Dataset Information

The role of susceptibility-weighted imaging & contrast-enhanced MRI in the diagnosis of primary CNS vasculitis: a large case series.

ABSTRACT: Primary CNS Vasculitis (PCNSV) is a rare, diverse, and polymorphic CNS blood vessel inflammatory condition. Due to its rarity, clinical variability, heterogeneous imaging results, and lack of definitive laboratory markers, PCNSV diagnosis is challenging. This retrospective cohort analysis identified patients with histological diagnosis of PCNSV. Demographic data, clinical presentation, neuroimaging studies, and histopathologic findings were recorded. We enrolled 56 patients with a positive biopsy of CNS vasculitis. Most patients had cerebral hemisphere or brainstem symptoms. Most brain MRI lesions were bilateral, diffuse discrete to confluent white matter lesions. Frontal lobe lesions predominated, followed by inferior cerebellar lesions. Susceptibility-weighted imaging (SWI) hemorrhages in 96.4% (54/56) of patients, either solitary microhemorrhages or a combination of micro and macrohemorrhages. Contrast-enhanced T1-WIs revealed parenchymal enhancement in 96.3% (52/54 patients). The most prevalent pattern of enhancement observed was dot-linear (87%), followed by nodular (61.1%), perivascular (25.9%), and patchy (16.7%). Venulitis was found in 19 of 20 individuals in cerebral DSA. Hemorrhages in SWI and dot-linear enhancement pattern should be incorporated as MINOR diagnostic criteria to diagnose PCNSV accurately within an appropriate clinical context. Microhemorrhages in SWI and venulitis in DSA, should be regarded as a potential marker for PCNSV.

SUBMITTER: Agarwal S

PROVIDER: S-EPMC10899183 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The role of susceptibility-weighted imaging & contrast-enhanced MRI in the diagnosis of primary CNS vasculitis: a large case series.

Agarwal Sushant S Sebastian Leve Joseph Devarajan LJD Gaikwad Shailesh S Srivastava M V Padma MVP Sharma M C MC Singh Manmohan M Bhatia Rohit R Agarwal Ayush A Sharma Jyoti J Dash Deepa D Goyal Vinay V Srivastava Achal K AK Tripathi Manjari M Suri Vaishali V Singh Mamta B MB Sarkar Chitra C Suri Ashish A Singh Rajesh K RK Vibha Deepti D Pandit Awadh K AK Rajan Roopa R Gupta Anu A Elavarasi A A Radhakrishnan Divya M DM Das Animesh A Tandon Vivek V Doddamani Ramesh R Upadhyay Ashish A Vishnu Venugopalan Y VY Garg Ajay A

Scientific reports 20240227 1

Primary CNS Vasculitis (PCNSV) is a rare, diverse, and polymorphic CNS blood vessel inflammatory condition. Due to its rarity, clinical variability, heterogeneous imaging results, and lack of definitive laboratory markers, PCNSV diagnosis is challenging. This retrospective cohort analysis identified patients with histological diagnosis of PCNSV. Demographic data, clinical presentation, neuroimaging studies, and histopathologic findings were recorded. We enrolled 56 patients with a positive biops ...[more]

PMID: 38413676

Similar Datasets

Project description:Background and purposeGlioblastoma and primary CNS lymphoma dictate different neurosurgical strategies; it is critical to distinguish them preoperatively. However, current imaging modalities do not effectively differentiate them. We aimed to examine the use of DWI and T1-weighted dynamic contrast-enhanced-MR imaging as potential discriminative tools.Materials and methodsWe retrospectively reviewed 18 patients with primary CNS lymphoma and 36 matched patients with glioblastoma with pretreatment DWI and dynamic contrast-enhanced-MR imaging. VOIs were drawn around the tumor on contrast-enhanced T1WI and FLAIR images; these images were transferred onto coregistered ADC maps to obtain the ADC and onto dynamic contrast-enhanced perfusion maps to obtain the plasma volume and permeability transfer constant. Histogram analysis was performed to determine the mean and relative ADCmean and relative 90th percentile values for plasma volume and the permeability transfer constant. Nonparametric tests were used to assess differences, and receiver operating characteristic analysis was performed for optimal threshold calculations.ResultsThe enhancing component of primary CNS lymphoma was found to have significantly lower ADCmean (1.1 × 10-3 versus 1.4 × 10-3; P < .001) and relative ADCmean (1.5 versus 1.9; P < .001) and relative 90th percentile values for plasma volume (3.7 versus 5.0; P < .05) than the enhancing component of glioblastoma, but not significantly different relative 90th percentile values for the permeability transfer constant (5.4 versus 4.4; P = .83). The nonenhancing portions of glioblastoma and primary CNS lymphoma did not differ in these parameters. On the basis of receiver operating characteristic analysis, mean ADC provided the best threshold (area under the curve = 0.83) to distinguish primary CNS lymphoma from glioblastoma, which was not improved with normalized ADC or the addition of perfusion parameters.ConclusionsADC was superior to dynamic contrast-enhanced-MR imaging perfusion, alone or in combination, in differentiating primary CNS lymphoma from glioblastoma.

Project description:BackgroundThe MRI Breast Imaging-Reporting and Data System (BI-RADS) lexicon recommends that a breast MRI protocol contain T2 -weighted and dynamic contrast-enhanced (DCE) MRI sequences. The addition of diffusion-weighted imaging (DWI) significantly improves diagnostic accuracy. This study aims to clarify which descriptors from DCE-MRI, DWI, and T2 -weighted imaging are most strongly associated with a breast cancer diagnosis.Purpose/hypothesisTo develop a multiparametric MRI (mpMRI) model for breast cancer diagnosis incorporating American College of Radiology (ACR) BI-RADS recommended descriptors for breast MRI with DCE, T2 -weighted imaging, and DWI with apparent diffusion coefficient (ADC) mapping.Study typeRetrospective.SubjectsIn all, 188 patients (mean 51.6 years) with 210 breast tumors (136 malignant and 74 benign) who underwent mpMRI from December 2010 to September 2014.Field strength/sequenceIR inversion recovert DCE-MRI dynamic contrast-enhanced magnetic resonance imaging VIBE Volume-Interpolated-Breathhold-Examination FLASH turbo fast-low-angle-shot TWIST Time-resolved angiography with stochastic Trajectories.AssessmentTwo radiologists in consensus and another radiologist independently evaluated the mpMRI data. Characteristics for mass (n = 182) and nonmass (n = 28) lesions were recorded on DCE and T2 -weighted imaging according to BI-RADS, as well as DWI descriptors. Two separate models were analyzed, using DCE-MRI BI-RADS descriptors, T2 -weighted imagines, and ADCmean as either a continuous or binary form using a previously published ADC cutoff value of ≤1.25 × 10-3 mm2 /sec for differentiation between benign and malignant lesions. Histopathology was the standard of reference.Statistical testsχ2 test, Fisher's exact test, Kruskal-Wallis test, Pearson correlation coefficient, multivariate logistic regression analysis, Hosmer-Lemeshow test of goodness-of-fit, receiver operating characteristics analysis.ResultsIn Model 1, ADCmean (P = 0.0031), mass margins with DCE (P = 0.0016), and delayed enhancement with DCE (P = 0.0016) were significantly and independently associated with breast cancer diagnosis; Model 2 identified ADCmean (P = 0.0031), mass margins with DCE (P = 0.0012), initial enhancement (P = 0.0422), and delayed enhancement with DCE (P = 0.0065) to be significantly independently associated with breast cancer diagnosis. T2 -weighted imaging variables were not included in the final models. DATA CONCLUSION: mpMRI with DCE-MRI and DWI with ADC mapping enables accurate breast cancer diagnosis. A model using quantitative and qualitative descriptors from DCE-MRI and DWI identifies breast cancer with a high diagnostic accuracy. T2 -weighted imaging does not significantly contribute to breast cancer diagnosis.Level of evidence3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:864-874.

Project description:In the context of neurologic disorders, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) MRI provide valuable insights into cerebral vascular function, integrity, and architecture. Even after two decades of use, these modalities continue to evolve as their biophysical and kinetic basis is better understood, with improvements in pulse sequences and accelerated imaging techniques and through application of more robust and automated data analysis strategies. Here, we systematically review each of these elements, with a focus on how their integration improves kinetic parameter accuracy and the development of new hemodynamic biomarkers that provide sub-voxel sensitivity (e.g., capillary transit time and flow heterogeneity). Regarding contrast mechanisms, we discuss the dipole-dipole interactions and susceptibility effects that give rise to simultaneous T1, T2 and T2∗ relaxation effects, including their quantification, influence on pulse sequence parameter optimization, and use in methods such as vessel size and vessel architectural imaging. The application of technologic advancements, such as parallel imaging, simultaneous multi-slice, undersampled k-space acquisitions, and sliding window strategies, enables improved spatial and/or temporal resolution of DSC and DCE acquisitions. Such acceleration techniques have also enabled the implementation of, clinically feasible, simultaneous multi-echo spin- and gradient echo acquisitions, providing more comprehensive and quantitative interrogation of T1, T2 and T2∗ changes. Characterizing these relaxation rate changes through different post-processing options allows for the quantification of hemodynamics and vascular permeability. The application of different biophysical models provides insight into traditional hemodynamic parameters (e.g., cerebral blood volume) and more advanced parameters (e.g., capillary transit time heterogeneity). We provide insight into the appropriate selection of biophysical models and the necessary post-processing steps to ensure reliable measurements while minimizing potential sources of error. We show representative examples of advanced DSC- and DCE-MRI methods applied to pathologic conditions affecting the cerebral microcirculation, including brain tumors, stroke, aging, and multiple sclerosis. The maturation and standardization of conventional DSC- and DCE-MRI techniques has enabled their increased integration into clinical practice and use in clinical trials, which has, in turn, spurred renewed interest in their technological and biophysical development, paving the way towards a more comprehensive assessment of cerebral hemodynamics.

Project description:BackgroundPrimary small vessel CNS vasculitis (sv-cPACNS) is a challenging inflammatory brain disease in children. Brain biopsy is mandatory to confirm the diagnosis. This study aims to develop and validate a histological scoring tool for diagnosing small vessel CNS vasculitis.MethodsA standardized brain biopsy scoring instrument was developed and applied to consecutive full-thickness brain biopsies of pediatric cases and controls at a single center. Stains included immunohistochemistry and Hematoxylin & Eosin. Nine North American neuropathologists, blinded to patients' presentation, diagnosis, and therapy, scored de-identified biopsies independently.ResultsA total of 31 brain biopsy specimens from children with sv-cPACNS, 11 with epilepsy, and 11 with non-vasculitic inflammatory brain disease controls were included. Angiocentric inflammation in the cortex or white matter increases the likelihood of sv-cPACNS, with odds ratios (ORs) of 3.231 (95CI: 0.914-11.420, p = 0.067) and 3.923 (95CI: 1.13-13.6, p = 0.031). Moderate to severe inflammation in these regions is associated with a higher probability of sv-cPACNS, with ORs of 5.56 (95CI: 1.02-29.47, p = 0.046) in the cortex and 6.76 (95CI: 1.26-36.11, p = 0.025) in white matter. CD3, CD4, CD8, and CD20 cells predominated the inflammatory infiltrate. Reactive endothelium was strongly associated with sv-cPACNS, with an OR of 8.93 (p = 0.001). Features reported in adult sv-PACNS, including granulomas, necrosis, or fibrin deposits, were absent in all biopsies. The presence of leptomeningeal inflammation in isolation was non-diagnostic.ConclusionDistinct histological features were identified in sv-cPACNS biopsies, including moderate to severe angiocentric inflammatory infiltrates in the cortex or white matter, consisting of CD3, CD4, CD8, and CD20 cells, alongside reactive endothelium with specificity of 95%. In the first study of its kind proposing histological criteria for evaluating brain biopsies, we aim to precisely characterize the type and severity of the inflammatory response in patients with sv-cPACNS; this can enable consolidation of this population to assess outcomes and treatment methodologies comprehensively.

Project description:ObjectiveFew attempts have been made to investigate the prognostic value of dynamic contrast-enhanced (DCE) MRI or dynamic susceptibility contrast (DSC) MRI of non-enhancing, T2-high-signal-intensity (T2-HSI) lesions of glioblastoma multiforme (GBM) in newly diagnosed patients. This study aimed to investigate the prognostic values of DCE MRI and DSC MRI parameters from non-enhancing, T2-HSI lesions of GBM.Materials and methodsA total of 76 patients with GBM who underwent preoperative DCE MRI and DSC MRI and standard treatment were retrospectively included. Six months after surgery, the patients were categorized into early progression (n = 15) and non-early progression (n = 61) groups. We extracted and analyzed the permeability and perfusion parameters of both modalities for the non-enhancing, T2-HSI lesions of the tumors. The optimal percentiles of the respective parameters obtained from cumulative histograms were determined using receiver operating characteristic (ROC) curve and univariable Cox regression analyses. The results were compared using multivariable Cox proportional hazards regression analysis of progression-free survival.ResultsThe 95th percentile value (PV) of Ktrans, mean Ktrans, and median Ve were significant predictors of early progression as identified by the ROC curve analysis (area under the ROC curve [AUC] = 0.704, p = 0.005; AUC = 0.684, p = 0.021; and AUC = 0.670, p = 0.0325, respectively). Univariable Cox regression analysis of the above three parametric values showed that the 95th PV of Ktrans and the mean Ktrans were significant predictors of early progression (hazard ratio [HR] = 1.06, p = 0.009; HR = 1.25, p = 0.017, respectively). Multivariable Cox regression analysis, which also incorporated clinical parameters, revealed that the 95th PV of Ktrans was the sole significant independent predictor of early progression (HR = 1.062, p < 0.009).ConclusionThe 95th PV of Ktrans from the non-enhancing, T2-HSI lesions of GBM is a potential prognostic marker for disease progression.

Dataset Information

The role of susceptibility-weighted imaging & contrast-enhanced MRI in the diagnosis of primary CNS vasculitis: a large case series.

Publications

The role of susceptibility-weighted imaging & contrast-enhanced MRI in the diagnosis of primary CNS vasculitis: a large case series.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets