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

The performance of MR perfusion-weighted imaging for the differentiation of high-grade glioma from primary central nervous system lymphoma: A systematic review and meta-analysis

It is always a great challenge to distinguish high-grade glioma (HGG) from primary central nervous system lymphoma (PCNSL). We conducted a meta-analysis to assess the performance of MR perfusion-weighted imaging (PWI) in differentiating HGG from PCNSL. The heterogeneity and threshold effect were evaluated, and the sensitivity (SEN), specificity (SPE) and areas under summary receiver operating characteristic curve (SROC) were calculated. Fourteen studies with a total of 598 participants were included in this meta-analysis. The results indicated that PWI had a high level of accuracy (area under the curve (AUC) = 0.9415) for differentiating HGG from PCNSL by using the best parameter from each study. The dynamic susceptibility-contrast (DSC) technique might be an optimal index for distinguishing HGGs from PCNSLs (AUC = 0.9812). Furthermore, the DSC had the best sensitivity 0.963 (95%CI: 0.924, 0.986), whereas the arterial spin-labeling (ASL) displayed the best specificity 0.896 (95% CI: 0.781, 0.963) among those techniques. However, the variability of the optimal thresholds from the included studies suggests that further evaluation and standardization are needed before the techniques can be extensively clinically used.

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.

Can morphological MRI differentiate between primary central nervous system lymphoma and glioblastoma?

Background

Primary central nervous system lymphoma (PCNSL) is a rare, aggressive brain neoplasm that accounts for roughly 2-6% of primary brain tumors. In contrast, glioblastoma (GBM) is the most frequent and severe glioma subtype, accounting for approximately 50% of diffuse gliomas. The aim of the present study was to evaluate morphological MRI characteristics in histologically-proven PCNSL and GBM at the time of their initial presentation.

Methods

We retrospectively evaluated standard diagnostic MRI examinations in 54 immunocompetent patients (26 female, 28 male; age 62.6 ± 11.5 years) with histologically-proven PCNSL and 54 GBM subjects (21 female, 33 male; age 59 ± 14 years).

Results

Several significant differences between both infiltrative brain tumors were found. PCNSL lesions enhanced homogenously in 64.8% of cases, while nonhomogeneous enhancement was observed in 98.1% of GBM cases. Necrosis was present in 88.9% of GBM lesions and only 5.6% of PCNSL lesions. PCNSL presented as multiple lesions in 51.9% cases and in 35.2% of GBM cases; however, diffuse infiltrative type of brain involvement was observed only in PCNSL (24.1%). Optic pathways were infiltrated more commonly in PCNSL than in GBM (42.6% vs. 5.6%, respectively, p <0.001). Other cranial nerves were affected in 5.6% of PCNSL, and in none of GBM. Signs of bleeding were rare in PCNSL (5.6%) and common in GBM (44.4%); p < 0.001. Both supratentorial and infratentorial localization was present only in PCNSL (27.7%). Involvement of the basal ganglia was more common in PCNSL (55.6%) than in GBM (18.5%); (p < 0.001). Cerebral cortex was affected significantly more often in GBM (83.3%) than in PCNSL (51.9%); mostly by both enhancing and non-enhancing infiltration.

Conclusion

Routine morphological MRI is capable of differentiating between GBM and PCNSL lesions in many cases at time of initial presentation. A solitary infiltrative supratentorial lesion with nonhomogeneous enhancement and necrosis was typical for GBM. PCNSL presented with multiple lesions that enhanced homogenously or as diffuse infiltrative type of brain involvement, often with basal ganglia and optic pathways affection.

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.

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.

PET/CT, MR, and PET/MR in Lymphoma and Melanoma

With the introduction of hybrid imaging technologies such as PET/CT and recently PET/MRI, staging and therapy-response monitoring have evolved. PET/CT has been shown to be of value for routine staging of FDG-avid lymphomas before as well as at the end of treatment. For interim staging, trials are ongoing to evaluate the use of PET/CT. In melanoma, PET/CT can be recommended for stages III and IV diseases for initial staging and before surgery. Studies investigating the use of PET/CT for early therapy response are promising. The role of PET/MR in lymphoma and melanoma imaging has to be defined because no larger studies exist so far. There may be an application of PET/MR in research especially for tumor characterization and therapy response. Furthermore, the potential role of non-FDG tracers is elucidated regarding the assessment of treatment response in targeted drug regimens.

The Combined Performance of ADC, CSF CXC Chemokine Ligand 13, and CSF Interleukin 10 in the Diagnosis of Central Nervous System Lymphoma

BACKGROUND AND PURPOSE

CXC chemokine ligand 13 and interleukin 10 have emerged as CSF biomarkers for the diagnosis of CNS lymphoma. Our hypothesis is that the combined use of ADC, CXC chemokine ligand 13, and interleukin 10 will result in increased diagnostic performance compared with the use of ADC values alone.

MATERIALS AND METHODS

Eighty-seven patients were included in this study, including 43 with CNS lymphoma and 44 without CNS lymphoma (21 metastases, 14 high-grade gliomas, 9 tumefactive demyelinating lesions) who had undergone CSF proteomic analysis and had a new enhancing mass on brain MR imaging. Average ADC was derived by contouring the contrast-enhancing tumor volume. Group means were compared via t tests for average ADC, CXC chemokine ligand 13, and interleukin 10. Receiver operating characteristic analysis was performed for each individual variable. Multiple-variable logistic regression with receiver operating characteristic analysis was performed, and the multiple-variable receiver operating characteristic was compared with single-variable receiver operating characteristics.

RESULTS

The average ADC was lower and CSF CXC chemokine ligand 13 and interleukin 10 values were higher in CNS lymphoma (P < .001). Areas under the curve ranged from 0.739 to 0.832 for single-variable ROC. Multiple-variable logistic regression yielded statistically significant individual effects for all 3 variables in a combined model. Multiple-variable receiver operating characteristics (area under the curve, 0.928) demonstrated statistically significantly superior diagnostic performance compared with the use of single variables alone.

CONCLUSIONS

The combined use of ADC, CSF CXC chemokine ligand 13, and interleukin 10 results in increased diagnostic performance for the diagnosis of CNS lymphoma. This finding highlights the importance of CSF analysis when the diagnosis of CNS lymphoma is considered on the basis of MR imaging.

Dynamic Contrast-Enhanced MRI in Low-Grade Versus Anaplastic Oligodendrogliomas

BACKGROUND AND PURPOSE

Low-grade and anaplastic oligodendrogliomas are often difficult to differentiate on the basis of conventional MR imaging characteristics. Dynamic contrast-enhanced (DCE) MRI can assess tumor microvasculature and has demonstrated utility for predicting glioma grade and prognosis in primary brain tumors. The aim of our study was to evaluate the performance of plasma volume (Vp) and volume transfer coefficient (K(trans) ) derived from DCE MRI in differentiating between grade II and grade III oligodendrogliomas.

MATERIALS AND METHODS

Twenty-four consecutive patients with pathologically confirmed oligodendroglioma (World Health Organization grade II, n = 14 and grade III, n = 10) were retrospectively assessed. Pretreatment DCE MRI was performed and regions of interest were manually drawn around the entire tumor volume to calculate Vp and K(trans) . The Mann-Whitney U test and receiver operating characteristic (ROC) analysis were performed to compare pharmacokinetic parameters between the 2 groups.

RESULTS

The Vpmean values for grade III oligodendrogliomas were significantly higher (P = .03) than those for grade II oligodendrogliomas. The K(trans) mean values were higher in grade III lesions, but the difference between the 2 groups was not statistically significant (P > .05). Based on ROC analysis, the Vpmean (area under curve = .757, SD = .1) cut-off value that provided the best combination of high sensitivity and specificity to distinguish between grade II and III oligodendrogliomas was 2.35 (P < .03).

CONCLUSION

The results of our study suggest the DCE MRI parameter Vpmean can noninvasively differentiate between grade II and grade III oligodendrogliomas.

Methods and challenges in quantitative imaging biomarker development

Academic radiology is poised to play an important role in the development and implementation of quantitative imaging (QI) tools. This article, drafted by the Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force, reviews current issues in QI biomarker research. We discuss motivations for advancing QI, define key terms, present a framework for QI biomarker research, and outline challenges in QI biomarker development. We conclude by describing where QI research and development is currently taking place and discussing the paramount role of academic radiology in this rapidly evolving field.

Differentiation between primary cerebral lymphoma and glioblastoma using the apparent diffusion coefficient: comparison of three different ROI methods

Objective

Apparent diffusion coefficients (ADC) can help differentiate between central nervous system (CNS) lymphoma and Glioblastoma (GBM). However, overlap between ADCs for GBM and lymphoma have been reported because of various region of interest (ROI) methods. Our aim is to explore ROI method to provide the most reproducible results for differentiation.

Materials and Methods

We studied 25 CNS lymphomas and 62 GBMs with three ROI methods: (1) ROI₁, whole tumor volume; (2) ROI₂, multiple ROIs; and (3) ROI₃, a single ROI. Interobserver variability of two readers for each method was analyzed by intraclass correlation(ICC). ADCs were compared between GBM and lymphoma, using two-sample t-test. The discriminative ability was determined by ROC analysis.

Results

ADCs from ROI₁ showed most reproducible results (ICC >0.9). For ROI₁, ADC_mean for lymphoma showed significantly lower values than GBM (p = 0.03). The optimal cut-off value was 0.98×10⁻³ mm²/s with 85% sensitivity and 90% specificity. For ROI₂, ADC_min for lymphoma was significantly lower than GBM (p = 0.02). The cut-off value was 0.69×10⁻³ mm²/s with 87% sensitivity and 88% specificity.

Conclusion

ADC values were significantly dependent on ROI method. ADCs from the whole tumor volume had the most reproducible results. ADC_mean from the whole tumor volume may aid in differentiating between lymphoma and GBM. However, multi-modal imaging approaches are recommended than ADC alone for differentiation.

Evaluation of dynamic contrast-enhanced MRI derived microvascular permeability in recurrent glioblastoma treated with bevacizumab

Bevacizumab, an antibody to vascular endothelial growth factor, is commonly used in the setting of recurrent glioblastoma (rGB). The aim of the present study was to evaluate whether dynamic-contrast-enhanced MRI (DCE-MRI) derived microvascular permeability is related to bevacizumab treatment outcome in rGB. Twenty-two patients with rGB underwent DCE-MRI at a median of 2.6 weeks prior initializing bevacizumab therapy. Follow-up MRI-scans (DCE-MRI available for 19/22 patients) were obtained after a median of 9.9 weeks. The volume transfer constant (K(trans))--an estimate related to microvascular permeability--at baseline and voxel-wise-reduction (VWR) in K(trans) at first follow-up were measured from the entire contrast-enhancing tumor (CET) and correlated with progression-free and overall survival (PFS, OS) using uni- and multivariate cox-regression (significance-level p < 0.05). Baseline K(trans) ranged from 0.050 to 0.205 min(-1) (median, 0.109 min(-1)). The VWR in K(trans) ranged from 19.9 to 97.2 % (median, 89.4 %). Patients with lower baseline K(trans) and higher VWR in K(trans) showed significantly longer PFS and OS. Given the strong correlation of VWR in K(trans) and CET-volume changes (Spearman's ρ = -0.73, p < 0.01) both variables were included in a multivariate model. Thereby, neither VWR in K(trans) nor CET-volume changes retained independent significance for PFS or OS. Pre-treatment K(trans) stratifies PFS and OS in patients with bevacizumab-treated rGB. Although early pharmacodynamics changes in K(trans) were not assessed, the VWR in K(trans) at first follow-up had no additional benefit over assessment of CET-volume changes. Further prospective trials are needed to confirm these findings and to elucidate the potential role of pre-treatment K(trans) as a predictive and/or prognostic biomarker.

Association of overall survival in patients with newly diagnosed glioblastoma with contrast-enhanced perfusion MRI: Comparison of intraindividually matched T1 - and T2 (*) -based bolus techniques

BACKGROUND

To compare intraindividual dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MR perfusion parameters and determine the association of DCE parameters with overall survival (OS) with the established predictive DSC parameter cerebral blood volume (CBV) in patients with newly diagnosed glioblastoma.

METHODS

Perfusion data were analyzed retrospectively, and included scans performed preoperatively at 3.0 Tesla in 37 patients (25 males, 12 females, 39-83 years, median 65) later diagnosed with glioblastoma. All patients received standard treatment consisting of surgery and radiochemotherapy. Images were spatially coregistered and maximum region of interest-based DCE and DSC parameter measurements compared and thresholds identified using multivariate linear regression, Pearson's correlation coefficients and using receiver operating characteristic analysis. Survival analysis was performed using Kaplan-Meier curves.

RESULTS

While both, elevated volume transfer constant (K(trans) ) (>0.29 min(-1) ; P = 0.041) and CBV (>23.7 mL/100 mL; P < 0.001) were significantly associated with OS, elevated CBV was associated with worse OS compared with elevated K(trans) . K(trans) was significantly correlated with the leakage correction factor K2 but not with CBV.

CONCLUSION

The combined use of DSC and DCE MR perfusion may provide additional information of prognostic value for glioblastoma patient survival prediction. As K(trans) was not tightly coupled to CBV, both parameters may reflect different stages in the pathogenetic sequence of glioblastoma growth.

Integrative analysis of cancer imaging readouts by networks

Cancer is a multifactorial and heterogeneous disease. The corresponding complexity appears at multiple levels: from the molecular and the cellular constitution to the macroscopic phenotype, and at the diagnostic and therapeutic management stages. The overall complexity can be approximated to a certain extent, e.g. characterized by a set of quantitative phenotypic observables recorded in time‐space resolved dimensions by using multimodal imaging approaches. The transition from measures to data can be made effective through various computational inference methods, including networks, which are inherently capable of mapping variables and data to node‐ and/or edge‐valued topological properties, dynamic modularity configurations, and functional motifs. We illustrate how networks can integrate imaging data to explain cancer complexity, and assess potential pre‐clinical and clinical impact.

Computational Multiplexing Imaging merges imaging and networks.

Networks show signatures of tumor heterogeneity and phenotypic profiles observed in‐vivo.

A profile ensemble establishes a tumor fingerprint, and this constitutes a novel type of marker.

Personalized treatment is embedded in a systems medicine approach.