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

Probing the glioma microvasculature: a case series of the comparison between perfusion MRI and intraoperative high-frame-rate ultrafast Doppler ultrasound

BACKGROUND

We aimed to describe the microvascular features of three types of adult-type diffuse glioma by comparing dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) with intraoperative high-frame-rate ultrafast Doppler ultrasound.

METHODS

Case series of seven patients with primary brain tumours underwent both DSC perfusion MRI and intra-operative high-frame-rate ultrafast Doppler ultrasound. From the ultrasound images, three-dimensional vessel segmentation was obtained of the tumour vascular bed. Relative cerebral blood volume (rCBV) maps were generated with leakage correction and normalised to the contralateral normal-appearing white matter. From tumour histograms, median, mean, and maximum rCBV ratios were extracted.

RESULTS

Low-grade gliomas (LGGs) showed lower perfusion than high-grade gliomas (HGGs), as expected. Within the LGG subgroup, oligodendroglioma showed higher perfusion than astrocytoma. In HGG, the median rCBV ratio for glioblastoma was 3.1 while astrocytoma grade 4 showed low perfusion with a median rCBV of 1.2. On the high-frame-rate ultrafast Doppler ultrasound images, all tumours showed a range of rich and organised vascular networks with visually apparent abnormal vessels, even in LGG.

CONCLUSIONS

This unique case series revealed in vivo insights about the microvascular architecture in both LGGs and HGGs. Ultrafast Doppler ultrasound revealed rich vascularisation, also in tumours with low perfusion at DSC MRI. These findings warrant further investigations using advanced MRI postprocessing, in particular for characterising adult-type diffuse glioma.

RELEVANCE STATEMENT

Our findings challenge the current assumption behind the estimation of relative cerebral blood volume that the distribution of blood vessels in a voxel is random.

KEY POINTS

• Ultrafast Doppler ultrasound revealed rich vascularity irrespective of perfusion dynamic susceptibility contrast MRI state. • Rich and organised vascularisation was also observed even in low-grade glioma. • These findings challenge the assumptions for cerebral blood volume estimation with MRI.

Perfusion-Weighted Imaging: The Use of a Novel Perfusion Scoring Criteria to Improve the Assessment of Brain Tumor Recurrence versus Treatment Effects

INTRODUCTION

Imaging surveillance of contrast-enhancing lesions after the treatment of malignant brain tumors with radiation is plagued by an inability to reliably distinguish between tumor recurrence and treatment effects. Magnetic resonance perfusion-weighted imaging (PWI)-among other advanced brain tumor imaging modalities-is a useful adjunctive tool for distinguishing between these two entities but can be clinically unreliable, leading to the need for tissue sampling to confirm diagnosis. This may be partially because clinical PWI interpretation is non-standardized and no grading criteria are used for assessment, leading to interpretation discrepancies. This variance in the interpretation of PWI and its subsequent effect on the predictive value has not been studied. Our objective is to propose structured perfusion scoring criteria and determine their effect on the clinical value of PWI.

METHODS

Patients treated at a single institution between 2012 and 2022 who had prior irradiated malignant brain tumors and subsequent progression of contrast-enhancing lesions determined by PWI were retrospectively studied from CTORE (CNS Tumor Outcomes Registry at Emory). PWI was given two separate qualitative scores (high, intermediate, or low perfusion). The first (control) was assigned by a neuroradiologist in the radiology report in the course of interpretation with no additional instruction. The second (experimental) was assigned by a neuroradiologist with additional experience in brain tumor interpretation using a novel perfusion scoring rubric. The perfusion assessments were divided into three categories, each directly corresponding to the pathology-reported classification of residual tumor content. The interpretation accuracy in predicting the true tumor percentage, our primary outcome, was assessed through Chi-squared analysis, and inter-rater reliability was assessed using Cohen's Kappa.

RESULTS

Our 55-patient cohort had a mean age of 53.5 ± 12.2 years. The percentage agreement between the two scores was 57.4% (κ: 0.271). Upon conducting the Chi-squared analysis, we found an association with the experimental group reads (p-value: 0.014) but no association with the control group reads (p-value: 0.734) in predicting tumor recurrence versus treatment effects.

CONCLUSIONS

With our study, we showed that having an objective perfusion scoring rubric aids in improved PWI interpretation. Although PWI is a powerful tool for CNS lesion diagnosis, methodological radiology evaluation greatly improves the accurate assessment and characterization of tumor recurrence versus treatment effects by all neuroradiologists. Further work should focus on standardizing and validating scoring rubrics for PWI evaluation in tumor patients to improve diagnostic accuracy.

Evaluation of the Value of Perfusion-Weighted Magnetic Resonance Imaging in the Differential Diagnosis of Sellar and Parasellar Tumors

The purpose of this study was to assess the value of perfusion-weighted imaging (PWI) in the differential diagnosis of sellar and parasellar tumors, as an additional sequence in the magnetic resonance imaging (MRI) protocol. Analysis was based on a substantial group of subjects and included 124 brain and pituitary MRI examinations with a dynamic susceptibility contrast (DSC) PWI sequence. The following perfusion parameters were determined for the tumors: relative cerebral blood volume (rCBV), relative peak height (rPH) and relative percentage of signal intensity recovery (rPSR). To ensure greater repeatability, each of the aforementioned parameters was calculated as: arithmetic mean of the values of the whole tumor, arithmetic mean of the maximum values on each axial slice within the tumor and maximum values derived from the whole tumor. In our study, we established that meningiomas compared to both non-functional and hormone-secreting pituitary adenomas (pituitary neuroendocrine tumors-PitNET) had significantly higher values of rCBV with cut-off points set at 3.45 and 3.54, respectively (mean rCBV). Additionally, meningiomas presented significantly higher maximum and mean maximum rPH values compared to adenomas. DSC PWI imaging adds significant value to conventional MRI examinations and can be helpful in differentiating equivocal pituitary tumors.

A Framework for Susceptibility Analysis of Brain Tumours Based on Uncertain Analytical Cum Algorithmic Modeling

Susceptibility analysis is an intelligent technique that not only assists decision makers in assessing the suspected severity of any sort of brain tumour in a patient but also helps them diagnose and cure these tumours. This technique has been proven more useful in those developing countries where the available health-based and funding-based resources are limited. By employing set-based operations of an arithmetical model, namely fuzzy parameterised complex intuitionistic fuzzy hypersoft set (FPCIFHSS), this study seeks to develop a robust multi-attribute decision support mechanism for appraising patients' susceptibility to brain tumours. The FPCIFHSS is regarded as more reliable and generalised for handling information-based uncertainties because its complex components and fuzzy parameterisation are designed to deal with the periodic nature of the data and dubious parameters (sub-parameters), respectively. In the proposed FPCIFHSS-susceptibility model, some suitable types of brain tumours are approximated with respect to the most relevant symptoms (parameters) based on the expert opinions of decision makers in terms of complex intuitionistic fuzzy numbers (CIFNs). After determining the fuzzy parameterised values of multi-argument-based tuples and converting the CIFNs into fuzzy values, the scores for such types of tumours are computed based on a core matrix which relates them with fuzzy parameterised multi-argument-based tuples. The sub-intervals within [0, 1] denote the susceptibility degrees of patients corresponding to these types of brain tumours. The susceptibility of patients is examined by observing the membership of score values in the sub-intervals.

Differentiating solitary brain metastases from high-grade gliomas with MR: comparing qualitative versus quantitative diagnostic strategies

Purpose

To investigate the diagnostic efficacy of MRI diagnostic algorithms with an ascending automatization, in distinguishing between high-grade glioma (HGG) and solitary brain metastases (SBM).

Methods

36 patients with histologically proven HGG (n = 18) or SBM (n = 18), matched by size and location were enrolled from a database containing 655 patients. Four different diagnostic algorithms were performed serially to mimic the clinical setting where a radiologist would typically seek out further findings to reach a decision: pure qualitative, analytic qualitative (based on standardized evaluation of tumor features), semi-quantitative (based on perfusion and diffusion cutoffs included in the literature) and a quantitative data-driven algorithm of the perfusion and diffusion parameters. The diagnostic yields of the four algorithms were tested with ROC analysis and Kendall coefficient of concordance.

Results

Qualitative algorithm yielded sensitivity of 72.2%, specificity of 78.8%, and AUC of 0.75. Analytic qualitative algorithm distinguished HGG from SBM with a sensitivity of 100%, specificity of 77.7%, and an AUC of 0.889. The semi-quantitative algorithm yielded sensitivity of 94.4%, specificity of 83.3%, and AUC = 0.889. The data-driven algorithm yielded sensitivity = 94.4%, specificity = 100%, and AUC = 0.948. The concordance analysis between the four algorithms and the histologic findings showed moderate concordance for the first algorithm, (k = 0.501, P < 0.01), good concordance for the second (k = 0.798, P < 0.01), and third (k = 0.783, P < 0.01), and excellent concordance for fourth (k = 0.901, p < 0.0001).

Conclusion

When differentiating HGG from SBM, an analytical qualitative algorithm outperformed qualitative algorithm, and obtained similar results compared to the semi-quantitative approach. However, the use of data-driven quantitative algorithm yielded an excellent differentiation.

Quantification of Tumor Blush of Highly Vascularized Tumors with Slow Feeding System: Representative Use for Giant Pituitary Adenomas

BACKGROUND

 Modern imaging techniques can identify adverse factors for tumor removal such as cavernous sinus invasion before surgery, but surgeries for giant pituitary adenomas often reveal discrepancies between preoperative imaging and intraoperative findings because pituitary adenomas have feeding arteries with narrow diameters. Current imaging methods are not suitable for tumors with not only large vascular beds but also slow arterial filling.

PATIENTS AND METHODS

 This prospective study recruited 13 male subjects and 9 female subjects with giant pituitary adenomas between November 2011 and 2018. All the patients were investigated with three-dimensional magnetic resonance (MR) imaging, bone image computerized tomography (CT), and digital subtraction angiography (DSA) using a C-arm cone-beam CT scanner with a flat-panel detector and 50% diluted contrast medium. Fine angioarchitecture was evaluated and the tumor blush was quantified using newly developed region of interest (ROI) analysis to establish surgical strategies.

RESULTS

 Seven patients demonstrated no or very faint tumor blushes. In these patients, feeding arteries run centripetally from the surface of the tumor. Fifteen patients showed significant tumor blushes, and the feeding arteries penetrated centrifugally from the inferoposterior pole to the upper pole of the tumor. All the patients were treated according to the angiographic information with successful hemostasis. The patients showed improvement and/or disappearance of the neurologic deficits. The faint and significant blush groups showed significant differences in intraoperative bleeding (p < 0.01) and operation time (p < 0.05).

CONCLUSION

 Specialized evaluation focused on vascularization is required for successful therapy of giant pituitary adenomas.

Role of Dynamic Susceptibility Contrast Perfusion MRI in Glioma Progression Evaluation

Accurately and quickly differentiating true progression from pseudoprogression in glioma patients is still a challenge. This study aims to explore if dynamic susceptibility contrast- (DSC-) MRI can improve the evaluation of glioma progression. We enrolled 65 glioma patients with suspected gadolinium-enhancing lesion. Longitudinal MRI follow-up (mean 590 days, range: 210-2670 days) or re-operation (n = 3) was used to confirm true progression (n = 51) and pseudoprogression (n = 14). We assessed the diagnostic performance of each MRI variable and the different combinations. Our results showed that the relative cerebral blood volume (rCBV) in the true progression group (1.094, 95%CI: 1.135-1.636) was significantly higher than that of the pseudoprogression group (0.541 ± 0.154) (p < 0.001). Among the 18 patients who had serial DSC-MRI, the rCBV of the progression group (0.480, 95%CI: 0.173-0.810) differed significantly from pseudoprogression (-0.083, 95%CI: -1.138-0.620) group (p=0.015). With an rCBV threshold of 0.743, the sensitivity and specificity for discriminating true progression from pseudoprogression were 76.5% and 92.9%, respectively. The Cho/Cr and Cho/NAA ratios of the true progression group (2.520, 95%CI: 2.331-2.773; 2.414 ± 0.665, respectively) were higher than those of the pseudoprogression group (1.719 ± 0.664; 1.499 ± 0.500, respectively) ((p=0.001), (p < 0.001), respectively). The areas under ROC curve (AUCs) of enhancement pattern, MRS, and DSC-MRI for the differentiation were 0.782, 0.881, and 0.912, respectively. Interestingly, when combined enhancement pattern, MRS, and DSC-MRI variables, the AUC was 0.965 and achieved sensitivity 90.2% and specificity 100.0%. Our results suggest that DSC-MRI can significantly improve the diagnostic performance for identifying glioma progression. DSC-MRI combined with conventional MRI may promptly distinguish true gliomas progression from pseudoprogression when the suspected gadolinium-enhancing lesion was found, without the need for a long-term follow-up.

Gibbs point field model quantifies disorder in microvasculature of U87-glioblastoma

Microvascular proliferation in glioblastoma multiforme is a biological key mechanism to facilitate tumor growth and infiltration and a main target for treatment interventions. The vascular architecture can be obtained by Single Plane Illumination Microscopy (SPIM) to evaluate vascular heterogeneity in tumorous tissue. We make use of the Gibbs point field model to quantify the order of regularity in capillary distributions found in the U87 glioblastoma model in a murine model and to compare tumorous and healthy brain tissue. A single model parameter Γ was assigned that is linked to tissue-specific vascular topology through Monte-Carlo simulations. Distributions of the model parameter Γ differ significantly between glioblastoma tissue with mean 〈Γ_G〉=2.1±0.4, as compared to healthy brain tissue with mean 〈Γ_H〉=4.9±0.4, suggesting that the average Γ-value allows for tissue differentiation. These results may be used for diagnostic magnetic resonance imaging, where it has been shown recently that Γ is linked to tissue-inherent relaxation parameters.

Differentiation of Glioblastoma and Solitary Brain Metastasis by Gradient of Relative Cerebral Blood Volume in the Peritumoral Brain Zone Derived from Dynamic Susceptibility Contrast Perfusion Magnetic Resonance Imaging

OBJECTIVE

The purpose of our study was to evaluate the efficacy of the relative cerebral blood volume (rCBV) gradient in the peritumoral brain zone (PBZ)-the difference in the rCBV values from the area closest to the enhancing lesion to the area closest to the healthy white matter-in differentiating glioblastoma (GB) from solitary brain metastasis (MET).

METHODS

A 3.0-T magnetic resonance imaging (MRI) machine was used to perform dynamic susceptibility contrast perfusion MRI (DSC-MRI) on 43 patients with a solitary brain tumor (24 GB, 19 MET). The rCBV ratios were acquired by DSC-MRI data in 3 regions of the PBZ (near the enhancing tumor, G1; intermediate distance from the enhancing tumor, G2; far from the enhancing tumor, G3). The maximum rCBV ratios in the PBZ (rCBVp) and the enhancing tumor were also calculated, respectively. The perfusion parameters were evaluated using the nonparametric Mann-Whitney test. The sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve were identified.

RESULTS

The rCBVp ratios and rCBV gradient in the PBZ were significantly higher in GB compared with MET (P < 0.05 for both rCBVp ratios and rCBV gradient). The threshold values of 0.50 or greater for rCBVp ratios provide sensitivity and specificity of 57.69% and 79.17%, respectively, for differentiation of GB from MET. Compared with rCBVp ratios, rCBV gradient had higher sensitivity (94.44%) and specificity (91.67%) using the threshold value of greater than 0.06.

CONCLUSIONS

The parameter of rCBV gradient derived from DSC-MRI in the PBZ seems to be the most efficient parameter to differentiate GB from METs.

Dynamic susceptibility contrast (DSC) perfusion MRI in differential diagnosis between radionecrosis and neoangiogenesis in cerebral metastases using rCBV, rCBF and K2

INTRODUCTION

Distinction between treatment-related changes and tumour recurrence in patients who have received radiation treatment for brain metastases can be difficult on conventional MRI. In this study, we investigated the ability of dynamic susceptibility contrast (DSC) perfusion in differentiating necrotic changes from pathological angiogenesis and compared measurements of relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF) and K2, using a dedicated software.

METHODS

Twenty-nine patients with secondary brain tumors were included in this retrospective study and underwent DSC perfusion MRI with a 3-month follow-up imaging after chemo- or radiation-therapy. Region-of-interests were drawn around the contrast enhancing lesions and measurements of rCBV, rCBF and K2 were performed in all patients. Based on subsequent histological examination or clinico-radiological follow-up, the cohort was divided in two groups: recurrent disease and stable disease. Differences between the two groups were analyzed using the Student's t test. Sensitivity, specificity and diagnostic accuracy of rCBV measurements were analyzed considering three different cut-off values.

RESULTS

Between patients with and without disease, only rCBV and rCBF values were significant (p < 0.05). The only cut-off value giving the best diagnostic accuracy of 100% was rCBV = 2.1 (sensitivity = 100%; specificity = 100%). Patients with tumor recurrence showed a higher mean value of rCBV (mean = 4.28, standard deviation = 2.09) than patients with necrotic-related changes (mean = 0.77, standard deviation = 0.44).

CONCLUSION

DSC-MRI appears a clinically useful method to differentiate between tumor recurrence, tumor necrosis and pseudoprogression in patients treated for cerebral metastases. Relative CBV using a cut-off value of 2.1 proved to be the most accurate and reliable parameter.

Advanced MRI for Pediatric Brain Tumors with Emphasis on Clinical Benefits

Conventional anatomic brain MRI is often limited in evaluating pediatric brain tumors, the most common solid tumors and a leading cause of death in children. Advanced brain MRI techniques have great potential to improve diagnostic performance in children with brain tumors and overcome diagnostic pitfalls resulting from diverse tumor pathologies as well as nonspecific or overlapped imaging findings. Advanced MRI techniques used for evaluating pediatric brain tumors include diffusion-weighted imaging, diffusion tensor imaging, functional MRI, perfusion imaging, spectroscopy, susceptibility-weighted imaging, and chemical exchange saturation transfer imaging. Because pediatric brain tumors differ from adult counterparts in various aspects, MRI protocols should be designed to achieve maximal clinical benefits in pediatric brain tumors. In this study, we review advanced MRI techniques and interpretation algorithms for pediatric brain tumors.

Measurement of arteriolar blood volume in brain tumors using MRI without exogenous contrast agent administration at 7T

PURPOSE

Arteriolar cerebral-blood-volume (CBVa) is an important perfusion parameter that can be measured using inflow-based vascular-space-occupancy (iVASO) MRI without exogenous contrast agent administration. The purpose of this study is to assess the potential diagnostic value of CBVa in brain tumor patients by comparing it with total-CBV (including arterial, capillary and venous vessels) measured by dynamic-susceptibility-contrast (DSC) MRI.

MATERIALS AND METHODS

Twelve brain tumor patients were scanned using iVASO (on 7T as part of a research project) and DSC (on 3T as part of routine clinical protocols) MRI. Region-of-interest analysis was performed to compare the resulting perfusion measures between tumoral and contralateral regions, and to evaluate their associations with tumor grades.

RESULTS

CBVa measured by iVASO MRI significantly correlated with WHO grade (ρ = 0.37, P = 0.04). Total-CBV measured by DSC MRI showed a trend of correlation with WHO grade (ρ = 0.28, P = 0.5). The signal-to-noise ratio was comparable (P > 0.1) between the two methods, while the contrast-to-noise ratio between tumoral and contralateral regions was higher in iVASO-CBVa than DSC-CBV in WHO II/III patients (P < 0.05) but comparable in WHO IV patients (P > 0.1). A trend of positive correlation between DSC-CBV and iVASO-CBVa was observed (R2 = 0.28, P = 0.07).

CONCLUSION

In this initial patient study, CBVa demonstrated a stronger correlation with WHO grade than total-CBV. Further investigation with a larger cohort is warranted to validate whether CBVa can be a better classifier than total-CBV for the stratification of brain tumors, and whether iVASO MRI can be a useful alternative method for the assessment of tumor perfusion, especially when exogenous contrast agent administration is difficult in certain patient populations. J. Magn. Reson. Imaging 2016;44:1244-1255.

Advanced neuroimaging in the clinic: critical appraisal of the evidence base

The shortage of high-quality systematic reviews in the field of radiology limits evidence-based integration of imaging methods into clinical practice and may perpetuate misconceptions regarding the efficacy and appropriateness of imaging techniques for specific applications. Diffusion tensor imaging for patients with mild traumatic brain injury (DTI-mTBI) and dynamic susceptibility contrast MRI for patients with glioma (DSC-glioma) are applications of quantitative neuroimaging, which similarly detect manifestations of disease where conventional neuroimaging techniques cannot. We performed a critical appraisal of reviews, based on the current evidence-based medicine methodology, addressing the ability of DTI-mTBI and DSC-glioma to (a) detect brain abnormalities and/or (b) predict clinical outcomes. 23 reviews of DTI-mTBI and 26 reviews of DSC-glioma met criteria for inclusion. All reviews addressed detection of brain abnormalities, whereas 12 DTI-mTBI reviews and 22 DSC-glioma reviews addressed prediction of a clinical outcome. All reviews were assessed using a critical appraisal worksheet consisting of 19 yes/no questions. Reviews were graded according to the total number of positive responses and the 2011 Oxford Centre for evidence-based medicine levels of evidence criteria. Reviews addressing DTI-mTBI detection had moderate quality, while those addressing DSC-glioma were of low quality. Reviews addressing prediction of outcomes for both applications were of low quality. Five DTI-mTBI reviews, but only one review of DSC-glioma met criteria for classification as a meta-analysis/systematic/quantitative review.

Additive antiangiogenesis effect of ginsenoside Rg3 with low-dose metronomic temozolomide on rat glioma cells both in vivo and in vitro

Background

Glioblastoma is the most common and deadly primary brain tumor in adults. Low-dose,metronomic (LDM) temozolomide (TMZ) displays improved efficacy in the treatment of glioblastoma by targeting angiogenesis, but has a limited effect on recurrence. The antiangiogenesis drug ginsenoside Rg3 (RG3) is the main active ingredient of ginseng, a popular herbal medicine.

Methods

Using an in vitro and a rat model of an orthotopic glioma allograft, this study was to determine whether RG3 enhanced the antiangiogenesis activity of LDM TMZ in the treatment of glioblastoma.

Results

Our results showed that combined use of TMZ with RG3 displayed additive inhibition on proliferation of both human umbilical vein endothelial cells (HUVEC) and rat C6 glioma cells in vitro. They additively arrested cell cycle, increased apoptosis, and decreased VEGF-A and BCL-2 expression in HUVEC. Antiangiogenesis effect was also evaluated in the rat model of orthotopic glioma allograft, based upon markers including relative cerebral blood volume (rCBV) by magnetic resonance imaging (MRI), VEGF levels and microvessel density (MVD)/CD34 staining. LDM TMZ alone was potent in suppressing angiogenesis and tumor growth, whereas RG3 alone only had modest antiangiogenesis effects. Combined treatment significantly and additively suppressed angiogenesis, without additive inhibitory effects on allografted tumor growth.

Conclusions

These data provide evidence showing the efficacy of LDM TMZ on glioma treatment. The combined additive antiangiogenesis effect suggests that RG3 has the potential to further increase the efficacy of LDM TMZ in the treatment of glioblastoma.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-015-0274-y) contains supplementary material, which is available to authorized users.

Astrocytic tumour grading: a comparative study of three-dimensional pseudocontinuous arterial spin labelling, dynamic susceptibility contrast-enhanced perfusion-weighted imaging, and diffusion-weighted imaging

OBJECTIVES

We hypothesized that three-dimensional pseudocontinuous arterial spin labelling (pCASL) may have similar efficacy in astrocytic tumour grading as dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC-PWI), and the grading accuracy may be further improved when combined with apparent diffusion coefficient (ADC) values.

METHODS

Forty-three patients with astrocytic tumours were studied using diffusion weighted imaging (DWI), pCASL, and DSC-PWI. Histograms of ADC and normalized tumour cerebral blood flow values (nCBF on pCASL and nrCBF on DSC-PWI) were measured and analyzed.

RESULTS

The mean 10 % ADC value was the DWI parameter that provided the best differentiation between low-grade astrocytoma (LGA) and high-grade astrocytoma (HGA). The nCBF and nrCBF (1.810 ± 0.979 and 2.070 ± 1.048) in LGA were significantly lower than those (4.505 ± 2.270 and 5.922 ± 2.630) in HGA. For differentiation between LGA and HGA, the cutoff values of 0.764 × 10(-3) mm(2)/s for mean 10 % ADC, 2.374 for nCBF, and 3.464 for nrCBF provided the optimal accuracy (74.4 %, 86.1 %, and 88.6 %, respectively). Combining the ADC values with nCBF or nrCBF could further improve the grading accuracy to 97.7 % or 95.3 %, respectively.

CONCLUSIONS

pCASL is an alternative to DSC-PWI for astrocytic tumour grading. The combination of DWI and contrast-free pCASL offers a valuable choice in patients with risk factors.

KEY POINTS

• pCASL shows positive correlation with DSC-PWI in astrocytic tumour grading. • ADC values based on ADC histograms can be an objective method. • Combination of DWI and pCASL or DSC-PWI can improve grading accuracy.

The fornix and limbic system

The limbic system is predominantly involved in memory and emotional output. Its 2 principle components are the hippocampus (involved in memory as part of the Papez circuit) and the amygdala (involved in emotional responses, memories and drives). The principle clinical manifestations of limbic disease are epilepsy, confusional states, and cognitive impairment. The connections of the limbic system are widespread and are now becoming visible on diffusion tensor imaging. Many different diseases may affect the limbic system. An appreciation of its functional anatomy along with its white matter tract connections improves assessment of infiltrative disease in particular. Small lesions in the Papez circuit may have devastating neuropsychological consequences. An active search strategy based on the knowledge presented in this paper will increase the likelihood of making an accurate diagnosis for patients affected by these conditions.

Recurrent glioblastoma multiforme versus radiation injury: a multiparametric 3-T MR approach

OBJECTIVE

The discrimination between recurrent glioma and radiation injury is often a challenge on conventional magnetic resonance imaging (MRI). We verified whether adding and combining proton MR spectroscopic imaging ((1)H-MRSI), diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI) information at 3 Tesla facilitate such discrimination.

MATERIALS AND METHODS

Twenty-nine patients with histologically verified high-grade gliomas, who had undergone surgical resection and radiotherapy, and had developed new contrast-enhancing lesions close to the treated tumour, underwent MRI, (1)H-MRSI, DWI and PWI at regular time intervals. The metabolite ratios choline (Cho)/normal( n )Cho n , N-acetylaspartate (NAA)/NAA n , creatine (Cr)/Cr n , lactate/lipids (LL)/LL n , Cho/Cr n , NAA/Cr n , Cho/NAA, NAA/Cr and Cho/Cr were derived from (1)H-MRSI; the apparent diffusion coefficient (ADC) from DWI; and the relative cerebral blood volume (rCBV) from PWI.

RESULTS

In serial MRI, recurrent gliomas showed a progressive enlargement, and radiation injuries showed regression or no modification. Discriminant analysis showed that discrimination accuracy was 79.3 % when considering only the metabolite ratios (predictor, Cho/Cr n ), 86.2 % when considering ratios and ADC (predictors, Cho/Cr n and ADC), 89.7 % when considering ratios and rCBV (predictors, Cho/Cr n , Cho/Cr and rCBV), and 96.6 % when considering ratios, ADC and rCBV (predictors, Cho/Cho n , ADC and rCBV).

CONCLUSIONS

The multiparametric 3-T MR assessment based on (1)H-MRSI, DWI and PWI in addition to MRI is a useful tool to discriminate tumour recurrence/progression from radiation effects.