Differentiation of cerebral tumors using multi-section echo planar MR perfusion imaging

The Utility of Multiparametric Magnetic Resonance Imaging in Reducing Diagnostic Uncertainty for Primary Central Nervous System Lymphoma

BACKGROUND

A key limitation in treatment initiation in primary central nervous system lymphoma (PCNSL) is the diagnostic delay caused by lack of recognition of a lesion as a possible lymphoma, steroid initiation, and lesion involution, often resulting in an inconclusive biopsy result. We highlight the importance of multiparametric magnetic resonance imaging (MRI), which incorporates diffusion-weighted imaging, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and proton magnetic resonance spectroscopy in addition to standard MRI sequences in resolving diagnostic uncertainty for PCNSL.

METHODS

At our center, a consecutive series of 10 patients with histology-proven PCNSL (specifically, diffuse large B-cell lymphoma of the central nervous system) underwent multiparametric MRI. We retrospectively analyzed qualitative and semiquantitative parameters and assessed their radiological concordance for this diagnosis.

RESULTS

We noted overall low apparent diffusion coefficient on diffusion-weighted imaging (mean minimum apparent diffusion coefficient of 0.74), high percentage signal recovery on perfusion-weighted imaging (mean 170%), a high choline-to-creatine ratio, and a high-grade lipid peak on proton magnetic resonance spectroscopy giving an appearance of twin towers. Of 10 patients, 9 had MRI findings concordant for PCNSL, defined as at least 3 of 4 parameters being consistent for PCNSL.

CONCLUSIONS

Concordance between these imaging multiparametric modalities could be used as a radiological predictor of PCNSL, reducing diagnostic delays, providing a more accurate biopsy target, and resulting in quicker treatment initiation.

Relative percentage signal intensity recovery of perfusion metrics—an efficient tool for differentiating grades of glioma

OBJECTIVE

Glioma classification and characterization may be facilitated by a multiparametric approach of perfusion metrics, which could not be achieved by conventional MRI alone. Our aim is to explore the potential of relative percentage signal intensity recovery (rPSR) values, in addition to relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) of first-pass T2* dynamic susceptibility contrast (DSC) perfusion MRI, in differentiating high- and low-grade glioma.

METHODS

This prospective study included 39 patients with low-grade and 25 patients with high-grade glioma. rPSR, rCBV and rCBF were calculated from the first-pass T2* DSC perfusion MRI. rPSR was calculated using standard software and validated with dedicated perfusion metrics analysis software. The statistical analysis was performed using analysis of variance and receiver operating characteristic (ROC) curves.

RESULTS

Variation in rPSR, rCBV and rCBF values between low- and high-grade gliomas were statistically significant (p < 0.005). The ROC curve analysis for each of them yielded 96% sensitivity and 71.8% specificity; 88% sensitivity and 69.2% specificity; and 72% sensitivity and 66.7% specificity. The area under the curve (AUC) from the ROC curve analysis yielded 0.893, 0.852 and 0.702 for rPSR, rCBV and rCBF, respectively. The rPSR calculation with the validation software yielded 92.3% sensitivity and 72% specificity with an AUC of 0.864.

CONCLUSION

rPSR inversely correlates while rCBV and rCBF values directly correlate with the tumour grade. Furthermore, the overall diagnostic performance of rPSR is better than rCBV and rCBF values.

ADVANCES IN KNOWLEDGE

rPSR of T2* DSC perfusion is an indicator of blood-brain barrier status and lesion leakiness, which has not been explored yet compared with the usual haemodynamic parameters, rCBV and rCBF.

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.

Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T

Purpose: To assess the contribution of ¹H-magnetic resonance spectroscopy (¹H-MRS), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic susceptibility contrast-enhanced (DSCE) imaging metrics in the differentiation of glioblastomas from solitary metastasis, and particularly to clarify the controversial reports regarding the hypothesis that there should be a significant differentiation between the intratumoral and peritumoral areas. Methods: Conventional MR imaging, ¹H-MRS, DWI, DTI and DSCE MRI was performed on 49 patients (35 glioblastomas multiforme, 14 metastases) using a 3.0-T MR unit. Metabolite ratios, apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) were measured in the intratumoral and peritumoral regions of the lesions. Receiver-operating characteristic analysis was used to obtain the cut-off values for the parameters presenting a statistical difference between the two tumor groups. Furthermore, we investigated the potential effect of the region of interest (ROI) size on the quantification of diffusion properties in the intratumoral region of the lesions, by applying two different ROI methods. Results: Peritumoral N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, Cho/NAA and rCBV significantly differentiated glioblastomas from intracranial metastases. ADC and FA presented no significant difference between the two tumor groups. Conclusions:¹H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases. The quantification of the diffusion properties in the intratumoral region is independent of the ROI size placed.

Role of perfusion-weighted imaging at 3T in the histopathological differentiation between astrocytic and oligodendroglial tumors

OBJECTIVE

The differentiation of oligodendroglial tumors from astrocytic tumors is important clinically, because oligodendroglial tumors are more chemosensitive than astrocytic tumors. This study was designed to clarify the usefulness of 3T MR perfusion imaging (PWI) in the histopathological differentiation between astrocytic and oligodendroglial tumors. This is because there is a growing interest in the diagnostic performance of 3T MR imaging, which has the advantages of a higher signal-to-noise ratio (SNR) and greater spatial and temporal resolution.

MATERIALS AND METHODS

This study retrospectively included 24 consecutive patients with supratentorial, WHO grade II and III astrocytic and oligodendroglial tumors (7 astrocytic, 10 oligoastrocytic, and 7 oligodendroglial tumors) that were newly diagnosed and resected between November 2006 and December 2009 at Hiroshima University Hospital. These patients underwent dynamic susceptibility contrast-enhanced (DSC) PWI relative cerebral blood volume (rCBV) measurements before treatment. Astrocytic tumors were designated as the astrocytic group, and oligoastrocytic and oligodendroglial tumors as the oligodendroglial group. The regions of interest with the maximum rCBV values within the tumors were normalized relative to the contra-lateral white matter (rCBVmax).

RESULTS

The average rCBVmax of astrocytic tumors (2.01±0.68) was significantly lower than that of the oligoastrocytic (4.60±1.05) and oligodendroglial tumors (6.17±0.867) (P<0.0001). A cut-off value of 3.0 allowed to differentiate the oligodendroglial group from the astrocytic group at 100% sensitivity and 87.5% specificity.

CONCLUSION

The rCBVmax values obtained from 3T MR PWI may be useful as an adjunct to the postoperative histopathological diagnosis of glioma patients.

Elevated peritumoural rCBV values as a mean to differentiate metastases from high-grade gliomas

PURPOSE

Increased relative cerebral blood volume (rCBV) was previously found in peritumoural oedema of glioblastomas (GBM). Supposing that peritumoural rCBV is not increased in metastases, we aimed to evaluate whether rCBV values of the whole peritumoural area are accurate to differentiate solitary metastasis from GBM irrespective of the peritumoural oedema.

METHODS

Contrast-enhanced T1-weighted (T1-w) and T2*-weighted dynamic susceptibility contrast MRI was performed in 52 patients with contrast-enhancing solitary brain tumours before surgery. In each T1-w slice depicting the contrast-enhancing tumour, a rim within approximately 15 mm was defined in the peritumoural area. The rCBV values were normalised to rCBV values of the contralateral normal white matter. Differences between metastases and GBM for normalised rCBV values for each slice were determined with the Mann-Whitney U test (p < 0.05).

RESULTS

Histopathological examination revealed 29 GBM and 23 metastases. Peritumoural rCBV was significantly lower in metastases than in GBM (p < 0.01). Using the cutoff value 1.0 for discriminating metastases from GBM yielded a sensitivity of 96%, specificity of 64%, a positive predictive value of 68% and a negative predictive value of 95%.

CONCLUSIONS

The rCBV in the peritumoural area of contrast-enhancing brain tumours has a high diagnostic accuracy to discriminate metastases from GBM irrespective of surrounding oedema and without the bias of slice selection and ROI positioning. Metastases should be excluded, if at least one tumour-depicting slice reveals an increase of peritumoural rCBV compared to the normal contralateral brain (normalised rCBV value >1). Conversely, the decrease of peritumoural rCBV may not reliably exclude GBM.

Stripe-like increase of rCBV beyond the visible border of glioblastomas: site of tumor infiltration growing after neurosurgery

We observed a stripe-like pattern of regional cerebral blood volume (rCBV) increase in a defined region adjacent to the contrast enhancement (CE) on MRI of glioblastomas (GBM) that we defined as the "striate sign" (SS). We hypothesized that the SS marks infiltration of GBM outside the CE volume transforming into future CE tumor in the follow-up. T2*-weighted dynamic susceptibility-weighted CE (DSC)-MRI, and T1 and T2-weighted images (WI) of 16 patients with GBM were retrospectively evaluated in a baseline MRI performed before neurosurgery. In seven of these patients we also performed a (1)H MR spectroscopic imaging ((1)H MRSI). The regions of interest (ROI) delineating the SS were defined on rCBV maps for each patient. ROIs were overlaid on follow-up T1-WI and T2-WI MRI performed 3, 6, and 9 months after neurosurgery. Size and maximum signal intensity (max SI) of de novo CE within the area of the SS were analyzed. Statistical analysis was performed with the Friedman test (P < 0.05). In 15/16 patients de novo CE completely covered the area of the SS within nine months. Normalized max SI of de-novo CE of the 3, 6, and 9-months follow-up MR examinations were significantly higher than in the baseline MRI (P < 0.001). Normalized choline was increased within the SS in all patients with de novo CE (n = 6). De-novo CE appeared within the SS in all patients (96% of all slices). This implies that the SS might indicate the site of future CE tumor, which represents the area of tumor growth after neurosurgery.

MR Perfusion Imaging of Intracranial Tumors

This retrospective study evaluated magnetic resonance (MR) perfusion imaging in the study of intracranial tumors; 218 patients were studied with 509 MR examinations. The first aim was to establish the usefulness of perfusion imaging for the differential diagnosis between neoplastic tissue and other lesions both in the first MR examination and in the post therapeutic controls (differentiation of tumor recurrence from radionecrosis). Then we evaluated the presence of infiltrating neoplastic tissue in CBV maps outside the enhancement area to differentiate infiltrating gliomas from metastases. In addition, post surgical evaluation was performed to identify residual neoplastic tissue, mainly if bleeding or inflammatory post surgical cerebral damage did not allow a definitive diagnosis with conventional morphologic images. Lastly, it was assessed whether hypervascularization (evaluated in CBV maps) is a favourable prognostic factor for a positive outcome to radiotherapy. The diagnostic gain of perfusion imaging in all these cases was established evaluating our case records.

Prediction of oligodendroglial tumor subtype and grade using perfusion weighted magnetic resonance imaging

OBJECT

Treatment of patients with oligodendrogliomas relies on histopathological grade and characteristic cytogenetic deletions of 1p and 19q, shown to predict radio- and chemosensitivity and prolonged survival. Perfusion weighted magnetic resonance (MR) imaging allows for noninvasive determination of relative tumor blood volume (rTBV) and has been used to predict the grade of astrocytic neoplasms. The aim of this study was to use perfusion weighted MR imaging to predict tumor grade and cytogenetic profile in oligodendroglial neoplasms.

METHODS

Thirty patients with oligodendroglial neoplasms who underwent preoperative perfusion MR imaging were retrospectively identified. Tumors were classified by histopathological grade and stratified into two cytogenetic groups: 1p or 1p and 19q loss of heterozygosity (LOH) (Group 1), and 19q LOH only on intact alleles (Group 2). Tumor blood volume was calculated in relation to contralateral white matter. Multivariate logistic regression analysis was used to develop predictive models of cytogenetic profile and tumor grade.

RESULTS

In World Health Organization Grade II neoplasms, the rTBV was significantly greater (p < 0.05) in Group 1 (mean 2.44, range 0.96-3.28; seven patients) compared with Group 2 (mean 1.69, range 1.27-2.08; seven patients). In Grade III neoplasms, the differences between Group 1 (mean 3.38, range 1.59-6.26; four patients) and Group 2 (mean 2.83, range 1.81-3.76; 12 patients) were not significant. The rTBV was significantly greater (p < 0.05) in Grade III neoplasms (mean 2.97, range 1.59-6.26; 16 patients) compared with Grade II neoplasms (mean 2.07, range 0.96-3.28; 14 patients). The models integrating rTBV with cytogenetic profile and grade showed prediction accuracies of 68 and 73%, respectively.

CONCLUSIONS

Oligodendroglial classification models derived from advanced imaging will improve the accuracy of tumor grading, provide prognostic information, and have potential to influence treatment decisions.

Quantitative assessment of intracranial tumor response to dexamethasone using diffusion, perfusion and permeability magnetic resonance imaging

There is increasing interest in obtaining quantitative imaging parameters to aid in the assessment of tumor responses to treatment. In this study, the feasibility of performing integrated diffusion, perfusion and permeability magnetic resonance imaging (MRI) for characterizing responses to dexamethasone in intracranial tumors was assessed. Eight patients with glioblastoma, five with meningioma and three with metastatic carcinoma underwent MRI prior to and 48-72 h following dexamethasone administration. The MRI protocol enabled quantification of the volume transfer constant (K(trans)), extracellular space volume fraction (nu(e)), plasma volume fraction (nu(p)), regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV), longitudinal relaxation time (T(1)) and mean diffusivity (D(av)). All subjects successfully completed the imaging protocol for the presteroid and poststeroid scans. Significant reductions were observed after the treatment for K(trans), nu(e) and nu(p) in enhancing tumor as well as for T(1) and D(av) in the edematous brain in glioblastoma; on the other hand, for meningioma, significant differences were seen only in edematous brain T(1) and D(av). No significant difference was observed for any parameter in metastatic carcinoma, most likely due to the small sample size. In addition, no significant difference was observed for enhancing tumor rCBF and rCBV in any of the tumor types, although the general trend was for rCBV to be reduced and for rCBF to be more variable. The yielded parameters provide a wealth of physiologic information and contribute to the understanding of dexamethasone actions on different types of intracranial tumors.

Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy

INTRODUCTION

Contrast-enhanced MR imaging is the method of choice for routine assessment of brain tumors, but it has limited sensitivity and specificity. We verified if the addition of metabolic, diffusion and hemodynamic information improved the definition of glioma extent and grade.

METHODS

Thirty-one patients with cerebral gliomas (21 high- and 10 low-grade) underwent conventional MR imaging, proton MR spectroscopic imaging ((1)H-MRSI), diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) at 3 Tesla, before undergoing surgery and histological confirmation. Normalized metabolite signals, including choline (Cho), N-acetylaspartate (NAA), creatine and lactate/lipids, were obtained by (1)H-MRSI; apparent diffusion coefficient (ADC) by DWI; and relative cerebral blood volume (rCBV) by PWI.

RESULTS

Perienhancing areas with abnormal MR signal showed 3 multiparametric patterns: "tumor", with abnormal Cho/NAA ratio, lower ADC and higher rCBV; "edema", with normal Cho/NAA ratio, higher ADC and lower rCBV; and "tumor/edema", with abnormal Cho/NAA ratio and intermediate ADC and rCBV. Perienhancing areas with normal MR signal showed 2 multiparametric patterns: "infiltrated", with high Cho and/or abnormal Cho/NAA ratio; and "normal", with normal spectra. Stepwise discriminant analysis showed that the better classification accuracy of perienhancing areas was achieved when regarding all MR variables, while (1)H-MRSI variables and rCBV better differentiated high- from low-grade gliomas.

CONCLUSION

Multiparametric MR assessment of gliomas, based on (1)H-MRSI, PWI and DWI, discriminates infiltrating tumor from surrounding vasogenic edema or normal tissues, and high- from low-grade gliomas. This approach may provide useful information for guiding stereotactic biopsies, surgical resection and radiation treatment.

Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors

OBJECTIVE

Common contrast-enhancing malignant tumors of the brain are glioblastoma multiforme (GBMs), anaplastic astrocytomas (AAs), metastases, and lymphomas, all of which have sometimes similar conventional MRI findings. Our aim was to evaluate the role of perfusion MR imaging (PWI) and diffusion-weighted imaging (DWI) in the differentiation of these contrast-enhancing malignant cerebral tumors.

MATERIALS AND METHODS

Forty-eight patients with contrast-enhancing and histologically proven brain tumors, 14 AAs, 17 GBMs, nine metastases, and eight lymphomas, were included in the study. All patients have undergone routine MR examination where DWI and PWI were performed in the same session. DWI was performed with b values of 0, 500, and 1000 mm(2)/s. Minimum ADC values (ADC(min)) of each tumor was later calculated from ADC map images. PWI was applied using dynamic susceptibility contrast technique and maximum relative cerebral blood volume (rCBV(max)) was calculated from each tumor, given in ratio with contralateral normal white matter. Comparisons of ADC(min) and rCBV(max) values with the histological types of the enhancing tumors were made with a one-way analysis of variance and Bonferroni test. A P value less than 0.05 indicated a statistically significant difference.

RESULTS

The ADC(min) values (mean+/-S.D.) in GBMs, AAs, lymphomas, and metastases were 0.79+/-0.21 (x10(-3)mm(2)/s), 0.75+/-0.21 (x10(-3)mm(2)/s), 0.51+/-0.09 (x10(-3)mm(2)/s), and 0.68+/-0.11 (x10(-3)mm(2)/s), respectively. The difference in ADC(min) values were statistically significant between lymphomas and GBMs (P<0.05). It was also statistically significant between lymphomas and AAs (P<0.03). However, there were no differences between lymphomas and metastasis, and between GBMs, AAs, and metastasis. The rCBV(max) ratio (mean+/-S.D.) in GBMs were 6.33+/-2.03, whereas it was 3.66+/-1.79 in AAs, 2.33+/-0.68 in lymphomas, and 4.45+/-1.87 in metastases. These values were statistically different between GBMs and AAs (P<0.001), GBMs and lymphoma (P<0.0001). Although there seemed to be difference between GBMs and metastases, it was not statistically significant (P<0.083).

CONCLUSION

Combination of DWI and PWI, with ADC(min) and rCBV(max) calculations, may aid routine MR imaging in the differentiation of common cerebral contrast-enhancing malignant tumors.

Imaging in neurooncology

Imaging in patients with brain tumors aims toward the determination of the localization, extend, type, and malignancy of the tumor. Imaging is being used for primary diagnosis, planning of treatment including placement of stereotaxic biopsy, resection, radiation, guided application of experimental therapeutics, and delineation of tumor from functionally important neuronal tissue. After treatment, imaging is being used to quantify the treatment response and the extent of residual tumor. At follow-up, imaging helps to determine tumor progression and to differentiate recurrent tumor growth from treatment-induced tissue changes, such as radiation necrosis. A variety of complementary imaging methods are currently being used to obtain all the information necessary to achieve the above mentioned goals. Computed tomography and magnetic resonance imaging (MRI) reveal mostly anatomical information on the tumor, whereas magnetic resonance spectroscopy and positron emission tomography (PET) give important information on the metabolic state and molecular events within the tumor. Functional MRI and functional PET, in combination with electrophysiological methods like transcranial magnetic stimulation, are being used to delineate functionally important neuronal tissue, which has to be preserved from treatment-induced damage, as well as to gather information on tumor-induced brain plasticity. In addition, optical imaging devices have been implemented in the past few years for the development of new therapeutics, especially in experimental glioma models. In summary, imaging in patients with brain tumors plays a central role in the management of the disease and in the development of improved imaging-guided therapies.

New criteria for assessing fit quality in dynamic contrast-enhancedT1-weighted MRI for perfusion and permeability imaging

Contrast-enhanced (CE) MRI provides in vivo physiological information that cannot be obtained by conventional imaging methods. This information is generally extracted by using models to represent the circulation of contrast agent in the body. However, the results depend on the quality of the fit obtained with the chosen model. Therefore, one must check the fit quality to avoid working on physiologically irrelevant parameters. In this study two dimensionless criteria-the fraction of modeling information (FMI) and the fraction of residual information (FRI)-are proposed to identify errors caused by poor fit. These are compared with more conventional criteria, namely the quadratic error and the correlation coefficient, both theoretically and with the use of simulated and real CE-MRI data. The results indicate the superiority of the new criteria. It is also shown that these new criteria can be used to detect oversimplified models.

Neuropsychological results and neuropathological findings at autopsy in a case of mild traumatic brain injury

Autopsy studies were undertaken in a 47-year-old college-educated male patient who, 7 months prior to an unexpected death, had sustained a mild traumatic brain injury (TBI) as manifested by brief loss of consciousness and an initial Glasgow Coma Scale score of 14. The patient died from cardiac arrest secondary to an undiagnosed and unknown arteriosclerotic cardiovascular disease as assessed by the coroners office at the time of autopsy. Gross inspection of the brain at autopsy was normal; however, microscopic analysis demonstrated what were considered trauma findings of hemosiderin-laden macrophages in the perivascular space and macrophages in the white matter, particularly the section taken from the frontal lobe. The patient had partially returned to work at the time of death, but had encountered problems with diminished cognitive performance in his work as an appraiser. Neuropsychological studies were generally within normal limits although several tests of either speed of processing or short-term memory showed lower than expected performance. This case demonstrates the presence of subtle neuropathological changes in the brain of a patient who sustained a mild TBI and was still symptomatic for the residual effects of the injury 7 months post injury when he unexpectedly died.