Dynamic CT perfusion imaging of intra-axial brain tumours: differentiation of high-grade gliomas from primary CNS lymphomas

Early and delayed blood-brain barrier permeability predicts delayed cerebral ischemia and outcomes following aneurysmal subarachnoid hemorrhage

OBJECTIVES

This study aimed to monitor blood-brain barrier permeability within 24 h and during the delayed cerebral ischemia (DCI) time window (DCITW) spanning 4-14 days after aneurysmal subarachnoid hemorrhage (aSAH) and to investigate its correlation with both DCI occurrence and outcomes at three months.

METHODS

A total of 128 patients were stratified based on the DCI occurrence and three-month modified Rankin scale scores. Comparison of Ktrans at admission (admission Ktrans) and during DCITW (DCITW Ktrans) was conducted between DCI and non-DCI groups, as well as between groups with good and poor outcomes. Changes in Ktrans were also analyzed. Multivariate logistic regression analysis was performed to identify independent predictors of DCI and poor outcomes.

RESULTS

Admission Ktrans (0.58 ± 0.18 vs 0.47 ± 0.12, p = 0.002) and DCITW Ktrans (0.54 ± 0.19 vs 0.41 ± 0.14, p < 0.001) were significantly higher in the DCI group compared with the non-DCI group. Although both were higher in the poor outcome group than the good outcome group, the difference was not statistically significant at admission (0.53 ± 0.18 vs 0.49 ± 0.14, p = 0.198). Ktrans in the non-DCI group (0.47 ± 0.12 vs 0.41 ± 0.14, p = 0.004) and good outcome group (0.49 ± 0.14 vs 0.41 ± 0.14, p < 0.001) decreased significantly from the admission to DCITW. Multivariate analysis identified DCITW Ktrans and admission Ktrans as independent predictors of poor outcomes (OR = 1.73, 95%CI: 1.24-2.43, p = 0.001) and DCI (OR = 1.75, 95%CI: 1.25-2.44, p = 0.001), respectively.

CONCLUSION

Elevated Ktrans at admission is associated with the occurrence of DCI. Continuous monitoring of Ktrans from admission to DCITW can accurately identify reversible and irreversible changes and can predict outcomes at 3 months.

CLINICAL RELEVANCE STATEMENT

Ktrans measured with CT perfusion is a valuable tool for predicting both delayed cerebral ischemia and three-month outcomes following aneurysmal subarachnoid hemorrhage. Monitoring changes in Ktrans from admission to time window of delayed cerebral ischemia can guide treatment and management decisions for aneurysmal subarachnoid hemorrhage patients.

KEY POINTS

• Ktrans measured at admission and during the delayed cerebral ischemia time window (4-14 days) holds distinct clinical significance following aneurysmal subarachnoid hemorrhage. • Admission Ktrans serves as a predictor for delayed cerebral ischemia, while continuous assessment of Ktrans from admission to the delayed cerebral ischemia time window can predict three-month outcomes. • Monitoring Ktrans at different stages improves instrumental in enhancing decision-making and treatment planning for patients with aneurysmal subarachnoid hemorrhage.

Diagnostic Algorithm for Intracranial Lesions in the Emergency Department: Effectiveness of the Relative Brain Volume and Hounsfield Unit Value Measured by Perfusion Tomography

Background Early treatment of intracranial lesions in the emergency department is crucial, but it can be challenging to differentiate between them. This differentiation is essential because the treatment of each type of lesion is different. Cerebral computed tomography perfusion (CTP) imaging can help visualize the vascularity of brain lesions and provide absolute quantification of physiological parameters. Compared to magnetic resonance imaging, CTP has several advantages, such as simplicity, wide availability, and reproducibility. Purpose This study aimed to assess the effectiveness of Hounsfield units (HU) in measuring the density of hypercellular lesions and the ability of CTP to quantify hemodynamics in distinguishing intracranial space-occupying lesions. Methods A retrospective study was conducted from March 2016 to March 2022. All patients underwent CTP and CT scans, and relative cerebral blood volume (rCBV) and HU were obtained for intracranial lesions. Results We included a total of 244 patients in our study. This group consisted of 87 (35.7%) individuals with glioblastomas (GBs), 48 (19.7%) with primary central nervous system lymphoma (PCNSL), 45 (18.4%) with metastases (METs), and 64 (26.2) with abscesses. Our study showed that the HUs for METs were higher than those for GB (S 57.4% and E 88.5%). In addition, rCBV values for PCNSL and abscesses were lower than those for GB and METs. The HU in PCNSL was higher than those in abscesses (S 94.1% and E 96.6%). Conclusion PCT parameters provide valuable information for diagnosing brain lesions. A comprehensive assessment improves accuracy. Combining rCBV and HU enhances diagnostic accuracy, making it a valuable tool for distinguishing between lesions. PCT's widespread availability allows for the use of both anatomical and functional information with high spatial resolution for diagnosing and managing brain tumor patients.

Machine Learning and Deep Learning CT-Based Models for Predicting the Primary Central Nervous System Lymphoma and Glioma Types: A Multicenter Retrospective Study

Purpose and Background

Distinguishing primary central nervous system lymphoma (PCNSL) and glioma on computed tomography (CT) is an important task since treatment options differ vastly from the two diseases. This study aims to explore various machine learning and deep learning methods based on radiomic features extracted from CT scans and end-to-end convolutional neural network (CNN) model to predict PCNSL and glioma types and compare the performance of different models.

Methods

A total of 101 patients from five Chinese medical centers with pathologically confirmed PCNSL and glioma were analyzed retrospectively, including 50 PCNSL and 51 glioma. After manual segmentation of the region of interest (ROI) on CT scans, 293 radiomic features of each patient were extracted. The radiomic features were used as input, and then, we established six machine learning models and one deep learning model and three readers to identify the two types of tumors. We also established a 2D CNN model using raw CT scans as input. The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) were used to evaluate different models.

Results

The cohort was split into a training (70, 70% patients) and validation cohort (31,30% patients) according to the stratified sampling strategy. Among all models, the MLP performed best, with an accuracy of 0.886 and 0.903, sensitivity of 0.914 and 0.867, specificity of 0.857 and 0.937, and AUC of 0.957 and 0.908 in the training and validation cohorts, respectively, which was significantly higher than the three primary physician's diagnoses (ACCs ranged from 0.710 to 0.742, p &lt; 0.001 for all) and comparable with the senior radiologist (ACC 0.839, p = 0.988). Among all the machine learning models, the AUC ranged from 0.605 to 0.821 in the validation cohort. The end-to-end CNN model achieved an AUC of 0.839 and an ACC of 0.840 in the validation cohort, which had no significant difference in accuracy compared to the MLP model (p = 0.472) and the senior radiologist (p = 0.470).

Conclusion

The established PCNSL and glioma prediction model based on deep neural network methods from CT scans or radiomic features are feasible and provided high performance, which shows the potential to assist clinical decision-making.

Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading

Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.

Whole-Brain Permeability Analysis on Admission Improves Prediction of Delayed Cerebral Ischemia Following Aneurysmal Subarachnoid Hemorrhage

PURPOSE

To evaluate the changes of blood-brain barrier permeability (BBBP) after aneurysmal subarachnoid hemorrhage (aSAH) and find out whether BBBP within 24 h after onset can further improve prediction of delayed cerebral ischemia (DCI).

METHODS

CT perfusion (CTP) was performed within 24 h after onset and in the DCI time window (DCITW). Whole brain average values of flow extraction product (mK^trans), qualitative and quantitative CTP parameters, and clinical data were compared between DCI and non-DCI groups. The changes of mK^trans were analysed using a Paired t test. Multivariate logistic regression analysis and ROC analyses were performed to identify predictors of DCI and evaluate the predictive performance.

RESULTS

One hundred and forty of 179 consecutive patients were included, 45 of whom (32%) developed DCI. mK^trans was higher in the DCI group both on admission and in the DCITW (P<0.001). mK^trans decreased significantly in the non-DCI group (P=0.003), but not in DCI group (P=0.285). Multivariate logistic regression analysis showed that mK^trans (OR=1.07, 95%CI: 1.03-1.11, P<0.001), World Federation of Neurosurgery Scale (OR=6.73, 95%CI: 1.09-41.41, P=0.040), Hunt-Hess grade (OR=0.16, 95%CI: 0.02-1.19, P=0.073), modified Fisher Score (OR=3.74, 95%CI: 1.30-10.75, P=0.014), and qualitative CTP (OR=4.31, 95%CI: 1.49-12.47, P=0.007) were independent predictors of DCI. The model with K^trans produced a larger AUC of 0.88 (95%CI: 0.81-0.95), with corresponding sensitivity and specificity of 84% and 86%, respectively.

CONCLUSION

BBBP measurement within 24 h after onset can improve the prediction of DCI. Early moderate BBB disruption may be reversible, whereas severe BBBP disruption indicates the risk of DCI.

A simple model for glioma grading based on texture analysis applied to conventional brain MRI

Accuracy of glioma grading is fundamental for the diagnosis, treatment planning and prognosis of patients. The purpose of this work was to develop a low-cost and easy-to-implement classification model which distinguishes low-grade gliomas (LGGs) from high-grade gliomas (HGGs), through texture analysis applied to conventional brain MRI. Different combinations of MRI contrasts (T1Gd and T2) and one segmented glioma region (necrotic and non-enhancing tumor core, NCR/NET) were studied. Texture features obtained from the gray level size zone matrix (GLSZM) were calculated. An under-sampling method was proposed to divide the data into different training subsets and subsequently extract complementary information for the creation of distinct classification models. The sensitivity, specificity and accuracy of the models were calculated, and the best model explicitly reported. The best model included only three texture features and reached a sensitivity, specificity and accuracy of 94.12%, 88.24% and 91.18%, respectively. According to the features of the model, when the NCR/NET region was studied, HGGs had a more heterogeneous texture than LGGs in the T1Gd images, and LGGs had a more heterogeneous texture than HGGs in the T2 images. These novel results partially contrast with results from the literature. The best model proved to be useful for the classification of gliomas. Complementary results showed that the heterogeneity of gliomas depended on the MRI contrast studied. The chosen model stands out as a simple, low-cost, easy-to-implement, reproducible and highly accurate glioma classifier. Importantly, it should be accessible to populations with reduced economic and scientific resources.

Is There a Direct Correlation Between Microvascular Wall Structure and k-Trans Values Obtained From Perfusion CT Measurements in Lymphomas?

RATIONALE AND OBJECTIVES

This study aimed to test the hypothesis that ultrastructural wall abnormalities of lymphoma vessels correlate with perfusion computed tomography (PCT) kinetics.

MATERIALS AND METHODS

Our local institutional review board approved this prospective study. Between February 2013 and June 2016, we included 23 consecutive subjects with newly diagnosed lymphoma, who were referred for computed tomography-guided biopsy (6 women, 17 men; mean age, 60.61 ± 12.43 years; range, 28-74 years) and additionally agreed to undergo PCT of the target lymphoma tissues. PCT was obtained for 40 seconds using 80 kV, 120 mAs, 64 × 0.6-mm collimation, 6.9-cm z-axis coverage, and 26 volume measurements. Mean and maximum k-trans (mL/100 mL/min), blood flow (BF; mL/100 mL/min) and blood volume (BV) were quantified using the deconvolution and the maximum slope + Patlak calculation models. Immunohistochemical staining was performed for microvessel density quantification (vessels/m²), and electron microscopy was used to determine the presence or absence of tight junctions, endothelial fenestration, basement membrane, and pericytes, and to measure extracellular matrix thickness.

RESULTS

Extracellular matrix thickness as well as the presence or absence of tight junctions, basal lamina, and pericytes did not correlate with computed tomography perfusion parameters. Endothelial fenestrations correlated significantly with mean BF_{deconvolution} (P = .047, r = 0.418) and additionally was significantly associated with higher mean BV_{deconvolution} (P < .005). Mean k-trans_Patlak correlated strongly with mean k-trans_{deconvolution} (r = 0.939, P = .001), and both correlated with mean BF_{deconvolution} (P = .001, r = 0.748), max BF_{deconvolution} (P = .028, r = 0.564), mean BV_{deconvolution} (P = .001, r = 0.752), and max BV_{deconvolution} (P = .001, r = 0.771). Microvessel density correlated with max k-trans_{deconvolution} (r = 0.564, P = .023). Vascular endothelial growth factor receptor-3 expression (receptor specific for lymphatics) correlated significantly with max k-trans_Patlak (P = .041, r = 0.686) and mean BF_{deconvolution} (P = .038, r = 0.695).

CONCLUSION

k-Trans values of PCT do not correlate with ultrastructural microvessel features, whereas endothelial fenestrations correlate with increased intra-tumoral BVs.

Imaging features (CT, MRI, MRS, and PET/CT) of primary central nervous system lymphoma in immunocompetent patients

Background

Because of the low incidence of primary central nervous system lymphoma (PCNSL) in non-HIV individuals and because of the lack of specific clinical manifestations and auxiliary examinations, the disease is easily missed or misdiagnosed.

Objective

To analyze the imaging features of PCNSL in non-HIV patients.

Methods

This was a retrospective study of patients with PCNSL treated between January 2001 and December 2011 at the Naval General Hospital (Beijing, China). All included patients were pathologically diagnosed with PCNSL. Specimens were obtained by stereotactic biopsy and diagnosed by pathological examination. Serological panel had to be negative for HIV.

Results

Out of the 118 patients, 73 (61.9%) were male and 45 (38.1%) were female. Median age was 54 (range 11–83) years. All patients had B cell lymphoma. The lesions showed slightly hyperintense shadows on computed tomography (CT) images, and mostly hyperintense T1 and iso- or hyperintense T2 signals on magnetic resonance imaging (MRI). Most lesions showed patchy enhancement after enhanced scanning, and some had the characteristic “butterfly sign” on enhanced MRI. The magnetic resonance spectroscopy of PCNSL manifested as increased Cho peak, moderately decreased NAA peak, and slightly decreased Cr peak. Positron emission computed tomography indicated high metabolism of ¹⁸F-FDG in PCNSL lesions.

Conclusion

MRI is important in the diagnosis of PCNSL. Understanding the imaging features of PCNSL will help improve its diagnosis in clinics.

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.

Local Glioma Cells Are Associated with Vascular Dysregulation

BACKGROUND AND PURPOSE

Malignant glioma is a highly infiltrative malignancy that causes variable disruptions to the structure and function of the cerebrovasculature. While many of these structural disruptions have known correlative histopathologic alterations, the mechanisms underlying vascular dysfunction identified by resting-state blood oxygen level-dependent imaging are not yet known. The purpose of this study was to characterize the alterations that correlate with a blood oxygen level-dependent biomarker of vascular dysregulation.

MATERIALS AND METHODS

Thirty-two stereotactically localized biopsies were obtained from contrast-enhancing (n = 16) and nonenhancing (n = 16) regions during open surgical resection of malignant glioma in 17 patients. Preoperative resting-state blood oxygen level-dependent fMRI was used to evaluate the relationships between radiographic and histopathologic characteristics. Signal intensity for a blood oxygen level-dependent biomarker was compared with scores of tumor infiltration and microvascular proliferation as well as total cell and neuronal density.

RESULTS

Biopsies corresponded to a range of blood oxygen level-dependent signals, ranging from relatively normal (z = -4.79) to markedly abnormal (z = 8.84). Total cell density was directly related to blood oxygen level-dependent signal abnormality (P = .013, R² = 0.19), while the neuronal labeling index was inversely related to blood oxygen level-dependent signal abnormality (P = .016, R² = 0.21). The blood oxygen level-dependent signal abnormality was also related to tumor infiltration (P = .014) and microvascular proliferation (P = .045).

CONCLUSIONS

The relationship between local, neoplastic characteristics and a blood oxygen level-dependent biomarker of vascular function suggests that local effects of glioma cell infiltration contribute to vascular dysregulation.

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.

Neuroimaging in Central Nervous System Lymphoma

Primary central nervous system lymphoma (PCNSL) is a rare aggressive high-grade type of extranodal lymphoma. PCNSL can have a variable imaging appearance and can mimic other brain disorders such as encephalitis, demyelination, and stroke. In addition to PCNSL, the CNS can be secondarily involved by systemic lymphoma. Computed tomography and conventional MRI are the initial imaging modalities to evaluate these lesions. Recently, however, advanced MRI techniques are more often used in an effort to narrow the differential diagnosis and potentially inform diagnostic and therapeutic decisions.

Efficacy of Perfusion Computed Tomography (PCT) in Differentiating High-Grade Gliomas from Low Grade Gliomas, Lymphomas, Metastases and Abscess

INTRODUCTION

Tumoural angioneogenesis and its quantification are important in predicting the tumour grade and in the management with respect to the treatment available and to assess the response to treatment and the prognosis. It also plays major role in the growth and spread of tumours. Hence, a need arises for non-invasive in vivo methods to assess tumour angioneogenesis and tumour grade at the time of presentation and for monitoring the response during treatment and follow up. In this regard Perfusion Computed Tomography (PCT) can be easily added into routine CT studies to obtain such information on lesion physiology along with its morphology.

AIM

Prospective evaluation of the efficacy of PCT in differentiating high grade gliomas from low grade glioma lymphomas, metastases and abscess.

MATERIALS AND METHODS

Perfusion CT was performed in 68 patients (17 high-grade gliomas, 10 low-grade gliomas, 7 lymphomas, 27 metastases and 7 abscess). Perfusion parameters which include Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Mean Transit Time (MTT) and Time To Peak (TTP) were derived both from the lesion and the normal parenchyma and were Normalized (n) by obtaining the ratio. Statistical analysis for high grade versus low-grade gliomas, high grade gliomas versus lymphomas, metastases and abscess was performed.

RESULTS

Difference in the mean nCBV and nCBF in high grade gliomas were statistically significant from low grade gliomas with cut off of > 3.07 for nCBV and > 2.08 for nCBF yielding good sensitivity and specificity. Difference in the mean nCBV and nMTT in the lymphomas were statistically significant from high grade gliomas (p<0.05) with cut off of <3.40 for nCBV and >1.83 for nMTT yielding good sensitivity and specificity. Difference in the mean nCBV and nMTT in the metastases were statistically significant from high grade gliomas (p<0.05) with cut off of >4.95 for nCBV and >1.88 for nMTT yielding a fair sensitivity and specificity. No statistical significant difference seen among the parameters in differentiating high grade gliomas and abscess.

CONCLUSION

Cerebral PCT greatly adds to the diagnostic accuracy when the diagnosis of a common intra-axial lesion based on morphological characters becomes uncertain.

Diagnostic Accuracy of T1-Weighted Dynamic Contrast-Enhanced-MRI and DWI-ADC for Differentiation of Glioblastoma and Primary CNS Lymphoma

BACKGROUND AND PURPOSE

Glioblastoma and primary CNS lymphoma dictate different neurosurgical strategies; it is critical to distinguish them preoperatively. However, current imaging modalities do not effectively differentiate them. We aimed to examine the use of DWI and T1-weighted dynamic contrast-enhanced-MR imaging as potential discriminative tools.

MATERIALS AND METHODS

We retrospectively reviewed 18 patients with primary CNS lymphoma and 36 matched patients with glioblastoma with pretreatment DWI and dynamic contrast-enhanced-MR imaging. VOIs were drawn around the tumor on contrast-enhanced T1WI and FLAIR images; these images were transferred onto coregistered ADC maps to obtain the ADC and onto dynamic contrast-enhanced perfusion maps to obtain the plasma volume and permeability transfer constant. Histogram analysis was performed to determine the mean and relative ADC_mean and relative 90th percentile values for plasma volume and the permeability transfer constant. Nonparametric tests were used to assess differences, and receiver operating characteristic analysis was performed for optimal threshold calculations.

RESULTS

The enhancing component of primary CNS lymphoma was found to have significantly lower ADC_mean (1.1 × 10^-3 versus 1.4 × 10^-3; P < .001) and relative ADC_mean (1.5 versus 1.9; P < .001) and relative 90th percentile values for plasma volume (3.7 versus 5.0; P < .05) than the enhancing component of glioblastoma, but not significantly different relative 90th percentile values for the permeability transfer constant (5.4 versus 4.4; P = .83). The nonenhancing portions of glioblastoma and primary CNS lymphoma did not differ in these parameters. On the basis of receiver operating characteristic analysis, mean ADC provided the best threshold (area under the curve = 0.83) to distinguish primary CNS lymphoma from glioblastoma, which was not improved with normalized ADC or the addition of perfusion parameters.

CONCLUSIONS

ADC was superior to dynamic contrast-enhanced-MR imaging perfusion, alone or in combination, in differentiating primary CNS lymphoma from glioblastoma.

Permeability Surface Area Product Using Perfusion Computed Tomography Is a Valuable Prognostic Factor in Glioblastomas Treated with Radiotherapy Plus Concomitant and Adjuvant Temozolomide

OBJECTIVE

The current standard treatment protocol for patients with newly diagnosed glioblastoma (GBM) includes surgery, radiotherapy, and concomitant and adjuvant temozolomide (TMZ). We hypothesized that the permeability surface area product (PS) from a perfusion computed tomography (PCT) study is associated with sensitivity to TMZ. The aim of this study was to determine whether PS values were correlated with prognosis of GBM patients who received the standard treatment protocol.

METHODS

This study included 36 patients with GBM that were newly diagnosed between October 2005 and September 2014 and who underwent preoperative PCT study and the standard treatment protocol. We measured the maximum value of relative cerebral blood volume (rCBVmax) and the maximum PS value (PSmax). We statistically examined the relationship between PSmax and prognosis using survival analysis, including other clinicopathologic factors (age, Karnofsky performance status [KPS], extent of resection, O6-methylguanine-DNA methyltransferase [MGMT] status, second-line use of bevacizumab, and rCBVmax).

RESULTS

Log-rank tests revealed that age, KPS, MGMT status, and PSmax were significantly correlated with overall survival. Multivariate analysis using the Cox regression model showed that PSmax was the most significant prognostic factor. Receiver operating characteristic curve analysis showed that PSmax had the highest accuracy in differentiating longtime survivors (LTSs) (surviving more than 2 years) from non-LTSs. At a cutoff point of 8.26 mL/100 g/min, sensitivity and specificity were 90% and 70%, respectively.

CONCLUSIONS

PSmax from PCT study can help predict survival time in patients with GBM receiving the standard treatment protocol. Survival may be related to sensitivity to TMZ.

Glioblastoma Induces Vascular Dysregulation in Nonenhancing Peritumoral Regions in Humans

OBJECTIVE

Glioblastoma is an invasive primary brain malignancy that typically infiltrates the surrounding tissue with malignant cells. It disrupts cerebral blood flow through a variety of biomechanical and biochemical mechanisms. Thus, neuroimaging focused on identifying regions of vascular dysregulation may reveal a marker of tumor spread. The purpose of this study was to use blood oxygenation level-dependent (BOLD) functional MRI (fMRI) to compare the temporal dynamics of the enhancing portion of a tumor with those of brain regions without apparent tumors.

MATERIALS AND METHODS

Patients with pathologically proven glioblastoma underwent preoperative resting-state BOLD fMRI, T1-weighted contrast-enhanced MRI, and FLAIR MRI. The contralesional control hemisphere, contrast-enhancing tumor, and peritu-moral edema were segmented by use of structural images and were used to extract the time series of these respective regions. The parameter estimates (beta values) for the two regressors and resulting z-statistic images were used as a metric to compare the similarity of the tumor dynamics to those of other brain regions.

RESULTS

The time course of the contrast-enhancing tumor was significantly different from that of the rest of the brain (p < 0.05). Similarly, the control signal intensity was significantly different from the tumor signal intensity (p < 0.05). Notably, the temporal dynamics in the peritumoral edema, which did not contain enhancing tumor, were most similar to the those of enhancing tumor than to those of control regions.

CONCLUSION

The findings show that the disruption in vascular regulation induced by a glioblastoma can be detected with BOLD fMRI and that the spatial distribution of these disruptions is localized to the immediate vicinity of the tumor and peritumoral edema.

Evaluation of glioblastomas and lymphomas with whole-brain CT perfusion: Comparison between a delay-invariant singular-value decomposition algorithm and a Patlak plot

OBJECTIVE

Correction of contrast leakage is recommended when enhancing lesions during perfusion analysis. The purpose of this study was to assess the diagnostic performance of computed tomography perfusion (CTP) with a delay-invariant singular-value decomposition algorithm (SVD+) and a Patlak plot in differentiating glioblastomas from lymphomas.

MATERIALS AND METHODS

This prospective study included 17 adult patients (12 men and 5 women) with pathologically proven glioblastomas (n=10) and lymphomas (n=7). CTP data were analyzed using SVD+ and a Patlak plot. The relative tumor blood volume and flow compared to contralateral normal-appearing gray matter (rCBV and rCBF derived from SVD+, and rBV and rFlow derived from the Patlak plot) were used to differentiate between glioblastomas and lymphomas. The Mann-Whitney U test and receiver operating characteristic (ROC) analyses were used for statistical analysis.

RESULTS

Glioblastomas showed significantly higher rFlow (3.05±0.49, mean±standard deviation) than lymphomas (1.56±0.53; P<0.05). There were no statistically significant differences between glioblastomas and lymphomas in rBV (2.52±1.57 vs. 1.03±0.51; P>0.05), rCBF (1.38±0.41 vs. 1.29±0.47; P>0.05), or rCBV (1.78±0.47 vs. 1.87±0.66; P>0.05). ROC analysis showed the best diagnostic performance with rFlow (Az=0.871), followed by rBV (Az=0.771), rCBF (Az=0.614), and rCBV (Az=0.529).

CONCLUSION

CTP analysis with a Patlak plot was helpful in differentiating between glioblastomas and lymphomas, but CTP analysis with SVD+ was not.

Perfusion computed tomography of intracranial meningiomas: In vivo correlation of cerebral blood volume and vascular permeability

BACKGROUND

A noninvasive method to predict the grade of a meningioma would be desirable since it would anticipate information about tumour nature, recurrence and improve tumour management and outcomes. The aim of the present study was to assess the ability of perfusion computed tomography (PCT) technique in predicting the meningioma grade before surgery. Data from PCT, such as cerebral blood volume (CBV) and permeability surface (PS), were correlated with immunohistolopathological information.

METHODS

Twenty-three patients with a diagnosis of intracranial meningioma underwent PCT for pre-surgical evaluation of CBV and PS. During surgery, samples from the centre and periphery of the tumour were obtained. Two correspondent regions of interest (ROIs) were drawn on CBV and PS maps. Central and peripheral CBV and PS mean values were calculated. PCT parameters were correlated to CD-34 and endoglin.

RESULTS

There was a positive correlation between PS and CD-34. No correlation was found between PS values and endoglin, CBV values and CD-34 and endoglin values.

CONCLUSION

Our findings suggest that PCT may support conventional morphological imaging in predicting meningioma grading before surgery.

Use of CT perfusion to discriminate between brain metastases from different primaries

Thirty-six metastases in 22 patients were studied prospectively using computed tomography perfusion. Regions of interests were drawn around: the enhancing part of the tumor, necrotic central part, periphery, peritumoral edema, and normal white matter. Cerebral blood volume, cerebral blood flow, and mean transit time were calculated for each zone. The enhancing part of the tumor significantly differed from the other zones in 11 of 12. Metastases of different primaries can be differentiated from one another with statistically significance (P<.05) by at least one perfusion parameter in 57% of cases.

Evaluation of microvascular permeability with dynamic contrast-enhanced MRI for the differentiation of primary CNS lymphoma and glioblastoma: radiologic-pathologic correlation

BACKGROUND AND PURPOSE

Dynamic contrast-enhanced MR imaging can provide in vivo assessment of the microvasculature in intracranial tumors. The aim of the present study was to evaluate the diagnostic performance of dynamic contrast-enhanced MR imaging derived vascular permeability parameters, including the volume transfer constant, the volume of extravascular extracellular space, and the flux rate constant between the extravascular extracellular space and plasma, for the differentiation of primary CNS lymphoma and glioblastoma.

MATERIALS AND METHODS

Sixty glioblastomas and 11 primary central nervous system lymphomas were included. Pretreatment T1-weighted dynamic contrast-enhanced MR imaging with a 3D T1-weighted spoiled gradient-echo sequence was performed on a 3T MR imaging scanner. Perfusion parameters (volume transfer constant, the volume of extravascular extracellular space, and the flux rate constant) were measured on the basis of the Tofts-Kernmode model. The Mann-Whitney U test and receiver operating characteristic analysis were used to compare those parameters between primary central nervous system lymphoma and glioblastoma. Histopathologic correlation of dynamic contrast-enhanced MR imaging findings was performed by using reticulin staining and CD31 immunohistochemistry.

RESULTS

Median volume transfer constant and flux rate constant values were significantly higher in primary central nervous system lymphoma (0.145 ± 0.057 and 0.396 ± 0.088) than in glioblastoma (0.064 ± 0.021 and 0.230 ± 0.058) (P < .001, respectively). Median volume of extravascular extracellular space values did not differ significantly between primary central nervous system lymphoma (0.434 ± 0.165) and glioblastoma (0.319 ± 0.107). On receiver operating characteristic analysis, volume transfer constant had the best discriminative value for differentiating primary central nervous system lymphoma and glioblastoma (threshold, 0.093; sensitivity, 90.9%; specificity, 95.0%). Histopathologic evaluation revealed intact vascular integrity in glioblastoma despite endothelial proliferation, whereas primary central nervous system lymphoma demonstrated destroyed vessel architecture, thereby promoting vascular disintegrity.

CONCLUSIONS

Primary central nervous system lymphoma demonstrated significantly higher volume transfer constant and flux rate constant values compared with glioblastoma, implying a higher vascular permeability in primary central nervous system lymphoma. These findings confirm initial observations from perfusion CT and dynamic contrast-enhanced MR imaging studies, correlating with underlying histopathologic features, and may be useful in distinguishing primary central nervous system lymphoma from glioblastoma.

The combination of 13N-ammonia and 18F-FDG in predicting primary central nervous system lymphomas in immunocompetent patients

OBJECTIVE

Accurate identification of primary central nervous system lymphoma (PCNSL) and its differentiation from other brain tumors remain difficult but are essential for treatment. In this study, we investigated whether (13)N-ammonia combined with (18)F-FDG could distinguish PCNSL from solid gliomas effectively.

METHODS

Ten consecutive patients with final diagnosis of PCNSL (5 female and 5 male patients; mean [SD] age, 59.10 [12.47] years; range, 43-74 years) and another fifteen consecutive patients with solid glioma lesions (5 female and 10 male patients; mean [SD] age, 46.73 [19.61] years; range, 14-72 years) were included in this study. PET/CT imaging was performed for all of them with both (18)F-FDG and (13)N-ammonia as tracers. Tumor-to-gray matter (T/G) ratios were calculated for the evaluation of tumor uptake. Both Student t test and discriminant analysis were recruited to assess the differential efficacy of these 2 tracers.

RESULTS

The T/G ratios of (18)F-FDG in PCNSL lesions were higher than in solid gliomas (3.26 [1.18] vs 1.56 [0.41], P < 0.001), whereas the T/G ratios of (13)N-ammonia in PCNSL lesions were lower than in solid gliomas significantly (1.38 [0.20] vs 2.11 [0.69], P < 0.001). All the lesions of PCNSL displayed higher T/G ratios of (18)F-FDG than (13)N-ammonia, whereas 14 (77.8%) of 18 glioma lesions showed contrary results. Tumor classification by means of canonical discriminant analysis yielded an overall accuracy of 96.9%, and only one glioma lesion was misclassified into the PCNSL group.

CONCLUSIONS

PCNSLs and solid gliomas have different metabolic profiles on N-ammonia and F-FDG imaging. The combination of these 2 tracers can distinguish these 2 clinical entities effectively and make an accurate prediction of PCNSL.

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.

Role of perfusion CT in differentiating between various cerebral masses using normalized permeability surface area product and cerebral blood volume

OBJECTIVE

The objective was to assess usefulness of a combined analysis using the perfusion computed tomography parameters permeability surface area product (PS) and cerebral blood volume (CBV) in the differential grouping of various cerebral masses.

METHODS

Thirty patients who had a cerebral mass, confirmed by pathologic verification, were included. We classified PS and CBV results for various cerebral masses by visual as well as semiquantitative assessment. To verify statistically significant differences between the groups, one-way analysis of variance was performed.

RESULTS

Patients were categorized into five groups with statistically significant differences (P<.01).

CONCLUSIONS

PS and CBV were useful in the differential diagnosis of cerebral masses.

Perfusion computed tomography assessments of peri-enhancing brain tissue in high-grade gliomas

PURPOSE

This study was undertaken to identify tumoural infiltration of peri-enhancing brain tissue in patients with glioblastoma by means of perfusion computed tomography (PCT) parameters, cerebral blood volume (CBV) and permeability surface (PS).

MATERIALS AND METHODS

Eight patients with surgically treated glioblastoma who were eligible for radiotherapy and nine patients with brain metastases from lung and breast cancer underwent CT before and after injection of contrast medium. CBV and PS were calculated in the contrast-enhancing lesion area, in the area of perilesional oedema and in the normal-appearing white matter (NAWM), normalised to contralateral symmetrical areas.

RESULTS

No significant differences were found for normalised CBV (nCBV) and nPS in NAWM regions between metastasis and glioma. Significant differences in nPS (p<0.005) were found between the typically vasogenic oedema surrounding the metastases and signal alteration surrounding the glial neoplasm. On the contrary, no significant differences were detected in the same areas for nCBV.

CONCLUSIONS

PCT can analyse the histopathological substrate underlying the hypodense peritumoural halo and differentiate between vasogenic oedema and neoplastic infiltration on the basis of the PS parameter. In our study, PS was more informative than CBV. These findings can be used to integrate plans for radiation therapy and/or surgery.

Regional and voxel-wise comparisons of blood flow measurements between dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) and arterial spin labeling (ASL) in brain tumors

The objective of the current study was to evaluate the regional and voxel-wise correlation between dynamic susceptibility contrast (DSC) and arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) measurement of cerebral blood flow (CBF) in patients with brain tumors. Thirty patients with histologically verified brain tumors were evaluated in the current study. DSC-MRI was performed by first using a preload dose of gadolinium contrast, then collecting a dynamic image acquisition during a bolus of contrast, followed by posthoc contrast agent leakage correction. Pseudocontinuous ASL was collected using 30 pairs of tag and control acquisition using a 3-dimensional gradient-echo spin-echo (GRASE) acquisition. All images were registered to a high-resolution anatomical atlas. Average CBF measurements within regions of contrast-enhancement and T2 hyperintensity were evaluated between the two modalities. Additionally, voxel-wise correlation between CBF measurements obtained with DSC and ASL were assessed. Results demonstrated a positive linear correlation between DSC and ASL measurements of CBF when regional average values were compared; however, a statistically significant voxel-wise correlation was only observed in around 30-40% of patients. These results suggest DSC and ASL may provide regionally similar, but spatially different measurements of CBF.

Monitoring response to antiangiogenic treatment and predicting outcomes in advanced hepatocellular carcinoma using image biomarkers, CT perfusion, tumor density, and tumor size (RECIST)

PURPOSE

Our aim was to investigate the hypothesis that the CT perfusion (CTP) is a more sensitive image biomarker when compared with tumor burden (Response Evaluation Criteria in Solid Tumors [RECIST]) and tumor density (HU) for monitoring treatment changes and for predicting long-term outcome in advanced hepatocellular carcinoma (HCC) treated with a combination of antiangiogenic treatment and chemotherapy.

MATERIAL AND METHODS

In this phase II clinical trial, 33 patients with advanced HCC were enrolled and 23 were included in the current study. A diagnostic dual-phase contrast-enhanced CT and perfusion CT was performed at baseline and days 10 to 12 after initiation of antiangiogenic treatment (Bevacizumab). The patients subsequently received bevacizumab in combination with gemcitabine and oxaliplatin (GEMOX-B) and contrast-enhanced CT was performed at the end of treatment (after completing 3 cycles of GEMOX-B chemotherapy) and after every 8 week until there was evidence of disease progression or intolerable toxicity. The CTP protocol included a targeted dynamic cine acquisition for 25 to 30 seconds after 50 to 70 mL of iodinated contrast media injection at 5 to 7 mL/s. The CTP parameters were compared with tumor size (according to Response Evaluation Criteria in Solid Tumors, RECIST 1.1) and density measurements (HU) before and after treatment and correlated with patient's outcome in groups with and without tumor thrombus. A one-sided P value was calculated and the Bonferroni correction was used to address the issue of multiple comparisons.

RESULTS

On days 10 to 12 after initiation of bevacizumab, significant decrease in CTP parameters was noted (P < 0.005). There was a mild reduction in mean tumor density (P = 0.016) without any significant change in mean tumor size. Tumors with higher baseline mean transit time values on CTP correlated with favorable clinical outcome (partial response and stable disease) and had better 6 months progression-free survival (P = 0.002 and P = 0.005, respectively). The baseline transfer constant (Ktrans) of responders (1425.19 ± 609.47 mL/1000 mL/min) was significantly higher than that of nonresponders (935.96 ± 189.47 mL/1000 mL/min). The tumor thrombus in the portal vein demonstrated baseline perfusion values and post-treatment change values similar to the HCC.

CONCLUSION

In advanced HCC, CTP is a more sensitive image biomarker for monitoring early antiangiogenic treatment effects as well as in predicting outcome at the end of treatment and progression-free survival as compared with RECIST and tumor density.

Current status and guidelines for the assessment of tumour vascular support with dynamic contrast-enhanced computed tomography

Dynamic contrast-enhanced computed tomography (DCE-CT) assesses the vascular support of tumours through analysis of temporal changes in attenuation in blood vessels and tissues during a rapid series of images acquired with intravenous administration of iodinated contrast material. Commercial software for DCE-CT analysis allows pixel-by-pixel calculation of a range of validated physiological parameters and depiction as parametric maps. Clinical studies support the use of DCE-CT parameters as surrogates for physiological and molecular processes underlying tumour angiogenesis. DCE-CT has been used to provide biomarkers of drug action in early phase trials for the treatment of a range of cancers. DCE-CT can be appended to current imaging assessments of tumour response with the benefits of wide availability and low cost. This paper sets out guidelines for the use of DCE-CT in assessing tumour vascular support that were developed using a Delphi process. Recommendations encompass CT system requirements and quality assurance, radiation dosimetry, patient preparation, administration of contrast material, CT acquisition parameters, terminology and units, data processing and reporting. DCE-CT has reached technical maturity for use in therapeutic trials in oncology. The development of these consensus guidelines may promote broader application of DCE-CT for the evaluation of tumour vascularity. Key Points • DCE-CT can robustly assess tumour vascular support • DCE-CT has reached technical maturity for use in therapeutic trials in oncology • This paper presents consensus guidelines for using DCE-CT in assessing tumour vascularity.

Comparison between acetazolamide challenge and 10% carbon dioxide challenge perfusion CT in rat C6 glioma

RATIONALE AND OBJECTIVES

The aim of this study was to investigate the effect of perfusion computed tomography (PCT) with acetazolamide (ACZ) challenge and compare it to 10% carbon dioxide (CO(2)) challenge in rat C6 glioma.

MATERIALS AND METHODS

PCT was performed on 32 rats, including 20 with orthotopically implanted C6 gliomas and 12 serving as controls. Ten rats with gliomas and six normal rats underwent PCT with ACZ challenge. The other 10 rats with gliomas and six normal rats underwent PCT with 10% CO(2) challenge. The raw data were processed using Philips computed tomographic brain perfusion software. Perfusion parameters before and after the challenge were recorded. Percentage changes due to ACZ administration and 10% CO(2) challenge were calculated. Pearson's correlation coefficients were used to investigate relationships between percentage changes in perfusion parameters and vascular endothelial growth factor and microvessel density.

RESULTS

In C6 gliomas, percentage change in cerebral blood flow was significantly different between ACZ (72.73%) and 10% CO(2) (28.47%) challenge (P < .01). Percentage change in cerebral blood volume was 37.85% with ACZ and 24.69% with 10% CO(2) challenge (P = .02). In controls, percentage change in cerebral blood flow was significantly different between ACZ (117.42%) and 10% CO(2) (65.86%) challenge (P < .01). For percentage change in cerebral blood volume, there was no significant difference between ACZ (107.51%) and 10% CO(2) (92.95%) challenge. Significant correlations were observed among percentage changes in vascular endothelial growth factor, microvessel density, and cerebral blood volume (P < .01). Percentage change in cerebral blood flow correlated well with vascular endothelial growth factor.

CONCLUSIONS

The results of this study indicate that PCT with ACZ challenge is a more reliable technique compared to 10% CO(2) challenge for the quantitative evaluation of microcirculation in gliomas.

Current strategies in the diagnosis of diffuse large B-cell lymphoma of the central nervous system

Lymphomas can arise within the central nervous system (CNS) as primary CNS lymphoma (PCNSL) typically involving the brain and less often the leptomeninges, eyes, and spinal cord. In contrast to PCNSL, secondary CNS lymphoma (SCNSL) is considered to originate as quasi metastasis from systemic lymphoma spreading to the CNS. Both types of CNS lymphomas are predominantly tumours of the diffuse large B-cell type and represent aggressive diseases necessitating a rapid diagnosis. Following neuroimaging based on magnetic resonance imaging, stereotaxy and histopathological diagnosis of CNS lymphoma currently remain obligatory to plan treatment. However, progress in cytopathological, immunophenotypic, and molecular genetic analyses of the cerebrospinal fluid (CSF) has been achieved recently and potentially will facilitate lymphoma diagnosis in the future. This review describes the diagnostic procedures in patients with suspected CNS lymphomas, primarily PCNSL. In addition to a summary of the standard diagnostic work-up, an overview and discussion of current data on different techniques for evaluation of the CSF in CNS lymphoma are given.

Intracranial Masses with Perilesional Edema: Differential Diagnosis with Perfusion CT

Perilesional edema (PE) is commonly observed in association with an intracranial mass. PE is thought to be determined by vasogenic effects in the cerebral parenchyma surrounding the mass due to the loss or absence of the blood-brain barrier (BBB) inside the lesion. Alterations in capillary permeability induce extrusion of fluids into the extravascular space around the mass. On Computed Tomography (CT) PE corresponds to an area of low density for the increased water content, outside the margins of the lesion. It is difficult to differentiate PE from areas of parenchymal compressive ischemia and sometimes the two events could be associated. A solitary mass with PE is more commonly discovered on a non-enhanced computed tomography (NECT) study performed for the onset of stable or rapidly progressive neurological symptoms. In such cases, a supplementary CT scan with contrast (CECT) is generally indicated to complete the baseline imaging before MRI. Contrast enhancement is generally present in a mass with PE and it is not specific for differential diagnosis. Perfusion computed tomography (PCT) requires a few minutes in addition to the time needed for CECT. PCT may give information on regional microvascular density, permeability and blood flow, thus it may play a role when tumoral neo-angiogenesis or non-neoplastic altered haemodynamics are suspected. We therefore investigated the utility of PCT in the differential diagnosis of the intracranial solitary masses with PE.

Brain volume perfusion CT performed with 128-detector row CT system in patients with cerebral gliomas: a feasibility study

OBJECTIVES

Validation of the feasibility and efficacy of volume perfusion computed tomography (VPCT) in the preoperative assessment of cerebral gliomas by applying a 128-slice CT covering the entire tumour.

METHODS

Forty-six patients (25 men, 21 women; mean age 52.8 years) with cerebral gliomas were evaluated with VPCT. Two readers independently evaluated VPCT data, drawing volumes of interest (VOIs) around the tumour according to maximum intensity projection volumes, which were mapped automatically onto the cerebral blood volume (CBV), flow (CBF) and permeability (Ktrans) perfusion datasets. As control, a second VOI was placed in the contralateral healthy cortex. Correlation among perfusion parameters, tumour grade, hemisphere and VOIs was assessed. The diagnostic power of perfusion parameters was analysed by receiver operating characteristics curve analyses.

RESULTS

VPCT was feasible in the assessment of the entire tumour extent. Mean values of Ktrans, CBV, CBF in high-grade gliomas were significantly higher compared with low-grade (p < 0.01). Ktrans demonstrated the highest diagnostic (97% sensitivity), positive (100%) and negative (94%) prognostic values.

CONCLUSIONS

VPCT was feasible in all subjects. All areas of different perfusion characteristics are depicted and quantified in colour-coded 3D maps. The derived parameters correlate well with tumour histopathology, differentiating low- from high-grade gliomas.