Model selection in measures of vascular parameters using dynamic contrast-enhanced MRI: experimental and clinical applications.
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ABSTRACT:
SUBMITTER: Ewing JR
PROVIDER: S-EPMC3752406 | biostudies-other | 2013 Aug
REPOSITORIES: biostudies-other
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Project description:Hypoxia in the tumor microenvironment is the leading factor in angiogenesis. Angiogenesis can be identified by dynamic contrast-enhanced breast MRI (DCE MRI). Here we investigate the relationship between perfusion parameters on DCE MRI and angiogenic and prognostic factors in patients with invasive ductal carcinoma (IDC). Perfusion parameters (Ktrans, kep and ve) of 81 IDC were obtained using histogram analysis. Twenty-fifth, 50th and 75th percentile values were calculated and were analyzed for association with microvessel density (MVD), vascular endothelial growth factor (VEGF) and conventional prognostic factors. Correlation between MVD and ve50 was positive (r = 0.33). Ktrans50 was higher in tumors larger than 2 cm than in tumors smaller than 2 cm. In multivariate analysis, Ktrans50 was affected by tumor size and MVD with 12.8% explanation. There was significant association between Ktrans50 and tumor size and MVD. Therefore we conclude that DCE MRI perfusion parameters are potential imaging biomarkers for prediction of tumor angiogenesis and aggressiveness.
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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.
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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.
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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
Project description:The purpose of this study was to identify the optimal tracer kinetic model from T1 -weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data and evaluate whether parameters estimated from the optimal model predict tumor aggressiveness determined from histopathology in patients with papillary thyroid carcinoma (PTC) prior to surgery. In this prospective study, 18 PTC patients underwent pretreatment DCE-MRI on a 3 T MR scanner prior to thyroidectomy. This study was approved by the institutional review board and informed consent was obtained from all patients. The two-compartment exchange model, compartmental tissue uptake model, extended Tofts model (ETM) and standard Tofts model were compared on a voxel-wise basis to determine the optimal model using the corrected Akaike information criterion (AICc) for PTC. The optimal model is the one with the lowest AICc. Statistical analysis included paired and unpaired t-tests and a one-way analysis of variance. Bonferroni correction was applied for multiple comparisons. Receiver operating characteristic (ROC) curves were generated from the optimal model parameters to differentiate PTC with and without aggressive features, and AUCs were compared. ETM performed best with the lowest AICc and the highest Akaike weight (0.44) among the four models. ETM was preferred in 44% of all 3419 voxels. The ETM estimates of Ktrans in PTCs with the aggressive feature extrathyroidal extension (ETE) were significantly higher than those without ETE (0.78 ± 0.29 vs. 0.34 ± 0.18 min-1 , P = 0.005). From ROC analysis, cut-off values of Ktrans , ve and vp , which discriminated between PTCs with and without ETE, were determined at 0.45 min-1 , 0.28 and 0.014 respectively. The sensitivities and specificities were 86 and 82% (Ktrans ), 71 and 82% (ve ), and 86 and 55% (vp ), respectively. Their respective AUCs were 0.90, 0.71 and 0.71. We conclude that ETM Ktrans has shown potential to classify tumors with and without aggressive ETE in patients with PTC.
| S-EPMC7687051 | 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 (HIF1α) and the unfolded protein response (UPR), were the most significant. In the remaining 32 tumors, low ABrix was associated with upregulation of HIF1α 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.
2012-08-16 | GSE36562 | GEO
Project description:The aim of the study was to investigate dynamic contrast enhanced MRI (DCE-MRI) as a potential marker to assess the therapeutic responses of fecal microbiota transplantation (FMT) in patients with Crohn's disease (CD) and to determine the parameter or combination of parameters most strongly associated with changes in clinical indicators after treatment.In 22 CD patients, DCE-MRI was performed with a 3.0T scanner. Parameters of DCE-MRI (vascular transfer constant [K] and blood volume [BV]) in the terminal ileum were compared between before and day 90 after FMT treatment. The differences of clinical indicators (C-reactive protein [CRP], Harvey-Bradshaw index [HBI]) and DCE-MRI parameters (K, BV) between pre- and post-treatment was calculated by Student's 2-tailed, paired t-test. The correlations between percent change of clinical indicators (ΔCRP, ΔHBI) with DCE-MRI parameters (ΔK, ΔBV) were analyzed by Pearson's correlation coefficients. A logistic regression model was used to identify the changes of DCE-MRI parameters related to the treatment outcomes. Receiver operating characteristic curves (ROCs) were generated to assess which DCE-MRI parameter showed the best accuracy for evaluation of therapeutic response.After treatment, mean values of clinical indicators decreased significantly (CRP: 62.68 ± 31.86 vs 43.55 ± 29.63 mg/L, P = .008; HBI: 7.18 ± 2.10 vs 5.73 ± 2.33, P = 0.012). Both DCE-MRI parameters showed prominent differences before and after treatment: K (1.86 ± 0.87 vs 1.39 ± 0.83 min, P = .017), BV (61.02 ± 28.49 vs 41.96 ± 22.75 mL/100 g, P = .005). There were significant correlations between ΔCRP or ΔHBI and percent change of CDE-MRI parameters (ΔK to ΔCRP: 0.659; ΔK to ΔHBI: 0.496; ΔBV to ΔCRP: 0.442; ΔBV to ΔHBI: 0.476). Compared to ΔK and ΔBV individually, the combination of both parameters performed best in assessment of therapeutic response with an area under the ROCs (AUC) of 0.948.K and BV parameters derived from DCE-MRI have the potential to assess for therapeutic response after FMT treatment for CD. The combination of K and BV measurements improved the predictive capability compared to the individual parameters.
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Project description:The passage of a vascular-injected paramagnetic contrast reagent (CR) bolus through a region-of-interest affects tissue (1)H(2)O relaxation and thus MR image intensity. For longitudinal relaxation [R(1) identical with (T(1))(-1)], the CR must have transient molecular interactions with water. Because the CR and water molecules are never uniformly distributed in the histological-scale tissue compartments, the kinetics of equilibrium water compartmental interchange are competitive. In particular, the condition of the equilibrium trans cytolemmal water exchange NMR system sorties through different domains as the interstitial CR concentration, [CR(o)], waxes and wanes. Before CR, the system is in the fast-exchange-limit (FXL). Very soon after CR(o) arrival, it enters the fast-exchange-regime (FXR). Near maximal [CR(o)], the system could enter even the slow-exchange-regime (SXR). These conditions are defined herein, and a comprehensive description of how they affect quantitative pharmacokinetic analyses is presented. Data are analyzed from a population of 22 patients initially screened suspicious for breast cancer. After participating in our study, the subjects underwent biopsy/pathology procedures and only 7 (32%) were found to have malignancies. The transient departure from FXL to FXR (and apparently not SXR) is significant in only the malignant tumors, presumably because of angiogenic capillary leakiness. Thus, if accepted, this analysis would have prevented the 68% of the biopsies that proved benign.
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Project description:ObjectiveSynovium is increasingly a target of osteoarthritis (OA) treatment, yet its optimal measurement is unclear. Using dynamic contrast enhanced (DCE) MRI in knee OA patients before and after intraarticular steroid injection, we compared the responsiveness of static synovial volume measures to measures of dynamic changes in synovial enhancement, changes that are strongly related to synovial vascularity.MethodsNinety three patients underwent DCE-MRI before and 1-2 weeks after intra-articular injection of 80 mg methylprednisolone. Synovium was segmented and volume, relative enhancement rate (RER), maximum relative enhancement (REmax), late relative enhancement (RElate) and pharmacokinetic parameters (K(trans), ve) were calculated. KOOS (?knee injury and osteoarthritis outcome score) pain score was recorded before and after injection. Standardized change scores were calculated for each parameter. Linear regression and Pearson's correlations were used to investigate the relationship between change in MRI parameters and change in pain.ResultsThe change in standardized score for the measures of synovial enhancement, RElate and REmax were -0.58 (95% CI -0.79 to -0.37) and -0.62 (95% CI -0.83 to -0.41) respectively, whereas the score for synovial volume was -0.30 (-0.52 to -0.09). Further, change in knee pain correlated more strongly with changes in enhancement (for both REmax and RElate, r = -0.27 (95% CI -0.45 to -0.07)) than with changes in synovial volume -0.15 (-0.35 to 0.05).ConclusionThis study suggests DCE-MRI derived measures of synovial enhancement may be more sensitive to the response to treatment and more strongly associated with changes in pain than synovial volume and may be better outcomes for assessment of structural effects of treatment in OA.
| S-EPMC4967444 | biostudies-literature
Project description:PURPOSE:To automate dynamic contrast-enhanced MRI (DCE-MRI) data analysis by unsupervised pattern recognition (PR) to enable spatial mapping of intratumoral vascular heterogeneity. METHODS:Three steps were automated. First, the arrival time of the contrast agent at the tumor was determined, including a calculation of the precontrast signal. Second, four criteria-based algorithms for the slice-specific selection of number of patterns (NP) were validated using 109 tumor slices from subcutaneous flank tumors of five different tumor models. The criteria were: half area under the curve, standard deviation thresholding, percent signal enhancement, and signal-to-noise ratio (SNR). The performance of these criteria was assessed by comparing the calculated NP with the visually determined NP. Third, spatial assignment of single patterns and/or pattern mixtures was obtained by way of constrained nonnegative matrix factorization. RESULTS:The determination of the contrast agent arrival time at the tumor slice was successfully automated. For the determination of NP, the SNR-based approach outperformed other selection criteria by agreeing >97% with visual assessment. The spatial localization of single patterns and pattern mixtures, the latter inferring tumor vascular heterogeneity at subpixel spatial resolution, was established successfully by automated assignment from DCE-MRI signal-versus-time curves. CONCLUSION:The PR-based DCE-MRI analysis was successfully automated to spatially map intratumoral vascular heterogeneity. Magn Reson Med 79:1736-1744, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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