Advanced MR Imaging Techniques in the Diagnosis of Intraaxial Brain Tumors in Adults

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

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

Primary central nervous system lymphoma: Imaging features and differential diagnosis

Primary central nervous system lymphoma (PCNSL) represents 5% of malignant primary brain tumors. The clinical presentation typically includes focal neurological symptoms, increased intracranial pressure, seizures, and psychiatric symptoms. Although histological examination remains the gold standard for diagnostic confirmation, non-invasive imaging plays a crucial role for the diagnosis. In immunocompetent individuals, PCNSL usually appears as a single, well-defined, supratentorial lesion with a predilection for periventricular areas, iso- or hypointense on T1- and T2-weighted magnetic resonance imaging, with restricted diffusion, slightly increased perfusion, and homogenous gadolinium-enhancement. Differential diagnoses include high-grade glioma and pseudotumoral demyelinating disease. In immunocompromised patients, PCNSL may present as multiple lesions, with a higher likelihood of hemorrhage and necrosis and less restricted diffusion than immunocompetent individuals. Differential diagnoses include neurotoxoplasmosis, progressive multifocal leukoencephalopathy, and cerebral abscess. Atypical forms of lymphoma are characterized by extra-axial lymphoma, lymphomatosis cerebri, and intravascular lymphoma. Extra-axial lymphoma presents as single or multiple extra-axial dural lesions with diffuse leptomeningeal contrast-enhancement. Lymphomatosis cerebri appears as an infiltrative and symmetric lesion, primarily affecting deep white matter and basal ganglia, appearing hyperintense on T2-weighted imaging, without significant contrast-enhancement or perfusion changes. Intravascular lymphoma presents as multiple rounded or oval-shaped "infarct-like" lesions, located cortically or subcortically. This study aims to highlight the imaging characteristics of PCNSL, focusing on magnetic resonance imaging and its differential diagnosis.

Balanced transformer: efficient classification of glioblastoma and primary central nervous system lymphoma

Objective.Primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) are malignant primary brain tumors with different biological characteristics. Great differences exist between the treatment strategies of PCNSL and GBM. Thus, accurately distinguishing between PCNSL and GBM before surgery is very important for guiding neurosurgery. At present, the spinal fluid of patients is commonly extracted to find tumor markers for diagnosis. However, this method not only causes secondary injury to patients, but also easily delays treatment. Although diagnosis using radiology images is non-invasive, the morphological features and texture features of the two in magnetic resonance imaging (MRI) are quite similar, making distinction with human eyes and image diagnosis very difficult. In order to solve the problem of insufficient number of samples and sample imbalance, we used data augmentation and balanced sample sampling methods. Conventional Transformer networks use patch segmentation operations to divide images into small patches, but the lack of communication between patches leads to unbalanced data layers.Approach.To address this problem, we propose a balanced patch embedding approach that extracts high-level semantic information by reducing the feature dimensionality and maintaining the geometric variation invariance of the features. This approach balances the interactions between the information and improves the representativeness of the data. To further address the imbalance problem, the balanced patch partition method is proposed to increase the receptive field by sampling the four corners of the sliding window and introducing a linear encoding component without increasing the computational effort, and designed a new balanced loss function.Main results.Benefiting from the overall balance design, we conducted an experiment using Balanced Transformer and obtained an accuracy of 99.89%, sensitivity of 99.74%, specificity of 99.73% and AUC of 99.19%, which is far higher than the previous results (accuracy of 89.6% ∼ 96.8%, sensitivity of 74.3% ∼ 91.3%, specificity of 88.9% ∼ 96.02% and AUC of 87.8% ∼ 94.9%).Significance.This study can accurately distinguish PCNSL and GBM before surgery. Because GBM is a common type of malignant tumor, the 1% improvement in accuracy has saved many patients and reduced treatment times considerably. Thus, it can provide doctors with a good basis for auxiliary diagnosis.

Diagnostic Approaches to Adult-Type Diffuse Glial Tumors: Comparative Literature and Clinical Practice Study

Gliomas are the most frequent intrinsic central nervous system tumors. The new 2021 WHO Classification of Central Nervous System Tumors brought significant changes into the classification of gliomas, that underline the role of molecular diagnostics, with the adult-type diffuse glial tumors now identified primarily by their biomarkers rather than histology. The status of the isocitrate dehydrogenase (IDH) 1 or 2 describes tumors at their molecular level and together with the presence or absence of 1p/19q codeletion are the most important biomarkers used for the classification of adult-type diffuse glial tumors. In recent years terminology has also changed. IDH-mutant, as previously known, is diagnostically used as astrocytoma and IDH-wildtype is used as glioblastoma. A comprehensive understanding of these tumors not only gives patients a more proper treatment and better prognosis but also highlights new difficulties. MR imaging is of the utmost importance for diagnosing and supervising the response to treatment. By monitoring the tumor on followup exams better results can be achieved. Correlations are seen between tumor diagnostic and clinical manifestation and surgical administration, followup care, oncologic treatment, and outcomes. Minimal resection site use of functional imaging (fMRI) and diffusion tensor imaging (DTI) have become indispensable tools in invasive treatment. Perfusion imaging provides insightful information about the vascularity of the tumor, spectroscopy shows metabolic activity, and nuclear medicine imaging displays tumor metabolism. To accommodate better treatment the differentiation of pseudoprogression, pseudoresponse, or radiation necrosis is needed. In this report, we present a literature review of diagnostics of gliomas, the differences in their imaging features, and our radiology's departments accumulated experience concerning gliomas.

A Novel Approach for Brain Tumor Classification Using an Ensemble of Deep and Hand-Crafted Features

One of the most severe types of cancer caused by the uncontrollable proliferation of brain cells inside the skull is brain tumors. Hence, a fast and accurate tumor detection method is critical for the patient's health. Many automated artificial intelligence (AI) methods have recently been developed to diagnose tumors. These approaches, however, result in poor performance; hence, there is a need for an efficient technique to perform precise diagnoses. This paper suggests a novel approach for brain tumor detection via an ensemble of deep and hand-crafted feature vectors (FV). The novel FV is an ensemble of hand-crafted features based on the GLCM (gray level co-occurrence matrix) and in-depth features based on VGG16. The novel FV contains robust features compared to independent vectors, which improve the suggested method's discriminating capabilities. The proposed FV is then classified using SVM or support vector machines and the k-nearest neighbor classifier (KNN). The framework achieved the highest accuracy of 99% on the ensemble FV. The results indicate the reliability and efficacy of the proposed methodology; hence, radiologists can use it to detect brain tumors through MRI (magnetic resonance imaging). The results show the robustness of the proposed method and can be deployed in the real environment to detect brain tumors from MRI images accurately. In addition, the performance of our model was validated via cross-tabulated data.

Ex vivo NMR metabolomics approach using cerebrospinal fluid for the diagnosis of primary CNS lymphoma: Correlation with MR imaging characteristics

PURPOSE

Primary central nervous system lymphoma (PCNSL) is an uncommon extranodal non-Hodgkin's lymphoma. Here, the feasibility of nuclear magnetic resonance (NMR) metabolomics for the diagnosis and prognosis prediction of PCNSL, as well as its correlation with magnetic resonance imaging (MRI) characteristics, was assessed.

PATIENTS AND METHODS

Cerebrospinal fluid (CSF) samples from PCNSL and normal groups (n = 41 for each) were obtained along with MRI data including pre- and postcontrast as well as T1-, T2-, and diffusion-weighted imaging for the treatment-naïve PCNSL patients (n = 24). The CSF samples were analyzed using nuclear magnetic resonance (NMR).

RESULTS

The CSF NMR metabolomic exhibited clear differences with a diagnostic sensitivity of 100% and a specificity of 97.6%. The citrate level of the leptomeningeal enhancement (LE) (+) group was significantly lower than that of the LE (-) group (p = 0.018). In addition, the MRI apparent diffusion coefficient (ADC) value of the tumor was positively correlated with the glucose level (p = 0.025). However, none of the marker metabolites were significant prognosis predictors in univariate analysis.

CONCLUSIONS

In conclusion, the NMR metabolomics could be helpful to diagnose PCNSL, but not for the prognosis, and MRI features (LE or ADC) can reflect the metabolic profiles of PCNSL.

Tumor volume and calcifications as indicators for preoperative differentiation of grade II/III diffuse gliomas

PURPOSE

To retrospectively evaluate preoperative clinical factors for their ability to preoperatively differentiate malignancy grades in patients with incipient supratentorial grade II/III diffuse gliomas.

METHODS

This retrospective study included 206 adult patients with incipient supratentorial grade II/III diffuse gliomas according to the 2016 World Health Organization classification of tumors of the central nervous system. The cohort included 136 men and 70 women, with a median age of 41 years. Preoperative factors included age, sex, presence of calcifications on computed tomography scans, and preoperative tumor volume measured using preoperative magnetic resonance imaging.

RESULTS

In patients with oligodendrogliomas (IDH-mutant and 1p/19q-codeleted), calcifications were significantly more frequent (p = 0.0034) and tumor volume was significantly larger (p < 0.001) in patients with grade III tumors than in those with grade II tumors. Moreover, in patients with IDH-mutant astrocytomas, preoperative tumor volume was significantly larger (p = 0.0042) in patients with grade III tumors than in those with grade II tumors. In contrast, none of the evaluated preoperative clinical factors were significantly different between the patients with grade II and III IDH-wildtype astrocytomas.

CONCLUSION

In adult patients with suspicison incipient supratentorial grade II/III diffuse gliomas, presence of calcifications and larger preoperative tumor volume might be used as preoperative indices to differentiate between malignancy grades II and III in oligodendrogliomas (IDH-mutant and 1p/19q-codeleted) and larger preoperative tumor volume might have similar utility in IDH-mutant astrocytomas.

Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives

MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases of patient management, starting from diagnosis, through therapy planning, to treatment response and/or recurrence assessment. Currently, neuroimaging can describe morphologic and non-morphologic (functional, hemodynamic, metabolic, cellular, microstructural, and sometimes even genetic) characteristics of brain tumors, greatly contributing to diagnosis and follow-up. Knowing the technical aspects, strength and limits of each MR technique is crucial to correctly interpret MR brain studies and to address clinicians to the best treatment strategy. This article aimed to provide an overview of neuroimaging in the assessment of adult primary brain tumors. We started from the basilar role of conventional/morphological MR sequences, then analyzed, one by one, the non-morphological techniques, and finally highlighted future perspectives, such as radiomics and artificial intelligence.

Brain metastases: A Society for Neuro-Oncology (SNO) consensus review on current management and future directions

Brain metastases occur commonly in patients with advanced solid malignancies. Yet, less is known about brain metastases than cancer-related entities of similar incidence. Advances in oncologic care have heightened the importance of intracranial management. Here, in this consensus review supported by the Society for Neuro-Oncology (SNO), we review the landscape of brain metastases with particular attention to management approaches and ongoing efforts with potential to shape future paradigms of care. Each coauthor carried an area of expertise within the field of brain metastases and initially composed, edited, or reviewed their specific subsection of interest. After each subsection was accordingly written, multiple drafts of the manuscript were circulated to the entire list of authors for group discussion and feedback. The hope is that the these consensus guidelines will accelerate progress in the understanding and management of patients with brain metastases, and highlight key areas in need of further exploration that will lead to dedicated trials and other research investigations designed to advance the field.

Metabolic Magnetic Resonance Imaging in Neuroimaging: Magnetic Resonance Spectroscopy, Sodium Magnetic Resonance Imaging and Chemical Exchange Saturation Transfer

Magnetic resonance (MR) is a powerful and versatile technique that offers much more beyond conventional anatomic imaging and has the potential of probing in vivo metabolism. Although MR spectroscopy (MRS) predates clinical MR imaging (MRI), its clinical application has been limited by technical and practical challenges. Other MR techniques actively being developed for in vivo metabolic imaging include sodium concentration imaging and chemical exchange saturation transfer. This article will review some of the practical aspects of MRS in neuroimaging, introduce sodium MRI and chemical exchange saturation transfer MRI, and highlight some of their emerging clinical applications.

Brain Tumor Causes, Symptoms, Diagnosis and Radiotherapy Treatment

The strategy used for the treatment of given brain cancer is critical in determining the post effects and survival. An oncological diagnosis of tumor evaluates a range of parameters such as shape, size, volume, location and neurological complexity that define the symptomatic severity. The evaluation determines a suitable treatment approach chosen from a range of options such as surgery, chemotherapy, hormone therapy, radiation therapy and other targeted therapies. Often, a combination of such therapies is applied to achieve superior results. Radiotherapy serves as a better treatment strategy because of a higher survival rate. It offers the flexibility of synergy with other treatment strategies and fewer side effects on organs at risk. This review presents a radiobiological perspective in the treatment of brain tumor. The cause, symptoms, diagnosis, treatment, post-treatment effects and the framework involved in its elimination are summarized.

Brain FET PET tumor-to-white mater ratio to differentiate recurrence from post-treatment changes in high-grade gliomas

BACKGROUND AND PURPOSE

Highergrade glial neoplasms undergo standard treatment with surgery, radiotherapy, and alkylating agents. There is often a clinical/neuroimaging dilemma in the post-treatment setting to differentiate disease recurrence from treatment-related changes. FET (fluoro-ethyl-tyrosine) PET has emerged as a molecular imaging modality for cases where MR imaging is inconclusive. This study aims to develop a cutoff on FET PET for differentiating true recurrence from post-treatment changes.

METHODS

We retrospectively analyzed72 patientswith post-treatment grade 3 or 4 brain gliomas. Five to six mCi of ¹⁸ F-FET was injected and static imaging of the brain was performed at 20 min. A tumor-to-white matter (T/Wm) ratio was used as semiquantitative parameter. A T/Wm cutoff of 2.5 was used for image interpretation. Imaging findings were confirmed by either histopathologic diagnosis in a multidisciplinary joint clinic or based on follow-up of clinical and neuroimaging findings.

RESULTS

Forty-one of 72 patients (57%) showed recurrent disease on FET PET. Thirty-five of them were confirmed to have tumor recurrence; six patients showed post-treatment changes. Thirty-one of 72 patients (43%) showed post-treatment changes on FET PET; 27 were confirmed as post-treatment change and four patients had tumor recurrence on subsequent MR imaging. An optimum T/Wm cutoff of 2.65 was derived based on receiver operating characteristic analysis with a sensitivity of 80% and specificity of 87.5%.

CONCLUSION

Static FET PET can be used as problem-solving imaging modality with a T/Wm cutoff of 2.65 to differentiate late recurrence from post-treatment changes in grade 3 or 4 brain gliomas with equivocal MR features.

Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities

Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient's clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.

Challenges and advances for the treatment of renal cancer patients with brain metastases: From immunological background to upcoming clinical evidence on immune-checkpoint inhibitors

The introduction of checkpoint inhibitors (ICIs) in renal cell carcinoma (RCC) treatment landscape, resulted in improvements in overall survival (OS) in metastatic patients. Brain metastases (BMs) are a specific metastatic site of interest representing a predictive factor of poor prognosis. Patients with BMs were usually excluded from prospective clinical trials in the past. Despite recent evidence suggest the efficacy and safety of ICIs, the BMs treatment remains a challenge; the immunotherapy responsiveness seems to be multifactorial and dependent on several factors, such as the genetic intratumor heterogeneity and the immunosuppressive role of the brain tumor microenvironment. This review, starting from the immunological background in RCC BMs, provide an overview of the upcoming evidence from clinical trials, address the issues related to the neuroradiological immunotherapy response evaluation and, with a look to the future, describes how the epigenetic modulation of immune evasion could represent a background for new therapeutic strategies.

Accuracy of apparent diffusion coefficient in differentiation of glioblastoma from metastasis

BACKGROUND

Brain metastasis and glioblastoma multiforme are two of the most common malignant brain neoplasms. There are many difficulties in distinguishing these diseases from each other.

PURPOSE

The purpose of this study was to determine whether the mean apparent diffusion coefficient and absolute standard deviation derived from apparent diffusion coefficient measurements can be used to differentiate glioblastoma multiforme from brain metastasis based on cellularity levels.

MATERIAL AND METHODS

Magnetic resonance images of 34 patients with histologically verified brain tumors were evaluated retrospectively. Apparent diffusion coefficient and standard deviation values were measured in the enhancing tumor, peritumoral region, and contralateral healthy white matter. Then, to determine whether there was a statistical difference between brain metastasis and glioblastoma multiforme, we analyzed different variables between the two groups.

RESULTS

Neither mean apparent diffusion coefficient values and ratios nor standard deviation values and ratios were significantly different between glioblastoma multiforme and brain metastasis. Receiver operating characteristic curve analysis of the logistic model with backward stepwise feature selection yielded an area under the curve of 0.77, a specificity of 84%, a sensitivity of 67%, a positive predictive value of 83.33%, and a negative predictive value of 78.26% for distinguishing between glioblastoma multiforme and brain metastasis. The absolute standard deviation and standard deviation ratios were significantly higher in the peritumoral edema compared to the tumor region in each case.

CONCLUSION

Apparent diffusion coefficient values and ratios, as well as standard deviation values and ratios in peritumoral edema, cannot be used to differentiate edema with infiltration of tumor cells from vasogenic edema. However, standard deviation values could successfully characterize areas of peritumoral edema from the tumoral region in each case.

Neuroimaging of pediatric infratentorial tumors and the value of diffusion-weighted imaging (DWI) in determining tumor grade

BACKGROUND

Diffusion-weighted imaging (DWI) provides information about the cellular density of tumors. This feature is useful in grading and identifying different tumor types.

PURPOSE

To assess the value of diffusion restriction and apparent diffusion coefficient (ADC) values in differentiating pediatric infratentorial tumors.

MATERIAL AND METHODS

This was a retrospective review of the magnetic resonance imaging (MRI) of 82 children (age range 1-16 years) with infratentorial tumors. Histopathological grading after surgical excision/biopsy was categorized as low grade (WHO grades I and II) (n = 31; 29 pilocytic astrocytomas, 2 ependymomas) and high grade (WHO grade III and IV) (n = 51; 40 medulloblastomas, 8 anaplastic ependymomas, 1 anaplastic astrocytoma, 2 atypical rhabdoid teratoid tumors [ATRT]). MRI features and ADC values were compared among tumor types and grades using a two-tailed t test, Mann-Whitney U test for continuous data and Chi-square test for categorical variables.

RESULTS

Diffusion restriction and low ADC value was a feature of high-grade tumors (P<0.001). The mean ADC values of the low-grade and high-grade tumors were 1.567 × 10^-3mm²/s and 0.661 × 10^-3mm²/s, respectively. Using 0.9 × 10^-3mm²/s as the cut-off value, the sensitivity, specificity, positive and negative predictive values for differentiating the grades was 87%, 100%, 100%, and 81.8%, respectively. Significant differences were found between the mean ADC values of the individual tumor types (P<0.05), except between medulloblastoma and ATRT.

CONCLUSION

ADC values and visual assessment of diffusion restriction are useful in tumor grading. The individual tumor types can be identified by an algorithmic approach, using DWI in conjunction with other described MRI features.

A decision support system for multimodal brain tumor classification using deep learning

Multiclass classification of brain tumors is an important area of research in the field of medical imaging. Since accuracy is crucial in the classification, a number of techniques are introduced by computer vision researchers; however, they still face the issue of low accuracy. In this article, a new automated deep learning method is proposed for the classification of multiclass brain tumors. To realize the proposed method, the Densenet201 Pre-Trained Deep Learning Model is fine-tuned and later trained using a deep transfer of imbalanced data learning. The features of the trained model are extracted from the average pool layer, which represents the very deep information of each type of tumor. However, the characteristics of this layer are not sufficient for a precise classification; therefore, two techniques for the selection of features are proposed. The first technique is Entropy–Kurtosis-based High Feature Values (EKbHFV) and the second technique is a modified genetic algorithm (MGA) based on metaheuristics. The selected features of the GA are further refined by the proposed new threshold function. Finally, both EKbHFV and MGA-based features are fused using a non-redundant serial-based approach and classified using a multiclass SVM cubic classifier. For the experimental process, two datasets, including BRATS2018 and BRATS2019, are used without increase and have achieved an accuracy of more than 95%. The precise comparison of the proposed method with other neural nets shows the significance of this work.

Conventional and advanced imaging throughout the cycle of care of gliomas

Although imaging of gliomas has evolved tremendously over the last decades, published techniques and protocols are not always implemented into clinical practice. Furthermore, most of the published literature focuses on specific timepoints in glioma management. This article reviews the current literature on conventional and advanced imaging techniques and chronologically outlines their practical relevance for the clinical management of gliomas throughout the cycle of care. Relevant articles were located through the Pubmed/Medline database and included in this review. Interpretation of conventional and advanced imaging techniques is crucial along the entire process of glioma care, from diagnosis to follow-up. In addition to the described currently existing techniques, we expect deep learning or machine learning approaches to assist each step of glioma management through tumor segmentation, radiogenomics, prognostication, and characterization of pseudoprogression. Thorough knowledge of the specific performance, possibilities, and limitations of each imaging modality is key for their adequate use in glioma management.

Magnetic resonance spectroscopy in pediatric brain tumors: how to make a more confident diagnosis

Background

Non-invasive diagnosis of pediatric brain tumors can be challenging due to diverse tumor pathologies and similar imaging appearances. Magnetic resonance spectroscopy (MRS), when combined with high spatial resolution anatomic imaging obtained with conventional magnetic resonance imaging (MRI), provides metabolic information within the lesion as well as the surrounding tissue. The differentiation of neoplastic from non-neoplastic lesions and low-grade from high-grade neoplasms is essential for determining the choice of treatment and the best treatment plan. We aimed to measure specific metabolic ratios and evaluate metabolic profiles of various lesions by MRS to assist in making a more confident diagnosis.

Results

The choline/creatine (Cho/Cr), choline/N-acetylaspartate (Cho/NAA), and Cho/NAA+Cr ratios all had statistically significant values for the differentiation between neoplastic and non-neoplastic lesions at cutoffs 1.8, 2, and 0.8 respectively. The Cho/NAA, Cho/Cr, Cho/NAA+Cr, and myo-inositol/creatine (mI/Cr) ratios all had statistically significant values for the differentiation of high-grade from low-grade neoplasms at cutoffs 3.3, 3.5, 1.3, and 1.5 respectively. The presence of a lipid lactate peak was only significant for differentiating high-grade from low-grade neoplasms. Medulloblastomas, diffuse pontine gliomas, and choroid plexus carcinoma all showed characteristic metabolic profiles on MRS. Metastasis showed lower Cho/NAA and Cho/Cr ratios outside the tumor margin than high-grade neoplasms.

Conclusion

The use of certain metabolite ratios with high sensitivity and specificity to distinguish neoplastic from non-neoplastic lesions and low-grade from high-grade neoplasms while assessing the metabolic profile of the lesion aids in the non-invasive diagnosis of pediatric brain tumors. MRS facilitates earlier treatment planning by determining tumor spatial extent and predicting tumor behavior with potential to solve sampling problems of inaccessible and heterogenous lesions as well as unnecessary sampling of benign lesions.

Evolving Use of fMRI in Medicare Beneficiaries

Using the Medicare Physician-Supplier Procedure Summary Master File, we evaluated the evolving use of fMRI in Medicare fee-for-service beneficiaries from 2007 through 2017. Annual use rates (per 1,000,000 enrollees) increased from 17.7 to 32.8 through 2014 and have remained static since. Radiologists have remained the dominant specialty group from 2007 to 2017 (86.4% and 88.6% of all services, respectively), and the outpatient setting has remained the dominant place of service (65.4% and 65.4%, respectively).

Comparing dynamic susceptibility contrast perfusion post-processing with different clinically available software among patients affected of a high-grade glioma

BACKGROUND AND PURPOSE

The main purpose of this retrospective study was to evaluate inter-software variability in patients affected of a high-grade glioma for the post-processing of dynamic susceptibility contrast (DSC¹) perfusion imaging in MRI.² MATERIALS AND METHODS: The included patients were either anaplastic astrocytoma (WHO³ grade III) or glioblastoma (WHO grade IV) located in the cerebral parenchyma. The postprocessing of 54 MRI-DSC imaging from 46 patients using both Intellispace© (Philips) and Olea© (Olea Medical) software was performed. The hemodynamic parameter studied was the normalised relative cerebral blood volume corrected for the T1 leakage effect (nrCBVc⁴). The inter-operator variabilities were also evaluated.

RESULTS

Regarding inter-software reproducibility, Cohen's Kappa from therapeutic follow-up obtained were 0.61, close to the recommended limit (0.60). Subgroups were created to complete the analysis and to evaluate the partial volume effect. Even if necrosis or vascular structures from regions of interest (ROI⁵) were avoided, results did not improve. ROI of a minimum area of 250 mm² yielded a Cohen's Kappa of 0.65. The inter-operator reproducibility on Intellispace and Olea were 0.90 and 0.73 respectively, which is satisfactory.

CONCLUSION

The reproducibility between Intellispace and Olea was below recommended threshold in a clinical context. This discrepancy can be explained by the partial volume effect and the models used. ROI with an area of at least 250 mm² improves this reproducibility and becomes acceptable.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

The diagnostic value of MR spectroscopy versus DWI-MRI in therapeutic planning of suspicious multi-centric cerebral lesions

Background

A broad spectrum of non-neoplastic lesions can radiologically mimic cerebral neoplasms. Magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and diffusion-weighted imaging (DWI) are the most extensively used for enabling lesional characterization of different brain disorders. We aimed to assess the diagnostic value of MRS versus DWI in the diagnosis and therapeutic planning of multicentric cerebral focal lesions and in our retrospective study, we enrolled 64 patients with 100 brain lesions who underwent pre- and post-contrast MRI, MRS, and DWI. Diagnoses supplied by the histopathology and follow up clinical results as a gold standard. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy were calculated.

Results

Conventional MRI poorly differentiates multiple cerebral lesions with 89.33% sensitivity, 44.4% specificity, and 78% accuracy. MRS results revealed statistical significance for differentiating neoplastic from non-neoplastic lesions as regards Cho/Cr, Cho/NAA, and NAA/Cr ratios (M ± SD) with P < 0.001 (significant), and there is statistical significance for neoplastic lesion differentiation when Cho/NAA and Ch/Cr ratios measured in the pre-lesional areas outside the tumor margin. DWI showed mixed diffusion changes in most of the studied lesions and the measured ADC values ranges showed overlap in neoplastic and non-neoplastic lesions, P value = 0.236* (insignificant).

Conclusion

MRS was found to be a more accurate diagnostic tool than DWI with ADC measurements in the differentiation and therapeutic planning of multicentric cerebral focal lesions.

Better efficacy in differentiating WHO grade II from III oligodendrogliomas with machine-learning than radiologist's reading from conventional T1 contrast-enhanced and fluid attenuated inversion recovery images

Background

The medical imaging to differentiate World Health Organization (WHO) grade II (ODG2) from III (ODG3) oligodendrogliomas still remains a challenge. We investigated whether combination of machine leaning with radiomics from conventional T1 contrast-enhanced (T1 CE) and fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) offered superior efficacy.

Methods

Thirty-six patients with histologically confirmed ODGs underwent T1 CE and 33 of them underwent FLAIR MR examination before any intervention from January 2015 to July 2017 were retrospectively recruited in the current study. The volume of interest (VOI) covering the whole tumor enhancement were manually drawn on the T1 CE and FLAIR slice by slice using ITK-SNAP and a total of 1072 features were extracted from the VOI using 3-D slicer software. Random forest (RF) algorithm was applied to differentiate ODG2 from ODG3 and the efficacy was tested with 5-fold cross validation. The diagnostic efficacy of radiomics-based machine learning and radiologist’s assessment were also compared.

Results

Nineteen ODG2 and 17 ODG3 were included in this study and ODG3 tended to present with prominent necrosis and nodular/ring-like enhancement (P < 0.05). The AUC, ACC, sensitivity, and specificity of radiomics were 0.798, 0.735, 0.672, 0.789 for T1 CE, 0.774, 0.689, 0.700, 0.683 for FLAIR, as well as 0.861, 0.781, 0.778, 0.783 for the combination, respectively. The AUCs of radiologists 1, 2 and 3 were 0.700, 0.687, and 0.714, respectively. The efficacy of machine learning based on radiomics was superior to the radiologists’ assessment.

Conclusions

Machine-learning based on radiomics of T1 CE and FLAIR offered superior efficacy to that of radiologists in differentiating ODG2 from ODG3.

Investigating dynamic susceptibility contrast-enhanced perfusion-weighted magnetic resonance imaging in posterior fossa tumors: differences and similarities with supratentorial tumors

PURPOSE

To assess the accuracy of dynamic susceptibility contrast-enhanced perfusion-weighted magnetic resonance imaging in glioma grading and brain tumor characterization of infratentorial tumors, and to investigate differences from supratentorial tumors.

METHODS

This retrospective study, approved by the institutional review board, included 246 patients with brain tumors (184 supratentorial, 62 infratentorial), grouped by tumor type: high-grade gliomas (HGG), low-grade gliomas (LGG), metastases (Met), and primary central nervous system lymphoma (PCNSL). Relative cerebral blood volume (rCBV) and mean percentage of signal recovery (PSR) were calculated. For statistical analyses, lesions were grouped by location and histology. Differences were tested with Mann-Whitney U tests. From ROC curves, we calculated accuracy, sensitivity, specificity, PPV, and NPV, for rCBV and PSR.

RESULTS

For infratentorial tumors, rCBV was highly accurate in differentiating HGG from LGG (AUC = 0.938). Mean PSR showed high accuracy in differentiating PCNSL and HGG from Met (AUC = 0.978 and AUC = 0.881, respectively). Infratentorial and supratentorial tumors had similarly high rCBV in HGG, high mean PSR in PCNSL, and low mean PSR in Met. The main differences were the optimum threshold rCBV values (3.04 for supratentorial, 1.77 for infratentorial tumors) and the mean PSR, which was significantly higher in LGG than in HGG in supratentorial (p = 0.035), but not infratentorial gliomas. Using infratentorial rCBV threshold values for supratentorial tumors decreased the sensitivity and specificity.

CONCLUSION

rCBV and mean PSR were useful in grading and differentiating infratentorial tumors. Proper cutoff values were important in the accuracy of perfusion-weighted imaging in posterior fossa tumors.

Imaging and Radiologic-Pathologic Correlation in Granular Cell Astrocytomas: Report of 2 Cases

BACKGROUND

Granular cell astrocytoma is a rare and aggressive subtype of astrocytoma that is histopathologically well defined in the literature. It is formed by polygonal cells with granular cytoplasm mixed with neoplastic astrocytes and usually a perivascular infiltrate of lymphocytes. Despite its unusual histologic appearance, relevant radiologic features have not yet been described.

CASE DESCRIPTION

We report 2 middle-aged patients with neurologic symptoms secondary to a newly diagnosed brain tumor. The absence of central tumor necrosis as well as the presence of an atypical pattern of enhancement and areas of intense diffusion restriction on magnetic resonance imaging in both cases led to the diagnosis of primary central nervous system lymphoma. Histopathologic findings in both tumors showed an aggressive astrocytoma with a prominent granular cell population and perivascular lymphocytic cuffing in tissue, corresponding to a granular cell astrocytoma. Despite the favorable prognostic factors, including World Health Organization grades II and III astrocytomas and IDH mutations, the outcome was poor.

CONCLUSIONS

Granular cell astrocytomas can show unusual aggressive radiologic features that do not correspond to their histopathologic grade of malignancy. The presence of perivascular lymphocytic infiltrate may alter the typical radiologic appearance of common astrocytomas.

MR Perfusion and MR Spectroscopy of Brain Neoplasms

Advances in imaging techniques, such as MR perfusion and spectroscopy, are increasingly indispensable in the management and treatment plans of brain neoplasms: from diagnosing, molecular/genetic typing and grading neoplasms, augmenting biopsy results and improving accuracy, to ultimately directing and monitoring treatment and response. New developments in treatment methods have resulted in new diagnostic challenges for conventional MR imaging, such as pseudoprogression, where MR perfusion has the widest current application. MR spectroscopy is showing increasing promise in noninvasively determining genetic subtypes and, potentially, susceptibility to molecular targeted therapies.

Neuroimaging of acute and chronic unilateral and bilateral thalamic lesions

The thalami are bilateral ovoid grey matter cerebral structures bordering the third ventricle on both sides, which participate in functions such as relaying of sensory and motor signals, regulation of consciousness, and alertness. Pathologies affecting the thalami can be of neoplastic, infectious, vascular, toxic, metabolic, or congenital origin.The purpose of this review is to provide a comprehensive approach to the thalamus focusing on its anatomy, the main pathologies affecting this structure and their radiological semiology on CT and MRI. We will also illustrate the importance of multimodal MR imaging (morphologic sequences, diffusion-weighted imaging, perfusion, spectroscopy) for the diagnosis and treatment of these conditions.

Smart MRI Agents for Detecting Extracellular Events In Vivo: Progress and Challenges

Many elegant inorganic designs have been developed to aid medical imaging. We know better now how to improve imaging due to the enormous efforts made by scientists in probe design and other fundamental sciences, including inorganic chemistry, physiochemistry, analytical chemistry, and biomedical engineering. However, despite several years being invested in the development of diagnostic probes, only a few examples have shown applicability in MRI in vivo. In this short review, we aim to show the reader the latest advances in the application of inorganic agents in preclinical MRI.

Brain tumour post-treatment imaging and treatment-related complications

Purpose

The imaging of primary and metastatic brain tumours is very complex and relies heavily on advanced magnetic resonance imaging (MRI). Utilisation of these advanced imaging techniques is essential in helping clinicians determine tumour response after initiation of treatment. Many options are currently available to treat brain tumours, and each can significantly alter the brain tumour appearance on post-treatment imaging. In addition, there are several common and uncommon treatment-related complications that are important to identify on standard post-treatment imaging.

Methods

This article provides a review of the various post-treatment-related imaging appearances of brain neoplasms, including a discussion of advanced MR imaging techniques available and treatment response criteria most commonly used in clinical practice. This article also provides a review of the multitude of treatment-related complications that can be identified on routine post-treatment imaging, with an emphasis on radiation-induced, chemotherapy-induced, and post-surgical entities.

Summary/Conclusion

Although radiological evaluation of brain tumours after treatment can be quite challenging, knowledge of the various imaging techniques available can help the radiologist distinguish treatment response from tumour progression and has the potential to save patients from inappropriate alterations in treatment. In addition, knowledge of common post-treatment-related complications that can be identified on imaging can help the radiologist play a key role in preventing significant patient morbidity/mortality.

Teaching points

• Contrast enhancement does not reliably define tumour extent in many low-grade or infiltrative gliomas.

• Focal regions of elevated cerebral blood volume (rCBV) on dynamic susceptibility contrast (DSC) perfusion-weighted imaging are suggestive of tumour growth/recurrence.

• Brain tumour treatment response criteria rely on both imaging and clinical parameters.

• Chemotherapeutic agents can potentiate many forms of radiation-induced injury.

• Ipilimumab-induced hypophysitis results in transient diffuse enlargement of the pituitary gland.

Cerebellar Tonsillar Cysts Associated with Chiari Malformation in Adults: A Short Series

BACKGROUND

Authors analyzed surgical patients with Chiari malformation (CM) associated with cerebellar tonsillar cyst. This association is quite rarely encountered in the literature.

CASE DESCRIPTION

We retrospectively reviewed 60 surgical adult patients with MRI evaluation who underwent posterior fossa decompression for treatment of CM type I. All surgeries were performed between January 1995 and July 2015. From 60 patients with CM, four cases presented cerebellar tonsillar cysts (male=2). Basilar invagination (BI) (n=4) and syringomyelia (n=1) were associated. There were pyramidal signs (n=4) and low cranial nerves dysfunction (n=1). Radiological evaluation showed T1-hypointense and T2-hyperintense image on the cystic tissue (n=4). The surgical technique was suboccipital craniectomy, C1-C2 laminectomy (if needed), y-shaped durotomy, total resection and coagulation/aspiration of tonsils.

CONCLUSIONS

In the present series, we were able to identify 7% of tonsillar cysts among 60 patients with CM. MRI with Flair and Diffusion sequences should be pre-operatively used for evaluation of tissue characteristics as differential diagnosis of cystic lesion and gliosis. The clinical presentation endorses surgical indication, with a good chance of clinical improvement. This was the first time that the frequency of tonsillar cysts has been evaluated in a series of adult patients.

Added Value of Spectroscopy to Perfusion MRI in the Differential Diagnostic Performance of Common Malignant Brain Tumors

BACKGROUND AND PURPOSE

Perfusion and spectroscopic MR imaging provide noninvasive physiologic and metabolic characterization of tissues, which can help in differentiating brain tumors. We investigated the diagnostic role of perfusion and spectroscopic MR imaging using individual and combined classifiers of these modalities and assessed the added performance value that spectroscopy can provide to perfusion using optimal combined classifiers that have the highest differential diagnostic performance to discriminate lymphomas, glioblastomas, and metastases.

MATERIALS AND METHODS

From January 2013 to January 2016, fifty-five consecutive patients with histopathologically proved lymphomas, glioblastomas, and metastases were included after undergoing MR imaging. The perfusion parameters (maximum relative CBV, maximum percentage of signal intensity recovery) and spectroscopic concentration ratios (lactate/Cr, Cho/NAA, Cho/Cr, and lipids/Cr) were analyzed individually and in optimal combinations. Differences among tumor groups, differential diagnostic performance, and differences in discriminatory performance of models with quantification of the added performance value of spectroscopy to perfusion were tested using 1-way ANOVA models, receiver operating characteristic analysis, and comparisons between receiver operating characteristic analysis curves using a bivariate χ², respectively.

RESULTS

The highest differential diagnostic performance was obtained with the following combined classifiers: maximum percentage of signal intensity recovery-Cho/NAA to discriminate lymphomas from glioblastomas and metastases, significantly increasing the sensitivity from 82.1% to 95.7%; relative CBV-Cho/NAA to discriminate glioblastomas from lymphomas and metastases, significantly increasing the specificity from 92.7% to 100%; and maximum percentage of signal intensity recovery-lactate/Cr and maximum percentage of signal intensity recovery-Cho/Cr to discriminate metastases from lymphomas and glioblastomas, significantly increasing the specificity from 83.3% to 97.0% and 100%, respectively.

CONCLUSIONS

Spectroscopy yielded an added performance value to perfusion using optimal combined classifiers of these modalities, significantly increasing the differential diagnostic performances for these common brain tumors.

Setting pressure can change the size and shape of MRI artifacts caused by adjustable shunt valves: a study of the 4 newest models

OBJECTIVEAdjustable shunt valves that have been developed for the management of hydrocephalus all rely on intrinsically magnetic components, and artifacts with these valves on MRI are thus inevitable. The authors have previously reported that the shapes of shunt artifacts differ under different valve pressures with the proGAV 2.0 valve. In the present study the authors compared the size and shape of artifacts at different pressure settings with 4 new-model shunt valves.METHODSThe authors attached 4 new models of MRI-resistant shunt valve to the temporal scalp of a healthy volunteer: the proGAV 2.0; Codman Certas Plus; Polaris; and Strata MR. They set 3 different scales of pressures for each valve, depending on magnet orientation to the body axis. Artifacts were evaluated and compared among all valves on a 3.0-T GE scanner and 2 valves were also evaluated on a Philips scanner and a Siemens scanner. In-plane artifact sizes were evaluated as the maximum distance of the artifact from the expected scalp.RESULTSThe sizes and shapes of artifacts changed depending on valve pressure for all valves on the 3 different MRI scanners. Artifacts were less prominent on spin echo sequences than on gradient echo sequences. For diffusion-weighted imaging and time-of-flight MR angiography, the authors matched image numbers within the same sequence and compared appearances of artifacts. For all valves, the number of images affected by artifacts and the image number showing the largest artifact differed among valve settings.CONCLUSIONSArtifacts of all adjustable shunt valves showed gross changes corresponding to pressure setting. Not only the maximum distance of artifacts but also the shape changed significantly. The authors suggest that changing pressure settings offers one of the easiest ways to minimize artifacts on MRI.

Cerebral Metastases of Lung Cancer Mimicking Multiple Ischaemic Lesions - A Case Report and Review of Literature

Background

Restricted diffusion that is found on magnetic resonance diffusion-weighted imaging (DWI) typically indicates acute ischaemic stroke. However, restricted diffusion can also occur in other diseases, like metastatic brain tumours, which we describe in this case report.

Case Report

A 57-year-old male, with a diagnosis of small-cell cancer of the right lung (microcellular anaplastic carcinoma), was admitted with focal neurological symptoms. Initial brain MRI revealed multiple, disseminated lesions that were hyperintense on T2-weighted images and did not enhance after contrast administration; notably, some lesions manifested restricted diffusion on DWI images. Based on these findings, disseminated ischaemic lesions were diagnosed. On follow-up MRI that was performed after 2 weeks, we observed enlargement of the lesions; there were multiple, disseminated, sharply outlined, contrast-enhancing, oval foci with persistent restriction of diffusion. We diagnosed the lesions as disseminated brain metastases due to lung cancer. To our knowledge, this is the first description of a patient with brain metastases that were characterised by restricted diffusion and no contrast enhancement.

Conclusions

Multiple, disseminated brain lesions, that are characterised by restricted diffusion on DWI, typically indicate acute or hyperacute ischemic infarcts; however, they can also be due to hypercellular metastases, even if no contrast enhancement is observed. This latter possibility should be considered particularly in patients with cancer.

Grading of oligodendroglial tumors of the brain with apparent diffusion coefficient, magnetic resonance spectroscopy, and dynamic susceptibility contrast imaging

Purpose We explored whether advanced magnetic resonance (MR) imaging techniques could grade oligodendrogliomas. Methods Forty patients (age 9-61 years) with oligodendroglial tumors were selected. There were 23 patients with World Health Organization grade II (group 1) and 17 patients with grade III (group 2) tumors. Apparent diffusion coefficient (ADC) maps were calculated by b values of 0 and 1000 s/mm². Dynamic susceptibility contrast (DSC) images were obtained during the first pass of a bolus of gadolinium-based contrast. These data were post-processed and cerebral blood volume (CBV) maps and permeability (PS) were calculated. MR spectroscopy was acquired after drawing a region of interest on the tumor using two-dimensional chemical shift imaging. Statistical analysis was performed using SPSS software. Results When the rPS_max was combined with the rCBV_max, there was a significant difference between the two groups ( p ≤ 0.03) with area under the curve of 0.742 (95% CI: 0.412-0.904). rCBV, rADC, choline/creatine, and choline/NAA alone were able to differentiate between the two groups; however, they did not show any statistical difference with p values of ≤ 0.121, ≤ 0.722, and ≤ 0.582, respectively. A CBV PS product threshold of 0.53 provided a sensitivity of 80% and a specificity of 83.3% in detection of grade III tumors. Conclusion Combined rCBV_max and rPS_max can be utilized to grade oligodendrogliomas. ADC values, relative cerebral blood volume (rCBV), and MR spectroscopy alone can be utilized to differentiate between the two groups of oligodendrogliomas but without statistical significance.

Magnetic resonance perfusion for differentiating low-grade from high-grade gliomas at first presentation

BACKGROUND

Gliomas are the most common primary brain tumour. They are graded using the WHO classification system, with Grade II-IV astrocytomas, oligodendrogliomas and oligoastrocytomas. Low-grade gliomas (LGGs) are WHO Grade II infiltrative brain tumours that typically appear solid and non-enhancing on magnetic resonance imaging (MRI) scans. People with LGG often have little or no neurologic deficit, so may opt for a watch-and-wait-approach over surgical resection, radiotherapy or both, as surgery can result in early neurologic disability. Occasionally, high-grade gliomas (HGGs, WHO Grade III and IV) may have the same MRI appearance as LGGs. Taking a watch-and-wait approach could be detrimental for the patient if the tumour progresses quickly. Advanced imaging techniques are increasingly used in clinical practice to predict the grade of the tumour and to aid clinical decision of when to intervene surgically. One such advanced imaging technique is magnetic resonance (MR) perfusion, which detects abnormal haemodynamic changes related to increased angiogenesis and vascular permeability, or "leakiness" that occur with aggressive tumour histology. These are reflected by changes in cerebral blood volume (CBV) expressed as rCBV (ratio of tumoural CBV to normal appearing white matter CBV) and permeability, measured by K^trans.

OBJECTIVES

To determine the diagnostic test accuracy of MR perfusion for identifying patients with primary solid and non-enhancing LGGs (WHO Grade II) at first presentation in children and adults. In performing the quantitative analysis for this review, patients with LGGs were considered disease positive while patients with HGGs were considered disease negative.To determine what clinical features and methodological features affect the accuracy of MR perfusion.

SEARCH METHODS

Our search strategy used two concepts: (1) glioma and the various histologies of interest, and (2) MR perfusion. We used structured search strategies appropriate for each database searched, which included: MEDLINE (Ovid SP), Embase (Ovid SP), and Web of Science Core Collection (Science Citation Index Expanded and Conference Proceedings Citation Index). The most recent search for this review was run on 9 November 2016.We also identified 'grey literature' from online records of conference proceedings from the American College of Radiology, European Society of Radiology, American Society of Neuroradiology and European Society of Neuroradiology in the last 20 years.

SELECTION CRITERIA

The titles and abstracts from the search results were screened to obtain full-text articles for inclusion or exclusion. We contacted authors to clarify or obtain missing/unpublished data.We included cross-sectional studies that performed dynamic susceptibility (DSC) or dynamic contrast-enhanced (DCE) MR perfusion or both of untreated LGGs and HGGs, and where rCBV and/or K^trans values were reported. We selected participants with solid and non-enhancing gliomas who underwent MR perfusion within two months prior to histological confirmation. We excluded studies on participants who received radiation or chemotherapy before MR perfusion, or those without histologic confirmation.

DATA COLLECTION AND ANALYSIS

Two review authors extracted information on study characteristics and data, and assessed the methodological quality using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We present a summary of the study characteristics and QUADAS-2 results, and rate studies as good quality when they have low risk of bias in the domains of reference standard of tissue diagnosis and flow and timing between MR perfusion and tissue diagnosis.In the quantitative analysis, LGGs were considered disease positive, while HGGs were disease negative. The sensitivity refers to the proportion of LGGs detected by MR perfusion, and specificity as the proportion of detected HGGs. We constructed two-by-two tables with true positives and false negatives as the number of correctly and incorrectly diagnosed LGG, respectively, while true negatives and false positives are the number of correctly and incorrectly diagnosed HGG, respectively.Meta-analysis was performed on studies with two-by-two tables, with further sensitivity analysis using good quality studies. Limited data precluded regression analysis to explore heterogeneity but subgroup analysis was performed on tumour histology groups.

MAIN RESULTS

Seven studies with small sample sizes (4 to 48) met our inclusion criteria. These were mostly conducted in university hospitals and mostly recruited adult patients. All studies performed DSC MR perfusion and described heterogeneous acquisition and post-processing methods. Only one study performed DCE MR perfusion, precluding quantitative analysis.Using patient-level data allowed selection of individual participants relevant to the review, with generally low risks of bias for the participant selection, reference standard and flow and timing domains. Most studies did not use a pre-specified threshold, which was considered a significant source of bias, however this did not affect quantitative analysis as we adopted a common rCBV threshold of 1.75 for the review. Concerns regarding applicability were low.From published and unpublished data, 115 participants were selected and included in the meta-analysis. Average rCBV (range) of 83 LGGs and 32 HGGs were 1.29 (0.01 to 5.10) and 1.89 (0.30 to 6.51), respectively. Using the widely accepted rCBV threshold of <1.75 to differentiate LGG from HGG, the summary sensitivity/specificity estimates were 0.83 (95% CI 0.66 to 0.93)/0.48 (95% CI 0.09 to 0.90). Sensitivity analysis using five good quality studies yielded sensitivity/specificity of 0.80 (95% CI 0.61 to 0.91)/0.67 (95% CI 0.07 to 0.98). Subgroup analysis for tumour histology showed sensitivity/specificity of 0.92 (95% CI 0.55 to 0.99)/0.42 (95% CI 0.02 to 0.95) in astrocytomas (6 studies, 55 participants) and 0.77 (95% CI 0.46 to 0.93)/0.53 (95% CI 0.14 to 0.88) in oligodendrogliomas+oligoastrocytomas (6 studies, 56 participants). Data were too sparse to investigate any differences across subgroups.

AUTHORS' CONCLUSIONS

The limited available evidence precludes reliable estimation of the performance of DSC MR perfusion-derived rCBV for the identification of grade in untreated solid and non-enhancing LGG from that of HGG. Pooled data yielded a wide range of estimates for both sensitivity (range 66% to 93% for detection of LGGs) and specificity (range 9% to 90% for detection of HGGs). Other clinical and methodological features affecting accuracy of the technique could not be determined from the limited data. A larger sample size of both LGG and HGG, preferably using a standardised scanning approach and with an updated reference standard incorporating molecular profiles, is required for a definite conclusion.

Noninvasive Glioblastoma Testing: Multimodal Approach to Monitoring and Predicting Treatment Response

Glioblastoma is the most aggressive adult primary brain tumor which is incurable despite intensive multimodal treatment. Inter- and intratumoral heterogeneity poses one of the biggest barriers in the diagnosis and treatment of glioblastoma, causing differences in treatment response and outcome. Noninvasive prognostic and predictive tests are highly needed to complement the current armamentarium. Noninvasive testing of glioblastoma uses multiple techniques that can capture the heterogeneity of glioblastoma. This set of diagnostic approaches comprises advanced MRI techniques, nuclear imaging, liquid biopsy, and new integrated approaches including radiogenomics and radiomics. New treatment options such as agents targeted at driver oncogenes and immunotherapy are currently being developed, but benefit for glioblastoma patients still has to be demonstrated. Understanding and unraveling tumor heterogeneity and microenvironment can help to create a treatment regime that is patient-tailored to these specific tumor characteristics. Improved noninvasive tests are crucial to this success. This review discusses multiple diagnostic approaches and their effect on predicting and monitoring treatment response in glioblastoma.

White Matter Diseases with Radiologic-Pathologic Correlation

White matter diseases include a wide spectrum of disorders that have in common impairment of normal myelination, either by secondary destruction of previously myelinated structures (demyelinating processes) or by primary abnormalities of myelin formation (dysmyelinating processes). The pathogenesis of many white matter diseases remains poorly understood. Demyelinating disorders are the object of this review and will be further divided into autoimmune, infectious, vascular, and toxic-metabolic processes. Autoimmune processes include multiple sclerosis and related diseases: tumefactive demyelinating lesions, Balo concentric sclerosis, Marburg and Schilder variants, neuromyelitis optica (Devic disease), acute disseminated encephalomyelitis, and acute hemorrhagic leukoencephalopathy (Hurst disease). Infectious processes include Lyme disease (neuroborreliosis), progressive multifocal leukoencephalopathy, and human immunodeficiency virus (HIV) encephalopathy. Vascular processes include different types of small-vessel disease: arteriolosclerosis, cerebral amyloid angiopathy, cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), primary angiitis of the central nervous system, Susac syndrome, and neurolupus. Toxic-metabolic processes include osmotic myelinolysis, methotrexate leukoencephalopathy, and posterior reversible encephalopathy syndrome. The imaging spectrum can vary widely from small multifocal white matter lesions to confluent or extensive white matter involvement. Understanding the pathologic substrate is fundamental for understanding the radiologic manifestations, and a systematic approach to the radiologic findings, in correlation with clinical and laboratory data, is crucial for narrowing the differential diagnosis. (©)RSNA, 2016.

Current Clinical Brain Tumor Imaging

Neuroimaging plays an ever evolving role in the diagnosis, treatment planning, and post-therapy assessment of brain tumors. This review provides an overview of current magnetic resonance imaging (MRI) methods routinely employed in the care of the brain tumor patient. Specifically, we focus on advanced techniques including diffusion, perfusion, spectroscopy, tractography, and functional MRI as they pertain to noninvasive characterization of brain tumors and pretreatment evaluation. The utility of both structural and physiological MRI in the post-therapeutic brain evaluation is also reviewed with special attention to the challenges presented by pseudoprogression and pseudoresponse.

Adult Brain Tumors: Clinical Applications of Magnetic Resonance Spectroscopy

Proton magnetic resonance spectroscopy (H-MRS) may be helpful in suggesting tumor histology and tumor grade and may better define tumor extension and the ideal site for biopsy compared with conventional magnetic resonance (MR) imaging. A multifunctional approach with diffusion-weighted imaging, perfusion-weighted imaging, and permeability maps, along with H-MRS, may enhance the accuracy of the diagnosis and characterization of brain tumors and estimation of therapeutic response. Integration of advanced imaging techniques with conventional MR imaging and the clinical history help to improve the accuracy, sensitivity, and specificity in differentiating tumors and nonneoplastic lesions.

Neuroimaging in Central Nervous System Lymphoma

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

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

INTRODUCTION

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Susceptibility Imaging in Glial Tumor Grading; Using 3 Tesla Magnetic Resonance (MR) System and 32 Channel Head Coil

Background

Susceptibility weighted imaging (SWI) is a velocity compensated, high-resolution three-dimensional (3D) spoiled gradient-echo sequence that uses magnitude and filtered-phase data. SWI seems to be a valuable tool for non-invasive evaluation of central nervous system gliomas. Relative cerebral blood volume (rCBV) ratio is one of the best noninvasive methods for glioma grading. Degree of intratumoral susceptibility signal (ITSS) on SWI correlates with rCBV ratio and histopathological grade. This study investigated the effectiveness of ITSS grading and rCBV ratio in preoperative assessment.

Material/Methods

Thirty-one patients (17 males and 14 females) with histopathogical diagnosis of glial tumor undergoing routine cranial MRI, SWI, and perfusion MRI examinations between October 2011 and July 2013 were retrospectively enrolled. All examinations were performed using 3T apparatus with 32-channel head coil. We used ITSS number for SWI grading. Correlations between SWI grade, rCBV ratio, and pathological grading were evaluated. ROC analysis was performed to determine the optimal rCBV ratio to distinguish between high-grade and low-grade glial tumors.

Results

There was a strong positive correlation between both pathological and SWI grading. We determined the optimal rCBV ratio to discriminate between high-grade and low-grade tumors to be 2.21

Conslusions

In conclusion, perfusion MRI and SWI using 3T MR and 32-channel head coil may provide useful information for preoperative glial tumor grading. SWI can be used as an accessory to perfusion MR technique in preoperative tumor grading.