The Contribution of Vessel Wall Magnetic Resonance Imaging to the Diagnosis of Primary and Secondary Central Nervous System Vasculitis

BACKGROUND

To describe high-resolution brain vessel wall MRI (VW-MRI) patterns and morphological brain findings in central nervous system (CNS) vasculitis patients.

METHODS

Fourteen patients with confirmed CNS Vasculitis from two tertiary centers underwent VW-MRI using a 3T scanner. The images were reviewed by two neuroradiologists to assess vessel wall enhancement characteristics and locations.

RESULTS

Fourteen patients were included (six females; average age 48 ± 19 years). Diagnoses included primary CNS vasculitis (PCNSV) in six patients and secondary CNS vasculitis (SCNSV) in eight, half of which were infection-related. Thirteen patients showed vessel wall enhancement, which was intense in eleven patients (84.6%) and concentric in twelve (92.3%), affecting the anterior circulation in nine patients (69.2%), posterior in two patients (15.4%), and both circulations in two patients (15.4%). The enhancement patterns were similar across different CNS vasculitis types. DWI changes corresponded with areas of vessel wall enhancement in 77% of patients. Conclusions: CNS vasculitis is often associated with intense, concentric vessel wall enhancement in VW-MRI, especially in the anterior circulation. The consistent presence of DWI alterations in affected territories suggests a possible link to microembolization or hypoperfusion. These imaging findings complement parenchymal brain MRI and MRA/DSA data, potentially increasing the possibility of a clinical diagnosis of CNS vasculitis.

Hemodynamic nature of black-blood enhancement in long-term coiled cerebral aneurysms

PURPOSE

Vessel wall imaging (VWI) with black-blood (BB) technique can demonstrate aneurysmal enhancement preluding to growth/rupture in treatment-naive cerebral aneurysms. Interestingly, recent works showed that BB enhancement may also occur in endovascularly treated aneurysms, though its meaning is controversial. Hypothesizing a flow-related mechanism of BB enhancement, we explored its relationship with incomplete occlusion status and coil packing density at DSA.

METHODS

We analyzed the subjects undergoing 3T MRI between January 2017 and October 2020 for a previous aneurysmal coiling. All the MRI studies included pre- and post-contrast 3D BB sequences. The presence of intra-aneurysmal pre-contrast BB signal was assessed. BB enhancement (when present) was classified as follows: (1) enhancement at the neck, (2) intrasaccular/intra-coil enhancement, and (3) peripheral enhancement. Coil packing density and aneurysmal occlusion status (according to the modified Raymond-Roy classification, MRRC) were determined on post-treatment DSA and compared with BB findings using generalized linear mixed-effect model and ANOVA. Significant p values were <0.05.

RESULTS

Forty-eight aneurysms from 44 patients were eligible for analysis. Pre-contrast BB signal was observed in 50% of the aneurysms and showed a relationship with baseline aneurysmal size. BB enhancement was detectable in 31 aneurysms (65%), being significantly associated with incomplete aneurysmal occlusion and reduced coil packing density at DSA.

CONCLUSION

BB enhancement of coiled aneurysms is related with increasing degrees of post-coiling aneurysmal remnants and with loose coil packing density at DSA. This supports a hemodynamic interpretation of BB enhancement in long-term coiled aneurysms.

Deep learning-based overall survival prediction model in patients with rare cancer: a case study for primary central nervous system lymphoma

PURPOSE

Primary central nervous system lymphoma (PCNSL) is a rare, aggressive form of extranodal non-Hodgkin lymphoma. To predict the overall survival (OS) in advance is of utmost importance as it has the potential to aid clinical decision-making. Though radiomics-based machine learning (ML) has demonstrated the promising performance in PCNSL, it demands large amounts of manual feature extraction efforts from magnetic resonance images beforehand. deep learning (DL) overcomes this limitation.

METHODS

In this paper, we tailored the 3D ResNet to predict the OS of patients with PCNSL. To overcome the limitation of data sparsity, we introduced data augmentation and transfer learning, and we evaluated the results using r stratified k-fold cross-validation. To explain the results of our model, gradient-weighted class activation mapping was applied.

RESULTS

We obtained the best performance (the standard error) on post-contrast T1-weighted (T1Gd)-area under curve [Formula: see text], accuracy [Formula: see text], precision [Formula: see text], recall [Formula: see text] and F1-score [Formula: see text], while compared with ML-based models on clinical data and radiomics data, respectively, further confirming the stability of our model. Also, we observed that PCNSL is a whole-brain disease and in the cases where the OS is less than 1 year, it is more difficult to distinguish the tumor boundary from the normal part of the brain, which is consistent with the clinical outcome.

CONCLUSIONS

All these findings indicate that T1Gd can improve prognosis predictions of patients with PCNSL. To the best of our knowledge, this is the first time to use DL to explain model patterns in OS classification of patients with PCNSL. Future work would involve collecting more data of patients with PCNSL, or additional retrospective studies on different patient populations with rare diseases, to further promote the clinical role of our model.

CSF-based liquid biopsy pointing to a diagnosis of diffuse glioma in a patient with supposed neurodegenerative disorder

INTRODUCTION

The differential diagnosis of brain diseases becomes challenging in cases where imaging is not sufficiently informative, and surgical biopsy is impossible or unacceptable to the patient.

METHODS

An elderly patient with progressive short-term memory loss and cognitive impairment presented with a normal brain CT scan, a brain FDG-PET that indicated symmetrical deterioration of the white matter in the frontal lobes, and inconclusive results of a molecular marker analysis of suspected dementia in cerebrospinal fluid (CSF). Brain MRI suggested the diagnosis of lower grade glioma. The patient refused surgical biopsy. In order to investigate whether somatic mutations associated with gliomas existed, we performed a "liquid biopsy" by the targeted sequencing of cell-free DNA (cfDNA) from his CSF.

RESULTS

Deep sequencing of the cfDNA from CSF revealed somatic mutations characteristically found in gliomas, including mutations of the TP53 (Arg282Trp), BRAF (Val600Glu), and IDH1 (Arg132His) genes. The patient is currently treated with temozolomide, and his clinical and MRI findings suggest the stabilization of his disease.

CONCLUSION

Neurological patients may benefit from liquid biopsy diagnostic work-up as it can reveal therapeutically targetable mutations.

Imaging characterization of an adult H3 K27M-altered diffuse midline glioma of the medulla oblongata with a confounding steroid response

We report an uncommon, infratentorial localization of adult H3 K27M-altered diffuse midline glioma arising in a particularly rare site (medulla oblongata). In addition to this unusual presentation, the lesion exhibited a substantial contrast enhancement and size decrease after dexamethasone, generating diagnostic dilemmas. Histology, molecular details, advanced Magnetic Resonance imaging features and differential diagnoses are here described and discussed, as well as common misconceptions about steroid-sensitive mass lesions, and practical difficulties for clinicians involved in the process of making diagnosis.

Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study

Background

Tumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.

Objectives

This study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.

Materials and Methods

Seventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.

Results

A highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.

Conclusion

Preliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.

Multiple hypointense veins on susceptibility weighted imaging as a promising biomarker of impaired cerebral hemodynamics in chronic steno-occlusive disease: a multiparametric MRI study

PURPOSE

Patients with steno-occlusive arterial disease may develop cerebral hypoperfusion with possible neurologic sequelae. The aim of the study is to verify the possible role of SWI, as a marker of cerebral hypoperfusion, in the identification of patient subgroups with significant chronic occlusions/stenoses at risk of critical cerebral hypoperfusion.

METHODS

We retrospectively identified 37 asymptomatic patients with chronic intra-extracranial occlusion/stenosis of the anterior circulation from a prospective brain MRI register between 2016 and 2020. All patients underwent 3 Tesla MRI. The imaging protocol included the following: SWI, 3D-FLAIR, DWI sequences, and 3D-TOF MRA. SWI findings were graded for the presence of asymmetric intracranial cortical veins (grades 1 to 4). The presence of collateralization was assessed with concomitant multiphase-CTA. FLAIR was evaluated for the presence of distal hyperintense vessels (DHVs), a described marker of flow impairment, and possible collateralization. Cerebral blood flow and arterial transit artifacts (ATAs) were evaluated at pCASL in 29 patients.

RESULTS

SWI showed multiple hypointense vessels (MHVs) in 22/37 patients in the cerebral hemisphere ipsilateral to vessel occlusion/stenosis. SWI-MHV grade 1 was found in 15 patients (40.5%), grade 2 in 18 patients (48.7%), and grade 3 in 3 patients (8.1%); in one patient, SWI was graded as 4 (2.7%). A significant relationship was found among MHV, DHV, collaterals, ATAs, and hypoperfused areas on pCASL and with patients' previous neurological symptoms.

CONCLUSION

SWI-MVH correlates with chronic cerebral flow impairment and is related to hypoperfusion and collateralization. It may help identify a subgroup of patients benefitting from revascularization.

Vascular Lesions and Brain Atrophy in Alzheimer's, Vascular and Mixed Dementia: An Optimized 3T MRI Protocol Reveals Distinctive Radiological Profiles

BACKGROUND

Vascular lesions may be a common finding also in Alzheimer's dementia, but their role on cognitive status is uncertain.

OBJECTIVE

The study aims to investigate their distribution in patients with Alzheimer's, vascular or mixed dementia and detect any distinctive neuroradiological profiles.

METHODS

Seventy-six subjects received a diagnosis of Alzheimer's (AD=32), vascular (VD=26) and mixed (MD=18) dementia. Three independent raters assessed the brain images acquired with an optimized 3T MRI protocol (including (3D FLAIR, T1, SWI, and 2D coronal T2 sequences) using semiquantitative scales for vascular lesions (periventricular lesions (PVL), deep white matter lesions (DWML), deep grey matter lesions (DGML), enlarged perivascular spaces (PVS), and microbleeds (MB)) and brain atrophy (medial temporal atrophy (MTA), posterior atrophy (PA), global cortical atrophy- frontal (GCA-F) and Evans' index).

RESULTS

Raters reached a good-to-excellent agreement for all scales (ICC ranging from 0.78-0.96). A greater number of PVL (p<0.001), DWML (p<0.001), DGML (p=0.010), and PVS (p=0.001) was observed in VD compared to AD, while MD showed a significant greater number of PVL (p=0.001), DWML (p=0.002), DGML (p=0.018), and deep and juxtacortical MB (p=0.006 and p<0.001, respectively). Comparing VD and MD, VD showed a higher number of PVS in basal ganglia and centrum semiovale (p=0.040), while MD showed more deep and juxtacortical MB (p=0.042 and p=0.022, respectively). No significant difference was observed in scores of cortical atrophy scales and Evans' index among the three groups.

CONCLUSION

The proposed MRI protocol represents a useful advancement in the diagnostic assessment of patients with cognitive impairment by more accurately detecting vascular lesions, mainly microbleeds, without a significant increase in time and resource expenditure. Our findings confirm that white and grey matter lesions predominate in vascular and mixed dementia, whereas deep and juxtacortical microbleeds predominate in mixed dementia, suggesting that cerebral amyloid angiopathy could be the main underlying pathology.

Neuroimaging in patients with COVID-19: a neuroradiology expert group consensus

Neurological and neuroradiological manifestations in patients with COVID-19 have been extensively reported. Available imaging data are, however, very heterogeneous. Hence, there is a growing need to standardise clinical indications for neuroimaging, MRI acquisition protocols, and necessity of follow-up examinations. A NeuroCovid working group with experts in the field of neuroimaging in COVID-19 has been constituted under the aegis of the Subspecialty Committee on Diagnostic Neuroradiology of the European Society of Neuroradiology (ESNR). The initial objectives of this NeuroCovid working group are to address the standardisation of the imaging in patients with neurological manifestations of COVID-19 and to give advice based on expert opinion with the aim of improving the quality of patient care and ensure high quality of any future clinical studies. KEY POINTS: • In patients with COVID-19 and neurological manifestations, neuroimaging should be performed in order to detect underlying causal pathology. • The basic MRI recommended protocol includes T2-weighted, FLAIR (preferably 3D), and diffusion-weighted images, as well as haemorrhage-sensitive sequence (preferably SWI), and at least for the initial investigation pre and post-contrast T1 weighted-images. • 3D FLAIR should be acquired after gadolinium administration in order to optimise the detection of leptomeningeal contrast enhancement.

A narrative review of consolidation strategies for young and fit patients with newly-diagnosed primary central nervous system lymphoma

INTRODUCTION

The modern treatment of patients with primary central nervous system lymphoma (PCNSL) consists of two phases: induction, currently represented by a high-dose-methotrexate-based polychemotherapy, and consolidation. The optimal consolidation therapy has not been defined yet, but several strategies, such as whole-brain radiotherapy (WBRT), high-dose chemotherapy supported by autologous stem cell transplantation (HDC/ASCT) or non-myeloablative chemotherapy, have been addressed in important randomized trials.

AREAS COVERED

This review provides an overview of the current role of consolidation strategies in young and fit patients with newly-diagnosed PCNSL. Publications in English language, peer-reviewed, from high-quality international journals, edited from 2003 to 2021 were identified on PubMed.

EXPERT OPINION

Consolidation treatment significantly improved outcomes of PCNSL. Radiotherapy had represented for years the only choice in the consolidation therapy, but large randomized trials have demonstrated that HDC/ASCT is equally effective and associated with lower neurotoxicity risk in patients younger than 65-70 years. Encouraging results have been obtained using reduced-dose WBRT, while a recent randomized trial failed to demonstrate that consolidation with non-myeloablative chemotherapy is more effective than HDC/ASCT in PCNSL patients. A personalized consolidation treatment, driven also by a response prediction model based on radiological and molecular details, may improve the management of PCNSL patients.

P14.55 Quantitative muscle mass biomarkers are independent prognosis factors in primary central nervous system lymphoma: the role of L3-Skeletal Muscle Index and temporal muscle thickness

BACKGROUND

Appropriate patient stratification is of paramount importance in patients with primary central nervous system lymphomas (PCNSL) in order to improve therapeutic choices and to reduce treatment-related neurotoxicity. Age and performance status, two widely used prognostic indicators, may not be the most appropriate parameters for an optimal patient stratification, as age seldom reveals the true biological frailty of a patient and performance status scores are subject to inter-rater variability. Quantitative muscle biomarkers such as the skeletal-muscle-index at the third lumbar vertebra (L3-SMI) and temporal muscle thickness (TMT) are associated with worse prognosis in several oncological diseases. We aim to evaluate the role of these biomarkers in predicting survival in patients with PCNSL undergoing high-dose methotrexate-based chemotherapy.

MATERIAL AND METHODS

L3-SMI and TMT were calculated on abdominal CT and brain high-resolution 3D-T1-weighted-MR images, respectively, using predefined validated methods. Standardized sex-specific cut-offs were used to divide patients in different risk categories. Kaplan-Meier plots were calculated, and survival analysis was performed using log-rank tests, univariate, and multivariable Cox-regression models, calculating hazard ratios (HR) and 95% confidence intervals (CI), also adjusting for potential confounders (age, sex, and performance status).

RESULTS

Forty-three patients were included in this study. Median follow-up was 23 months (interquartile range 12–40); at median follow-up, rates of progression-free and overall survival for the cohort were 46% and 57%, respectively. Thirteen (30%) and 11 (26%) patients showed L3-SMI or TMT values below the predefined cut-offs. Subgroup analyses showed a significant association between quantitative muscle mass biomarkers and progression-free and overall survival. One-year progression free and overall survival rates were 8% and 21% for the 13 patients with L3-SMI below the standard cut-off value, respectively, compared to 66% and 68% for the 30 patients with L3-SMI above the cut-off values. Likewise, one-year progression free and overall survival rates were 10% and 15% for the 11 patients with low TMT, respectively, compared to 61% and 70% for the 32 patients with high TMT. In Cox-regression multivariable analysis patients with low L3-SMI or TMT showed significantly worse progression-free (HR 4.40, 95%CI 1.66–11.61, p = 0.003; HR 4.40, 95%CI 1.68–11.49, p=0.003, respectively) and overall survival (HR 3.16, 95%CI 1.09–9.11, p = 0.034; HR 4.93, 95%CI 1.78–13.65, p=0.002, respectively) compared to patients with high L3-SMI or TMT.

CONCLUSION

Quantitative muscle mass evaluation assessed by both L3-SMI and TMT is a promising tool to identify PCNSL patients at high risk of negative outcome. Confirmatory studies on larger independent series are warranted.

Quantitative muscle mass biomarkers are independent prognosis factors in primary central nervous system lymphoma: The role of L3-skeletal muscle index and temporal muscle thickness

OBJECTIVE

To investigate the role of quantitative muscle biomarkers assessed with skeletal muscle index at the third lumbar vertebra (L3-SMI) and temporal muscle thickness (TMT) in predicting progression-free and overall survival in patients with primary central nervous system lymphoma (PCNSL) undergoing first-line high-dose methotrexate-based chemotherapy.

METHODS

L3-SMI and TMT were calculated on abdominal CT and brain high-resolution 3D-T1-weighted MR images, respectively, using predefined validated methods. Standardized sex-specific cut-off values were used to divide patients in different risk categories. Kaplan-Meier plots were calculated, and survival analysis was performed using log-rank tests, univariate, and multivariable Cox-regression models, calculating hazard ratios (HR) and 95% confidence intervals (CI), also adjusting for potential confounders (age, sex, and performance status).

RESULTS

Forty-three patients were included in this study. Median follow-up was 23 months (interquartile range 12-40); at median follow-up, rates of progression-free and overall survival for the cohort were 46% and 57%, respectively. Thirteen (30%) and 11 (26%) patients showed L3-SMI or TMT values below the predefined cut-offs. In Cox-regression multivariable analysis patients with low L3-SMI or TMT showed significantly worse progression-free (HR 4.40, 95% CI 1.66-11.61, p = 0.003; HR 4.40, 95% CI 1.68-11.49, p = 0.003, respectively) and overall survival (HR 3.16, 95% CI 1.09-9.11, p = 0.034; HR 4.93, 95% CI 1.78-13.65, p = 0.002, respectively) compared to patients with high L3-SMI or TMT.

CONCLUSIONS

Quantitative muscle mass evaluation assessed by both L3-SMI and TMT is a promising tool to identify PCNSL patients at high risk of negative outcome. Confirmatory studies on larger independent series are warranted.

Consensus recommendations for MRI and PET imaging of primary central nervous system lymphoma: guideline statement from the International Primary CNS Lymphoma Collaborative Group (IPCG)

Advanced molecular and pathophysiologic characterization of primary central nervous system lymphoma (PCNSL) has revealed insights into promising targeted therapeutic approaches. Medical imaging plays a fundamental role in PCNSL diagnosis, staging, and response assessment. Institutional imaging variation and inconsistent clinical trial reporting diminishes the reliability and reproducibility of clinical response assessment. In this context, we aimed to: (1) critically review the use of advanced positron emission tomography (PET) and magnetic resonance imaging (MRI) in the setting of PCNSL; (2) provide results from an international survey of clinical sites describing the current practices for routine and advanced imaging, and (3) provide biologically based recommendations from the International PCNSL Collaborative Group (IPCG) on adaptation of standardized imaging practices. The IPCG provides PET and MRI consensus recommendations built upon previous recommendations for standardized brain tumor imaging protocols (BTIP) in primary and metastatic disease. A biologically integrated approach is provided to addresses the unique challenges associated with the imaging assessment of PCNSL. Detailed imaging parameters facilitate the adoption of these recommendations by researchers and clinicians. To enhance clinical feasibility, we have developed both “ideal” and “minimum standard” protocols at 3T and 1.5T MR systems that will facilitate widespread adoption.

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics

OBJECTIVES

The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and compare model performance with that of 2 expert neuroradiologists.

MATERIALS AND METHODS

A total of 268 T2-weighted and T1-weighted brain magnetic resonance imagin scans were retrospectively collected from patients with migraine (n = 56), multiple sclerosis (n = 70), neuromyelitis optica spectrum disorders (n = 91), and central nervous system vasculitis (n = 51). The neural network architecture, trained on 178 scans, was based on a cascade of 4 three-dimensional convolutional layers, followed by a fully dense layer after feature extraction. The ability of the final algorithm to correctly classify the diseases in an independent test set of 90 scans was compared with that of the neuroradiologists.

RESULTS

The interrater agreement was 84.9% (Cohen κ = 0.78, P < 0.001). In the test set, deep learning and expert raters reached the highest diagnostic accuracy in multiple sclerosis (98.8% vs 72.8%, P < 0.001, for rater 1; and 81.8%, P < 0.001, for rater 2) and the lowest in neuromyelitis optica spectrum disorders (88.6% vs 4.4%, P < 0.001, for both raters), whereas they achieved intermediate values for migraine (92.2% vs 53%, P = 0.03, for rater 1; and 64.8%, P = 0.01, for rater 2) and vasculitis (92.1% vs 54.6%, P = 0.3, for rater 1; and 45.5%, P = 0.2, for rater 2). The overall performance of the automated method exceeded that of expert raters, with the worst misdiagnosis when discriminating between neuromyelitis optica spectrum disorders and vasculitis or migraine.

CONCLUSIONS

A neural network performed better than expert raters in terms of accuracy in classifying white matter disorders from magnetic resonance imaging and may help in their diagnostic work-up.

The role of CE-MRA of the supraortic vessels in the detection of associated intracranial pathology

BACKGROUND

Contrast-enhanced magnetic resonance angiography (CE-MRA) has become a very popular imaging technique in the evaluation of the extracranial vessels pathology, while it is not commonly used to rule out intracranial vascular pathology. On the contrary, 3D time of flight MRA (TOF-MRA) has a solid role in the study of intracranial arterial vessels disease.

MATERIALS AND METHODS

One hundred and eight patients were consecutively included in the study. All patients were submitted to a 3 Tesla 3D CE-MRA imaging to rule out extracranial vessels pathology. A comparison was made with a 3D-TOF sequence acquired at the same time in the assessment of intracranial vessels diseases such as steno-occlusion, dissection, and aneurysms.

RESULTS

With regard to steno-occlusive disease, Spearman's rank correlation coefficient was of 0.56 for stenosis detection and of 0.57 for occlusive disease detection. The two techniques shared similar results in the evaluation of anterior circulation, while 3D-TOF found higher grades of stenosis for posterior circulation. With regard to dissection, Spearman's rank correlation coefficient was of 0.7. 3D-TOF depicted more intramural hematoma (Spearman's rank = 0.46), while CE-MRA showed more pseudo-aneurysms (Spearman's rank = 0.56). Both the technique equally evaluated the presence of intracranial aneurysms (Spearman's rank = 1).

CONCLUSION

CE-MRA can be considered a reliable tool to rule out intracranial pathology associated to supraortic steno-occlusive disease, also allowing time reduction. In the suspicion of dissection a T1-weighted sequence has to be added to detect the presence of a subacute vessel wall hematoma.

MYD88 L265P mutation and interleukin-10 detection in cerebrospinal fluid are highly specific discriminating markers in patients with primary central nervous system lymphoma: results from a prospective study

Reliable biomarkers are needed to avoid diagnostic delay and its devastating effects in patients with primary central nervous system (CNS) lymphoma (PCNSL). We analysed the discriminating sensitivity and specificity of myeloid differentiation primary response (88) (MYD88) L265P mutation (mut-MYD88) and interleukin-10 (IL-10) in cerebrospinal fluid (CSF) of both patients with newly diagnosed (n = 36) and relapsed (n = 27) PCNSL and 162 controls (118 CNS disorders and 44 extra-CNS lymphomas). The concordance of MYD88 mutational status between tumour tissue and CSF sample and the source of ILs in PCNSL tissues were also investigated. Mut-MYD88 was assessed by TaqMan-based polymerase chain reaction. IL-6 and IL-10 messenger RNA (mRNA) was assessed on PCNSL biopsies using RNAscope technology. IL levels in CSF were assessed by enzyme-linked immunosorbent assay. Mut-MYD88 was detected in 15/17 (88%) PCNSL biopsies, with an 82% concordance in paired tissue-CSF samples. IL-10 mRNA was detected in lymphomatous B cells in most PCNSL; expression of IL-6 transcripts was negligible. In CSF samples, mut-MYD88 and high IL-10 levels were detected, respectively, in 72% and 88% of patients with newly diagnosed PCNSL and in 1% of controls; conversely, IL-6 showed a low discriminating sensitivity and specificity. Combined analysis of MYD88 and IL-10 exhibits a sensitivity and specificity to distinguish PCNSL of 94% and 98% respectively. Similar figures were recorded in patients with relapsed PCNSL. In conclusion, high detection rates of mut-MYD88 and IL-10 in CSF reflect, respectively, the MYD88 mutational status and synthesis of this IL in PCNSL tissue. These biomarkers exhibit a very high sensitivity and specificity in detecting PCNSL both at initial diagnosis and relapse. Implications of these findings in patients with lesions unsuitable for biopsy deserve to be investigated.

Frontal and Cerebellar Atrophy Supports FTSD-ALS Clinical Continuum

Background

Frontotemporal Spectrum Disorder (FTSD) and Amyotrophic Lateral Sclerosis (ALS) are neurodegenerative diseases often considered as a continuum from clinical, epidemiologic, and genetic perspectives. We used localized brain volume alterations to evaluate common and specific features of FTSD, FTSD-ALS, and ALS patients to further understand this clinical continuum.

Methods

We used voxel-based morphometry on structural magnetic resonance images to localize volume alterations in group comparisons: patients (20 FTSD, seven FTSD-ALS, and 18 ALS) versus healthy controls (39 CTR), and patient groups between themselves. We used mean whole-brain cortical thickness ( C T ¯ ) to assess whether its correlations with local brain volume could propose mechanistic explanations of the heterogeneous clinical presentations. We also assessed whether volume reduction can explain cognitive impairment, measured with frontal assessment battery, verbal fluency, and semantic fluency.

Results

Common (mainly frontal) and specific areas with reduced volume were detected between FTSD, FTSD-ALS, and ALS patients, confirming suggestions of a clinical continuum, while at the same time defining morphological specificities for each clinical group (e.g., a difference of cerebral and cerebellar involvement between FTSD and ALS). C T ¯ values suggested extensive network disruption in the pathological process, with indications of a correlation between cerebral and cerebellar volumes and C T ¯ in ALS. The analysis of the neuropsychological scores indeed pointed toward an important role for the cerebellum, along with fronto-temporal areas, in explaining impairment of executive, and linguistic functions.

Conclusion

We identified common elements that explain the FTSD-ALS clinical continuum, while also identifying specificities of each group, partially explained by different cerebral and cerebellar involvement.

Extent and characteristics of carotid plaques and brain parenchymal loss in asymptomatic patients with no indication for revascularization

BACKGROUND AND AIMS

Extent of subclinical atherosclerosis has been associated with brain parenchymal loss in community-dwelling aged subjects. Identification of patient-related and plaque-related markers could identify subjects at higher risk of brain atrophy, independent of cerebrovascular accidents. Aim of the study was to investigate the relation between extent and characteristics of carotid plaques and brain atrophy in asymptomatic patients with no indication for revascularization.

METHODS AND RESULTS

Sixty-four patients (aged 69 ± 8 years, 45% females) with carotid stenosis <70% based on Doppler flow velocity were enrolled in the study. Potential causes of cerebral damage other than atherosclerosis, including history of atrial fibrillation, heart failure, previous cardiac or neurosurgery and neurological disorders were excluded. All subjects underwent carotid computed tomography angiography, contrast enhanced ultrasound for assessment of plaque neovascularization and brain magnetic resonance imaging for measuring brain volumes. On multivariate regression analysis, age and fibrocalcific plaques were independently associated with lower total brain volumes (β = -3.13 and β = -30.7, both p < 0.05). Fibrocalcific plaques were also independently associated with lower gray matter (GM) volumes (β = -28.6, p = 0.003). On the other hand, age and extent of carotid atherosclerosis were independent predictors of lower white matter (WM) volumes.

CONCLUSIONS

WM and GM have different susceptibility to processes involved in parenchymal loss. Contrary to common belief, our results show that presence of fibrocalcific plaques is associated with brain atrophy.

Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status

Background

Combining MRI techniques with machine learning methodology is rapidly gaining attention as a promising method for staging of brain gliomas. This study assesses the diagnostic value of such a framework applied to dynamic susceptibility contrast (DSC)-MRI in classifying treatment-naïve gliomas from a multi-center patients into WHO grades II-IV and across their isocitrate dehydrogenase (IDH) mutation status.

Methods

Three hundred thirty-three patients from 6 tertiary centres, diagnosed histologically and molecularly with primary gliomas (IDH-mutant = 151 or IDH-wildtype = 182) were retrospectively identified. Raw DSC-MRI data was post-processed for normalised leakage-corrected relative cerebral blood volume (rCBV) maps. Shape, intensity distribution (histogram) and rotational invariant Haralick texture features over the tumour mask were extracted. Differences in extracted features across glioma grades and mutation status were tested using the Wilcoxon two-sample test. A random-forest algorithm was employed (2-fold cross-validation, 250 repeats) to predict grades or mutation status using the extracted features.

Results

Shape, distribution and texture features showed significant differences across mutation status. WHO grade II-III differentiation was mostly driven by shape features while texture and intensity feature were more relevant for the III-IV separation. Increased number of features became significant when differentiating grades further apart from one another. Gliomas were correctly stratified by mutation status in 71% and by grade in 53% of the cases (87% of the gliomas grades predicted with distance less than 1).

Conclusions

Despite large heterogeneity in the multi-center dataset, machine learning assisted DSC-MRI radiomics hold potential to address the inherent variability and presents a promising approach for non-invasive glioma molecular subtyping and grading.

Diagnostic efficacy and safety of gadoteridol compared to gadobutrol and gadoteric acid in a large sample of CNS MRI studies at 1.5T

PURPOSE

To evaluate safety and diagnostic accuracy of gadoteridol vs. other macrocyclic gadolinium-based contrast agents (GBCAs) in a large cohort of consecutive and non-selected patients referred for CE-MRI of the CNS.

MATERIAL AND METHODS

Between November 2017 and March 2018, we prospectively enrolled a consecutive cohort of patients referred for neuroradiological CE-MRI (1.5T MRI). Image quality and adverse events were assessed. Diagnostic performance was determined for a subgroup of patients with truth standard findings available. Comparison was made between patients receiving gadoteridol and patients receiving other macrocyclic GBCAs. Inter-reader agreement (kappa) between two expert neuroradiologists was calculated for the diagnosis of malignancy.

RESULTS

Overall, 460 patients (220M/240F; mean age 54±16 years) were enrolled of which 230 received gadoteridol (Group 1) and 230 either gadoteric acid or gadobutrol [n=83 (36.1%) and n=147 (63.9%), respectively; Group 2]. Image quality was rated as good or excellent in both groups. The sensitivity, specificity and diagnostic accuracy for determination of malignancy was 88.2%, 96.5% and 95.4%, respectively, for Group 1 and 93.7%, 97.4% and 96.9%, respectively, for Group 2, with no significant differences between groups (P>0.75) for any determination. Inter-reader agreement for the identification of malignancy was excellent [K=0.877 (95%CI: 0.758-0.995) and K=0.818 (95%CI: 0.663-0.972) for groups 1 and 2, respectively; P=0.0913]. Adverse events occurred in 5 of 460 (1.09%) patients overall, with no significant difference (P=0.972) between groups.

CONCLUSION

Gadoteridol was safe and guaranteed good image quality without significant differences when compared to gadobutrol and gadoteric acid in a wide range of CNS pathologies.

Substantia Nigra Volumetry with 3-T MRI in De Novo and Advanced Parkinson Disease

Background Magnetization transfer-prepared T1-weighted MRI can depict a hyperintense subregion of the substantia nigra involved in the degeneration process of Parkinson disease. Purpose To evaluate quantitative measurement of substantia nigra volume by using MRI to support clinical diagnosis and staging of Parkinson disease. Materials and Methods In this prospective study, a high-spatial-resolution magnetization transfer-prepared T1-weighted volumetric sequence was performed with a 3-T MRI machine between January 2014 and October 2015 for participants with de novo Parkinson disease, advanced Parkinson disease, and healthy control participants. A reproducible semiautomatic quantification analysis method that entailed mesencephalic intensity as an internal reference was used for hyperintense substantia nigra volumetry normalized to intracranial volume. A general linear model with age and sex as covariates was used to compare the three groups. Results Eighty participants were evaluated: 20 healthy control participants (mean age ± standard deviation, 56 years ± 11; 11 women), 29 participants with de novo Parkinson disease (64 years ± 10; 19 men), and 31 participants with advanced Parkinson disease (60 years ± 9; 16 women). Volumetric measurement of hyperintense substantia nigra from magnetization transfer-prepared T1-weighted MRI helped differentiate healthy control participants from participants with advanced Parkinson disease (mean difference for ipsilateral side, 64 mm³ ± 14, P < .001; mean difference for contralateral side, 109 mm³ ± 14, P < .001) and helped distinguish healthy control participants from participants with de novo Parkinson disease (mean difference for ipsilateral side, 45 mm³ ± 15, P < .01; mean difference for contralateral side, 66 mm³ ± 15, P < .001) and participants with de novo Parkinson disease from those with advanced Parkinson disease (mean difference for ipsilateral side, 20 mm³ ± 13, P = .40; mean difference for contralateral side, 43 mm³ ± 13, P = .004). Conclusion Magnetization transfer-prepared T1-weighted MRI volumetry of the substantia nigra helped differentiate the stages of Parkinson disease. © RSNA, 2020 Online supplemental material is available for this article.

A Machine Learning Approach for the Differential Diagnosis of Alzheimer and Vascular Dementia Fed by MRI Selected Features

Among dementia-like diseases, Alzheimer disease (AD) and vascular dementia (VD) are two of the most frequent. AD and VD may share multiple neurological symptoms that may lead to controversial diagnoses when using conventional clinical and MRI criteria. Therefore, other approaches are needed to overcome this issue. Machine learning (ML) combined with magnetic resonance imaging (MRI) has been shown to improve the diagnostic accuracy of several neurodegenerative diseases, including dementia. To this end, in this study, we investigated, first, whether different kinds of ML algorithms, combined with advanced MRI features, could be supportive in classifying VD from AD and, second, whether the developed approach might help in predicting the prevalent disease in subjects with an unclear profile of AD or VD. Three ML categories of algorithms were tested: artificial neural network (ANN), support vector machine (SVM), and adaptive neuro-fuzzy inference system (ANFIS). Multiple regional metrics from resting-state fMRI (rs-fMRI) and diffusion tensor imaging (DTI) of 60 subjects (33 AD, 27 VD) were used as input features to train the algorithms and find the best feature pattern to classify VD from AD. We then used the identified VD–AD discriminant feature pattern as input for the most performant ML algorithm to predict the disease prevalence in 15 dementia patients with a “mixed VD–AD dementia” (MXD) clinical profile using their baseline MRI data. ML predictions were compared with the diagnosis evidence from a 3-year clinical follow-up. ANFIS emerged as the most efficient algorithm in discriminating AD from VD, reaching a classification accuracy greater than 84% using a small feature pattern. Moreover, ANFIS showed improved classification accuracy when trained with a multimodal input feature data set (e.g., DTI + rs-fMRI metrics) rather than a unimodal feature data set. When applying the best discriminant pattern to the MXD group, ANFIS achieved a correct prediction rate of 77.33%. Overall, results showed that our approach has a high discriminant power to classify AD and VD profiles. Moreover, the same approach also showed potential in predicting earlier the prevalent underlying disease in dementia patients whose clinical profile is uncertain between AD and VD, therefore suggesting its usefulness in supporting physicians' diagnostic evaluations.

Unsuspected Involvement of Spinal Cord in Alzheimer Disease

Objective: Brain atrophy is an established biomarker for dementia, yet spinal cord involvement has not been investigated to date. As the spinal cord is relaying sensorimotor control signals from the cortex to the peripheral nervous system and vice-versa, it is indeed a very interesting question to assess whether it is affected by atrophy due to a disease that is known for its involvement of cognitive domains first and foremost, with motor symptoms being clinically assessed too. We, therefore, hypothesize that in Alzheimer's disease (AD), severe atrophy can affect the spinal cord too and that spinal cord atrophy is indeed an important in vivo imaging biomarker contributing to understanding neurodegeneration associated with dementia. Methods: 3DT1 images of 31 AD and 35 healthy control (HC) subjects were processed to calculate volume of brain structures and cross-sectional area (CSA) and volume (CSV) of the cervical cord [per vertebra as well as the C2-C3 pair (CSA23 and CSV23)]. Correlated features (ρ > 0.7) were removed, and the best subset identified for patients' classification with the Random Forest algorithm. General linear model regression was used to find significant differences between groups (p ≤ 0.05). Linear regression was implemented to assess the explained variance of the Mini-Mental State Examination (MMSE) score as a dependent variable with the best features as predictors. Results: Spinal cord features were significantly reduced in AD, independently of brain volumes. Patients classification reached 76% accuracy when including CSA23 together with volumes of hippocampi, left amygdala, white and gray matter, with 74% sensitivity and 78% specificity. CSA23 alone explained 13% of MMSE variance. Discussion: Our findings reveal that C2-C3 spinal cord atrophy contributes to discriminate AD from HC, together with more established features. The results show that CSA23, calculated from the same 3DT1 scan as all other brain volumes (including right and left hippocampi), has a considerable weight in classification tasks warranting further investigations. Together with recent studies revealing that AD atrophy is spread beyond the temporal lobes, our result adds the spinal cord to a number of unsuspected regions involved in the disease. Interestingly, spinal cord atrophy explains also cognitive scores, which could significantly impact how we model sensorimotor control in degenerative diseases with a primary cognitive domain involvement. Prospective studies should be purposely designed to understand the mechanisms of atrophy and the role of the spinal cord in AD.

Diagnosing autoimmune encephalitis in a real-world single-centre setting

BACKGROUND

Early recognition and treatment of autoimmune encephalitis (AE) are crucial for patients, but diagnosis is often difficult and time-consuming. For this purpose, a syndrome-based diagnostic approach was published by Graus et al. (Lancet Neurol 15:391-404, 2016), but very little is known in the literature about its application in clinical practice.

AIM

Our aims are to test the feasibility of such approach in a real-world single-centre setting and to analyse the most relevant factors in criteria fulfilment.

METHODS

We retrospectively applied these criteria to our cohort of patients discharged from our hospital with diagnosis of autoimmune encephalitis (n = 33, 58% antibody-positive).

RESULTS

All the subjects fulfilled criteria for possible AE (pAE), with EEG and MRI playing a central role in diagnosis, while CSF was useful mainly to rule out other conditions. Three patients respected criteria for probable anti-NMDA-R encephalitis (pNMDA). Definite anti-NMDAR encephalitis was diagnosed in 4 patients with detection of the autoantibody but, surprisingly, none of these subjects had fulfilled criteria for pNMDA. 18 patients were diagnosed with definite limbic AE (15 patients were antibody-positive, three antibody-negative). Need for MRI bilateral involvement in antibody-negative limbic AE limited diagnosis. One patient fulfilled criteria for probable antibody-negative AE, while ten patients remained classified as pAE.

CONCLUSION

From our retrospective analysis, some suggestions for a better definition of the criteria may emerge. Larger studies on prospective cohorts may be more helpful to explore possible important issues.

Comparison of T1 mapping and fixed T1 method for dynamic contrast-enhanced MRI perfusion in brain gliomas

OBJECTIVES

To compare dynamic contrast-enhanced MRI (DCE-MRI) data obtained using different prebolus T1 values in glioma grading and molecular profiling.

METHODS

We retrospectively reviewed 83 cases of gliomas: 46 lower-grade gliomas (LGG; grades II and III) and 37 high-grade gliomas (HGG; grade IV). DCE-MRI maps of plasma volume fraction (Vp), extravascular-extracellular volume fraction (Ve), and tracer transfer constant from plasma to tissue (K^trans) were obtained using a fixed T1 value of 1400 ms and a measured T1 obtained with variable flip angle (VFA). Tumour segmentations were performed and first-order histogram parameters were extracted from volumes of interest (VOIs) after co-registration with the perfusion maps. The two methods were compared using Wilcoxon matched-pairs signed-rank test and Bland-Altman analysis. Diagnostic accuracy was obtained and compared using ROC curve analysis and DeLong's test.

RESULTS

Perfusion parameters obtained with the fixed T1 value were significantly higher than those obtained with the VFA. As regards diagnostic accuracy, there were no significant differences between the two methods both for glioma grading and molecular classification, except for few parameters of both methods.

CONCLUSIONS

DCE-MRI data obtained with different prebolus T1 are not comparable and the definition of a prebolus T1 by T1 mapping is not mandatory since it does not improve the diagnostic accuracy of DCE-MRI.

KEY POINTS

• DCE-MRI data obtained with different prebolus T1 are significantly different, thus not comparable. • The definition of a prebolus T1 by T1 mapping is not mandatory since it does not improve the diagnostic accuracy of DCE-MRI for glioma grading. • The use of a fixed T1 value represents a valid alternative to T1 mapping for DCE-MRI analysis.

Carotid artery imaging: The study of intra-plaque vascularization and hemorrhage in the era of the "vulnerable" plaque

Intraplaque hemorrhage (IPH) is one of the main factors involved in atherosclerotic plaque (AP) instability. Its recognition is crucial for the correct staging and management of patients with carotid artery plaques to limit ischemic stroke. Imaging plays a crucial role in identifying IPH, even if the great variability of intraplaque vascularization and the limitations of our current imaging technologies make it difficult. The intent of this review is to give a general overview of the main features of intraplaque vascularization and IPH on Ultrasound (US), Computed Tomography (CT), Magnetic Resonance (MR) and Nuclear Medicine, and a brief description on the future prospectives.

Specific Patterns of White Matter Alterations Help Distinguishing Alzheimer's and Vascular Dementia

Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls—HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.

Gadobutrol in India-A Comprehensive Review of Safety and Efficacy

Gadobutrol is a gadolinium (Gd)-based contrast agent for magnetic resonance imaging (MRI). In India, gadobutrol is approved for MRI of the central nervous system (CNS), liver, kidneys, breast and for MR angiography for patients 2 years and older. The standard dose for all age groups is 0.1 mmol/kg body weight. The safety profile has been demonstrated in 42 clinical phase 2 to 4 studies (>6800 patients), 7 observational studies, and by assessing pharmacovigilance data of 29 million applications. Furthermore, studies in children, adults, and elderly and in patients with impaired liver or kidney function did not show any increased adverse event rate. Diagnostic efficacy was demonstrated in numerous studies and various indications, such as diseases of the CNS, peripheral and supra-aortic vessels, kidneys, liver, and breast.

Relation between characteristics of carotid atherosclerotic plaques and brain white matter hyperintensities in asymptomatic patients

White matter hyperintensities (WMH) can be incidentally found in patients with carotid atherosclerosis on brain magnetic resonance imaging (MRI). We investigated the relationship between WMH and characteristics of carotid plaques in asymptomatic patients without indication for carotid revascularization. We prospectively screened 235 consecutive patients with carotid stenosis <70%. After excluding patients with confounding causes of cerebral damage, 67 asymptomatic patients underwent carotid computed tomography angiography (CTA), contrast-enhanced ultrasound and brain MRI. Number and quantitative measurement of volume of WMH were associated with history of resistant hypertension, degree of stenosis (Doppler) and presence of an ulcerated plaque at CTA (p < 0.05). At multivariate regression analysis, resistant hypertension was independently associated with both number and volume of WMH, presence of an ulcer with number of WMH and degree of stenosis with WMH volume (p < 0.05), although WMH were equally distributed in both hemispheres irrespectively of plaque side. In conclusion, in asymptomatic patients with carotid plaques <70%, a higher burden of WMHs is associated with history of resistant hypertension that could be the expression of microvascular damage. Stenosis severity and presence of plaque ulceration are also associated with WMH burden although their causative relation is not supported by the bilateral distribution of WMH.

Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software

PURPOSE

Dynamic susceptibility contrast MRI (DSC) and dynamic contrast-enhanced MRI (DCE) are useful tools in the diagnosis and follow-up of brain gliomas; nevertheless, both techniques leave the open issue of data reproducibility. We evaluated the reproducibility of data obtained using two different commercial software for perfusion maps calculation and analysis, as one of the potential sources of variability can be the software itself.

METHODS

DSC and DCE analyses from 20 patients with gliomas were tested for both the intrasoftware (as intraobserver and interobserver reproducibility) and the intersoftware reproducibility, as well as the impact of different postprocessing choices [vascular input function (VIF) selection and deconvolution algorithms] on the quantification of perfusion biomarkers plasma volume (Vp), volume transfer constant (K ^trans) and rCBV. Data reproducibility was evaluated with the intraclass correlation coefficient (ICC) and Bland-Altman analysis.

RESULTS

For all the biomarkers, the intra- and interobserver reproducibility resulted in almost perfect agreement in each software, whereas for the intersoftware reproducibility the value ranged from 0.311 to 0.577, suggesting fair to moderate agreement; Bland-Altman analysis showed high dispersion of data, thus confirming these findings. Comparisons of different VIF estimation methods for DCE biomarkers resulted in ICC of 0.636 for K ^trans and 0.662 for Vp; comparison of two deconvolution algorithms in DSC resulted in an ICC of 0.999.

CONCLUSIONS

The use of single software ensures very good intraobserver and interobservers reproducibility. Caution should be taken when comparing data obtained using different software or different postprocessing within the same software, as reproducibility is not guaranteed anymore.

Carotid atherosclerosis, silent ischemic brain damage and brain atrophy: A systematic review and meta-analysis

BACKGROUND

The widespread use of brain imaging has led to increased recognition of subclinical brain abnormalities, including white matter hyperintensities (WMH) and silent brain infarctions (SBI), which have a vascular origin, and have been associated to a high risk of stroke, disability and dementia. Carotid atherosclerosis (CA) may be causative in the development of WMH, SBI and eventually brain atrophy. Aim of the present systematic review and meta-analysis was to assess the existing evidence linking CA to WMH, SBI and brain atrophy.

METHODS

The relation between CA and WMH, SBI and brain atrophy was investigated through the systematic search of online databases up to September 2015 and manual searching of references and related citations. Pooled estimates were calculated by random-effects model, using restricted maximum likelihood method with inverse variance weighting method.

RESULTS

Of the 3536 records identified, fifteen were included in the systematic review and 9 were found to be eligible for the meta-analysis. CA was significantly associated with the presence of WMH (Odds Ratio, OR 1.42, confidence interval, CI 1.22-1.66, p<0.0001) and of SBI (OR 1.89, CI 1.46-2.45, p<0.0001). No meta-analysis could be performed for the relation between CA and brain atrophy due to the lack of suitable studies.

CONCLUSIONS

CA was found to be associated to WMH and SBI. While no causative association can be inferred from the available data, the presence of carotid plaque may be considered a significant risk factor for subclinical cerebral damage.

Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis

INTRODUCTION

Dynamic susceptibility contrast (DSC)-MRI is a perfusion technique with high diagnostic accuracy for glioma grading, despite limitations due to inherent susceptibility effects. Dynamic contrast-enhanced (DCE)-MRI has been proposed as an alternative technique able to overcome the DSC-MRI shortcomings. This pilot study aimed at comparing the diagnostic accuracy of DSC and DCE-MRI for glioma grading by evaluating two estimates of blood volume, the DCE-derived plasma volume (Vp) and the DSC-derived relative cerebral blood volume (rCBV), and a measure of vessel permeability, the DCE-derived volume transfer constant K(trans).

METHODS

Twenty-six newly diagnosed glioma patients underwent 3T-MR DCE and DSC imaging. Parametric maps of CBV, Vp and K(trans) were calculated and the region of highest value (hotspot) was measured on each map. Histograms of rCBV, Vp and K(trans) values were calculated for the tumor volume. Statistical differences according to WHO grade were assessed. The diagnostic accuracy for tumor grading of the two techniques was determined by ROC analysis.

RESULTS

rCBV, Vp and K(trans) measures differed significantly between high and low-grade gliomas. Hotspot analysis showed the highest correlation with grading. K(trans) hotspots co-localized with Vp hotspots only in 56% of enhancing gliomas. For differentiating high from low-grade gliomas the AUC was 0.987 for rCBVmax, and 1.000 for Vpmax and K(trans)max. Combination of DCE-derived Vp and K(trans) parameters improved the diagnostic performance of the histogram method.

CONCLUSION

This initial experience of DCE-derived Vp evaluation shows that this parameter is as accurate as the well-established DSC-derived rCBV for glioma grading. DCE-derived K(trans) is equally useful for grading, providing different informations with respect to Vp.