Bi-exponential Intravoxel Incoherent Motion Model Research Articles

Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging

BackgroundTo compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue.MethodsThis prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model.ResultsAlmost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively).ConclusionsQuantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.

Assessment of fitting methods and variability of IVIM parameters in muscles of the lumbar spine at rest

Intravoxel incoherent motion (IVIM) MRI provides insight into tissue diffusion and perfusion. Here, estimates of perfusion fraction (f), pseudo-diffusion coefficient (D*), and diffusion coefficient (D) obtained via different fitting methods are compared to ascertain (1) the optimal analysis strategy for muscles of the lumbar spine and (2) repeatability of IVIM parameters in skeletal muscle at rest. Diffusion-weighted images were acquired in the lumbar spine at rest in 15 healthy participants. Data were fit to the bi-exponential IVIM model to estimate f, D* and D using three variably segmented approaches based on non-linear least squares fitting, and a Bayesian fitting method. Assuming that perfusion and diffusion are temporally stable in skeletal muscle at rest, and spatially uniform within a spinal segment, the optimal analysis strategy was determined as the approach with the lowest temporal or spatial variation and smallest residual between measured and fit data. Inter-session repeatability of IVIM parameters was evaluated in a subset of 11 people. Finally, simulated IVIM signal at varying signal to noise ratio were evaluated to understand precision and bias. Experimental results showed that IVIM parameter values differed depending on the fitting method. A three-step non-linear least squares fitting approach, where D, f, and D* were estimated sequentially, generally yielded the lowest spatial and temporal variation. Solving all parameters simultaneously yielded the lowest residual between measured and fit data, however there was substantial spatial and temporal variability. Results obtained by Bayesian fitting had high spatial and temporal variability in addition to a large residual between measured and fit data. Simulations showed that all fitting methods can fit the IVIM data at signal to noise ratios &amp;gt;35, and that D* was the most challenging to accurately obtain. Overall, this study motivates use of a three-step non-linear least squares fitting strategy to quantify IVIM parameters in skeletal muscle.

Reproducibility and Repeatability of Intravoxel Incoherent Motion MRI Acquisition Methods in Liver.

Intravoxel incoherent motion (IVIM) diffusion weighted MRI (DWI) has potential for evaluating hepatic fibrosis but image acquisition technique influence on diffusion parameter estimation bears investigation. To minimize variability and maximize repeatably in abdominal DWI in terms of IVIM parameter estimates. Prospective test-retest and image quality comparison. Healthy volunteers (3F/7M, 29.9 ± 12.9 years) and Family Study subjects (18F/12M, 51.7 ± 16.7 years), without and with liver steatosis. Abdominal single-shot echo-planar imaging (EPI) and simultaneous multi-slice (SMS) DWI sequences with respiratory triggering (RT), breath-holding (BH), and navigator echo (NE) at 3 Tesla. SMS-BH, EPI-NE, and SMS-RT data from twice-scanned healthy volunteers were analyzed using 6 × b-values (0-800 s⋅mm-2 ) and lower (LO) and higher (HI) b-value ranges. Family Study subjects were scanned using SMS and standard EPI sequences. The biexponential IVIM model was used to estimate fast-diffusion coefficient (Df ), fraction of fast diffusion (f), and slow-diffusion coefficient (Ds ). Scan time, estimated signal-to-noise ratio (eSNR), eSNR per acquisition, and distortion ratio were compared. Coefficients of variation (CoV) and Bland Altman analyses were performed for test-retest repeatability. Interclass correlation coefficient (ICC) assessed interobserver agreement with P < 0.05 deemed significant. Within-subject CoVs among volunteers (N = 10) for f and Ds were lowest in EPI-NE-LO (11.6%) and SMS-RT-HI (11.1%). Inter-observer ICCs for f and Ds were highest for EPI-NE-LO (0.63) and SMS-RT-LO (0.76). Df could not be estimated for most subjects. Estimated eSNR (EPI = 21.9, SMS = 4.7) and eSNR time (EPI = 6.7, SMS = 16.6) were greater for SMS, with less distortion in the liver region (DR-PE: EPI = 23.6, SMS = 13.1). Simultaneous multislice acquisitions had significantly less variability and higher ICCs of Ds , higher eSNR, less distortion, and reduced scan time compared to EPI. 2 TECHNICAL EFFICACY: Stage 1.

Bifurcated Topological Optimization for IVIM.

In this work, we shed light on the issue of estimating Intravoxel Incoherent Motion (IVIM) for diffusion and perfusion estimation by characterizing the objective function using simplicial homology tools. We provide a robust solution via topological optimization of this model so that the estimates are more reliable and accurate. Estimating the tissue microstructure from diffusion MRI is in itself an ill-posed and a non-linear inverse problem. Using variable projection functional (VarPro) to fit the standard bi-exponential IVIM model we perform the optimization using simplicial homology based global optimization to better understand the topology of objective function surface. We theoretically show how the proposed methodology can recover the model parameters more accurately and consistently by casting it in a reduced subspace given by VarPro. Additionally we demonstrate that the IVIM model parameters cannot be accurately reconstructed using conventional numerical optimization methods due to the presence of infinite solutions in subspaces. The proposed method helps uncover multiple global minima by analyzing the local geometry of the model enabling the generation of reliable estimates of model parameters.

Correction for fast pseudo-diffusive fluid motion contaminations in diffusion tensor imaging

In this prospective study, we quantified the fast pseudo-diffusion contamination by blood perfusion or cerebrospinal fluid (CSF) intravoxel incoherent movements on the measurement of the diffusion tensor metrics in healthy brain tissue.Diffusion-weighted imaging (TR/TE = 4100 ms/90 ms; b-values: 0, 5, 10, 20, 35, 55, 80, 110, 150, 200, 300, 500, 750, 1000, 1300 s/mm2, 20 diffusion-encoding directions) was performed on a cohort of five healthy volunteers at 3 Tesla. The projections of the diffusion tensor along each diffusion-encoding direction were computed using a two b-value approach (2b), by fitting the signal to a monoexponential curve (mono), and by correcting for fast pseudo-diffusion compartments using the biexponential intravoxel incoherent motion model (IVIM) (bi). Fractional anisotropy (FA) and mean diffusivity (MD) of the diffusion tensor were quantified in regions of interest drawn over white matter areas, gray matter areas, and the ventricles.A significant dependence of the MD from the evaluation method was found in all selected regions. A lower MD was computed when accounting for the fast-diffusion compartments. A larger dependence was found in the nucleus caudatus (bi: median 0.86 10−3 mm2/s, Δ2b: −11.2%, Δmono: −14.4%; p = 0.007), in the anterior horn (bi: median 2.04 10−3 mm2/s, Δ2b: −9.4%, Δmono: −11.5%, p = 0.007) and in the posterior horn of the lateral ventricles (bi: median 2.47 10−3 mm2/s, Δ2b: −5.5%, Δmono: −11.7%; p = 0.007). Also for the FA, the signal modeling affected the computation of the anisotropy metrics. The deviation depended on the evaluated region with significant differences mainly in the nucleus caudatus (bi: median 0.15, Δ2b: +39.3%, Δmono: +14.7%; p = 0.022) and putamen (bi: median 0.19, Δ2b: +3.1%, Δmono: +17.3%; p = 0.015).Fast pseudo-diffusive regimes locally affect diffusion tensor imaging (DTI) metrics in the brain. Here, we propose the use of an IVIM-based method for correction of signal contaminations through CSF or perfusion.

On the Field Strength Dependence of Bi- and Triexponential Intravoxel Incoherent Motion (IVIM) Parameters in the Liver.

Studies on intravoxel incoherent motion (IVIM) imaging are carried out with different acquisition protocols. To investigate the dependence of IVIM parameters on the B0 field strength when using a bi- or triexponential model. Prospective. 20 healthy volunteers (age: 19-28 years). Volunteers were examined at two field strengths (1.5 and 3T). Diffusion-weighted images of the abdomen were acquired at 24 b-values ranging from 0.2 to 500 s/mm2 . ROIs were manually drawn in the liver. Data were fitted with a bi- and a triexponential IVIM model. The resulting parameters were compared between both field strengths. One-way analysis of variance (ANOVA) and Kruskal-Wallis test were used to test the obtained IVIM parameters for a significant field strength dependency. At b-values below 6 s/mm2 , the triexponential model provided better agreement with the data than the biexponential model. The average tissue diffusivity was D = 1.22/1.00 μm2 /msec at 1.5/3T. The average pseudodiffusion coefficients for the biexponential model were D* = 308/260 μm2 /msec at 1.5/3T; and for the triexponential model = 81.3/65.9 μm2 /msec, = 2453/2333 μm2 /msec at 1.5/3T. The average perfusion fractions for the biexponential model were f = 0.286/0.303 at 1.5/3T; and for the triexponential model f1 = 0.161/0.174 and f2 = 0.152/0.159 at 1.5/3T. A significant B0 dependence was only found for the biexponential pseudodiffusion coefficient (ANOVA/KW P = 0.037/0.0453) and tissue diffusivity (ANOVA/KW: P < 0.001). Our experimental results suggest that triexponential pseudodiffusion coefficients and perfusion fractions obtained at different field strengths could be compared across different studies using different B0 . However, it is recommended to take the field strength into account when comparing tissue diffusivities or using the biexponential IVIM model. Considering published values for oxygenation-dependent transversal relaxation times of blood, it is unlikely that the two blood compartments of the triexponential model represent venous and arterial blood. 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1883-1892.

Performance of U-net based pyramidal lucas-kanade registration on free-breathing multi-b-value diffusion MRI of the kidney.

In free-breathing multi-b-value diffusion-weighted imaging (DWI), a series of images typically requires several minutes to collect. During respiration the kidney is routinely displaced and may also undergo deformation. These respiratory motion effects generate artifacts and these are the main sources of error in the quantification of intravoxel incoherent motion (IVIM) derived parameters. This work proposes a fully automated framework that combines a kidney segmentation to improve the registration accuracy. 10 healthy subjects were recruited to participate in this experiment. For the segmentation, U-net was adopted to acquire the kidney's contour. The segmented kidney then served as a region of interest (ROI) for the registration method, known as pyramidal Lucas-Kanade. Our proposed framework confines the kidney's solution range, thus increasing the pyramidal Lucas-Kanade's accuracy. To demonstrate the feasibility of our presented framework, eight regions of interest were selected in the cortex and medulla, and data stability was estimated by comparing the normalized root-mean-square error (NRMSE) values of the fitted data from the bi-exponential intravoxel incoherent motion model pre- and post- registration. The results show that the NRMSE was significantly lower after registration both in the cortex (p < 0.05) and medulla (p < 0.01) during free-breathing measurements. In addition, expert visual scoring of the derived apparent diffusion coefficient (ADC), f, D and D* maps indicated there were significant improvements in the alignment of the kidney in the post-registered image. The proposed framework can effectively reduce the motion artifacts of misaligned multi-b-value DWIs and the inaccuracies of the ADC, f, D and D* estimations. Advances in knowledge: This study demonstrates the feasibility of our proposed fully automated framework combining U-net based segmentation and pyramidal Lucas-Kanade registration method for improving the alignment of multi-b-value diffusion-weighted MRIs and reducing the inaccuracy of parameter estimation during free-breathing.

Investigation of the pulsatility of cerebrospinal fluid using cardiac-gated Intravoxel Incoherent Motion imaging

The quantitative and non-invasive monitoring of cerebrospinal fluid (CSF) dynamics and composition may have high clinical relevance in the management of CSF disorders. In this study, we propose the use of the Intravoxel Incoherent Motion (IVIM) MRI for obtaining simultaneous measurements of CSF self-diffusion and fluid circulation. The rationale for this study was that turbulent fluid and mesoscopic fluid fluctuations can be modeled in a first approximation as a fast diffusion process. In this case, we expect that the fast fluid circulation and slower molecular diffusion dynamics can be quantified, assuming a bi-exponential attenuation pattern of the diffusion-weighted signal in MRI.IVIM indexes of fast and slow diffusion measured at different sites of the CSF system were systematically evaluated depending on both the phase of the heart cycle and the direction of the diffusion-encoding. The IVIM measurements were compared to dynamic measurements of fluid circulation performed by phase-contrast MRI.Concerning the dependence on the diffusion/flow-encoding direction, similar patterns were found both in the fraction of fast diffusion, f, and in the fluid velocity. Generally, we observed a moderate to high correlation between the fraction of fast diffusion and the maximum fluid velocity along the high-flow directions. Exploratory data analysis detected similarities in the dependency of the fraction of fast diffusion and of the velocity from the phase of the cardiac cycle. However, no significant differences were found between parameters measured during different phases of the cardiac cycle.Our results suggest that the fraction of fast diffusion may reflect CSF circulation. The bi-exponential IVIM model potentially allows us to disentangle the two diffusion components of the CSF dynamics by providing measurements of fluid cellularity (via the slow-diffusion coefficient) and circulation (via the fraction of fast-diffusion index).

Effect of multiple perfusion components on pseudo-diffusion coefficient in intravoxel incoherent motion imaging

The aim of this work was to investigate the effect of multiple perfusion components on the pseudo-diffusion coefficient D* in the bi-exponential intravoxel incoherent motion (IVIM) model. Simulations were first performed to examine how the presence of multiple perfusion components influences D*. The real data of livers (n = 31), spleens (n = 31) and kidneys (n = 31) of 31 volunteers was then acquired using DWI for in vivo study and the number of perfusion components in these tissues was determined together with their perfusion fraction and D*, using an adaptive multi-exponential IVIM model. Finally, the bi-exponential model was applied to the real data and the mean, standard variance and coefficient of variation of D* as well as the fitting residual were calculated over the 31 volunteers for each of the three tissues and compared between them. The results of both the simulations and the in vivo study showed that, for the bi-exponential IVIM model, both the variance of D* and the fitting residual tended to increase when the number of perfusion components was increased or when the difference between perfusion components became large. In addition, it was found that the kidney presented the fewest perfusion components among the three tissues. The present study demonstrated that multi-component perfusion is a main factor that causes high variance of D* and the bi-exponential model should be used only when the tissues under investigation have few perfusion components, for example the kidney.

Diffusional kurtosis imaging (DKI) incorporation into an intravoxel incoherent motion (IVIM) MR model to measure cerebral hypoperfusion induced by hyperventilation challenge in healthy subjects.

The objectives were to investigate the diffusional kurtosis imaging (DKI) incorporation into the intravoxel incoherent motion (IVIM) model for measurements of cerebral hypoperfusion in healthy subjects. Eight healthy subjects underwent a hyperventilation challenge with a 4-min diffusion weighted imaging protocol, using 8 b values chosen with the Cramer-Rao Lower Bound optimization approach. Four regions of interest in gray matter (GM) were analyzed with the DKI-IVIM model and the bi-exponential IVIM model, for normoventilation and hyperventilation conditions. A significant reduction in the perfusion fraction (f) and in the product fD* of the perfusion fraction with the pseudodiffusion coefficient (D*) was found with the DKI-IVIM model, during the hyperventilation challenge. In the cerebellum GM, the percentage changes were f: -43.7±40.1, p=0.011 and fD*: -50.6±32.1, p=0.011; in thalamus GM, f: -47.7±34.7, p=0.012 and fD*: -47.2±48.7, p=0.040. In comparison, using the bi-exponential IVIM model, only a significant decrease in the parameter fD* was observed for the same regions of interest. In frontal-GM and posterior-GM, the reduction in f and fD* did not reach statistical significance, either with DKI-IVIM or the bi-exponential IVIM model. When compared to the bi-exponential IVIM model, the DKI-IVIM model displays a higher sensitivity to detect changes in perfusion induced by the hyperventilation condition.

A two-pool model to describe the IVIM cerebral perfusion

IntraVoxel Incoherent Motion (IVIM) is a magnetic resonance imaging (MRI) technique capable of measuring perfusion-related parameters. In this manuscript, we show that the mono-exponential model commonly used to process IVIM data might be challenged, especially at short diffusion times. Eleven rat datasets were acquired at 7T using a diffusion-weighted pulsed gradient spin echo sequence with b-values ranging from 7 to 2500 s/mm2 at three diffusion times. The IVIM signals, obtained by removing the diffusion component from the raw MR signal, were fitted to the standard mono-exponential model, a bi-exponential model and the Kennan model. The Akaike information criterion used to find the best model to fit the data demonstrates that, at short diffusion times, the bi-exponential IVIM model is most appropriate. The results obtained by comparing the experimental data to a dictionary of numerical simulations of the IVIM signal in microvascular networks support the hypothesis that such a bi-exponential behavior can be explained by considering the contribution of two vascular pools: capillaries and somewhat larger vessels.

Motion Correction of Multi-b-value Diffusion-weighted Imaging in the Liver

Motion artifacts are a significant source of error in the acquisition and quantification of parameters from multi-b-value diffusion-weighted imaging (DWI). The objective of this article is to present a reliable method to reduce motion-related artifacts during free-breathing at higher b-values when signal levels are low. Twelve patients referred for magnetic resonance imaging of the liver underwent a clinical magnetic resonance imaging examination of the abdominal region that included DWI. Conventional single-shot spin-echo echo planar imaging acquisitions of the liver during free breathing were repeated in a "time-resolved" manner during a single acquisition to obtain data for multi-b-value analysis, alternating between low and high b-values. Image registration using a normalized mutual information similarity measure was used to correct for spatial misalignment of diffusion-weighted volumes caused by motion. Registration error was estimated indirectly by comparing the normalized root-mean-square error (NRMSE) values of data fitted to the biexponential intra-voxel incoherent motion model before and after motion correction. Regions of interest (ROIs) were selected in the liver close to the surface of the liver and close to internal structures such as large bile ducts and blood vessels. For the 12 patient datasets, the mean NRMSE value for the motion-corrected ROIs (0.38 ± 0.16) was significantly lower than the mean NRMSE values for the non-motion-corrected ROIs (0.41 ± 0.13) (P < .05). In cases where there was substantial respiratory motion during the acquisition, visual inspection verified that the algorithm markedly improved alignment of the liver contours between frames. The proposed method addresses motion-related artifacts to increase robustness in multi-b-value acquisitions.

Temporally Resolved Electrocardiogram-Triggered Diffusion-Weighted Imaging of the Human Kidney

To evaluate the influence of pulsatile blood flow on apparent diffusion coefficients (ADC) and the fraction of pseudodiffusion (F(P)) in the human kidney. The kidneys of 6 healthy volunteers were examined by a 3-T magnetic resonance scanner. Electrocardiogram (ECG)-gated and respiratory-triggered diffusion-weighted imaging (DWI) and phase-contrast flow measurements were performed. Flow imaging of renal arteries was carried out to quantify the dependence of renal blood flow on the cardiac cycle. ECG-triggered DWI was acquired in the coronal plane with 16 b values in the range of 0 s/mm(2) and 750 s/mm(2) at the time of minimum (MIN) (20 milliseconds after R wave) and maximum renal blood flow (MAX) (197 ± 24 milliseconds after R wave). The diffusion coefficients were calculated using the monoexponential approach as well as the biexponential intravoxel incoherent motion model and correlated to phase-contrast flow measurements. Flow imaging showed pulsatile renal blood flow depending on the cardiac cycle. The mean flow velocity at MIN was 45 cm/s as compared with 61 cm/s at MAX. F(p) at MIN (0.29) was significantly lower than at MAX (0.40) (P = 0.001). Similarly, ADC(mono), derived from the monoexponential model, also showed a significant difference (P < 0.001) between MIN (ADC(mono) = 2.14 ± 0.08 × 10(-3) mm(2)/s) and MAX (ADC(mono) = 2.37 ± 0.04 × 10(-3) mm(2)/s). The correlation between renal blood flow and F(p) (r = 0.85) as well as ADC(mono) (r = 0.67) was statistically significant. Temporally resolved ECG-gated DWI enables for the determination of the diffusion coefficients at different time points of the cardiac cycle. ADC(mono) and FP vary significantly among acquisitions at minimum (diastole) and maximum (systole) renal blood flow. Temporally resolved ECG-gated DWI might therefore serve as a novel technique for the assessment of pulsatility in the human kidney.