Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas.
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ABSTRACT:
SUBMITTER: Boxerman JL
PROVIDER: S-EPMC7523451 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND: We assessed the diagnostic accuracy of diffusion kurtosis imaging (DKI), dynamic susceptibility-weighted contrast-enhanced (DSC) MRI, and short echo time chemical shift imaging (CSI) for grading gliomas. METHODS: In this prospective study, 35 patients with cerebral gliomas underwent DKI, DSC, and CSI on a 3 T MR scanner. Diffusion parameters were mean diffusivity (MD), fractional anisotropy, and mean kurtosis (MK). Perfusion parameters were mean relative regional cerebral blood volume (rrCBV), mean relative regional cerebral blood flow (rrCBF), mean transit time, and relative decrease ratio (rDR). The diffusion and perfusion parameters along with 12 CSI metabolite ratios were compared among 22 high-grade gliomas and 14 low-grade gliomas (Mann-Whitney U-test, P < .05). Classification accuracy was determined with a linear discriminant analysis for each MR modality independently. Furthermore, the performance of a multimodal analysis is reported, using a decision-tree rule combining the statistically significant DKI, DSC-MRI, and CSI parameters with the lowest P-value. The proposed classifiers were validated on a set of subsequently acquired data from 19 clinical patients. RESULTS: Statistically significant differences among tumor grades were shown for MK, MD, mean rrCBV, mean rrCBF, rDR, lipids over total choline, lipids over creatine, sum of myo-inositol, and sum of creatine. DSC-MRI proved to be the modality with the best performance when comparing modalities individually, while the multimodal decision tree proved to be most accurate in predicting tumor grade, with a performance of 86%. CONCLUSIONS: Combining information from DKI, DSC-MRI, and CSI increases diagnostic accuracy to differentiate low- from high-grade gliomas, possibly providing diagnosis for the individual patient.
| S-EPMC4057134 | biostudies-literature
Project description:Standard pre- and postcontrast (T1 + C) anatomical MR imaging is proving to be insufficient for accurately monitoring bevacizumab treatment response in recurrent glioblastoma (GBM). We present a novel imaging biomarker that detects abnormal tumor vasculature exhibiting both arterial and venous perfusion characteristics. We hypothesized that a decrease in the extent of this abnormal vasculature after bevacizumab treatment would predict treatment efficacy and overall survival.Dynamic susceptibility contrast perfusion MRI was gathered in 43 patients with high-grade glioma. Independent component analysis separated vasculature into arterial and venous components. Voxels with perfusion characteristics of both arteries and veins (ie, arterio-venous overlap [AVOL]) were measured in patients with de novo untreated GBM and patients with recurrent high-grade glioma before and after bevacizumab treatment. Treated patients were separated on the basis of an increase or decrease in AVOL volume (+/-?AVOL), and overall survival following bevacizumab onset was then compared between +/-?AVOL groups.AVOL in untreated GBM was significantly higher than in normal vasculature (P < .001). Kaplan-Meier survival curves revealed a greater median survival (348 days) in patients with GBM with a negative ?AVOL after bevacizumab treatment than in patients with a positive change (197 days; hazard ratio, 2.51; P < .05). Analysis of patients with combined grade III and IV glioma showed similar results, with median survivals of 399 days and 153 days, respectively (hazard ratio, 2.71; P < .01). Changes in T1+C volume and ?rCBV after treatment were not significantly different across +/-?AVOL groups, and ?AVOL was not significantly correlated with ?T1+C or ?rCBV.The independent component analysis dynamic susceptibility contrast-derived biomarker AVOL adds additional information for determining bevacizumab treatment efficacy.
| S-EPMC3607265 | biostudies-other
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.
| S-EPMC6538021 | biostudies-literature
Project description:ObjectivesThis study evaluates the repeatability of brain perfusion using dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a variety of post-processing methods.MethodsThirty-two patients with newly diagnosed glioblastoma were recruited. On a 3-T MRI using a dual-echo, gradient-echo spin-echo DSC-MRI protocol, the patients were scanned twice 1 to 5 days apart. Perfusion maps including cerebral blood volume (CBV) and cerebral blood flow (CBF) were generated using two contrast agent leakage correction methods, along with testing normalization to reference tissue, and application of arterial input function (AIF). Repeatability of CBV and CBF within tumor regions and healthy tissues, identified by structural images, was assessed with intra-class correlation coefficients (ICCs) and repeatability coefficients (RCs). Coefficients of variation (CVs) were reported for selected methods.ResultsCBV and CBF were highly repeatable within tumor with ICC values up to 0.97. However, both CBV and CBF showed lower ICCs for healthy cortical tissues (up to 0.83), healthy gray matter (up to 0.95), and healthy white matter (WM; up to 0.93). The values of CV ranged from 6% to 10% in tumor and 3% to 11% in healthy tissues. The values of RC relative to the mean value of measurement within healthy WM ranged from 22% to 42% in tumor and 7% to 43% in healthy tissues. These percentages show how much variation in perfusion parameter, relative to that in healthy WM, we expect to observe to consider it statistically significant. We also found that normalization improved repeatability, but AIF deconvolution did not.ConclusionsDSC-MRI is highly repeatable in high-grade glioma patients.
| S-EPMC4486737 | biostudies-literature
Project description:MR Fingerprinting (MRF)-based Arterial-Spin-Labeling (ASL) has the potential to measure multiple parameters such as cerebral blood flow (CBF), bolus arrival time (BAT), and tissue T1 in a single scan. However, the previous reports have only demonstrated a proof-of-principle of the technique but have not examined the performance of the sequence in the context of key imaging parameters. Furthermore, there has not been a study to directly compare the technique to clinically used perfusion method of dynamic-susceptibility-contrast (DSC) MRI. The present report consists of two studies. In the first study (N = 8), we examined the dependence of MRF-ASL sequence on TR time pattern. Ten different TR patterns with a range of temporal characteristics were examined by both simulations and experiments. The results revealed that there was a significance dependence of the sequence performance on TR pattern (p < 0.001), although there was not a single pattern that provided dramatically improvements. Among the TR patterns tested, a sinusoidal pattern with a period of 125 TRs provided an overall best estimation in terms of spatial consistency. These experimental observations were consistent with those of numerical simulations. In the second study (N = 8), we compared MRF-ASL results with those of DSC MRI. It was found that MRF-ASL and DSC MRI provided highly comparable maps of cerebral blood flow (CBF) and bolus-arrival-time (BAT), with spatial correlation coefficients of 0.79 and 0.91, respectively. However, in terms of quantitative values, BAT obtained with MRF-ASL was considerably lower than that from DSC (p < 0.001), presumably because of the differences in tracer characteristics in terms of diffusible versus intravascular tracers. Test-retest assessment of MRF-ASL MRI revealed that the spatial correlations of parametric maps were 0.997, 0.962, 0.746 and 0.863 for B1 + , T1 , CBF, and BAT, respectively. MRF-ASL is a promising technique for assessing multiple perfusion parameters simultaneously without contrast agent.
| S-EPMC7229700 | biostudies-literature
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.
| S-EPMC8316772 | biostudies-literature
Project description:BackgroundT1-weighted dynamic contrast-enhanced (DCE) perfusion magnetic resonance imaging (MRI) has been broadly utilized in the evaluation of brain tumors. We aimed at assessing the diagnostic accuracy of DCE-MRI in discriminating between low-grade gliomas (LGGs) and high-grade gliomas (HGGs), between tumor recurrence and treatment-related changes, and between primary central nervous system lymphomas (PCNSLs) and HGGs.MethodsWe performed this study based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis of Diagnostic Test Accuracy Studies criteria. We systematically surveyed studies evaluating the diagnostic accuracy of DCE-MRI for the aforementioned entities. Meta-analysis was conducted with the use of a random effects model.ResultsTwenty-seven studies were included after screening of 2945 possible entries. We categorized the eligible studies into three groups: those utilizing DCE-MRI to differentiate between HGGs and LGGs (14 studies, 546 patients), between recurrence and treatment-related changes (9 studies, 298 patients) and between PCNSLs and HGGs (5 studies, 224 patients). The pooled sensitivity, specificity, and area under the curve for differentiating HGGs from LGGs were 0.93, 0.90, and 0.96, for differentiating tumor relapse from treatment-related changes were 0.88, 0.86, and 0.89, and for differentiating PCNSLs from HGGs were 0.78, 0.81, and 0.86, respectively.ConclusionsDynamic contrast-enhanced-Magnetic resonance imaging is a promising noninvasive imaging method that has moderate or high accuracy in stratifying gliomas. DCE-MRI shows high diagnostic accuracy in discriminating between HGGs and their low-grade counterparts, and moderate diagnostic accuracy in discriminating recurrent lesions and treatment-related changes as well as PCNSLs and HGGs.
| S-EPMC6745862 | biostudies-literature
Project description:PurposeBrain tumor dynamic susceptibility contrast (DSC) MRI is adversely impacted by T1 and T2∗ contrast agent leakage effects that result in inaccurate hemodynamic metrics. While multi-echo acquisitions remove T1 leakage effects, there is no consensus on the optimal set of acquisition parameters. Using a computational approach, we systematically evaluated a wide range of acquisition strategies to determine the optimal multi-echo DSC-MRI perfusion protocol.MethodsUsing a population-based DSC-MRI digital reference object (DRO), we assessed the influence of preload dosing (no preload and full dose preload), field strength (1.5 and 3T), pulse sequence parameters (echo time, repetition time, and flip angle), and leakage correction on relative cerebral blood volume (rCBV) and flow (rCBF) accuracy. We also compared multi-echo DSC-MRI protocols with standard single-echo protocols.ResultsMulti-echo DSC-MRI is highly consistent across all protocols, and multi-echo rCBV (with or without use of a preload dose) had higher accuracy than single-echo rCBV. Regression analysis showed that choice of repetition time and flip angle had minimal impact on multi-echo rCBV and rCBV, indicating the potential for significant flexibility in acquisition parameters. The echo time combination had minimal impact on rCBV, though longer echo times should be avoided, particularly at higher field strengths. Leakage correction improved rCBV accuracy in all cases. Multi-echo rCBF was less biased than single-echo rCBF, although rCBF accuracy was reduced overall relative to rCBV.ConclusionsMulti-echo acquisitions were more robust than single-echo, essentially decoupling both repetition time and flip angle from rCBV accuracy. Multi-echo acquisitions obviate the need for preload dosing, although leakage correction to remove residual T2∗ leakage effects remains compulsory for high rCBV accuracy.
| S-EPMC6778704 | biostudies-literature
Project description:PURPOSE:To identify clinically relevant magnetic resonance imaging (MRI) features of different types of metastatic brain lesions, including standard anatomical, diffusion weighted imaging (DWI) and dynamic susceptibility contrast (DSC) perfusion MRI. METHODS:MRI imaging was retrospectively assessed on one hundred and fourteen (N = 114) brain metastases including breast (n = 27), non-small cell lung cancer (NSCLC, n = 43) and 'other' primary tumors (n = 44). Based on 114 patient's MRI scans, a total of 346 individual contrast enhancing tumors were manually segmented. In addition to tumor volume, apparent diffusion coefficients (ADC) and relative cerebral blood volume (rCBV) measurements, an independent component analysis (ICA) was performed with raw DSC data in order to assess arterio-venous components and the volume of overlap (AVOL) relative to tumor volume, as well as time to peak (TTP) of T2* signal from each component. RESULTS:Results suggests non-breast or non-NSCLC ('other') tumors had higher volume compare to breast and NSCLC patients (p = 0.0056 and p = 0.0003, respectively). No differences in median ADC or rCBV were observed across tumor types; however, breast and NSCLC tumors had a significantly higher "arterial" proportion of the tumor volume as indicated by ICA (p = 0.0062 and p = 0.0018, respectively), while a higher "venous" proportion were prominent in breast tumors compared with NSCLC (p = 0.0027) and 'other' lesions (p = 0.0011). The AVOL component was positively related to rCBV in all groups, but no correlation was found for arterial and venous components with respect to rCBV values. Median time to peak of arterial and venous components were 8.4 s and 12.6 s, respectively (p < 0.0001). No difference was found in arterial or venous TTP across groups. CONCLUSIONS:Advanced ICA-derived component analysis demonstrates perfusion differences between metastatic brain tumor types that were not observable with classical ADC and rCBV measurements. These results highlight the complex relationship between brain tumor vasculature characteristics and the site of primary tumor diagnosis.
| S-EPMC6423873 | biostudies-literature
Project description:We explored the prognostic impact of the dynamic contrast enhanced MR imaging (DCE-MRI) parameter ABrix in cervical cancer combined with global gene expression data to reveal the underlying molecular phenotype of the parameter and construct a gene signature that reflected ABrix. Based on 78 cervical cancer patients subjected to curative chemoradiotherapy, we identified a prognostic ABrix parameter by pharmacokinetic analysis of DCE-MR images based on the Brix model, where tumors with low ABrix appeared to be most aggressive. Gene set enrichment analysis of 46 tumors with pairwise DCE-MRI and gene expression data showed a significant correlation between ABrix and the hypoxia gene sets, whereas gene sets related to proliferation, radioresistance, and wound healing were not significant. Hypoxia gene sets specific for cervical cancer created in cell culture experiments, including targets of the hypoxia inducible factor (HIF1M-NM-1) and the unfolded protein response (UPR), were the most significant. In the remaining 32 tumors, low ABrix was associated with upregulation of HIF1M-NM-1 protein expression, as assessed by immunohistochemistry, consistent with increased hypoxia. Based on the hypoxia gene sets, a signature of 31 genes that were upregulated in tumors with low ABrix was constructed. This DCE-MRI hypoxia gene signature showed prognostic impact in an independent validation cohort of 109 patients. Gene expression correlating with the DCE-MRI parameter ABrix were identified in 46 patients (DCE-MRI cohort) and used to find a hypoxia gene signature. The prognsotic impact of the gene signature was validated in an independent cohort of 109 patients (validation chort). Cell culture experiments were performed to generate cervical cancer specific gene lists associated with hypoxia (GSM897799 - GSM897804).
2012-08-16 | E-GEOD-36562 | biostudies-arrayexpress