas and other high perfusion tumors in rPH and rPSR values.

CONCLUSIONS

PWI can provide additional information helpful in differential diagnosis of sellar/parasellar tumors. In our opinion PWI, as an easy to perform and fast technique should be incorporated into the MR protocol of all intracranial neoplasms including sellar/parasellar tumors.

Combined diffusion and perfusion MR imaging as biomarkers of prognosis in immunocompetent patients with primary central nervous system lymphoma

BACKGROUND AND PURPOSE

ADC derived from DWI has been shown to correlate with PFS and OS in immunocompetent patients with PCNSL. The purpose of our study was to confirm the validity of ADC measurements as a prognostic biomarker and to determine whether rCBV measurements derived from DSC perfusion MR imaging provide prognostic information.

MATERIALS AND METHODS

Pretherapy baseline DWI and DSC perfusion MR imaging in 25 patients with PCNSL was analyzed before methotrexate-based induction chemotherapy. Contrast-enhancing tumor was segmented and coregistered with ADC and rCBV maps, and mean and minimum values were measured. Patients were separated into high or low ADC groups on the basis of previously published threshold values of ADC(min) < 384 × 10(-6) mm(2)/s. High and low rCBV groups were defined on the basis of receiver operating curve analysis. High and low ADC and rCBV groups were analyzed independently and in combination. Multivariate Cox survival analysis was performed.

RESULTS

Patients with ADC(min) values < 384 × 10(-6) mm(2)/s or rCBV(mean) values < 1.43 had worse PFS and OS. The patient cohort with combined low ADC(min)-low rCBV(mean) had the worst prognosis. No other variables besides ADC and rCBV significantly affected survival.

CONCLUSIONS

Our study reinforces the validity of ADC values as a prognostic biomarker and provides the first evidence of low tumor rCBV as a novel risk factor for adverse prognosis in immunocompetent patients with PCNSL.

Comparison of DSC-MRI post-processing techniques in predicting microvascular histopathology in patients newly diagnosed with GBM

PURPOSE

To evaluate which common post-processing method applied to gradient-echo DSC-MRI data, acquired with a single gadolinium injection and low flip-angle, most accurately reflects microvascular histopathology for patients with de novo, treatment-naive glioblastoma multiforme (GBM).

MATERIALS AND METHODS

Seventy-two tissue samples were collected from 35 patients with treatment-naive GBM. Sample locations were co-registered to preoperative gradient-echo dynamic susceptibility contrast (DSC) MRI acquired with 35° flip-angle and 0.1 mmol/kg gadolinium. Estimates of blood volume and leakiness at each sample location were calculated using four common postprocessing methods (leakage-corrected nonlinear gamma-variate, non-parametric, scaled MR-signal, and unscaled MR-signal). Tissue sample microvascular morphology was characterized using Factor VIII immunohistochemical analysis. A random-effects regression model, adjusted for repeated measures and contrast-enhancement (CE), identified whether MR parameter estimates significantly predicted IHC findings.

RESULTS

Elevated blood volume estimates from nonlinear and non-parametric methods significantly predicted increased microvascular hyperplasia. Abnormal microvasculature existed beyond the CE-lesion and was significantly reflected by increased blood volume from nonlinear, non-parametric, and scaled MR-signal analysis.

CONCLUSION

This study provides histopathological support for both non-parametric and nonlinear post-processing of low flip-angle DSC-MRI for characterizing microvascular hyperplasia within GBM. Non-parametric analysis with a single gadolinium injection may be a particularly useful strategy clinically, as it requires less computational expense and limits gadolinium exposure.

Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed.

Differentiation between brain glioblastoma multiforme and solitary metastasis: qualitative and quantitative analysis based on routine MR imaging

BACKGROUND AND PURPOSE

The differentiation between cerebral GBM and solitary MET is clinically important and may be radiologically challenging. Our hypothesis is that routine MR imaging with qualitative and quantitative analysis is helpful for this differentiation.

MATERIALS AND METHODS

Forty-five GBM and 21 solitary metastases were retrospectively identified, with their preoperative routine MR imaging analyzed. According to the comparison of the area of peritumoral T2 prolongation with that of the lesion, the tumors were classified into grade I (prolongation area ≤ tumor area) and grade II (prolongation area > tumor area). The signal intensities of peritumoral T2 prolongation were measured on T2WI and normalized to the values of the contralateral normal regions by calculating the ratios. The ratio (nSI) of both types of tumors was compared in grade I, grade II, and in tumors without grading. The best cutoff values to optimize the sensitivity and specificity were determined for optimal differentiation.

RESULTS

The nSI of GBM was significantly higher than that of MET without T2 prolongation grading (P < .001), resulting in AUC = 0.725. The difference was significant (P = .014) in grade I tumors (GBM, 38; MET, 9), with AUC = 0.741, and in grade II tumors (GBM, 7; MET, 12), with AUC = 0.869 (P = .017). Both types of tumors showed a different propensity in T2 prolongation grading (χ(2) = 12.079, P = .001).

CONCLUSIONS

Combined with qualitative and quantitative analysis of peritumoral T2 prolongation, routine MR imaging can help in the differentiation between brain GBM and solitary MET.

Regional variation in histopathologic features of tumor specimens from treatment-naive glioblastoma correlates with anatomic and physiologic MR Imaging

Histopathologic evaluation of glioblastoma multiforme (GBM) at initial diagnosis is typically performed on tissue obtained from regions of contrast enhancement (CE) as depicted on gadolinium-enhanced, T1-weighted images. The non-enhancing (NE) portion of the lesion, which contains both reactive edema and infiltrative tumor, is only partially removed due to concerns about damaging functioning brain. The purpose of this study was to evaluate histopathologic and physiologic MRI features of image-guided tissue specimens from CE and NE regions to investigate correlations between imaging and histopathologic parameters. One hundred nineteen tissue specimens (93 CE and 26 NE regions) were acquired from 51 patients with newly diagnosed GBM by utilizing stereotactic image-guided sampling. Variables of anatomic, diffusion-weighted imaging (DWI), and dynamic susceptibility-weighted, contrast-enhanced perfusion imaging (DSC) from each tissue sample location were obtained and compared with histopathologic features such as tumor score, cell density, proliferation, architectural disruption, hypoxia, and microvascular hyperplasia. Tissue samples from CE regions had increased tumor score, cellular density, proliferation, and architectural disruption compared with NE regions. DSC variables such as relative cerebral blood volume, peak height, and recovery factor were significantly higher, and the percentage of signal intensity recovery was significantly lower in the CE compared with the NE regions. DWI variables were correlated with histopathologic features of GBM within NE regions. Image-guided tissue acquisition and assessment of residual tumor from treatment-naive GBM should be guided by DSC in CE regions and by DWI in NE regions.

Distinction between postoperative recurrent glioma and delayed radiation injury using MR perfusion weighted imaging

INTRODUCTION

Distinction between postoperative recurrent glioma and radiation injury remains a tough diagnostic problem for routine imaging methods. The purpose of this study is to evaluate the differentiated effectiveness of perfusion weighted imaging (PWI) for the two entities.

METHODS

PWI was performed using Siemens 3.0-T MR system for 35 patients with new contrast-enhancing lesions at the site of treated glioma. Regions of interest (ROIs) were manually drawn at the contrast-enhancing lesion and peri-lesion edema areas. For calculation of standardised relative cerebral blood volume (rCBV) ratios, the same size ROIs were drawn at the area of contralateral hemisphere normal white matter on rCBV maps. At least five ROIs were selected at each lesion. The rCBV values were measured and the rCBV ratios were calculated. The maximum rCBV (rCBV(max)) ratio at each region was chosen for analysis. The patients were divided into two groups: tumour recurrence and radiation injury. The mean rCBV(max) ratios were compared between the two groups.

RESULTS

The mean rCBV(max) ratio in the contrast-enhancing lesion was significantly higher in the tumour recurrence (4.36 ± 1.98) compared with that (1.28 ± 0.64) in the radiation injury (P < 0.01). The mean rCBV(max) ratio in the peri-lesion edema was also significantly higher in the tumour recurrence (1.79 ± 0.51) compared with that (0.85 ± 0.28) in the radiation injury (P < 0.05). A recurrent tumour was suggested when the rCBV(max) ratio >2.15 based on the receiver operating characteristic curve. Four patients with recurrent tumour and three with radiation injury were misclassified.

CONCLUSION

PWI is a useful method to distinguish tumour recurrence and radiation injury.

Multiparametric magnetic resonance imaging to differentiate high-grade gliomas and brain metastases

PURPOSE

To assess the performance of parameters used in conventional magnetic resonance imaging (MRI), perfusion-weighted MR imaging (PWI) and visual texture analysis, alone and in combination, to differentiate a single brain metastasis (MET) from glioblastoma multiforme (GBM).

PATIENTS AND METHODS

In a retrospective study of 50 patients (41 GBM and 14 MET) who underwent T2/FLAIR/T1(post-contrast) imaging and PWI, morphological (circularity, surface area), perfusion (rCBV in the ring-like tumor area, rCBV in the peritumoral area, percentage of signal intensity recovery at the end of first pass) and texture parameters in the peritumoral area were estimated. Statistical differences and performances were assessed using Wilcoxon's test and receiver operating characteristic curves, respectively. Multiparametric classification of tumors was performed using k-means clustering.

RESULTS

Significant statistical differences in circularity, surface area, rCBVs, percentage of signal intensity recovery and texture parameters (energy, entropy, homogeneity, correlation, inverse differential moment, sum average) were observed between MET and GBM (P<0.05). Moderate-to-good classification performances were found with these parameters. Clustering based on rCBV and texture parameters (contrast, sum average) differentiated MET from GBM with a sensitivity of 92% and a specificity of 71%.

CONCLUSION

Combining perfusion and visual texture parameters within a statistical classifier significantly improved the differentiation of a single brain MET and GBM.

Mean intensity curve on dynamic contrast-enhanced susceptibility-weighted perfusion MR imaging--review of a new parameter to differentiate intracranial tumors

Dynamic susceptibility contrast (DSC) perfusion imaging has been in clinical use for various indications, including characterization and grading of intracranial neoplasms. However, several technical factors can lead to pitfalls in image interpretation. This review discusses the extraction of T1 and T2* information from mean curve analysis of DSC perfusion imaging of various brain tumors, which provides further insights into tumor biology and, thus, may be useful in the differential diagnosis of such tumors. Indeed, by looking at the mean time-signal intensity curve from the tumor bed in addition to the rCBV maps, it is possible to obtain further inferences of capillary density and lesion leakiness. When dynamic contrast enhanced (DCE) T1 perfusion is not available, DSC perfusion with mean curve analysis appears to be a valid alternative for characterizing various brain neoplasms in a routine clinical setting.

Clinical applications of dynamic susceptibility contrast perfusion-weighted MR imaging in brain tumours

Magnetic resonance imaging (MRI) with a dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) sequence to study brain tumours provides information on the haemodynamic characteristics of the neoplastic tissue. Brain perfusion maps and calculation of perfusion parameters, such as relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV) and mean transit time (MTT) allow assessment of vascularity and angiogenesis within tumours of the central nervous system (CNS), thus providing additional information to conventional MRI sequences. Although DSC-PWI has long been used, its clinical use in the study of brain tumours in daily clinical practice is still to be defined. The aim of this review was to analyse the application of perfusion MRI in the study of brain tumours by summarising our personal experience and the main results reported in the literature.

Differentiating treatment-induced necrosis from recurrent/progressive brain tumor using nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion

Differentiating treatment-induced necrosis (TIN) from recurrent/progressive tumor (RPT) in brain tumor patients using conventional morphologic imaging features is a very challenging task. Functional imaging techniques also offer moderate success due to the complexity of the tissue microenvironment and the inherent limitation of the various modalities and techniques. The purpose of this retrospective study was to assess the utility of nonmodel-based semiquantitative indices derived from dynamic contrast-enhanced T1-weighted MR perfusion (DCET1MRP) in differentiating TIN from RPT. Twenty-nine patients with previously treated brain tumors who showed recurrent or progressive enhancing lesion on follow-up MRI underwent DCET1MRP. Another 8 patients with treatment-naive high-grade gliomas who also underwent DCET1MRP were included as the control group. Semiquantitative indices derived from DCET1MRP included maximum slope of enhancement in initial vascular phase (MSIVP), normalized MSIVP (nMSIVP), normalized slope of delayed equilibrium phase (nSDEP), and initial area under the time-intensity curve (IAUC) at 60 and 120 s (IAUC(60) and IAUC(120)) obtained from the enhancement curve. There was a statistically significant difference between the 2 groups (P < .01), with the RPT group showing higher MSIVP (15.78 vs 8.06), nMSIVP (0.046 vs 0.028), nIAUC(60) (33.07 vs 6.44), and nIAUC(120) (80.14 vs 65.55) compared with the TIN group. nSDEP was significantly lower in the RPT group (7.20 × 10(-5) vs 15.35 × 10(-5)) compared with the TIN group. Analysis of the receiver-operating-characteristic curve showed nMSIVP to be the best single predictor of RPT, with very high (95%) sensitivity and high (78%) specificity. Thus, nonmodel-based semiquantitative indices derived from DCET1MRP that are relatively easy to derive and do not require a complex model-based approach may aid in differentiating RPT from TIN and can be used as robust noninvasive imaging biomarkers.

MR perfusion-weighted imaging may help in differentiating between nonenhancing gliomas and nonneoplastic lesions in the cervicomedullary junction

PURPOSE

To evaluate the ability of dynamic susceptibility-weighted contrast-enhanced magnetic resonance (MR) perfusion imaging (DSC-PWI) in distinguishing between nonenhancing gliomas and nonenhancing, nonneoplastic lesions in the cervicomedullary junction region.

MATERIALS AND METHODS

This retrospective study involved eight patients with nonenhancing gliomas in the medulla oblongata and eight patients with nonenhancing nonneoplastic lesions. The relative cerebral blood volume (rCBV) ratios, peak heights, and percentage of signal intensity recovery derived from time-signal intensity curves of these nonenhancing lesions were compared.

RESULTS

The mean peak height of nonenhancing gliomas was significantly higher than the value of their reference regions of interest (ROIs). In contrast, mean peak height of nonneoplastic lesions was significantly lower than their reference ROIs. The mean peak height and mean maximal rCBV ratio of nonenhancing gliomas were significantly higher than those of nonenhancing, nonneoplastic lesions (P<0.05). There was no significant difference with regard to percentage of signal intensity recovery between the two groups.

CONCLUSION

DSC-PWI could be a useful adjuvant tool to differentiate between nonenhancing gliomas and nonenhancing, nonneoplastic lesions in the cervicomedullary junction region.

Distinguishing recurrent high-grade gliomas from radiation injury: a pilot study using dynamic contrast-enhanced MR imaging

RATIONALE AND OBJECTIVES

The accurate delineation of tumor recurrence and its differentiation from radiation injury in the follow-up of adjuvantly treated high-grade gliomas presents a significant problem in neuro-oncology. The aim of this study was to investigate whether hemodynamic parameters derived from dynamic contrast-enhanced (DCE) T1-weighted magnetic resonance imaging (MRI) can be used to distinguish recurrent gliomas from radiation necrosis.

MATERIALS AND METHODS

Eighteen patients who were being treated for glial neoplasms underwent prospectively conventional and DCE-MRI using a 3T scanner. The pharmacokinetic modelling was based on a two-compartment model that allows for the calculation of K(trans) (transfer constant between intra- and extravascular, extracellular space), v(e) (extravascular, extracellular space), k(ep) (transfer constant from the extracellular, extravascular space into the plasma), and iAUC (initial area under the signal intensity-time curve). Regions of interest (ROIs) were drawn around the entire recurrence-suspected contrast-enhanced region. A definitive diagnosis was established at subsequent surgical resection or clinicoradiologic follow-up. The hemodynamic parameters in the contralateral normal white matter, the radiation injury sites, and the tumor recurrent lesions were compared using nonparametric tests.

RESULTS

The K(trans), v(e), k(ep), and iAUC values in the normal white matter were significantly different than those in the radiation necrosis and recurrent gliomas (0.01, <P < .0001). The only significantly different hemodynamic parameter between the recurrent tumor lesions and the radiation-induced necrotic sites were K(trans) and iAUC, which were significantly higher in the recurrent glioma group than in the radiation necrosis group (P ≤ .0184). A K(trans) cutoff value higher than 0.19 showed 100% sensitivity and 83% specificity for detecting the recurrent gliomas, whereas an iAUC cutoff value higher than 15.35 had 71% sensitivity and 71% specificity. The v(e) and k(ep) values in recurrent tumors were not significantly higher than those in radiation-induced necrotic lesions.

CONCLUSIONS

These findings suggest that DCE-MRI may be used to distinguish between recurrent gliomas and radiation injury and thus, assist in follow-up patient management strategy.

Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain

BACKGROUND AND PURPOSE

Differentiation of enhancing malignant lesions on conventional MR imaging can be difficult and various newer imaging techniques have been suggested. Our aim was to evaluate the role of PSR obtained from DSC perfusion measurements in differentiating lymphoma, GBM, and metastases. The effectiveness of PSR was compared with that of rCBV. We hypothesized that the newly defined parameter of PSR is more sensitive and specific in differentiating these lesions.

MATERIALS AND METHODS

This retrospective study included 66 patients (39 men and 27 women; age range: 27-82 years) with a pathologically proved diagnosis of primary CNS lymphoma, GBM, or metastases (22 patients in each group). Mean PSR, min PSR, max PSR, and rCBV were calculated. The classification accuracy of these parameters was investigated by using ROC.

RESULTS

Mean PSR was high (113.15 ± 41.59) in lymphoma, intermediate in GBM (78.22 ± 14.27), and low in metastases (53.46 ± 12.87) with a P value < .000. F values obtained from 1-way ANOVA analysis for mean, min, and max PSR ratios were 29.9, 39.4, and 23.4, respectively, which were better than those of rCBV (11.1) in differentiating the 3 groups. Max PSR yielded the best ROC characteristics with an A(z) of 0.934 (95% CI, 0.877-0.99) in differentiating lymphoma from metastases and GBM. The A(z) for mean and min PSR of 0.938 (95% CI, 0.0.884-0.990) and 0.938 (95% CI, 0.884-0.991), respectively, was better than rCBV (A(z), 0.534; 95% CI, 0.391-0.676) in the differentiation of metastases from GBM and lymphoma (P ≤ .0001).

CONCLUSIONS

PSR appears to be a parameter that helps in differentiating intracerebral malignant lesions such as GBM, metastases, and lymphoma.

Permeability estimates in histopathology-proved treatment-induced necrosis using perfusion CT: can these add to other perfusion parameters in differentiating from recurrent/progressive tumors?

BACKGROUND AND PURPOSE

Differentiating treatment effects from RPT is a common yet challenging task in a busy neuro-oncologic practice. PS probably represents a different aspect of angiogenesis and vasculature and can provide additional physiologic information about recurrent/progressive enhancing lesions. The purpose of the study was to use PS measured by using PCT to differentiate TIN from RPT in patients with previously irradiated brain tumor who presented with a recurrent/progressive enhancing lesion.

MATERIALS AND METHODS

Seventy-two patients underwent PCT for assessment of a recurrent/progressive enhancing lesion from January 2006 to November 2009. Thirty-eight patients who underwent surgery and histopathologic diagnosis were included in this analysis. Perfusion parameters such as PS, CBV, CBF, and MTT were obtained from the enhancing lesion as well as from the NAWM.

RESULTS

Of 38 patients, 11 were diagnosed with pure TIN and 27 had RPT. Patients with TIN showed significantly lower mean PS values than those with RPT (1.8 ± 0.8 versus 3.6 ± 1.6 mL/100 g/min; P value=.001). The TIN group also showed lower rCBV (1.2 ± 0.3 versus 2.1 ± 0.7; P value<.001), lower rCBF (1.2 ± 0.5 versus 2.6 ± 1.7; P value=.004), and higher rMTT (1.4 ± 0.4 versus 1.0 ± 0.4; P value=.018) compared with the RPT group.

CONCLUSIONS

PCT and particularly PS can be used in patients with previously treated brain tumors to differentiate TIN from RPT. PS estimates can help increase the accuracy of PCT in differentiating these 2 entities.

Cerebral peritumoral oedema study: does a single dynamic MR sequence assessing perfusion and permeability can help to differentiate glioblastoma from metastasis?

Our purpose was to differentiate glioblastoma from metastasis using a single dynamic MR sequence to assess perfusion and permeability parameters. 24 patients with glioblastoma or cerebral metastasis with peritumoral oedema were recruited and explored with a 3T MR unit. Post processing used DPTools software. Regions of interest were drawn around contrast enhancement to assess relative cerebral blood volume and permeability parameters. Around the contrast enhancement Glioblastoma present high rCBV with modification of the permeability, metastasis present slight modified rCBV without modification of permeability. In conclusion, peritumoral T2 hypersignal exploration associating morphological MR and functional MR parameters can help to differentiate cerebral metastasis from glioblastoma.

Diagnostic dilemma of pseudoprogression in the treatment of newly diagnosed glioblastomas: the role of assessing relative cerebral blood flow volume and oxygen-6-methylguanine-DNA methyltransferase promoter methylation status

BACKGROUND AND PURPOSE

Methylation of the MGMT gene promoter is associated with a favorable prognosis in adult patients with GBM treated with TMZ. We determined the incidence of pseudoprogression according to the MGMT methylation status and the potential value of DSC perfusion MR images for predicting pseudoprogression.

MATERIALS AND METHODS

New or enlarged enhancing lesions after CCRT in adult patients with newly diagnosed GBMs were prospectively assessed by measuring their rCBV by using DSC perfusion MR images. Tumor tissue was assayed to determine MGMT promoter methylation status. All patients were regularly followed up at an interval of 2 months by MR images, including DSC perfusion MR images.

RESULTS

Ninety eligible patients were enrolled in this study. After CCRT, new or enlarged enhanced lesions were found in 59 of 90 patients, which were subsequently classified as pseudoprogression (26 patients, 28.9%) and real progression (33 patients, 36.7%). Overall, there was a significant difference in the mean rCBV between pseudoprogression and real tumor progression (P = .003). The ROC curve revealed that an rCBV ratio >1.47 had an 81.5% sensitivity and a 77.8% specificity. The unmethylated MGMT promoter group had a significant difference of mean rCBV between pseudoprogression and real progression (P = .009), though the methylated MGMT promoter group had no significant difference (P = .258).

CONCLUSIONS

The current study suggests that rCBV measured by DSC perfusion MR images has a differential impact on the predictability of pseudoprogression in patients with GBM.

Imaging of brain tumors: perfusion/permeability

The use of biomarkers of microvascular structure and function from perfusion and permeability imaging is now well established in neuro-oncological research. There remain significant challenges to be overcome before these techniques and related biomarkers can find general clinical acceptance. Core to this is the standardization of acquisition and processing protocols for robust use across multiple clinical sites. The potential clinical benefits of these approaches are already becoming clear, particularly in the setting of novel antiangiogenic therapies. With an increasing body of evidence in the scientific literature, and with a steadily falling barrier to entry, the coming decade should see rapid developments in imaging biomarkers, and facilitate their transition into routine clinical practice.

Differentiation among glioblastoma multiforme, solitary metastatic tumor, and lymphoma using whole-tumor histogram analysis of the normalized cerebral blood volume in enhancing and perienhancing lesions

BACKGROUND AND PURPOSE

The histogram method has been shown to demonstrate heterogeneous morphologic features of tumor vascularity. This study aimed to determine whether whole-tumor histogram analysis of the normalized CBV for contrast-enhancing lesions and perienhancing lesions can differentiate among GBMs, SMTs, and lymphomas.

MATERIALS AND METHODS

Fifty-nine patients with histopathologically confirmed GBMs (n = 28), SMTs (n = 22), or lymphomas (n = 12) underwent conventional MR imaging and dynamic susceptibility contrast-enhanced imaging before surgery. Histogram distribution of the normalized CBV was obtained from whole-tumor voxels in contrast-enhancing lesions and perienhancing lesions. The HW, PHP, and MV were determined from histograms. One-way ANOVA was used initially to test the overall equality of mean values for each type of tumor. Subsequently, posttest multiple comparisons were performed.

RESULTS

For whole-tumor histogram analyses for contrast-enhancing lesions, only PHP could differentiate among GBMs (4.79 ± 1.31), SMTs (3.32 ± 1.10), and lymphomas (2.08 ± 0.54). The parameters HW and MV were not significantly different between GBMs and SMTs, whereas the 2 histogram parameters were significantly higher in GBMs and SMTs compared with lymphomas. For the analyses of perienhancing lesions, only MV could differentiate among GBMs (1.90 ± 0.26), SMTs (0.80 ± 0.21), and lymphomas (1.27 ± 0.34). HW and PHP were not significantly different between SMTs and lymphomas.

CONCLUSIONS

Using a whole-tumor histogram analysis of normalized CBV for contrast-enhancing lesions and perienhancing lesions facilitates differentiation of GBMs, SMTs and lymphomas.

Glioblastoma multiforme regional genetic and cellular expression patterns: influence on anatomic and physiologic MR imaging

PURPOSE

To determine whether magnetic resonance (MR) imaging is influenced by genetic and cellular features of glioblastoma multiforme (GBM) aggressiveness.

MATERIALS AND METHODS

In this HIPAA-compliant institutional review board-approved study, multiple enhancing and peritumoral nonenhancing stereotactic neurosurgical biopsy samples from treatment-naïve GBMs were collected prospectively, with guidance from cerebral blood volume (CBV) MR imaging measurements. By using monoclonal antibodies, tissue specimens were examined for microvascular expression, hypoxia, tumor and overall cellular density, and histopathologic features of GBM aggressiveness. Genetic expression patterns were investigated with RNA microarrays. Imaging and histopathologic variables were compared with the Welch t test and Pearson correlations. Microarray analysis was performed by using false discovery rate (FDR) statistics.

RESULTS

Tumor biopsy of 13 adult patients yielded 16 enhancing and 14 peritumoral nonenhancing specimens. Enhancing regions had elevated relative CBV and reduced relative apparent diffusion coefficient (ADC) measurements compared with peritumoral nonenhancing biopsy regions (P < .01). A positive correlation was found between relative CBV and all histopathologic features of aggressiveness (P < .04). An inverse correlation was found between relative ADC and all histopathologic features of aggressiveness (P < .05). RNA expression patterns between tumor regions were found to be significantly different (FDR < 0.05), with hierarchical clustering by biopsy region only.

CONCLUSION

These findings suggest MR imaging is significantly influenced by GBM genetic and cellular biologic features of aggressiveness and imply physiologic MR imaging may be useful in pinpointing regions of highest malignancy within heterogeneous tissues, thus facilitating histologic grading of primary glial brain tumors.