T2 relaxation time elongation of hepatocellular carcinoma relative to native liver tissue leads to an underestimation of perfusion fraction measured by standard intravoxel incoherent motion magnetic resonance imaging.
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SUBMITTER: Ma FZ
PROVIDER: S-EPMC10784108 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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<i>T<sub>2</sub></i> relaxation time elongation of hepatocellular carcinoma relative to native liver tissue leads to an underestimation of perfusion fraction measured by standard intravoxel incoherent motion magnetic resonance imaging.
Ma Fu-Zhao FZ Wáng Yì Xiáng J YXJ
Quantitative imaging in medicine and surgery 20231129 1
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Project description: Not available
| S-EPMC10895138 | biostudies-literature
Project description:Background and purposeIntravoxel incoherent motion MRI has been proposed as an alternative method to measure brain perfusion. Our aim was to evaluate the utility of intravoxel incoherent motion perfusion parameters (the perfusion fraction, the pseudodiffusion coefficient, and the flow-related parameter) to differentiate high- and low-grade brain gliomas.Materials and methodsThe intravoxel incoherent motion perfusion parameters were assessed in 21 brain gliomas (16 high-grade, 5 low-grade). Images were acquired by using a Stejskal-Tanner diffusion pulse sequence, with 16 values of b (0-900 s/mm(2)) in 3 orthogonal directions on 3T systems equipped with 32 multichannel receiver head coils. The intravoxel incoherent motion perfusion parameters were derived by fitting the intravoxel incoherent motion biexponential model. Regions of interest were drawn in regions of maximum intravoxel incoherent motion perfusion fraction and contralateral control regions. Statistical significance was assessed by using the Student t test. In addition, regions of interest were drawn around all whole tumors and were evaluated with the help of histograms.ResultsIn the regions of maximum perfusion fraction, perfusion fraction was significantly higher in the high-grade group (0.127 ± 0.031) than in the low-grade group (0.084 ± 0.016, P < .001) and in the contralateral control region (0.061 ± 0.011, P < .001). No statistically significant difference was observed for the pseudodiffusion coefficient. The perfusion fraction correlated moderately with dynamic susceptibility contrast relative CBV (r = 0.59). The histograms of the perfusion fraction showed a "heavy-tailed" distribution for high-grade but not low-grade gliomas.ConclusionsThe intravoxel incoherent motion perfusion fraction is helpful for differentiating high- from low-grade brain gliomas.
| S-EPMC7965752 | biostudies-literature
Project description:Measurement of microvascular perfusion with Intravoxel Incoherent Motion (IVIM) MRI is gaining interest. Yet, the physiological influences on the IVIM perfusion parameters ("pseudo-diffusion" coefficient D*, perfusion fraction f, and flow related parameter fD*) remain insufficiently characterized. In this article, we hypothesize that D* and fD*, which depend on blood speed, should vary during the cardiac cycle. We extended the IVIM model to include time dependence of D*?=?D*(t), and demonstrate in the healthy human brain that both parameters D* and fD* are significantly larger during systole than diastole, while the diffusion coefficient D and f do not vary significantly. The results non-invasively demonstrate the pulsatility of the brain's microvasculature.
| S-EPMC3758329 | biostudies-literature
Project description:PurposeIntravoxel incoherent motion (IVIM) modeling for estimation of the diffusion coefficient (D) and perfusion fraction (f) is increasingly popular, but no consensus on standard protocols exists. This study provides a framework for optimization of b-value schemes for reduced estimation uncertainty of D and f from segmented model fitting.TheoryAnalytical expressions for uncertainties of D and f from segmented model fitting were derived as Cramer-Rao lower bounds (CRLBs).MethodsOptimized b-value schemes were obtained for 3 to 12 acquisitions and in the limit of infinitely many acquisitions through constrained minimization of the CRLBs, with b-values constrained to be 0 or 200 to 800 s/mm2 . The optimized b-value scheme with eight acquisitions was compared with b-values linearly distributed in the allowed range using simulations and in vivo liver data from seven healthy volunteers.ResultsAll optimized b-value schemes contained exactly three unique b-values regardless of the total number of acquisitions (0, 200, and 800 s/mm2 ) with repeated acquisitions distributed approximately as 1:2:2. Compared with linearly distributed b-values, the variability of estimates of D and f was reduced by approximately 30% as seen both in simulations and in repeated in vivo measurements.ConclusionThe uncertainty of IVIM D and f estimates can be reduced by the use of optimized b-value schemes.
| S-EPMC6772171 | biostudies-literature
Project description:In general, only one diffusion model would be applied to whole field-of-view voxels in the intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI) study. However, the choice of the applied diffusion model can significantly influence the estimated diffusion parameters. The quality of the diffusion analysis can influence the reliability of the perfusion analysis. This study proposed an optimal model mapping method to improve the reliability of the perfusion parameter estimation in the IVIM study. Six healthy volunteers (five males and one female; average age of 38.3 ± 7.5 years). Volunteers were examined using a 3.0 Tesla scanner. IVIM-MRI of the brain was applied at 17 b-values ranging from 0 to 2,500 s/mm2. The Gaussian model, the Kurtosis model, and the Gamma model were found to be optimal for the CSF, white matter (WM), and gray matter (GM), respectively. In the mean perfusion fraction (fp) analysis, the GM/WM ratios were 1.16 (Gaussian model), 1.80 (Kurtosis model), 1.94 (Gamma model), and 1.54 (Optimal model mapping); in the mean pseudo diffusion coefficient (D*) analysis, the GM/WM ratios were 1.18 (Gaussian model), 1.19 (Kurtosis model), 1.56 (Gamma model), and 1.24 (Optimal model mapping). With the optimal model mapping method, the estimated fp and D* were reliable compared with the conventional methods. In addition, the optimal model maps, the associated products of this method, may provide additional information for clinical diagnosis.
| S-EPMC7937866 | biostudies-literature
Project description:IntroductionThe intravoxel incoherent motion (IVIM) model of diffusion weighted imaging (DWI) provides imaging biomarkers for breast tumor characterization. It has been extensively applied for both diagnostic and prognostic goals in breast cancer, with increasing evidence supporting its clinical relevance. However, variable performance exists in literature owing to the heterogeneity in datasets and quantification methods.MethodsThis work used retrospective anonymized breast MRI data (302 patients) from three sites employing three different software utilizing least-squares segmented algorithms and Bayesian fit to estimate 1st order radiomics of IVIM parameters perfusion fraction (fp ), pseudo-diffusion (Dp ) and tissue diffusivity (Dt ). Pearson correlation (r) coefficients between software pairs were computed while logistic regression model was implemented to test malignancy detection and assess robustness of the IVIM metrics.ResultsDt and fp maps generated from different software showed consistency across platforms while Dp maps were variable. The average correlation between the three software pairs at three different sites for 1st order radiomics of IVIM parameters were Dtmin/Dtmax/Dtmean/Dtvariance/Dtskew/Dtkurt: 0.791/0.891/0.98/0.815/0.697/0.584; fpmax/fpmean/fpvariance/fpskew/fpkurt: 0.615/0.871/0.679/0.541/0.433; Dpmax/Dpmean/Dpvariance/Dpskew/Dpkurt: 0.616/0.56/0.587/0.454/0.51. Correlation between least-squares algorithms were the highest. Dtmean showed highest area under the ROC curve (AUC) with 0.85 and lowest coefficient of variation (CV) with 0.18% for benign and malignant differentiation using logistic regression. Dt metrics were highly diagnostic as well as consistent along with fp metrics.DiscussionMultiple 1st order radiomic features of Dt and fp obtained from a heterogeneous multi-site breast lesion dataset showed strong software robustness and/or diagnostic utility, supporting their potential consideration in controlled prospective clinical trials.
| S-EPMC11891049 | biostudies-literature
Project description:Intravoxel incoherent motion (IVIM) imaging is a magnetic resonance imaging (MRI) technique widely used in clinical applications for various organs. However, IVIM imaging at low b-values is a persistent problem. This paper aims to investigate in a systematic and detailed manner how the number of low b-values influences the estimation of IVIM parameters. To this end, diffusion-weighted (DW) data with different low b-values were simulated to get insight into the distributions of subsequent IVIM parameters. Then, in vivo DW data with different numbers of low b-values and different number of excitations (NEX) were acquired. Finally, least-squares (LSQ) and Bayesian shrinkage prior (BSP) fitting methods were implemented to estimate IVIM parameters. The influence of the number of low b-values on IVIM parameters was analyzed in terms of relative error (RE) and structural similarity (SSIM). The results showed that the influence of the number of low b-values on IVIM parameters is variable. LSQ is more dependent on the number of low b-values than BSP, but the latter is more sensitive to noise.
| S-EPMC6364995 | biostudies-literature
Project description:ObjectivesTo determine the potential of intravoxel incoherent motion (IVIM) MR imaging for staging of hepatic fibrosis (HF).MethodsWe searched PubMed and EMBASE from their inception to 31 July 2015 to select studies reporting IVIM MR imaging and HF staging. We defined F1-2 as non-advanced HF, F3-4 as advanced HF, F0 as normal liver, F1 as very early HF, and F2-4 as significant HF. Then we compared stage F0 with F1, F0-1 with F2-3, and F1-2 with F3-4 using IVIM-derived parameters (pseudo-diffusion coefficient D*, perfusion fraction f, and pure molecular diffusion parameter D). The effect estimate was expressed as a pooled weighted mean difference (WMD) with 95% confidence interval (CI), using the fixed-effects model.ResultsOverall, we included six papers (406 patients) in this study. Significant differences in D* were observed between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 2.46, 95% CI 0.83-4.09, P = 0.006; WMD 13.10, 95% CI 9.53-16.67, P < 0.001; WMD 14.34, 95% CI 10.26-18.42, P < 0.001, respectively). Significant differences in f were also found between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 1.62, 95% CI 0.06-3.18, P = 0.027; WMD 5.63, 95% CI 2.74-8.52, P < 0.001; WMD 3.30, 95% CI 2.10-4.50, P < 0.001, respectively). However, D showed no differences between F0 and F1, F0-1 and F2-3, and F1-2 and F3-4 (WMD 0.05, 95% CI -0.01─0.11, P = 0.105; WMD 0.04, 95% CI -0.01─0.10, P = 0.230; WMD 0.02, 95% CI -0.02─0.06, P = 0.378, respectively).ConclusionsIVIM MR imaging provides an effective method of staging HF and can distinguish early HF from normal liver, significant HF from normal liver or very early HF, and advanced HF from non-advanced HF.
| S-EPMC4731200 | biostudies-literature
Project description:BackgroundIntravoxel incoherent motion magnetic resonance imaging (IVIM) enables non-invasive measurement of brain perfusion.PurposeTo investigate whether IVIM could be used to evaluate the hemodynamic disturbance of Moyamoya disease (MMD) by comparison with the gold-standard 15O-gas positron emission tomography (PET) method.Material and methodsTen consecutive patients with MMD (six women; mean age = 42.8 years) and 10 age-matched healthy controls were evaluated by diffusion-weighted images with 12 different b values in the range of 0-900 s/mm2 and 15O-gas PET. Tomographic maps of IVIM parameters, perfusion fraction (f ), pseudo-diffusion coefficient (D*), and f・D*, as well as cerebral blood volume (CBV), cerebral blood flow (CBF), and mean transit time (MTT) maps obtained with PET, were normalized and hemispheric gray and white matter values were calculated. IVIM parametric values were compared with PET parameters and with clinically assessed disease severity.ResultsThere was significant correlation between D* and MTT (r = -0.74, P < 0.001) and between f・D* and CBF (r = 0.52, P = 0.02) in the cortical areas. The f values in the white matter were significantly higher in symptomatic MMD patients than in healthy controls (P = 0.01).ConclusionIVIM may be used to non-invasively investigate cerebral hemodynamic impairment in patients with MMD. Further evaluation is needed to establish IVIM usage in clinical settings.
| S-EPMC6535913 | biostudies-literature
Project description:ObjectiveIntravoxel incoherent motion (IVIM) is an MRI technique with potential applications in measuring brain tumor perfusion, but its clinical impact remains to be determined. We assessed the usefulness of IVIM-metrics in predicting survival in newly diagnosed glioblastoma.MethodsFifteen patients with glioblastoma underwent MRI including spin-echo echo-planar DWI using 13 b-values ranging from 0 to 1000 s/mm2. Parametric maps for diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were generated for contrast-enhancing regions (CER) and non-enhancing regions (NCER). Regions of interest were manually drawn in regions of maximum f and on the corresponding dynamic susceptibility contrast images. Prognostic factors were evaluated by Kaplan-Meier survival and Cox proportional hazards analyses.ResultsWe found that fCER and D*CER correlated with rCBFCER. The best cutoffs for 6-month survival were fCER>9.86% and D*CER>21.712 x10-3mm2/s (100% sensitivity, 71.4% specificity, 100% and 80% positive predictive values, and 80% and 100% negative predictive values; AUC:0.893 and 0.857, respectively). Treatment yielded the highest hazard ratio (5.484; 95% CI: 1.162-25.88; AUC: 0.723; P = 0.031); fCER combined with treatment predicted survival with 100% accuracy.ConclusionsThe IVIM-metrics fCER and D*CER are promising biomarkers of 6-month survival in newly diagnosed glioblastoma.
| S-EPMC4936699 | biostudies-literature