Meningiomas with conventional MRI findings resembling intraaxial tumors: can perfusion-weighted MRI be helpful in differentiation?

Arterial spin labeled perfusion MRI for the assessment of radiation-treated meningiomas

Purpose

Conventional contrast-enhanced MRI is currently the primary imaging technique used to evaluate radiation treatment response in meningiomas. However, newer perfusion-weighted MRI techniques, such as 3D pseudocontinuous arterial spin labeling (3D pCASL) MRI, capture physiologic information beyond the structural information provided by conventional MRI and may provide additional complementary treatment response information. The purpose of this study is to assess 3D pCASL for the evaluation of radiation-treated meningiomas.

Methods

Twenty patients with meningioma treated with surgical resection followed by radiation, or by radiation alone, were included in this retrospective single-institution study. Patients were evaluated with 3D pCASL and conventional contrast-enhanced MRI before and after radiation (median follow up 6.5 months). Maximum pre- and post-radiation ASL normalized cerebral blood flow (ASL-nCBF) was measured within each meningioma and radiation-treated meningioma (or residual resected and radiated meningioma), and the contrast-enhancing area was measured for each meningioma. Wilcoxon signed-rank tests were used to compare pre- and post-radiation ASL-nCBF and pre- and post-radiation area.

Results

All treated meningiomas demonstrated decreased ASL-nCBF following radiation (p < 0.001). Meningioma contrast-enhancing area also decreased after radiation (p = 0.008) but only for approximately half of the meningiomas (9), while half (10) remained stable. A larger effect size (Wilcoxon signed-rank effect size) was seen for ASL-nCBF measurements (r = 0.877) compared to contrast-enhanced area measurements (r = 0.597).

Conclusions

ASL perfusion may provide complementary treatment response information in radiation-treated meningiomas. This complementary information could aid clinical decision-making and provide an additional endpoint for clinical trials.

Multiparametric analysis from dynamic susceptibility contrast-enhanced perfusion MRI to evaluate malignant brain tumors

BACKGROUND AND PURPOSE

Dynamic susceptibility contrast-enhanced (DSC) MR perfusion is a valuable technique for distinguishing brain tumors. Diagnostic potential of measurable parameters derived from preload leakage-corrected-DSC-MRI remains somewhat underexplored. This study aimed to evaluate these parameters for differentiating primary CNS lymphoma (PCNSL), glioblastoma, and metastasis.

METHODS

Thirty-nine patients with pathologically proven PCNSL (n = 14), glioblastoma (n = 14), and metastasis (n = 11) were analyzed. Five DSC parameters-relative CBV (rCBV), percentage of signal recovery (PSR), downward slope (DS), upward slope (US), and first-pass slope ratio-were derived from tumor-enhancing areas. Diagnostic performance was assessed using receiver operating characteristic curve analysis.

RESULTS

RCBV was higher in metastasis (4.58; interquartile range [IQR]: 2.54) and glioblastoma (3.98; IQR: 1.87), compared with PCNSL (1.46; IQR: 0.29; p = .00006 for both). rCBV better distinguished metastasis and glioblastoma from PCNSL, with an area under the curve (AUC) of 0.97 and 0.99, respectively. PSR was higher in PCNSL (88.11; IQR: 21.21) than metastases (58.30; IQR: 22.28; p = .0002), while glioblastoma (74.54; IQR: 21.23) presented almost significant trend-level differences compared to the others (p≈.05). AUCs were 0.79 (PCNSL vs. glioblastoma), 0.91 (PCNSL vs. metastasis), and 0.78 (glioblastoma vs. metastasis). DS and US parameters were statistically significant between glioblastoma (-109.92; IQR: 152.71 and 59.06; IQR: 52.87) and PCNSL (-47.36; IQR: 44.30 and 21.68; IQR: 16.85), presenting AUCs of 0.86 and 0.87.

CONCLUSION

Metastasis and glioblastoma can be better differentiated from PCNSL through rCBV. PSR demonstrated higher differential performance compared to the other parameters and seemed useful, allowing a proper distinction among all, particularly between metastasis and glioblastoma, where rCBV failed. Finally, DS and US were only helpful in differentiating glioblastoma from PCNSL.

Atypical radiological aspect of meningioma: Web-like enhancement

Meningiomas are the most common extra-axial neoplasmof the central nervous system (CNS). There are a number of characteristic imaging features of meningiomas on magnetic resonance imaging (MRI) that allow an accurate diagnosis, however there are a number of atypical features that may be diagnostically challenging. Furthermore, a number of other neoplastic and non-neoplastic conditions may mimic meningiomas. This case highlights the importance of careful analysis of imaging findings and the need for consideration of all possible diagnoses, including rare or atypical presentations of common neoplasms such as meningiomas. Early detection and accurate diagnosis are crucial in determining the appropriate management and improving the outcomes for patients with intracranial tumors.

Advanced Meningioma Imaging

Noninvasive imaging methods are used to accurately diagnose meningiomas and track their growth and location. These techniques, including computed tomography, MRI, and nuclear medicine, are also being used to gather more information about the biology of the tumors and potentially predict their grade and impact on prognosis. In this article, we will discuss the current and developing uses of these imaging techniques including additional analysis using radiomics in the diagnosis and treatment of meningiomas, including treatment planning and prediction of tumor behavior.

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.

Dynamic contrast-enhanced computed tomography perfusion parameters of canine suspected brain tumors at baseline and during radiotherapy might be different depending on tumor location but not associated with survival

Introduction

Treatment of brain tumors in dogs can be associated with significant morbidity and reliable prognostic factors are lacking. Dynamic contrast-enhanced computed tomography (DCECT) can be used to assess tumor perfusion. The objectives of this study were to assess perfusion parameters and change in size of suspected brain tumors before and during radiotherapy (RT) depending on their location and find a potential correlation with survival.

Methods

Seventeen client-owned dogs with suspected brain tumors were prospectively recruited. All dogs had a baseline DCECT to assess mass size, blood volume (BV), blood flow (BF), and transit time (TT). Twelve dogs had a repeat DCECT after 12 Gy of megavoltage RT. Survival times were calculated.

Results

Intra-axial masses had lower BF (p = 0.005) and BV (p < 0.001) than extra-axial masses but not than pituitary masses. Pituitary masses had lower BF (p = 0.001) and BV (p = 0.004) than extra-axial masses. The volume of the mass was positively associated with TT (p = 0.001) but not with BF and BV. Intra-axial masses showed a more marked decrease in size than extra-axial and pituitary masses during RT (p = 0.022 for length, p = 0.05 for height). Extra-axial masses showed a greater decrease in BF (p = 0.011) and BV (p = 0.012) during RT than pituitary masses and intra-axial masses. Heavier dogs had a shorter survival time (p = 0.011). Perfusion parameters were not correlated with survival.

Conclusion

DCECT perfusion parameters and change in size of brain masses during RT might be different based on the location of the mass.

Uncommon and atypical meningiomas and imaging variants: A report of 7 cases

Meningiomas constitute the most common extra-axial tumor of the central nervous system and can have a wide-ranging manifestation of imaging. There are several types of unusual depictions depicted with the magnetic resonance imaging (MRI) of meningiomas that have been established thus far. It is thus crucial for the reporting radiologist or neurosurgeon to have an in-depth knowledge of their variable manifestations in order to be able to differentiate these neoplasms from the numerous tumors that can mimic their appearance. Meningioma is frequently challenging to diagnose when imaging variants are present. Nevertheless, a number of unusual histological variants have imaging or clinical features which are related to typical meningiomas and, in numerous cases, these require specific surgical management. The present study describes 7 cases of meningiomas, which were either simple atypical, unusual gigantic extracranial intracranial parasagittal, or not visible meningiomas. These uncommon and atypical imaging variants of meningiomas are described herein in an aim to underline their various potential presentations.

Recommendations for the diagnosis and radiological follow-up of pituitary neuroendocrine tumours

Pituitary neuroendocrine tumours (PitNETs) constitute a heterogeneous group of tumours with a gradually increasing incidence, partly accounted for by more sensitive imaging techniques and more extensive experience in neuroradiology in this regard. Although most PitNETs are indolent, some exhibit aggressive behaviour, and recurrence may be seen after surgical removal. The changes introduced in the WHO classification in 2017 and terminological debates in relation to neuroendocrine tumours warrant an update of the guidelines for the diagnosis, preoperative and postoperative management, and follow-up of response to treatment of PitNETs. This multidisciplinary document, an initiative of the Neuroendocrinology area of the Sociedad Española de Endocrinología y Nutrición [Spanish Society of Endocrinology and Nutrition] (SEEN), focuses on neuroimaging studies for the diagnosis, prognosis and follow-up of PitNETs. The basic requirements and elements that should be covered by magnetic resonance imaging are described, and a minimum radiology report to aid clinicians in treatment decision-making is proposed. This work supplements the consensus between the Neuroendocrinology area of the SEEN and the Sociedad Española de Anatomía Patológica [Spanish Society of Pathology] (SEAP) for the pathological study of PitNETs.

Grading Trigone Meningiomas Using Conventional Magnetic Resonance Imaging With Susceptibility-Weighted Imaging and Perfusion-Weighted Imaging

OBJECTIVE

To compare conventional magnetic resonance imaging (MRI), susceptibility-weighted imaging (SWI), and perfusion-weighted imaging (PWI) characteristics in different grades of trigone meningiomas.

METHODS

Thirty patients with trigone meningiomas were enrolled in this retrospective study. Conventional MRI was performed in all patients; SWI (17 cases), dynamic contrast-enhanced PWI (10 cases), and dynamic susceptibility contrast PWI (6 cases) were performed. Demographics, conventional MRI features, SWI- and PWI-derived parameters were compared between different grades of trigone meningiomas.

RESULTS

On conventional MRI, the irregularity of tumor shape (ρ = 0.497, P = 0.005) and the extent of peritumoral edema (ρ = 0.187, P = 0.022) might help distinguish low-grade and high-grade trigone meningiomas. On multiparametric functional MRI, rTTPmax (1.17 ± 0.06 vs 1.30 ± 0.05, P = 0.048), Kep, Ve, and iAUC demonstrated their potentiality to predict World Health Organization grades I, II, and III trigone meningiomas.

CONCLUSIONS

Conventional MRI combined with dynamic susceptibility contrast and dynamic contrast-enhanced can help predict the World Health Organization grade of trigone meningiomas.

Multiparametric magnetic resonance imaging features of giant intracranial tuberculomas

OBJECTIVES

To evaluate Magnetic Resonance Imaging (MRI) features of Giant Tuberculomas (GT) of the brain and deduce characteristic imaging phenotypes which may differentiate GT from higher grade glioma.

METHODS

A retrospective analysis of MRI was done on Tuberculomas of size >2 cm. The diagnosis was established by histopathology or presumed from size reduction on follow-up MRI while on empirical anti-tubercular therapy (ATT). Multimodality characteristics of GT on T1/T2W, Fluid attenuation recovery (FLAIR), Diffusion-Weighted imaging (DWI), Susceptibility Weighted Imaging (SWI), Spectroscopy (MRS) and Perfusion weighted sequences were assessed. These imaging features were also evaluated in WHO Grade IV, IDH-wild type glioma (histopathologically and genetically proven) and a comparative analysis of the imaging features between GT and glioma was done.

RESULTS

Thirty-two GT and 20 glioma were evaluated. Pronounced intralesional T2 hypointensity (n = 8;25%), T2 hyperintense crescent beneath the periphery (n = 25, 78.1%), T2W lamellated/whorled appearance (n = 17;53.125%), hyperintense rim on T1W MT (n = 25;78.1%), peripheral rim of diffusion restriction (n = 22; 68.75%), peripheral rim of blooming on SWI (n = 20, 62.5%), prominent lipid resonance on MR spectroscopy (n = 30; 93.75%), overshoot of the signal intensity-time curve above the base line (n = 9/10; 90%) on dynamic susceptibility contrast (DSC) perfusion, were remarkable imaging characteristics. Reduction of peripheral T1 hyperintensity, compaction of T2 hypointense core, expansion of sub-marginal T2 hyperintense rim and increased peripheral susceptibility (n = 20; 62.5%) during follow-up imaging, while on ATT, were standout features. GT could be differentiated from WHO grade IV (IDH-wild type) glioma on the basis of a significantly higher proportion of GTs showing a whorled/lamellated appearance, T1 hyperintense rim, T2 hypointense core, DWI-ADC mismatch, well-defined rim on SWI, prominent lipid peak on MRS and a submarginal T2 hyperintense rim. GT showed a higher normalized ADC ratio from the core as well as the rim. Significantly higher proportion of glioma showed a T1 hypointense and T2 hyperintense core and a nodular rim enhancement. A significantly higher r CBV, Choline to creatine, choline to NAA ratio and mean thickness of the peripheral enhancing rim were defining features among gliomas.

CONCLUSION

Neuroimaging features of GT have been elucidated. Reduction of peripheral T1 hyperintensity, compaction of T2 hypointense core, expansion of sub-marginal T2 hyperintense rim, and increased peripheral susceptibility on follow-up may be considered imaging markers of response to anti-tubercular therapy. Multiparametric MRI features can differentiate GT from WHO grade IV (IDH-wild type) glioma.

WHO grade III meningioma: De novo tumors show improved progression free survival as compared to secondary progressive tumors

Emerging evidence suggest WHO grade III meningiomas that arise de novo as opposed to dedifferentiating from a lower grade may harbor differing prognoses. To investigate this, a single institution retrospective analysis of prospectively acquired patients between 1999 and 2018 was performed. Clinical data and radiographic parameters were reviewed to calculate progression free survival and overall survival in patients undergoing microsurgical resection. Next generation targeted sequencing of meningioma associated genes was performed on 11 tumors. Eighteen patients were identified as undergoing surgical resection of WHO grade III meningioma. Nine patients (50%) had de novo arising tumors and nine patients had secondary progressive tumors. To compare outcomes, only those patients undergoing gross total resection (Simpson grade I) were included for survival analysis. There was an improvement in median progression free survival for de novo resected tumors as compared to secondary progressive tumors (p = 0.02). Median overall survival for patients with de novo tumors was not statistically improved compared to that of secondary progressive tumors (p = 0.22). Next generation sequencing of targeted genes (NF2, BAP1, TRAF7, KLF4, SMO and AKT) revealed 5/11 tumors containing mutations in the NF2 gene, 2/11 containing BAP1 mutations, and a single tumor containing mutations in both NF2 and TRAF7. More mutations in NF2 and BAP1 were seen in the secondary progressive tumors. In conclusion, patients undergoing gross total resection for de novo arising grade III meningiomas showed improved progression free survival, though similar overall survival, as compared to those patients with secondary progressive tumors. Further studies focused on tumor associated genes and other associated risk factors are needed to improve risk-stratification.

Utility of 3T single-voxel proton MR spectroscopy for differentiating intracranial meningiomas from intracranial enhanced mass lesions

Background

Proton magnetic resonance spectroscopy (MRS) provides structural and metabolic information that is useful for the diagnosis of meningiomas with atypical radiological appearance. However, the metabolite that should be prioritized for the diagnosis of meningiomas has not been established.

Purpose

To evaluate the differences between the metabolic peaks of meningiomas and other intracranial enhanced mass lesions (non-meningiomas) using MR spectroscopy in short echo time (TE) spectra and the most useful metabolic peak for discriminating between the groups.

Material and Methods

The study involved 9 meningiomas, 22 non-meningiomas, intracranial enhancing tumors and abscesses, and 15 normal controls. The ranking of the peak at 3.8 ppm, peak at 3.8 ppm/Creatine (Cr), β-γ Glutamine-Glutamate (bgGlx)/Cr, N-acetyl compounds (NACs)/Cr, choline (Cho)/Cr, lipid and/or lactate (Lip-Lac) at 1.3 ppm/Cr, and the presence of alanine (Ala) were derived. The metabolic peaks were compared using the Mann-Whitney U test. ROC analysis was used to determine the cut-off values for differentiating meningiomas from non-meningiomas using statistically significant metabolic peaks.

Results

The ranking of the peak at 3.8 ppm among all the peaks, peak at 3.8 ppm/Cr, bgGlx/Cr, Lip-Lac/Cr, and the presence of Ala discriminated meningiomas from non-meningiomas with moderate to high accuracy. The highest accuracy was 96.9% at a threshold value of 3 for the rank of the peak at 3.8 ppm.

Conclusion

A distinct elevated peak at 3.8 ppm, ranked among the top three highest peaks, allowed the detection of meningiomas.

Comparison of MR-PWI quantitative and semi-quantitative parameters for the evaluation of liver fibrosis

Background

To evaluate different stages of liver fibrosis in cynomolgus monkeys by comparing magnetic resonance-perfusion weighted imaging (MR-PWI) quantitative and semi-quantitative parameters, and confirm the best detection indicators for diagnosis of liver fibrosis.

Methods

A liver fibrosis model of different stages (S0–S4) was established in cynomolgus monkeys. The changes in MR-PWI quantitative and semi-quantitative parameters with the progression of liver fibrosis were investigated.

Results

MR-PWI quantitative parameters gradually decreased with the progression of liver fibrosis. Hepatic arterial perfusion index (HPI) was found to increase with the progression of liver fibrosis and significant differences of HPI between each group were observed. There was a highly positive correlation between HPI and the stages of liver fibrosis. Receiver operating characteristic (ROC) curve analysis showed that HPI had the highest efficacy of the MR-PWI quantitative parameters for the diagnosis of liver fibrosis. The MR-PW semi-quantitative parameters gradually reduced with the progression of liver fibrosis, and the differences were statistically significant between stages S3–S4 and S0–S2. Time to peak (TPP) gradually extended and showed a positive correlation with the stages of liver fibrosis. TTP had the highest efficacy of the semi-quantitative parameters for diagnosis of liver fibrosis.

Conclusions

Both the MR-PWI quantitative and semi-quantitative parameters of the liver fibrosis model in cynomolgus monkeys varied at different stages of liver fibrosis, and HPI and TTP were the best detection indices for quantitative and semi-quantitative evaluation of liver fibrosis, respectively.

Investigating Effective Factors on Estimated Hemorrhage Intraoperative in Brain Meningioma Surgery

Introduction

The primary and definitive diagnosis of meningioma is based on histological assessment; however, employing imaging methods, like Magnetic Resonance Imaging (MRI) is very helpful to describe lesion's characteristics. Accordingly, we decided to study the effect of imaging factors, like MRI data on the volume of hemorrhage (estimated blood loss) during meningioma surgery.

Methods

This was a cross-sectional, retrospective, and analytical study. The eligible patients were those with meningioma who were candidates for surgery. A total of 40 patients with meningioma were selected and assessed. The preoperative imaging findings were recorded, then estimated blood loss during the surgery was determined.

Results

A reverse association was revealed between the degree of proximity to the nearest sinus and the rate of bleeding. Furthermore, the size of the mass was positively associated with the rate of bleeding; however, there was no significant correlation between the volume of bleeding and other parameters, including the degree of edema, the volume of mass, the site of the tumor in the brain, and the histological subtype of the tumor. The mean time of operation was strongly correlated with blood loss. The rate of bleeding was more expected in hypertensive versus normotensive patients.

Conclusion

Bleeding in various volumes could be a frequent finding in intracranial meningioma surgery. Overall, tumor size, the duration of surgery, a history of hypertension, and distance to the nearest sinuses were the main determinants for the severity of hemorrhage in patients undergoing meningioma surgery.

Advances in the Imaging of Pituitary Tumors

In most patients with pituitary adenomas magnetic resonance imaging (MRI) is essential to guide effective decision-making. T1- and T2-weighted sequences allow the majority of adenomas to be readily identified. Supplementary MR sequences (e.g. FLAIR; MR angiography) may also help inform surgery. However, in some patients MRI findings are 'negative' or equivocal (e.g. with failure to reliably identify a microadenoma or to distinguish postoperative change from residual/recurrent disease). Molecular imaging [e.g. ¹¹C-methionine PET/CT coregistered with volumetric MRI (Met-PET/MR^CR)] may allow accurate localisation of the site of de novo or persistent disease to guide definitive treatment (e.g. surgery or radiosurgery).

Imaging and diagnostic advances for intracranial meningiomas

The archetypal imaging characteristics of meningiomas are among the most stereotypic of all central nervous system (CNS) tumors. In the era of plain film and ventriculography, imaging was only performed if a mass was suspected, and their results were more suggestive than definitive. Following more than a century of technological development, we can now rely on imaging to non-invasively diagnose meningioma with great confidence and precisely delineate the locations of these tumors relative to their surrounding structures to inform treatment planning. Asymptomatic meningiomas may be identified and their growth monitored over time; moreover, imaging routinely serves as an essential tool to survey tumor burden at various stages during the course of treatment, thereby providing guidance on their effectiveness or the need for further intervention. Modern radiological techniques are expanding the power of imaging from tumor detection and monitoring to include extraction of biologic information from advanced analysis of radiological parameters. These contemporary approaches have led to promising attempts to predict tumor grade and, in turn, contribute prognostic data. In this supplement article, we review important current and future aspects of imaging in the diagnosis and management of meningioma, including conventional and advanced imaging techniques using CT, MRI, and nuclear medicine.

Theragnostic Use of Radiolabelled Dota-Peptides in Meningioma: From Clinical Demand to Future Applications

Meningiomas account for approximately 30% of all new diagnoses of intracranial masses. The 2016 World Health Organization's (WHO) classification currently represents the clinical standard for meningioma's grading and prognostic stratification. However, watchful waiting is frequently the chosen treatment option, although this means the absence of a certain histological diagnosis. Consequently, MRI (or less frequently CT) brain imaging currently represents the unique available tool to define diagnosis, grading, and treatment planning in many cases. Nonetheless, these neuroimaging modalities show some limitations, particularly in the evaluation of skull base lesions. The emerging evidence supporting the use of radiolabelled somatostatin receptor analogues (such as dota-peptides) to provide molecular imaging of meningiomas might at least partially overcome these limitations. Moreover, their potential therapeutic usage might enrich the current clinical offering for these patients. Starting from the strengths and weaknesses of structural and functional neuroimaging in meningiomas, in the present article we systematically reviewed the published studies regarding the use of radiolabelled dota-peptides in surgery and radiotherapy planning, in the restaging of treated patients, as well as in peptide-receptor radionuclide therapy of meningioma.

Application of MR morphologic, diffusion tensor, and perfusion imaging in the classification of brain tumors using machine learning scheme

PURPOSE

While MRI is the modality of choice for the assessment of patients with brain tumors, differentiation between various tumors based on their imaging characteristics might be challenging due to overlapping imaging features. The purpose of this study was to apply a machine learning scheme using basic and advanced MR sequences for distinguishing different types of brain tumors.

METHODS

The study cohort included 141 patients (41 glioblastoma, 38 metastasis, 50 meningioma, and 12 primary central nervous system lymphoma). A computer-assisted classification scheme, combining morphologic MRI, perfusion MRI, and DTI metrics, was developed and used for tumor classification. The proposed multistep scheme consists of pre-processing, ROI definition, features extraction, feature selection, and classification. Feature subset selection was performed using support vector machines (SVMs). Classification performance was assessed by leave-one-out cross-validation. Given an ROI, the entire classification process was done automatically via computer and without any human intervention.

RESULTS

A binary hierarchical classification tree was chosen. In the first step, selected features were chosen for distinguishing glioblastoma from the remaining three classes, followed by separation of meningioma from metastasis and PCNSL, and then to discriminate PCNSL from metastasis. The binary SVM classification accuracy, sensitivity and specificity for glioblastoma, metastasis, meningiomas, and primary central nervous system lymphoma were 95.7, 81.6, and 91.2%; 92.7, 95.1, and 93.6%; 97, 90.8, and 58.3%; and 91.5, 90, and 96.9%, respectively.

CONCLUSION

A machine learning scheme using data from anatomical and advanced MRI sequences resulted in high-performance automatic tumor classification algorithm. Such a scheme can be integrated into clinical decision support systems to optimize tumor classification.

Modern imaging of pituitary adenomas

Decision-making in pituitary disease is critically dependent on high quality imaging of the sella and parasellar region. Magnetic resonance imaging (MRI) is the investigation of choice and, for the majority of patients, combined T1 and T2 weighted sequences provide the information required to allow surgery, radiotherapy (RT) and/or medical therapy to be planned and long-term outcomes to be monitored. However, in some cases standard clinical MR sequences are indeterminate and additional information is needed to help inform the choice of therapy for a pituitary adenoma (PA). This article reviews current recommendations for imaging of PA, examines the potential added value that alternative MR sequences and/or CT can offer, and considers how the use of functional/molecular imaging might allow definitive treatment to be recommended for a subset of patients who would otherwise be deemed unsuitable for (further) surgery and/or RT.

rCBV- and ADC-based Grading of Meningiomas With Glimpse Into Emerging Molecular Diagnostics

Introduction

This study was conducted to grade meningiomas based on relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC) to help surgeons plan the approach and extent of operation as well as decide on the need of any adjuvant radio/chemo therapy. The current and evolving genomic, proteomic, and spectroscopic technologies are also discussed which can supplement the current radiologic methods and procedures in grading meningiomas.

Methods

A total of 35 patients with meningioma prospectively underwent basic MR sequences (T1W, T2W, T2W/FLAIR) in axial, sagittal and coronal planes followed by Diffusion Weighted (DW) imaging having b value of 1000 (minimum ADC values used for analysis). Then, gadobenate dimeglumine/meglumine gadoterate was administered (0.1 mmol/kg at a rate of 4 mL/s) followed by saline flush (20 mL at a rate of 4 mL/s). Next, T₂*W/FFE dynamic images were acquired; dynamics showing maximum fall in intensity was used for creating rCBV and relative Cerebral Blood Flow (rCBF) maps and calculating rCBV.

Results

Both maximum rCBV and minimum ADC within the tumor were not significant for differentiating benign from malignant meningiomas. A cut-off maximum rCBV of 2.5 mL/100 g in peritumoral edema was 75% sensitive, 84.6% specific, and 83.3% accurate in differentiating benign from malignant meningiomas.

Conclusion

Benign and malignant meningiomas can be differentiated based on maximum rCBV in peritumoral edema but ADC values within the tumor are insignificant in differentiating benign and malignant tumors. rCBV values within tumor, however, may be helpful in subtyping meningiomas, especially transitional and meningothelial meningiomas.

Characteristic features and proposed classification in 69 cases of intracranial microcystic meningiomas

Microcystic meningioma (MM) is a rare subtype of intracranial meningiomas, with clinical and radiologic features not well characterized in the literature. Based on our experience, we propose a classification system of intracranial MMs. We reviewed the medical records, radiographic studies, and operative notes of a group of consecutive patients with intracranial MM. The mean age of the 69 patients was 46.8 ± 10.6 years (range, 21-75 years). Three types of intracranial MMs could be identified. Type 1 MMs presented as a solid lesion, hypointense or isointense on T1WI, hyperintense on T2WI, and homogeneous or heterogeneous enhancement, and were found in 43 patients (67.2%). Type 2 MMs represented signals similar to CSF both on T1WI and T2WI, and faint reticular enhancement with marginal enhancement, and these were found in 7 patients (10.9%). Type 3 MMs consisted of cystic-solid or cystic lesion and were found in 14 patients (21.9%). Significant differences were observed among the different types of MMs for the following variables: sex, presence of severe peritumoral brain edema (PTBE), and extent of tumor resection. Females were found in all of patients with type 2 MMs, but were only 35.7% of those with type 3 MMs (P = 0.018). Severe PTBEs were more common among patients with type 1 MMs (55.8%) than among those with type 2 (14.3%) and type 3 MMs (14.3%) (P = 0.007). Type 1 MMs (97.7%) were associated with a significantly higher rate of gross total resection compared with the other two types (71.4 and 78.6%) (P = 0.019). Total length of hospital stay after craniotomy ranged from 4 to 30 days (median, 8 days). There were no significant differences in progression-free survival among the three types of MMs (P = 0.788). The current classification identifies three distinct types of intracranial MM based on their radiological findings and growth patterns. The type 1 MMs are more commonly associated with severe PTBE. Type 2 and Type 3 MMs have a higher predilection towards parasaggital location with venous involvement and therefore have a lower rate of gross total resection.

Radiation Therapy for Residual or Recurrent Atypical Meningioma: The Effects of Modality, Timing, and Tumor Pathology on Long-Term Outcomes

BACKGROUND

Optimal use of stereotactic radiosurgery (SRS) vs external beam radiation therapy (EBRT) for treatment of residual/recurrent atypical meningioma is unclear.

OBJECTIVE

To analyze features associated with progression after radiation therapy.

METHODS

Fifty radiation-naive patients who received SRS or EBRT for residual and/or recurrent atypical meningioma were examined for predictors of progression using Cox regression and Kaplan-Meier analyses.

RESULTS

Thirty-two patients (64%) received adjuvant radiation after subtotal resection, 12 patients (24%) received salvage radiation after progression following subtotal resection, and 6 patients (12%) received salvage radiation after recurrence following gross total resection. Twenty-one patients (42%) received SRS (median 18 Gy), and 7 (33%) had tumor progression. Twenty-nine patients (58%) received EBRT (median 54 Gy), and 13 (45%) had tumor progression. Whereas tumor volume (P = .53), SRS vs EBRT (P = .45), and adjuvant vs salvage (P = .34) were not associated with progression after radiation therapy, spontaneous necrosis (hazard ratio [HR] = 82.3, P < .001), embolization necrosis (HR = 15.6, P = .03), and brain invasion (HR = 3.8, P = .008) predicted progression in univariate and multivariate analyses. Tumors treated with SRS/EBRT had 2- and 5-year actuarial locoregional control rates of 91%/88% and 71%/69%, respectively. Tumors with spontaneous necrosis, embolization necrosis, and no necrosis had 2- and 5-year locoregional control rates of 76%, 92%, and 100% and 36%, 73%, and 100%, respectively (P < .001).

CONCLUSION

This study suggests that necrosis may be a negative predictor of radiation response regardless of radiation timing or modality.

ABBREVIATIONS

AM, atypical meningiomaEBRT, external beam radiation therapyGTR, gross total resectionLC, locoregional controlOS, overall survivalPOE, preoperative embolizationRT, radiation therapySRS, stereotactic radiosurgerySTR, subtotal resection.

Usefulness of enhancement-perfusion mismatch in differentiation of CNS lymphomas from other enhancing malignant tumors of the brain

Background

Surgical planning and treatment options for primary or secondary central nervous system lymphomas (PCNSL or SCNSL) are different from other enhancing malignant lesions such as glioblastoma multiforme (GBM), anaplastic gliomas and metastases; so, it is critical to distinguish them preoperatively. We hypothesized that enhancement-perfusion (E-P) mismatch on dynamic susceptibility weighted magnetic resonance (DSC-MR) perfusion imaging which corresponds to low mean relative cerebral blood volume (mean rCBV) in an enhancing portion of the tumor should allow differentiation of CNS lymphomas from other enhancing malignant lesions.

Methods

We retrospectively reviewed pre-treatment MRI exams, including DSC-MR perfusion images of 15 lymphoma patients. As a control group, pre-treatment DSC-MR perfusion images of biopsy proven 18 GBMs (group II), 13 metastases (group III), and 10 anaplastic enhancing gliomas (group IV) patients were also reviewed. Region of interests (ROIs) were placed around the most enhancing part of tumor on contrast-enhanced T1WI axial images and images were transferred onto co-registered DSC perfusion maps to obtain CBV in all 4 groups. The mean and maximum relative CBV values were obtained. Statistical analysis was performed on SPSS software and significance of the results between the groups was done with Mann-Whitney test, whereas optimal thresholds for tumor differentiation were done by receiver operating characteristic (ROC) analysis.

Results

The enhancing component of CNS lymphomas were found to have significantly lower mean rCBV compared to enhancing component of GBM (1.2 versus 4.3; P<0.001), metastasis (1.2 versus 2.7; P<0.001), and anaplastic enhancing gliomas (1.2 versus 2.4; P<0.001). Maximum rCBV of enhancing component of lymphoma were significantly lower than GBM (3.1 versus 6.5; P<0.001) and metastasis (3.1 versus 4.9; P<0.013), and not significantly lower than anaplastic enhancing gliomas (3.9 versus 4.2; P<0.08). On the basis of ROC analysis, mean rCBV provided the best threshold [area under the curve (AUC) =0.92] and had better accuracy in differentiating malignant lesions.

Conclusions

E-P mismatch in DSC perfusion MR, i.e., low mean rCBV in an enhancing portion of the tumor is strongly suggestive of lymphoma and should allow differentiation of CNS lymphoma from other enhancing malignant lesions.

Incidental Meningiomas: Management in the Neuroimaging Era

The number of patient imaging studies has increased because of precautious physicians ordering scans when a vague symptom is presented; subsequently, the number of incidental meningiomas detected has increased as well. These brain tumors do not present with related symptoms and are usually small. MRI and computed tomographic scans most frequently capture incidental meningiomas. Incidental meningiomas are managed with observation, radiation, and surgical resection. Ultimately, a conservative approach is recommended, such as observing an incidental meningioma and then only radiating if the tumor displays growth, whereas a surgical approach is to be used only when proven necessary.

Quantitative Perfusion and Permeability Biomarkers in Brain Cancer from Tomographic CT and MR Images

Dynamic contrast-enhanced perfusion and permeability imaging, using computed tomography and magnetic resonance systems, are important techniques for assessing the vascular supply and hemodynamics of healthy brain parenchyma and tumors. These techniques can measure blood flow, blood volume, and blood-brain barrier permeability surface area product and, thus, may provide information complementary to clinical and pathological assessments. These have been used as biomarkers to enhance the treatment planning process, to optimize treatment decision-making, and to enable monitoring of the treatment noninvasively. In this review, the principles of magnetic resonance and computed tomography dynamic contrast-enhanced perfusion and permeability imaging are described (with an emphasis on their commonalities), and the potential values of these techniques for differentiating high-grade gliomas from other brain lesions, distinguishing true progression from posttreatment effects, and predicting survival after radiotherapy, chemotherapy, and antiangiogenic treatments are presented.

Benign neck masses showing restricted diffusion: Is there a histological basis for discordant behavior?

Diffusion weighted imaging (DWI) evolved as a complementary tool to morphologic imaging by offering additional functional information about lesions. Although the technique utilizes movement of water molecules to characterize biological tissues in terms of their cellularity, there are other factors related to the histological constitution of lesions which can have a significant bearing on DWI. Benign lesions with atypical histology including presence of lymphoid stroma, inherently increased cellularity or abundant extracellular collagen can impede movement of water molecules similar to malignant tissues and thereby, show restricted diffusion. Knowledge of these atypical entities while interpreting DWI in clinical practice can avoid potential misdiagnosis. This review aims to present an imaging spectrum of such benign neck masses which, owing to their distinct histology, can show discordant behavior on DWI.

Advanced Imaging of Intracranial Meningiomas

Although typically not necessary for the diagnosis of intracranial meningiomas, advanced imaging techniques, including perfusion and diffusion imaging, spectroscopy, and nuclear medicine imaging, can help confirm the diagnosis of intracranial meningiomas, especially for meningiomas that do not exhibit the typical anatomic imaging findings. Advanced imaging techniques also have the potential to be able to differentiate between the subtypes of meningiomas, predict clinical aggressiveness of the tumor, and better characterize response to treatment. Although no advanced imaging technique has been able to definitively subclassify meningiomas, current results are encouraging and may be helpful in surgical planning.

Fast spectroscopic multiple analysis (FASMA) for brain tumor classification: a clinical decision support system utilizing multi-parametric 3T MR data

INTRODUCTION

A clinical decision support system (CDSS) for brain tumor classification can be used to assist in the diagnosis and grading of brain tumors. A Fast Spectroscopic Multiple Analysis (FASMA) system that uses combinations of multiparametric MRI data sets was developed as a CDSS for brain tumor classification.

METHODS

MRI metabolic ratios and spectra, from long and short TE, respectively, as well as diffusion and perfusion data were acquired from the intratumoral and peritumoral area of 126 patients with untreated intracranial tumors. These data were categorized based on the pathology, and different machine learning methods were evaluated regarding their classification performance for glioma grading and differentiation of infiltrating versus non-infiltrating lesions. Additional databases were embedded to the system, including updated literature values of the related MR parameters and typical tumor characteristics (imaging and histological), for further comparisons. Custom Graphical User Interface (GUI) layouts were developed to facilitate classification of the unknown cases based on the user's available MR data.

RESULTS

The highest classification performance was achieved with a support vector machine (SVM) using the combination of all MR features. FASMA correctly classified 89 and 79% in the intratumoral and peritumoral area, respectively, for cases from an independent test set. FASMA produced the correct diagnosis, even in the misclassified cases, since discrimination between infiltrative versus non-infiltrative cases was possible.

CONCLUSIONS

FASMA is a prototype CDSS, which integrates complex quantitative MR data for brain tumor characterization. FASMA was developed as a diagnostic assistant that provides fast analysis, representation and classification for a set of MR parameters. This software may serve as a teaching tool on advanced MRI techniques, as it incorporates additional information regarding typical tumor characteristics derived from the literature.

Management of Atypical Cranial Meningiomas, Part 2

BACKGROUND:

The efficacies of adjuvant stereotactic radiosurgery (SRS) and external beam radiation therapy (EBRT) for atypical meningiomas (AMs) after subtotal resection (STR) remain unclear.

OBJECTIVE:

To analyze the clinical, histopathological, and radiographic features associated with progression in AM patients after STR.

METHODS:

Fifty-nine primary AMs after STR were examined for predictors of progression, including the impact of SRS and EBRT, in a retrospective cohort study.

RESULTS:

Twenty-seven patients (46%) progressed after STR (median, 30 months). On univariate analysis, spontaneous necrosis positively (hazard ratio = 5.2; P = .006) and adjuvant radiation negatively (hazard ratio = 0.3; P = .009) correlated with progression; on multivariate analysis, only adjuvant radiation remained independently significant (hazard ratio = 0.3; P = .006). SRS and EBRT were associated with greater local control (LC; P = .02) and progression-free survival (P = .007). The 2-, 5-, and 10-year actuarial LC rates after STR vs STR/EBRT were 60%, 34%, and 34% vs 96%, 65%, and 45%. The 2-, 5-, and 10-year actuarial progression-free survival rates after STR vs STR/EBRT were 60%, 30%, and 26% vs 96%, 65%, and 45%. Compared with STR alone, adjuvant radiation therapy significantly improved LC in AMs that lack spontaneous necrosis (P = .003) but did not improve LC in AMs with spontaneous necrosis (P = .6).

CONCLUSION:

Adjuvant SRS or EBRT improved LC of AMs after STR but only for tumors without spontaneous necrosis. Spontaneous necrosis may aid in decisions to administer adjuvant SRS or EBRT after STR of AMs.

Prognostic Value of Conventional Magnetic Resonance Imaging for Adult Patients with Brain Tumors

PURPOSE

Magnetic resonance imaging (MRI) is the pivotal diagnostic step in patients with brain tumors, and is performed before histological diagnosis is available. We hypothesized that conventional MRI is as accurate as tumor histology in differentiating malignant from benign clinical course.

METHODS

Two neuroradiologists blinded to any clinical information evaluated the first diagnostic MRI of 244 brain tumor patients before any treatment, using a self-developed standardized list of image criteria and prospectively determined world health organization (WHO) tumor grade and tumor entity. All patients were examined with at least T1- and T2-weighted spin echo sequences before and after contrast injection on 1 and 1.5-T MRI scanners. Following the patients prospectively for 8-13 years after diagnosis, we were able to use nonsurvival at 5 years as a criterion for malignity and reference for the prognostic accuracy of both MRI and tumor tissue histology.

RESULTS

The accuracy for predicting nonsurvival at 5 years was 91% (95% confidence interval (CI): 87-94%) for MRI and 92% (95% CI: 88-95%) for histology. The Kaplan-Meier survival curves of patients with benign and malignant brain tumors as diagnosed by MRI or histology differed significantly (p < 0.001). Histology confirmed benignity or malignity in 201 patients (82%, 95% CI: 77-87%). Sources of misdiagnosis were metastases diagnosed as astrocytoma WHO IV, atypical meningiomas, and low-grade astrocytoma with malignant transformation.

CONCLUSION

MRI appears as accurate as histology in predicting survival at 5 years after diagnosis. Histological diagnosis may be more specific, however, and is needed to assess the tumor's specific biology.

The role of diffusion and perfusion weighted imaging in the differential diagnosis of cerebral tumors: a review and future perspectives

The role of conventional Magnetic Resonance Imaging (MRI) in the detection of cerebral tumors has been well established. However its excellent soft tissue visualization and variety of imaging sequences are in many cases non-specific for the assessment of brain tumor grading. Hence, advanced MRI techniques, like Diffusion-Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI) and Dynamic-Susceptibility Contrast Imaging (DSCI), which are based on different contrast principles, have been used in the clinical routine to improve diagnostic accuracy. The variety of quantitative information derived from these techniques provides significant structural and functional information in a cellular level, highlighting aspects of the underlying brain pathophysiology. The present work, reviews physical principles and recent results obtained using DWI/DTI and DSCI, in tumor characterization and grading of the most common cerebral neoplasms, and discusses how the available MR quantitative data can be utilized through advanced methods of analysis, in order to optimize clinical decision making.

Magnetic resonance imaging of meningiomas: a pictorial review

Meningiomas are the most common non-glial tumour of the central nervous system (CNS). There are a number of characteristic imaging features of meningiomas on magnetic resonance imaging (MRI) that allow an accurate diagnosis, however there are a number of atypical features that may be diagnostically challenging. Furthermore, a number of other neoplastic and non-neoplastic conditions may mimic meningiomas. This pictorial review discusses the typical and atypical MRI features of meningiomas and their mimics.

TEACHING POINTS

There are several characteristic features of meningiomas on MRI that allow an accurate diagnosis Some meningiomas may display atypical imaging characteristics that may be diagnostically challenging Routine MRI sequences do not reliably distinguish between benign and malignant meningiomas Spectroscopy and diffusion tensor imaging may be useful in the diagnosis of malignant meningiomas A number of conditions may mimic meningiomas; however, they may have additional differentiating features.

Investigating brain tumor differentiation with diffusion and perfusion metrics at 3T MRI using pattern recognition techniques

The aim of this study was to evaluate the contribution of diffusion and perfusion MR metrics in the discrimination of intracranial brain lesions at 3T MRI, and to investigate the potential diagnostic and predictive value that pattern recognition techniques may provide in tumor characterization using these metrics as classification features. Conventional MRI, diffusion weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic-susceptibility contrast imaging (DSCI) were performed on 115 patients with newly diagnosed intracranial tumors (low-and- high grade gliomas, meningiomas, solitary metastases). The Mann-Whitney U test was employed in order to identify statistical differences of the diffusion and perfusion parameters for different tumor comparisons in the intra-and peritumoral region. To assess the diagnostic contribution of these parameters, two different methods were used; the commonly used receiver operating characteristic (ROC) analysis and the more sophisticated SVM classification, and accuracy, sensitivity and specificity levels were obtained for both cases. The combination of all metrics provided the optimum diagnostic outcome. The highest predictive outcome was obtained using the SVM classification, although ROC analysis yielded high accuracies as well. It is evident that DWI/DTI and DSCI are useful techniques for tumor grading. Nevertheless, cellularity and vascularity are factors closely correlated in a non-linear way and thus difficult to evaluate and interpret through conventional methods of analysis. Hence, the combination of diffusion and perfusion metrics into a sophisticated classification scheme may provide the optimum diagnostic outcome. In conclusion, machine learning techniques may be used as an adjunctive diagnostic tool, which can be implemented into the clinical routine to optimize decision making.

Classification methods for the differentiation of atypical meningiomas using diffusion and perfusion techniques at 3-T MRI

The purpose was to investigate the contribution of machine learning algorithms using diffusion and perfusion techniques in the differentiation of atypical meningiomas from glioblastomas and metastases. Apparent diffusion coefficient, fractional anisotropy, and relative cerebral blood volume were measured in different tumor regions. Naive Bayes, k-Nearest Neighbor, and Support Vector Machine classifiers were used in the classification procedure. The application of classification methods adds incremental differential diagnostic value. Differentiation is mainly achieved using diffusion metrics, while perfusion measurements may provide significant information for the peritumoral regions.

Usefulness of perfusion weighted magnetic resonance imaging with signal-intensity curves analysis in the differential diagnosis of sellar and parasellar tumors: preliminary report

PURPOSE

The most common pituitary tumors are adenomas, which however may be mimicked by other tumors that can show a very similar appearance in plain MRI. The aim of our study was to evaluate the usefulness of perfusion weighted MR imaging (PWI), including signal-intensity curves analysis in the differential diagnosis of sellar/parasellar tumors.

METHODS

Forty-one patients with sellar/parasellar tumors (23 macroadenomas, 10 meningiomas, 5 craniopharyngiomas, 1 intrasellar hemangioblastoma, 1 intrasellar prostate cancer metastasis, 1 suprasellar glioma), underwent plain MRI followed by PWI using a 1.5T unit. In each tumor, the mean and maximum values of relative cerebral blood volume (rCBV), as well as the relative peak height (rPH) and the relative percentage of signal intensity recovery (rPSR) were calculated.

RESULTS

The high perfusion tumors were: macroadenomas, meningiomas, squamous-papillary type of craniopharyngiomas, hemangioblastoma, glioma and metastasis. The low perfusion neoplasms included adamantinomatous type of craniopharyngiomas. By comparing adenomas and meningiomas, we found statistically significant differences in the mean and maximum rCBV values (p=0.026 and p=0.019, respectively), but not in rPH and rPSR. The maximum rCBV values >7.14 and the mean rCBV values >5.74 with the typical perfusion curve were very suggestive of the diagnosis of meningioma. There were differences between adenomas and other high perfusion tumors in rPH and rPSR values.

CONCLUSIONS

PWI can provide additional information helpful in differential diagnosis of sellar/parasellar tumors. In our opinion PWI, as an easy to perform and fast technique should be incorporated into the MR protocol of all intracranial neoplasms including sellar/parasellar tumors.

Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed.

Advanced magnetic resonance imaging biomarkers of cerebral metastases

There are a number of magnetic resonance imaging techniques available for use in the diagnosis and management of patients with cerebral metastases. This article reviews these techniques, in particular, the advanced imaging methodologies from which quantitative parameters can be derived, the role of these imaging biomarkers have in distinguishing metastases from primary central nervous system tumours and tumour mimics, and metrics that may be of value in predicting the origin of the primary tumour.

Distinct peak at 3.8 ppm observed by 3T MR spectroscopy in meningiomas, while nearly absent in high-grade gliomas and cerebral metastases

The purpose of the present study was to evaluate distinct metabolic features of meningiomas to distinguish them from other brain lesions using proton magnetic resonance spectroscopy. The study was performed on 17 meningiomas, 24 high-grade gliomas and 9 metastases. Elevated signal intensity at 3.8 ppm observed in low TE spectra adequately differentiated meningioma from other brain tumors while alanine was not indicative of meningioma occurrence; the presence of lipids and lactate did not provide a strong index for meningioma malignancy.

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.

Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the brain

BACKGROUND AND PURPOSE

Differentiation of enhancing malignant lesions on conventional MR imaging can be difficult and various newer imaging techniques have been suggested. Our aim was to evaluate the role of PSR obtained from DSC perfusion measurements in differentiating lymphoma, GBM, and metastases. The effectiveness of PSR was compared with that of rCBV. We hypothesized that the newly defined parameter of PSR is more sensitive and specific in differentiating these lesions.

MATERIALS AND METHODS

This retrospective study included 66 patients (39 men and 27 women; age range: 27-82 years) with a pathologically proved diagnosis of primary CNS lymphoma, GBM, or metastases (22 patients in each group). Mean PSR, min PSR, max PSR, and rCBV were calculated. The classification accuracy of these parameters was investigated by using ROC.

RESULTS

Mean PSR was high (113.15 ± 41.59) in lymphoma, intermediate in GBM (78.22 ± 14.27), and low in metastases (53.46 ± 12.87) with a P value < .000. F values obtained from 1-way ANOVA analysis for mean, min, and max PSR ratios were 29.9, 39.4, and 23.4, respectively, which were better than those of rCBV (11.1) in differentiating the 3 groups. Max PSR yielded the best ROC characteristics with an A(z) of 0.934 (95% CI, 0.877-0.99) in differentiating lymphoma from metastases and GBM. The A(z) for mean and min PSR of 0.938 (95% CI, 0.0.884-0.990) and 0.938 (95% CI, 0.884-0.991), respectively, was better than rCBV (A(z), 0.534; 95% CI, 0.391-0.676) in the differentiation of metastases from GBM and lymphoma (P ≤ .0001).

CONCLUSIONS

PSR appears to be a parameter that helps in differentiating intracerebral malignant lesions such as GBM, metastases, and lymphoma.

Investigation of blood perfusion and metabolic activity of brain tumours in adults by using 99mTc-methoxyisobutylisonitrile

OBJECTIVES

(i) To examine blood perfusion and metabolic activity of various brain tumours using radionuclide cerebral angiography (RCA) and single-photon emission tomography (SPET) after a single dose of Tc-methoxyisobutylisonitrile (MIBI). (ii) To examine if the inclusion of RCA can improve insight into the relative contribution of tumour perfusion to the uptake of MIBI shown by SPET, and to improve evaluation of tumour biology. (iii) To determine the value and the roles of MIBI in the management of brain tumour patients.

METHODS

Fifty adult patients (38 male, 12 female) with a total of 56 intracranial space-occupying lesions have been included prospectively, 37 of which were newly diagnosed and the remaining with signs of recurrence/rest of earlier resected and irradiated brain tumours. The control group consisted of nine volunteers with no evidence of organic cerebral disease. Scintigraphic examination consisted of a dynamic first-pass study lasting 60 s (3 s/frame) and two SPET studies (60 projections each, 25 s/projection), starting 15 min and 2 h after intravenous injection of MIBI. Regions of interest of the tumour and normal brain tissue were drawn on RCA and both early and delayed SPET slices. The following tumour/brain activity ratios have been calculated: (i) tumour perfusion index (P); (ii) early uptake index (E); (iii) delayed uptake index (D); and(iv) retention index (R). Analogous indices have been calculated from the same examinations performed in controls, reflecting maximal physiologic regional variations of perfusion and uptake in brain tissue.

RESULTS

Mean P of various brain tumours (low-grade gliomas 0.98, anaplastic gliomas 1.14, glioblastoma multiforme 1.20, metastases 1.09, lymphomas 1.08) differ little from each other and do not exceed maximal physiologic regional variations of cerebral perfusion (1.33), with the exception of meningioma (1.87, F=2.83, P=0.015). The receiver operating characteristics curve analysis of P showed that for the cut-off value of 1.45 the sensitivity for distinguishing meningioma from other tumours is 75%, specificity 87%, positive predictive value 33% and negative predictive value 97%. Mean E of malignant brain tumours (8.3, n=31, 23 primary, eight secondary), except anaplastic gliomas (3.5, n=5), differed significantly (P=0.02) from those of benign gliomas (3, n=9) but not from that of meningioma (11.9, n=4). The cut-off value for distinguishing malignant from benign lesions on the basis of E set at 4.8 resulted in sensitivity 67%, specificity 75%, accuracy 70%, positive predictive value 80% and negative predictive value 60%. D and R showed tendency of wash-out of MIBI from meningiomas, but otherwise did not improve the results substantially.

CONCLUSION

Integrated results of RCA and SPET with Tc-MIBI indicate that blood perfusion, blood-tumour barrier permeability and metabolic activity of the tumour are all very important for the resultant uptake shown by SPET. If the perfusion index is less than 1.45, then meningioma can be ruled out. Early SPET is recommendable for distinguishing glioblastoma from low-grade gliomas, as a complement to standard magnetic resonance imaging and/or computed tomography.

Magnetic resonance perfusion imaging in neuro-oncology

Recent advances in magnetic resonance imaging (MRI) have seen the development of techniques that allow quantitative imaging of a number of anatomical and physiological descriptors. These techniques have been increasingly applied to cancer imaging where they can provide some insight into tumour microvascular structure and physiology. This review details technical approaches and application of quantitative MRI, focusing particularly on perfusion imaging and its role in neuro-oncology.