Perfusion-sensitive MRI of cerebral lymphomas: a preliminary report

Improved early outcome prediction by MRI-based 3D tumor volume assessment in patients with CNS lymphomas

BACKGROUND

Central nervous system lymphomas (CNSL) display remarkable clinical heterogeneity, yet accurate prediction of outcomes remains challenging. The IPCG criteria are widely used in routine practice for the assessment of treatment response. However, the value of the IPCG criteria for ultimate outcome prediction is largely unclear, mainly due to the uncertainty in delineating complete from partial responses during and after treatment.

METHODS

We explored various MRI features including semi-automated 3D tumor volume measurements at different disease milestones and their association with survival in 93 CNSL patients undergoing curative-intent treatment.

RESULTS

At diagnosis, patients with more than 3 lymphoma lesions, periventricular involvement, and high 3D tumor volumes showed significantly unfavorable PFS and OS. At first interim MRI during treatment, the IPCG criteria failed to discriminate outcomes in responding patients. Therefore, we randomized these patients into training and validation cohorts to investigate whether 3D tumor volumetry could improve outcome prediction. We identified a 3D tumor volume reduction of ≥97% as the optimal threshold for risk stratification (=3D early response, 3D_ER). Applied to the validation cohort, patients achieving 3D_ER had significantly superior outcomes. In multivariate analyses, 3D_ER was independently prognostic of PFS and OS. Finally, we leveraged prognostic information from 3D MRI features and circulating biomarkers to build a composite metric that further improved outcome prediction in CNSL.

CONCLUSIONS

We developed semi-automated 3D tumor volume measurements as strong and independent early predictors of clinical outcomes in CNSL patients. These radiologic features could help improve risk stratification and help guide future treatment approaches.

Primary central nervous system lymphoma

Primary central nervous system lymphoma (PCNSL) is a diffuse large B cell lymphoma in which the brain, spinal cord, leptomeninges and/or eyes are exclusive sites of disease. Pathophysiology is incompletely understood, although a central role seems to comprise immunoglobulins binding to self-proteins expressed in the central nervous system (CNS) and alterations of genes involved in B cell receptor, Toll-like receptor and NF-κB signalling. Other factors such as T cells, macrophages or microglia, endothelial cells, chemokines, and interleukins, probably also have important roles. Clinical presentation varies depending on the involved regions of the CNS. Standard of care includes methotrexate-based polychemotherapy followed by age-tailored thiotepa-based conditioned autologous stem cell transplantation and, in patients unsuitable for such treatment, consolidation with whole-brain radiotherapy or single-drug maintenance. Personalized treatment, primary radiotherapy and only supportive care should be considered in unfit, frail patients. Despite available treatments, 15-25% of patients do not respond to chemotherapy and 25-50% relapse after initial response. Relapse rates are higher in older patients, although the prognosis of patients experiencing relapse is poor independent of age. Further research is needed to identify diagnostic biomarkers, treatments with higher efficacy and less neurotoxicity, strategies to improve the penetration of drugs into the CNS, and roles of other therapies such as immunotherapies and adoptive cell therapies.

Multiparametric MR Imaging Features of Primary CNS Lymphomas

Objective

Primary central nervous system lymphomas (PCNS) are relatively rare tumors, accounting for about 4% of all brain tumors. On neuroimaging, they are characterized by a low MR signal in T1, isointense in T2, bright uniform contrast enhancement, and diffusion restriction. The aim of this study is to note the lack of effectiveness of the MR/CT perfusion technique in complex multiparametric imaging in the differential diagnosis of primary lymphomas of the central nervous system in comparison with highly malignant gliomas and brain metastases.

Materials and Methods

This prospective study included 80 patients with CNS tumors examined/operated at the Federal Center for Neurosurgery (Tyumen, Russia) from 2018 to 2021. The patients were divided into 4 groups: group 1 consisted of 33 cases with primary CNS lymphomas (10 cases with atypical manifestations according to perfusion parameters and 23 cases of classic CNS lymphomas), group 2 with anaplastic astrocytomas—14 cases, group 3—23 cases with glioblastomas and group 4—10 cases with solitary metastatic lesions. The study was carried out on a General Electric Discovery W750 3T magnetic resonance tomograph, a Canon Aquilion One multispiral X-ray computed tomograph (Gadovist 7.5 ml, Yomeron 400 mg−50 ml). Additionally, immunohistochemical analysis was carried out with the following markers: CD3, CD20, CD34, Ki-67, VEGF.

Results

It has been established that MR/CT perfusion is not a highly sensitive method for visualizing primary CNS lymphomas, as previously thought, but at the same time, the method has a number of undeniable advantages that make it indispensable in the algorithm of a complex multiparametric diagnostic approach for this type of tumor. Nevertheless, PLCNS is characterized by an atypical manifestation, which is an exception to the rule.

Conclusions

The possibilities of neuroimaging of primary lymphomas, even with the use of improved techniques for collecting MR/CT data, are limited and do not always allow reliable differentiation from other neoplasms.

Consensus recommendations for MRI and PET imaging of primary central nervous system lymphoma: guideline statement from the International Primary CNS Lymphoma Collaborative Group (IPCG)

Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both “ideal” and “minimum standard” protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.

Classification of glioblastoma versus primary central nervous system lymphoma using convolutional neural networks

A subset of primary central nervous system lymphomas (PCNSL) are difficult to distinguish from glioblastoma multiforme (GBM) on magnetic resonance imaging (MRI). We developed a convolutional neural network (CNN) to distinguish these tumors on contrast-enhanced T₁-weighted images. Preoperative brain tumor MRIs were retrospectively collected among 320 patients with either GBM (n = 160) and PCNSL (n = 160) from two academic institutions. The individual images from these MRIs consisted of a training set (n = 1894 GBM and 1245 PCNSL), a validation set (n = 339 GBM; 202 PCNSL), and a testing set (99 GBM and 108 PCNSL). Three CNNs using the EfficientNetB4 architecture were evaluated. To increase the size of the training set and minimize overfitting, random flips and changes to color were performed on the training set. Our transfer learning approach (with image augmentation and 292 epochs) yielded an AUC of 0.94 (95% CI: 0.91–0.97) for GBM and an AUC of 0.95 (95% CI: 0.92–0.98) for PCNL. In the second case (not augmented and 137 epochs), the images were augmented prior to training. The area under the curve for GBM was 0.92 (95% CI: 0.88–0.96) for GBM and an AUC of 0.94 (95% CI: 0.91–0.97) for PCNSL. For the last case (augmented, Gaussian noise and 238 epochs) the AUC for GBM was 0.93 (95% CI: 0.89–0.96) and an AUC 0.93 (95% CI = 0.89–0.96) for PCNSL. Even with a relatively small dataset, our transfer learning approach demonstrated CNNs may provide accurate diagnostic information to assist radiologists in distinguishing PCNSL and GBM.

Delayed Contrast Enhancement in Magnetic Resonance Imaging and Vascular Morphology of Primary Diffuse Large B-Cell Lymphoma (DLBCL) of the Central Nervous System (CNS): A Retrospective Study

Background

This study aimed to compare the magnetic resonance imaging (MRI) findings of primary diffuse large B-cell lymphoma (DLBCL) of the central nervous system (CNS) with delayed contrast enhancement and histological microvessel density (MVD). T1-weighted and T2-weighted contrast-enhanced and non-enhanced brain imaging were used. CNS lymphoma tissue was evaluated using primary antibodies to endothelial cells and smooth muscle cells, and histochemical staining for reticulin fibers and basement membrane, which allowed quantification of the MVD.

Material/Methods

Twenty-one patients with histologically confirmed primary DLBCL of the CNS underwent pre-contrast-enhanced and postcontrast-enhanced MRI. Histology of the CNS lymphoma tissue included immunohistochemical staining with antibodies to CD34 for vascular endothelial cells and alpha smooth muscle actin (ASMA) for vascular smooth muscle cells, and histochemical staining included periodic acid-Schiff (PAS) and silver staining for reticulin fibers to evaluate microvessel density (MVD).

Results

In primary DLBCL of the CNS, a positive correlation was found between the degree of necrosis and the size of the lymphoma (r=0.546, P=0.01). Delayed imaging enhancement was significantly correlated with the number of mature vessels, MVD, basement membrane, and reticulin fibers (r=0.593, 0.466, 0.446 and 0.497, respectively). Standardized β regression coefficient analysis showed that the MVD, PAS-positive structures, the number of mature vessels, and reticulin fibers, were significantly associated with delayed enhancement on MRI (β values, 0.425, 0.409, 0.295, and 0.188, respectively).

Conclusions

In primary DLBCL of the CNS, delayed imaging enhancement on MRI may be due to reduced neovascularization and vascular infiltration by lymphoma cells.

Clinical Value of Vascular Permeability Estimates Using Dynamic Susceptibility Contrast MRI: Improved Diagnostic Performance in Distinguishing Hypervascular Primary CNS Lymphoma from Glioblastoma

BACKGROUND AND PURPOSE

A small subset of primary central nervous system lymphomas exhibits high cerebral blood volume, which is indistinguishable from that in glioblastoma on dynamic susceptibility contrast MR imaging. Our study aimed to test whether estimates of combined perfusion and vascular permeability metrics derived from DSC-MR imaging can improve the diagnostic performance in differentiating hypervascular primary central nervous system lymphoma from glioblastoma.

MATERIALS AND METHODS

A total of 119 patients (with 30 primary central nervous system lymphomas and 89 glioblastomas) exhibited hypervascular foci using the reference method of leakage-corrected CBV (reference-normalized CBV). An alternative postprocessing method used the tissue residue function to calculate vascular permeability (extraction fraction), leakage-corrected CBV, cerebral blood flow, and mean transit time. Parameters were compared using Mann-Whitney U tests, and the diagnostic performance to distinguish primary central nervous system lymphoma from glioblastoma was calculated using the area under the curve from the receiver operating characteristic curve and was cross-validated with bootstrapping.

RESULTS

Hypervascular primary central nervous system lymphoma showed similar leakage-corrected normalized CBV and leakage-corrected CBV compared with glioblastoma (P > .05); however, primary central nervous system lymphoma exhibited a significantly higher extraction fraction (P < .001) and CBF (P = .01) and shorter MTT (P < .001) than glioblastoma. The extraction fraction showed the highest diagnostic performance (the area under the receiver operating characteristic curve [AUC], 0.78; 95% confidence interval, 0.69-0.85) for distinguishing hypervascular primary central nervous system lymphoma from glioblastoma, with a significantly higher performance than both CBV (AUC, 0.53-0.59, largest P = .02) and CBF (AUC, 0.72) and MTT (AUC, 0.71).

CONCLUSIONS

Estimation of vascular permeability with DSC-MR imaging further characterizes hypervascular primary central nervous system lymphoma and improves diagnostic performance in glioblastoma differentiation.

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T₁ and T₂* changes observed across multiple glioblastomas, the DRO's input parameters were trained using DSC-MRI data from 23 glioblastomas (>40 000 voxels). The DRO's ability to produce reliable signals for combinations of pulse sequence parameters and contrast agent dosing schemes unlike those in the training data set was validated by comparison with in vivo dual-echo DSC-MRI data acquired in a separate cohort of patients with glioblastomas. Representative applications of the DRO are presented, including the selection of DSC-MRI acquisition and postprocessing methods that optimize CBV accuracy, determination of the impact of DSC-MRI methodology choices on sample size requirements, and the assessment of treatment response in clinical glioblastoma trials.

Contrast Leakage Patterns from Dynamic Susceptibility Contrast Perfusion MRI in the Grading of Primary Pediatric Brain Tumors

BACKGROUND AND PURPOSE

The pattern of contrast leakage from DSC tissue signal intensity time curves have shown utility in distinguishing adult brain neoplasms, but has limited description in the literature for pediatric brain tumors. The purpose of this study is to evaluate the utility of grading pediatric brain tumors with this technique.

MATERIALS AND METHODS

A retrospective review of tissue signal-intensity time curves from 63 pediatric brain tumors with preoperative DSC perfusion MR imaging was performed independently by 2 neuroradiologists. Tissue signal-intensity time curves were generated from ROIs placed in the highest perceived tumor relative CBV. The postbolus portion of the curve was independently classified as returning to baseline, continuing above baseline (T1-dominant contrast leakage), or failing to return to baseline (T2*-dominant contrast leakage). Interobserver agreement of curve classification was evaluated by using the Cohen κ. A consensus classification of curve type was obtained in discrepant cases, and the consensus classification was compared with tumor histology and World Health Organization grade.

RESULTS

Tissue signal-intensity time curve classification concordance was 0.69 (95% CI, 0.54-0.84) overall and 0.79 (95% CI, 0.59-0.91) for a T1-dominant contrast leakage pattern. Twenty-five of 25 tumors with consensus T1-dominant contrast leakage were low-grade (positive predictive value, 1.0; 95% CI, 0.83-1.00). By comparison, tumors with consensus T2*-dominant contrast leakage or return to baseline were predominantly high-grade (10/15 and 15/23, respectively) with a high negative predictive value (1.0; 95% CI, 0.83-1.0). For pilomyxoid or pilocytic astrocytomas, a T1-dominant leak demonstrated high sensitivity (0.91; 95% CI, 0.70-0.98) and specificity (0.90, 95% CI, 0.75-0.97).

CONCLUSIONS

There was good interobserver agreement in the classification of DSC perfusion tissue signal-intensity time curves for pediatric brain tumors, particularly for T1-dominant leakage. Among patients with pediatric brain tumors, a T1-dominant leakage pattern is highly specific for a low-grade tumor and demonstrates high sensitivity and specificity for pilocytic or pilomyxoid astrocytomas.

Neuroimaging

Imaging is integral to the management of patients with brain tumors. Conventional structural imaging provides exquisite anatomic detail but remains limited in the evaluation of molecular characteristics of intracranial neoplasms. Quantitative and physiologic biomarkers derived from advanced imaging techniques have been increasingly utilized as problem-solving tools to identify glioma grade and assess response to therapy. This chapter provides a comprehensive overview of the imaging strategies used in the clinical assessment of patients with gliomas and describes how novel imaging biomarkers have the potential to improve patient management.

Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy

Glioma are the most common supra-tentorial brain tumor in the USA with an estimated annual incidence of 17,000 new cases per year. Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MRI noninvasively characterizes tumor biology allowing for the diagnosis and therapeutic monitoring of glioma. This MRI technique utilizes the rapid changes in signal intensity caused by a rapid intravascular bolus of paramagnetic contrast agent to calculate physiologic perfusion metrics. DSC perfusion MRI has increasingly become an integrated part of glioma imaging. The specific aim of this article is to review the benefits of DSC perfusion MRI in the therapy of glioma.

Differentiation of primary central nervous system lymphoma from high-grade glioma and brain metastases using susceptibility-weighted imaging

BACKGROUND AND PURPOSE

Conventional MRI is often difficult to distinguish between primary central nervous system lymphomas (PCNSLs), high-grade gliomas and brain metastases due to the similarity of their appearance. The aim of this study was to investigate whether the susceptibility-weighted imaging (SWI) has higher sensitivity than conventional MRI in detecting hemorrhage between PCNSLs, high-grade gliomas and brain metastases, and can be used to differentiate the diagnosis between these tumors.

METHODS

The number of lesions with hemorrhage was quantified by both the conventional MR imaging and SWI. The number of micro-hemorrhage and vessels within lesions were counted on SWI.

RESULTS

The detection rate of hemorrhage on SWI was significantly higher than that on the conventional MR imaging. The intralesional hemorrhagic burden and the number of the vessels within lesions detected by SWI were significantly higher in high-grade gliomas and brain metastases than those in PCNSLs. There was no significant difference in these two parameters between high-grade gliomas and brain metastases. The best predictor to differentiate PCNSLs from high-grade gliomas and brain metastases was intralesional vessel number that yielded the best ROC characteristics and highest classification accuracy.

CONCLUSIONS

SWI is useful in differentiating of PCNSLs from high-grade gliomas and brain metastases.

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.

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.

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.

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.

Dynamic susceptibility contrast-enhanced MRI evaluation of cerebral intraventricular tumors: preliminary results

INTRODUCTION

The aims of the present study were to determine the perfusion characteristics of several types of intraventricular tumors and to evaluate the usefulness of dynamic contrast-enhanced MRI in making the differential diagnosis.

METHODS

A total of 28 patients with intraventricular tumors (five meningiomas, five papillomas, three ependymomas, four subependymomas, seven central neurocytomas, two subependymal giant cell astrocytomas and two metastases) underwent conventional and dynamic susceptibility contrast-enhanced MRI. Cerebral blood volume (CBV) maps were obtained and the relative CBV (rCBV) calculated for each tumor. Mean rCBV(max) values were compared across the different types of tumors (ANOVA, P=0.05).

RESULTS

Intraventricular tumors presented with three different patterns of vascularization: highly vascularized tumors (mean rCBV(max)>3), including papillomas, meningiomas and renal carcinoma metastases; poorly vascularized tumors (mean rCBV(max)<2), including ependymomas and subependymomas; and intermediately vascularized tumors (mean rCBV(max)>2 but<3), including central neurocytomas and lung metastases. There was a significant difference between the highly vascularized (papillomas, meningiomas) and poorly vascularized (subependymomas) tumors. In cases of suspected meningioma, papilloma or neurocytoma, low rCBV values (<3) point to a diagnosis of neurocytoma rather than either of the other tumor types.

CONCLUSION

Susceptibility contrast-enhanced MRI can provide additional information on the vascularization of intraventricular cerebral tumors and may help in making the differential diagnosis.

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.

Neuroimaging in neuro-oncology

Neuroimaging of brain tumors has evolved from a strictly morphology-based discipline to one that encompasses function, physiology, and anatomy. This review outlines the current imaging standard for patients with brain tumor and summarizes the latest advances in physiology-based imaging methods that complement traditional brain tumor imaging protocols. Emphasis is on the strength and limitations of the current imaging standards and on an overview of several advanced imaging methods including diffusion-weighted magnetic resonance imaging (MRI), perfusion MRI, and proton magnetic resonance spectroscopic (MRS) imaging. Basic physical principles behind each imaging method are briefly presented, along with a more in-depth discussion of clinical application and potential pitfalls of each technique.

Perfusion Weighted MR Imaging may Differentiate Primary CNS Lymphoma from other Homogeneously Enhancing Brain Tumors

Primary central nervous system lymphoma (PCNSL), glioblastoma multiforme (GBM) and metastases may be difficult to differentiate based on conventional imaging alone. The aim of this study was to investigate the value of perfusion weighted imaging (PWI) in differentiating homogeneously enhancing PCNSL from homogeneously enhancing GBM and metastases. Seven consecutive patients presenting with homogeneously enhancing intraaxial tumors on MRI were retrospectively analyzed. All seven patients (three immunocompetent patients with PCNSL, three with GBM, and one with cerebral metastases) were examined with identical MR-sequences including PWI. The relative regional Cerebral Blood Volume (rrCBV) and the rrCBV ratio (rrCBVratio) were calculated. In lymphomas rrCBVratio was 0.93 ± 0.42 (mean ± SD) compared with 7.93 ± 1.44 in GBM and metastases. All lymphomas had rrCBVratio < 1.43 while all GBM and metastases had rrCBVratio > 1.43 (Fischer exact test; p < 0.001). PWI may be a valuable method in differentiating homogenously enhancing PCNSL from GBM and metastases.

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.

Perfusion-sensitive MRI of pilocytic astrocytomas: initial results

PURPOSE

To present the imaging and perfusion data obtained in nine patients with pilocytic astrocytomas (PA) and to discuss the original functional issues of this technique.

METHOD

Nine patients with pathologically proven PA underwent conventional and perfusion MR imaging. Various areas of relative cerebral blood volume (rCBV) within the tumors were obtained. The maximum rCBV ratios were identified and considered as representative of the tumor. The results were compared with the pathological findings.

RESULTS

In all patients, rCBV was <1.5 (mean 1) and the signal intensity curve overshot the baseline.

CONCLUSION

PA tend to have low rCBV values and a first-pass curve that crosses the baseline. These characteristics may be explained by the histological profile of the tumoral vascularity and are of relevance in the identification of these rare tumors.

Evaluation of different cerebral mass lesions by perfusion-weighted MR imaging

PURPOSE

To investigate the contribution of perfusion-weighted MR imaging (PWI) by using the relative cerebral blood volume (rCBV) ratio in the differential diagnosis of various intracranial space-occupying lesions.

MATERIALS AND METHODS

This study involved 105 patients with lesions (high-grade glioma (N=26), low-grade glioma (N=11), meningioma (N=23), metastasis (N=25), hemangioblastoma (N=6), pyogenic abscess (N=4), schwannoma (N=5), and lymphoma (N=5)). The patients were examined with a T2*-weighted (T2*W) gradient-echo single-shot EPI sequence. The rCBV ratios of the lesions were obtained by dividing the values obtained from the normal white matter. Statistical analysis was performed with the Mann-Whitney U-test. A P-value less than 0.05 was considered statistically significant.

RESULTS

The rCBV ratio was 5.76+/-3.35 in high-grade gliomas, 1.69+/-0.51 in low-grade gliomas, 8.02+/-3.89 in meningiomas, 5.27+/-3.22 in metastases, 11.36+/-4.41 in hemangioblastomas, 0.76+/-0.12 in abscesses, 1.10+/-0.32 in lymphomas, and 3.23+/-0.81 in schwannomas. The rCBV ratios were used to discriminate between 1) high- and low-grade gliomas (P<0.001), 2) hemangioblastomas and metastases (P<0.05), 3) abscesses from high-grade gliomas and metastases (P<0.001), 4) schwannomas and meningiomas (P<0.001), 5) lymphomas from high-grade gliomas and metastases (P<0.001), and 6) typical meningiomas and atypical meningiomas (P<0.01).

CONCLUSION

rCBV ratios can help discriminate intracranial space-occupying lesions by demonstrating lesion vascularity. It is possible to discriminate between 1) high- and low-grade gliomas, 2) hemangioblastomas and other intracranial posterior fossa masses, 3) abscesses from high-grade gliomas and metastases, 4) schwannomas and meningiomas, 5) lymphomas and high-grade gliomas and metastases, and 6) typical and atypical meningiomas.

FAIR-TrueFISP imaging of cerebral perfusion in areas of high magnetic susceptibility differences at 1.5 and 3 Tesla

PURPOSE

To estimate cerebral blood perfusion in areas of strong magnetic susceptibility changes with high spatial and temporal resolution using a flow-sensitive alternating inversion recovery (FAIR) arterial spin labeling (ASL) method.

MATERIALS AND METHODS

We implemented an ASL method that is capable of imaging perfusion in areas of high magnetic susceptibility changes by combining a FAIR spin preparation with a true fast imaging in steady precession (TrueFISP) data acquisition strategy. A TrueFISP readout sequence was applied especially in regions with magnetic field inhomogeneities and compared with corresponding FAIR measurements obtained with a standard echo-planar imaging (EPI) readout. Quantitative perfusion images were obtained at 1.5 Tesla (1.5T) from eight healthy volunteers (24-42 years old) and one patient (23 years old). FAIR-TrueFISP perfusion images were compared with FAIR echo-planar images. T1 maps, which are necessary for quantitative perfusion estimation, were obtained with inversion recovery (IR) TrueFISP and IR EPI. Additionally, high-resolution perfusion measurements were performed on four volunteers at 3T.

RESULTS

The two ASL perfusion imaging modalities yielded comparable diagnostic image quality in brain areas with low susceptibility differences at 1.5T. Cerebral perfusion of gray matter (GM) areas was 105.7 +/- 5.2 mL/100 g/minute for FAIR-TrueFISP and 88.8 +/- 14.6 mL/100 g/minute for FAIR-EPI at 1.5T, and 70.4 +/- 7.1 mL/100 g/minute for FAIR-TrueFISP and 63.5 +/- 6.9 mL/100 g/minute for FAIR-EPI at 3.0T. Higher perfusion values at 1.5T were due to more pronounced partial-volume effects from fast moving spins at lower spatial resolution. The FAIR-TrueFISP sequence showed no significant distortions and markedly reduced signal void artifacts in areas of high susceptibility changes (e.g., near brain-bone transitions and close to metallic clips) compared to FAIR-EPI. At 3T, highly resolved FAIR-TrueFISP perfusion images were acquired with an in-plane resolution of up to 1.3 mm.

CONCLUSION

FAIR-TrueFISP allows for assessment of cerebral perfusion in areas of critically high susceptibility changes with conventional ASL methods.

Spectroscopie 1H, perfusion, diffusion : quelle place pour ces techniques lors du diagnostic et du suivi des principales tumeurs cérébrales sus-tentorielles de l’adulte ?

INTRODUCTION

In a few years, magnetic resonance imaging (MRI) has evolved from a morphology-based examination to one that encompasses metabolism and function.

STATE OF ART

MRI is a well-established tool for the initial evaluation of brain tumors, but conventional MR sequences have some limitations. Conventional MRI is unable to distinguish high-grade glioma from metastasis and abscess, to define precisely the histopathological grade of gliomas, to determine exactly the limits of tumor extension, to characterize meningeal tumors. Differentiation of tumor recurrence from treatment-related changes may be difficult with standard MR imaging because the interpretation is essentially based on volume analysis.

PERSPECTIVES

1H Spectroscopy, diffusion and perfusion imaging become possible with the development of MR imagers and can be routinely performed in clinical settings. They give complementary information about tumor metabolism and vascularity and allow a better analysis of post-treatment modifications. Functional and metabolic explorations should be used to characterize brain tumors.

IRM de diffusion-perfusion dans l’évaluation des lymphomes cérébraux

Because of the increasing incidence of cerebral lymphoma, it is critical for patient management to recognize the MR features of this disease. We present the characteristic morphological and functional MRI features of this tumor. The findings on MRI studies, including morphological, diffusion and perfusion imaging, performed in 9 biopsy-proven cases of cerebral lymphoma with 13 lesions are presented and analyzed, and are discussed in comparison with published literature data. All patients underwent diffusion-weighted imaging with a single shot echo-planar pulse sequence. Dynamic susceptibility-contrast MRI was performed using a T2*-weighted gradient-echo echo-planar sequence after intravenous injection of chelates of gadolinium at the rate of 6 ml/s and a temporal resolution of 1 second. All cases of cerebral lymphoma appeared hypointense or isointense on T1-weighted images and in 75% of cases iso- or hypointense on T2-weighted images. All lesions enhanced except one in a patient receiving steroid therapy. On diffusion-weighted images, tumours were hyperintense with normal or decreased ADC values (0.717+/-0.152.10-3 mm2/sec, range: 0.550-1.014) and an ADC ratio tumour/normal white matter of 0.974+/-0.190 (range: 0.768-1.410). On perfusion, the signal intensity-time curve of each tumour showed a characteristic type of curve with a significant increase of the signal intensity above the baseline and a low maximum relative cerebral blood volume ratio (rCVBmax) of 1.43+/-0.64 (0.55-2.62). Due to their higher cellularity, the lack of neoangiogenesis, and the increased permeability of the blood-brain barrier related to the infiltration of blood vessels wall by lymphomatous cells, cerebral lymphoma presents characteristic diffusion and perfusion MRI features that should be useful for diagnosis and patient follow-up.

Comparison of first-pass and second-bolus dynamic susceptibility perfusion MRI in brain tumors

INTRODUCTION

Our goal was to evaluate whether the T1 shortening effect caused by contrast leakage into brain tumors, a well-known confounding effect in the quantification of relative cerebral blood volume (rCBV) measurements, may be corrected by the administration of a predose of gadolinium-DTPA.

METHODS

As part of their presurgical imaging protocol, 25 patients with primary brain tumors underwent two consecutive dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR studies. Intratumoral rCBV measurements and normalized rCBV values obtained during the first-pass and second-bolus studies were compared (Wilcoxon signed-ranks test). The frequency of relatively increased rCBV ratios on the second-bolus study was compared between enhancing and non-enhancing neoplasms (Fisher's exact test). Postprocessing perfusion studies were evaluated for image quality on a scale of 0-3 (Wilcoxon signed-ranks test). Four studies were excluded due to unacceptable image quality.

RESULTS

Mean normalized rCBVs were 9.04 (SD 4.64) for the first-pass and 7.99 (SD 3.84) for the second-bolus study. There was no statistically significant difference between the two perfusion studies in either intratumoral rCBV (P=0.237) or rCBV ratio (P=0.181). Five enhancing and four non-enhancing tumors showed a relative increase in rCBV ratio on the second-bolus study, without a significant difference between the groups. Image quality was not significantly different between perfusion studies.

CONCLUSION

Our results did not demonstrate a significant difference between first-pass and second-bolus rCBV measurements in DSC perfusion MR imaging. The administration of a predose of gadolinium-DTPA does not appear to be an efficient way of compensating for the underestimation of intratumoral rCBV values due to the T1 shortening effect.

Dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in pediatric patients

Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR (pMR) imaging provides hemodynamic information that complements traditional structural MR imaging and is becoming increasingly used in clinical practice to diagnose, manage, and understand brain tumors in the pediatric patient group. pMR imaging-derived regional cerebral blood volume (rCBV) maps provide quantitative estimates of rCBV that can be used to grade gliomas, differentiate between different brain tumor types, and distinguish tumor from nonneoplastic lesions. There are a few minor limitations of the DSC pMR imaging technique, such as susceptibility artifacts, relative rather than absolute quantification of cerebral blood volume (CBV), and inaccurate estimation of CBV in situations of severe disruption or absence of the blood-brain barrier. Recognizing its strengths and potential pitfalls, pMR imaging can be used as part of the routine evaluation of brain tumors to improve the diagnostic accuracy, understand tumor pathophysiology, detect and quantify tumor angiogenesis, and, with further work, serve as an arbiter to assess existing and novel cancer therapies that target blood vessels.

[Perfusion measurement using the T2* contrast media dynamics in neuro-oncology. Physical basics and clinical applications]

Perfusion imaging in the central nervous system (CNS) is mostly performed using the first-pass dynamic susceptibility-weighted contrast-enhanced (DSC) MRI. The first-pass of a contrast bolus in brain tissue is monitored by a series of T2*-weighted MR images. The susceptibility effect of the paramagnetic contrast agent leads to a signal loss that can be converted, using the principles of the indicator dilution theory, into an increase of the contrast agent concentration. From these data, parameter maps of cerebral blood volume (CBV) and flow (CBF) can be derived. Regional CBF and CBV values can be obtained by region-of-interest analysis. This review article describes physical basics of DSC MRI and summarizes the literature of DSC MRI in neurooncological issues.Studies, all with relatively limited patient numbers, report that DSC MRI is useful in the preoperative diagnosis of gliomas, CNS-lymphomas, and solitary metastases, as well as in the differentiation of these neoplastic lesions from infections and tumor-like manifestations of demyelinating disease. Additionally, DSC MRI is suitable for determining glioma grade and regions of active tumor growth which should be the target of stereotactic biopsy. After therapy, DSC MRI helps better assessing the tumor response to therapy, residual tumor after therapy, and possible treatment failure and therapy-related complications, such as radiation necrosis. The preliminary results show that DSC MRI is a diagnostic tool depicting regional variations in microvasculature of normal and diseased brains.

Update on brain tumor imaging

Brain tumor imaging has evolved from a strictly morphology-based discipline to one that encompasses function, physiology, and anatomy, enabled by advances in imaging and computer technology. This review outlines the current imaging standard for patients with brain tumors and summarizes the latest advances in physiology-based imaging methods that complement traditional brain tumor imaging protocol. Emphasis is placed on the strengths and limitations of the current imaging standards and on an overview of several advanced imaging methods, including diffusion-weighted magnetic resonance imaging, perfusion magnetic resonance imaging, and proton magnetic resonance spectroscopic imaging. Basic physical principles behind each imaging method are briefly presented, along with a more in-depth discussion of the clinical applications and potential pitfalls of each technique.

Perfusion MR imaging of brain tumors

Brain tumors rank second as the cause of cancer-related deaths in children and adults younger than 34 years old, and they are seen in adults of all ages. Primary malignant brain tumors are associated with the third highest cancer-related mortality rate and a disproportionate level of disability and morbidity. Considering this, accurate diagnosis and grading of brain tumors are critical to determining prognosis and therapy. Equally important is to evaluate for tumor status during therapy to assess for therapeutic response and treatment-related complications. Brain tumors can be characterized as a heterogeneous group of neoplasm with a correspondingly wide variation in malignant phenotype and a diverse array of imaging features. Magnetic resonance (MR) imaging with intravenous contrast agent is the test of choice to diagnose and monitor brain tumors before, during, and after therapy. Recent advances in imaging methods such as diffusion-weighted imaging, perfusion imaging, and spectroscopic imaging all have in common the ability to provide quantitative cellular, hemodynamic, and metabolic information that may enhance our understanding of brain tumor biology, help us to better assess treatment response, more accurately determine tumor activity during therapy, and differentiate recurrent tumor and treatment related complications. In this article, we will review the basics of brain tumor imaging and focus on the role of perfusion MR imaging in improving accurate diagnosis and monitoring brain tumors during therapy. Both strengths and shortcomings of perfusion MR imaging over standard anatomic MR imaging will be discussed as will important pitfalls of the technique.

Perfusion MR imaging: basic principles and clinical applications

Dynamic contrast-enhanced perfusion MR imaging provides hemodynamic information that complements traditional structural imaging and is increasingly used in clinical practice to diagnose, manage, and understand brain tumors. Relative cerebral blood volume maps derived from perfusion MR imaging data provide quantifiable estimates of regional blood volume that can be used to grade gliomas, differentiate different brain tumor types, and distinguish tumors from non-neoplastic lesions. There are a few minor limitations of the dynamic contrastenhanced perfusion MR imaging technique-susceptibility artifacts, relative rather than absolute quantification of cerebral blood volume, and the inaccurate estimation of cerebral blood volume in patients in whom the blood-brain barrier has been severely disrupted or destroyed. Despite the minor potential pitfalls of the technique, inclusion of perfusion MR imaging as part of a routine evaluation of brain tumors can lead to improved diagnostic accuracy, understanding of tumor pathophysiology, and detection and quantification of tumor angiogenesis. With further work, perfusion MR imaging could be used to assess existing and novel cancer therapies that target blood vessels.

Dynamic contrast enhanced perfusion MRI in mycosis fungoides

Mycosis fungoides is a malignant, cutaneous lymphoma of T-helper (TH or CD4+) cells. At presentation, the disease is usually limited to the skin, with lesions that resemble eczema or psoriasis. Neurologic involvement is uncommon. This case demonstrates the conventional MRI and dynamic contrast enhanced perfusion MRI findings in intracerebral mycosis fungoides. T1-weighted spin echo imaging demonstrated a lesion with slightly decreased signal within the body of the corpus callosum. The lesion was isointense with grey matter on axial T2-weighted imaging. Following administration of contrast, there was patchy heterogeneous enhancement. Multiple relative cerebral blood volume (rCBV) measurements were made and the minimum rCBV was 0.30 with the maximum rCBV being 1.61. The mean rCBV was 0.81 +/- 0.49 (average of 10 measurements and standard deviation).

Distinguishing of primary cerebral lymphoma from high-grade glioma with perfusion-weighted magnetic resonance imaging

To assess the usefulness of perfusion-weighted echo-planar magnetic resonance imaging in the differential diagnosis of primary supratentorial lymphoma (PCNSL) and glioblastoma (GBM), 12 patients with a PCNSL and 12 with a GBM were examined using a 1.5 T magnetic resonance (MR) imager. With dynamic-susceptibility contrast MR imaging the intensity-time curves of each tumor were analyzed, and we determined the relative regional cerebral blood volume ratios (rrCBV [tumor/contralateral white matter (WM)]) to find out whether these parameters could be used to separate PCNSL from GBM. The maximum rrCBV ratio in the PCNSL was significantly lower than that of the GBM (P<0.0001). Comparing the intensity-time curves for the two tumor groups, the PCNSL showed a characteristic type of curve with a significant increase in signal intensity above the baseline due to massive leakage of contrast media into the interstitial space. PCNSL tend to have low maximum CBV ratios and typical intensity-time curves. These two parameters may be useful in distinguishing PCNSL from GBM.

Perfusion MR imaging: clinical utility for the differential diagnosis of various brain tumors

Objective

To determine the utility of perfusion MR imaging in the differential diagnosis of brain tumors.

Materials and Methods

Fifty-seven patients with pathologically proven brain tumors (21 high-grade gliomas, 8 low-grade gliomas, 8 lymphomas, 6 hemangioblastomas, 7 metastases, and 7 various other tumors) were included in this study. Relative cerebral blood volume (rCBV) and time-to-peak (TTP) ratios were quantitatively analyzed and the rCBV grade of each tumor was also visually assessed on an rCBV map.

Results

The highest rCBV ratios were seen in hemangioblastomas, followed by high-grade gliomas, metastases, low-grade gliomas, and lymphomas. There was no significant difference in TTP ratios between each tumor group (p>0.05). At visual assessment, rCBV was high in 17 (81%) of 21 high-grade gliomas and in 4 (50%) of 8 low-grade gliomas. Hemangioblastomas showed the highest rCBV and lymphomas the lowest.

Conclusion

Perfusion MR imaging may be helpful in the differentiation of thevarious solid tumors found in the brain, and in assessing the grade of the various glial tumors occurring there.

Intracranial mass lesions: dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging

Dynamic contrast agent-enhanced perfusion magnetic resonance (MR) imaging provides physiologic information that complements the anatomic information available with conventional MR imaging. Analysis of dynamic data from perfusion MR imaging, based on tracer kinetic theory, yields quantitative estimates of cerebral blood volume that reflect the underlying microvasculature and angiogenesis. Perfusion MR imaging is a fast and robust imaging technique that is increasingly used as a research tool to help evaluate and understand intracranial disease processes and as a clinical tool to help diagnose, manage, and understand intracranial mass lesions. With the increasing number of applications of perfusion MR imaging, it is important to understand the principles underlying the technique. In this review, the essential underlying physics and methods of dynamic contrast-enhanced susceptibility-weighted echo-planar perfusion MR imaging are described. The clinical applications of cerebral blood volume maps obtained with perfusion MR imaging in the differential diagnosis of intracranial mass lesions, as well as the pitfalls and limitations of the technique, are discussed. Emphasis is on the clinical role of perfusion MR imaging in providing insight into the underlying pathophysiology of cerebral microcirculation.

Discrimination of an infected brain tumor from a cerebral abscess by combined MR perfusion and diffusion imaging

The aim of this study was to investigate the signal characteristics of the abscess wall and tumor wall on diffusion-weighted and perfusion-weighted images and thus to evaluate the feasibility of using combined MR diffusion and perfusion imaging to differentiate pyogenic cerebral abscess from infected brain tumor. The tumor wall of various types of cystic or necrotic brain tumor was significantly hyperintense relative to that of cerebral abscess wall on both diffusion-weighted images and regional cerebral blood volume maps. Sixteen patients who had cerebral masses with large cystic or necrotic cavities were imaged to generate diffusion-weighted images and regional cerebral blood volume maps using single-shot echoplanar imaging (EPI) pulse sequences. Apart from qualitative analysis, apparent diffusion coefficients (ADC) as well as regional cerebral blood volume (rCBV) ratios were calculated from the abscess wall and peripheral tumor wall and comparison was made by using Student's t-test. The tumor wall of various types of cystic or necrotic brain tumor had significantly lower ADCs relative to those of the abscess wall (P<0.005) and thus appeared relatively hyperintense on diffusion-weighted images. The mean rCBV ratio relative to normal white matter (2.90+/-0.62) of the peripheral tumor wall of various types of cystic or necrotic brain tumor were significantly larger than the mean rCBV ratio (0.45+/-0.11) of the pyogenic cerebral abscess wall (P<0.001) by Student's t-test. It is concluded that the combined MR diffusion and perfusion imaging might be capable of differentiating an infected brain tumor from a pyogenic cerebral abscess.