IVIM analysis of brain tumors: an investigation of the relaxation effects of CSF, blood, and tumor tissue on the estimated perfusion fraction

Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics

OBJECTIVE

This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity.

METHODS

In this study, we employed the noninvasive intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) technique to examine brain fractional perfusion (FP) in two groups: individuals with obesity (N = 72) and healthy controls (N = 66). Additionally, we investigated potential associations between FP, cognitive function, and depressive symptoms in the participants with and without obesity. Finally, artificial intelligence algorithms (Boruta analysis) were also used.

RESULTS

Participants with obesity exhibited increased FP within dopaminergic brain circuits, particularly involving prefrontal cortex areas, anterior and posterior sections of the cingulate cortex, the right striatum, and the midbrain. Additionally, these individuals demonstrated lower working memory and higher depressive symptoms compared to the control group. Notably, higher FP in the inferior temporal and occipital cortices correlated with greater depressive symptoms, whereas increased FP in the right ventral caudate and the midbrain was associated with better working memory performance. A link between inflammatory and metabolic variables, with a particular emphasis on monocytes, and FP in obesity was also evidenced by Boruta analysis.

CONCLUSIONS

Increased brain perfusion in individuals with obesity is associated with cognitive function and mental health through interaction with metabolic and inflammatory factors.

Loss of aquaporin-4 results in glymphatic system dysfunction via brain-wide interstitial fluid stagnation

The glymphatic system is a fluid transport network of cerebrospinal fluid (CSF) entering the brain along arterial perivascular spaces, exchanging with interstitial fluid (ISF), ultimately establishing directional clearance of interstitial solutes. CSF transport is facilitated by the expression of aquaporin-4 (AQP4) water channels on the perivascular endfeet of astrocytes. Mice with genetic deletion of AQP4 (AQP4 KO) exhibit abnormalities in the brain structure and molecular water transport. Yet, no studies have systematically examined how these abnormalities in structure and water transport correlate with glymphatic function. Here, we used high-resolution 3D magnetic resonance (MR) non-contrast cisternography, diffusion-weighted MR imaging (MR-DWI) along with intravoxel-incoherent motion (IVIM) DWI, while evaluating glymphatic function using a standard dynamic contrast-enhanced MR imaging to better understand how water transport and glymphatic function is disrupted after genetic deletion of AQP4. AQP4 KO mice had larger interstitial spaces and total brain volumes resulting in higher water content and reduced CSF space volumes, despite similar CSF production rates and vascular density compared to wildtype mice. The larger interstitial fluid volume likely resulted in increased slow but not fast MR diffusion measures and coincided with reduced glymphatic influx. This markedly altered brain fluid transport in AQP4 KO mice may result from a reduction in glymphatic clearance, leading to enlargement and stagnation of fluid in the interstitial space. Overall, diffusion MR is a useful tool to evaluate glymphatic function and may serve as valuable translational biomarker to study glymphatics in human disease.

Advanced Diffusion of the Pediatric Brain and Spine

This article discusses new diffusion-weighted imaging (DWI) sequences, diffusion tensor imaging (DTI), and fiber tractography (FT), as well as more advanced diffusion imaging in pediatric brain and spine. Underlying disorder and pathophysiology causing diffusion abnormalities are discussed. Multishot echo planar imaging (EPI) DWI and non-EPI DWI provide higher spatial resolution with less susceptibility artifact and distortion, which are replacing conventional single-shot EPI DWI. DTI and FT have established clinical significance in pediatric brain and spine. This article discusses advanced diffusion imaging, including diffusion kurtosis imaging, neurite orientation dispersion and density imaging, diffusion spectrum imaging, intravoxel incoherent motion, and oscillating-gradient spin-echo.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Accurate intravoxel incoherent motion parameter estimation using Bayesian fitting and reduced number of low b-values

PURPOSE

Intravoxel incoherent motion (IVIM) magnetic resonance imaging is a potential noninvasive technique for the diagnosis of brain tumors. However, perfusion-related parameter mapping is a persistent problem. The purpose of this paper is to investigate the IVIM parameter mapping of brain tumors using Bayesian fitting and low b-values.

METHODS

Bayesian shrinkage prior (BSP) fitting method and different low b-value distributions were used to estimate IVIM parameters (diffusion D, pseudo-diffusion D*, and perfusion fraction F). The results were compared to those obtained by least squares (LSQ) on both simulated and in vivo brain data. Relative error (RE) and reproducibility were used to evaluate the results. The differences of IVIM parameters between brain tumor and normal regions were compared and used to assess the performance of Bayesian fitting in the IVIM application of brain tumor.

RESULTS

In tumor regions, the value of D* tended to be decreased when the number of low b-values was insufficient, especially with LSQ. BSP required less low b-values than LSQ for the correct estimation of perfusion parameters of brain tumors. The IVIM parameter maps of brain tumors yielded by BSP had smaller variability, lower RE, and higher reproducibility with respect to those obtained by LSQ. Obvious differences were observed between tumor and normal regions in parameters D (P < 0.05) and F (P < 0.001), especially F. BSP generated fewer outliers than LSQ, and distinguished better tumors from normal regions in parameter F.

CONCLUSIONS

Intravoxel incoherent motion parameters clearly allow brain tumors to be differentiated from normal regions. Bayesian fitting yields robust IVIM parameter mapping with fewer outliers and requires less low b-values than LSQ for the parameter estimation.

Feasibility of IVIM parameters from diffusion-weighted imaging at 11.7T MRI for detecting ischemic changes in common carotid artery occlusion rats

This study aimed to investigate whether intravoxel incoherent motion (IVIM) parameters can identify ischemic changes in the rat cerebral cortex using a preclinical ultra-high-field 11.7 Tesla magnetic resonance imaging (11.7TMRI) scanner. In nine female Wistar rats (eight weeks old), diffusion-weighted imaging (DWI) for IVIM analysis was successfully performed before (Pre) and after unilateral (UCCAO) and bilateral (BCCAO) common carotid artery occlusion. From the acquired DWI signals averaged in six regions of interest (ROI) placed on the cortex, volume fraction of perfusion compartment (F), pseudo diffusion coefficient (D*), F × D* and apparent diffusion coefficient (ADC) were determined as IVIM parameters in the following three DWI signal models: the bi-exponential, kurtosis, and tri-exponential model. For a subgroup analysis, four rats that survived two weeks after BCCAO were assigned to the long survival (LS) group, whereas the non-LS group consisted of the remaining five animals. Each IVIM parameter change among three phases (Pre, UCCAO and BCCAO) was statistically examined in each ROI. Then, the change in each rat group was also examined for subgroup analysis. All three models were able to identify cerebral ischemic change and damage as IVIM parameter change among three phases. Furthermore, the kurtosis model could identify the parameter changes in more regions than the other two models. In the subgroup analysis with the kurtosis model, ADC in non-LS group significantly decreased between UCCAO and BCCAO but not in LS group. IVIM parameters at 11.7TMRI may help us to detect the subtle ischemic change; in particular, with the kurtosis model.

Can the low and high b-value distribution influence the pseudodiffusion parameter derived from IVIM DWI in normal brain?

Background

Our study aims to reveal whether the low b-values distribution, high b-values upper limit, and the number of excitation (NEX) influence the accuracy of the intravoxel incoherent motion (IVIM) parameter derived from multi-b-value diffusion-weighted imaging (DWI) in the brain.

Methods

This prospective study was approved by the local Ethics Committee and informed consent was obtained from each participant. The five consecutive multi-b DWI with different b-value protocols (0–3500 s/mm²) were performed in 22 male healthy volunteers on a 3.0-T MRI system. The IVIM parameters from normal white matter (WM) and gray matter (GM) including slow diffusion coefficient (D), fast perfusion coefficient (D*) and perfusion fraction (f) were compared for differences among defined groups with different IVIM protocols by one-way ANOVA.

Results

The D* and f value of WM or GM in groups with less low b-values distribution (less than or equal to 5 b-values) were significantly lower than ones in any other group with more low b-values distribution (all P <  0.05), but no significant differences among groups with more low b-values distribution (P > 0.05). In addition, no significant differences in the D, D* and f value of WM or GM were found between group with one and more NEX of low b-values distribution (all P > 0.05). IVIM parameters in normal WM and GM strongly depended on the choice of the high b-value upper limit.

Conclusions

Metrics of IVIM parameters can be affected by low and high b value distribution. Eight low b-values distribution with high b-value upper limit of 800–1000 s/mm² may be the relatively proper set when performing brain IVIM studies.

Impact of b-Value Sampling Scheme on Brain IVIM Parameter Estimation in Healthy Subjects

Purpose:

Intravoxel incoherent motion (IVIM) analysis has attracted the interest of the clinical community due to its close relationship with microperfusion. Nevertheless, there is no clear reference protocol for its implementation; one of the questions being which b-value distribution to use. This study aimed to stress the importance of the sampling scheme and to show that an optimized b-value distribution decreases the variance associated with IVIM parameters in the brain with respect to a regular distribution in healthy volunteers.

Methods:

Ten volunteers were included in this study; images were acquired on a 1.5T MR scanner. Two distributions of 16 b-values were used: one considered ‘regular’ due to its close association with that used in other studies, and the other considered ‘optimized’ according to previous studies. IVIM parameters were adjusted according to the bi-exponential model, using two-step method. Analysis was undertaken in ROI defined using in the Automated Anatomical Labeling atlas, and parameters distributions were compared in a total of 832 ROI.

Results:

Maps with fewer speckles were obtained with the ‘optimized’ distribution. Coefficients of variation did not change significantly for the estimation of the diffusion coefficient D but decreased by approximately 39% for the pseudo-diffusion coefficient estimation and by 21% for the perfusion fraction. Distributions of adjusted parameters were found significantly different in 50% of the cases for the perfusion fraction, in 80% of the cases for the pseudo-diffusion coefficient and 17% of the cases for the diffusion coefficient. Observations across brain areas show that the range of average values for IVIM parameters is smaller in the ‘optimized’ case.

Conclusion:

Using an optimized distribution, data are sampled in a way that the IVIM signal decay is better described and less variance is obtained in the fitted parameters. The increased precision gained could help to detect small variations in IVIM parameters.

Estimation of diffusion, perfusion and fractional volumes using a multi-compartment relaxation-compensated intravoxel incoherent motion (IVIM) signal model

Compartmental diffusion MRI models that account for intravoxel incoherent motion (IVIM) of blood perfusion allow for estimation of the fractional volume of the microvascular compartment. Conventional IVIM models are known to be biased by not accounting for partial volume effects caused by free water and cerebrospinal fluid (CSF), or for tissue-dependent relaxation effects. In this work, a three-compartment model (tissue, free water and blood) that includes relaxation terms is introduced. To estimate the model parameters, in vivo human data were collected with multiple echo times (TE), inversion times (TI) and b-values, which allowed a direct relaxation estimate alongside estimation of perfusion, diffusion and fractional volume parameters. Compared to conventional two-compartment models (with and without relaxation compensation), the three-compartment model showed less effects of CSF contamination. The proposed model yielded significantly different volume fractions of blood and tissue compared to the non-relaxation-compensated model, as well as to the conventional two-compartment model, suggesting that previously reported parameter ranges, using models that do not account for relaxation, should be reconsidered.

A robust deconvolution method to disentangle multiple water pools in diffusion MRI

The diffusion-weighted magnetic resonance imaging (dMRI) signal measured in vivo arises from multiple diffusion domains, including hindered and restricted water pools, free water and blood pseudo-diffusion. Not accounting for the correct number of components can bias metrics obtained from model fitting because of partial volume effects that are present in, for instance, diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Approaches that aim to overcome this shortcoming generally make assumptions about the number of considered components, which are not likely to hold for all voxels. The spectral analysis of the dMRI signal has been proposed to relax assumptions on the number of components. However, it currently requires a clinically challenging signal-to-noise ratio (SNR) and accounts only for two diffusion processes defined by hard thresholds. In this work, we developed a method to automatically identify the number of components in the spectral analysis, and enforced its robustness to noise, including outlier rejection and a data-driven regularization term. Furthermore, we showed how this method can be used to take into account partial volume effects in DTI and DKI fitting. The proof of concept and performance of the method were evaluated through numerical simulations and in vivo MRI data acquired at 3 T. With simulations our method reliably decomposed three diffusion components from SNR = 30. Biases in metrics derived from DTI and DKI were considerably reduced when components beyond hindered diffusion were taken into account. With the in vivo data our method determined three macro-compartments, which were consistent with hindered diffusion, free water and pseudo-diffusion. Taking free water and pseudo-diffusion into account in DKI resulted in lower mean diffusivity and higher fractional anisotropy values in both gray and white matter. In conclusion, the proposed method allows one to determine co-existing diffusion compartments without prior assumptions on their number, and to account for undesired signal contaminations within clinically achievable SNR levels.

Cardiac-gated intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for the investigation of intracranial cerebrospinal fluid dynamics in the lateral ventricle: a feasibility study

PURPOSE

Intravoxel incoherent motion (IVIM) in diffusion-weighted magnetic resonance imaging (DW-MRI) attributes the signal attenuation to the molecular diffusion and to a faster pseudo-diffusion. Purpose of the study was to demonstrate the feasibility of IVIM for the investigation of intracranial cerebrospinal fluid (CSF) dynamics.

METHODS

Cardiac-gated DW-MRI images with fifteen b-values (0-1300s/mm²) along three orthogonal directions (mediolateral (ML), anteroposterior (AP), and craniocaudal (CC)) were acquired during maximum systole and diastole in 10 healthy volunteers (6 males, mean age 36 ± 15 years). A pixel-wise bi-exponential fitting with an iterative nonparametric algorithm was carried out to calculate the following parameters: diffusion coefficient (D), fast diffusion coefficient (D*), and fraction of fast diffusion (f). Region of interest measurements were performed in both lateral ventricles. Comparison of IVIM parameters was performed among two cardiac cycle acquisitions and among the diffusion-encoding directions using a paired Student's t test.

RESULTS

f significantly (p < 0.05) depended on the diffusion-encoding direction and on the cardiac cycle (diastole AP 0.30 ± 0.13, ML 0.22 ± 0.12, CC 0.26 ± 0.17; systole AP 0.45 ± 0.17, ML 0.34 ± 0.15, CC 0.40 ± 0.21). Neither a cardiac cycle nor a direction dependency was found among mean D values (which is in line with the expected intraventricular isotropic diffusion) and D* values (p > 0.05 each).

CONCLUSION

The fraction of fast diffusion from IVIM is feasible to detect a direction-dependent and cardiac-dependent pulsatile CSF flow within the lateral ventricles allowing for quantitative monitoring of CSF dynamics. This technique might provide opportunities to further investigate the pathophysiology of various neurological disorders involving altered CSF dynamics.

Differentiating between benign and malignant sinonasal lesions using dynamic contrast-enhanced MRI and intravoxel incoherent motion

PURPOSE

To explore the value of dynamic contrast-enhanced MRI (DCE-MRI) and intravoxel incoherent motion (IVIM) for distinguishing between benign and malignant sinonasal lesions and investigate the correlations between the two methods.

METHODS AND MATERIALS

Patients with sinonasal lesions (42 benign and 31 malignant) who underwent DCE-MRI and IVIM before confirmation by histopathology were enrolled in this prospective study. Parameters derived from DCE-MRI and IVIM were measured, the optimal cut-off values for differential diagnosis were determined, and the correlations between the two methods were evaluated. Statistical analyses were performed using the Wilcoxon rank sum test, receiver operating characteristic (ROC) curve analysis, and Spearman's rank correlation.

RESULTS

Significantly higher K^trans and K_ep values but lower D and f values were found in malignant lesions than in benign lesions (all p<0.001). There were no significant differences in the V_e and D* values between the two groups. The area under the curve (AUC) of K^trans was significantly higher than those of other parameters. There was no significant difference between the AUCs of DCE-MRI and IVIM with parameters combined (p=0.86). Significant inverse but weak correlations were found between D and K^trans (r=-0.46, p<0.001), f and K^trans (r=-0.41, p<0.001), D and K_ep (r=-0.37, p=0.008), and f and K_ep (r=-0.33, p=0.004).

CONCLUSIONS

DCE-MRI and IVIM can effectively differentiate between benign and malignant sinonasal lesions. IVIM findings correlate with DCE-MRI results and may represent an alternative to DCE-MRI.

To predict the radiosensitivity of nasopharyngeal carcinoma using intravoxel incoherent motion MRI at 3.0 T

PURPOSE

To investigate intravoxel incoherent motion (IVIM) MRI for evaluating the sensitivity of radiotherapy on nasopharyngeal carcinoma (NPC).

RESULTS

The reproducibility between intra-observer and inter-observer was relatively good. D (0.72×10^-3 mm²/s±0.14 vs. 0.54×10^-3 mm²/s±0.23; P < 0.001) and D* (157.92×10^-3 mm²/s±15.21 vs. 120.36×10^-3 mm²/s±10.22; P < 0.0001) were significantly higher in effective group than poor-effective group, whereas the difference of f (18.79%±2.51 vs. 16.47%±1.51) and ADC (1.21×10^-3 mm²/s±0.11 vs. 1.33×10^-3 mm²/s±0.23) could not reach statistical significant between the 2 groups (P > 0.05).

CONCLUSIONS

IVIM may be potentially useful in assessing the radiosensitivity of NPC. The higher D value combining with higher D* value might indicate the more radiosensitive of NPC, and increased D* might reflect increased blood vessel generation and parenchymal perfusion in NPC.

MATERIALS AND METHODS

Sixty consecutive patients (20 female, range, 27-83 years, mean age, 52 years) newly diagnosed NPC in the stage of T3 or T4 were enrolled. Forty-two of them were divided into effective group clinically after a standard radiotherapy according to the RECIST criteria. IVIM with 13 b-values (range, 0-800 s/mm²) and general MRI were performed at 3.0T MR scanner before and after radiotherapy. The parameters of IVIM including perfusion fraction (f), perfusion-related diffusion (D*), pure molecular diffusion (D) and apparent diffusion coefficient (ADC) were calculated. Two radiologists major in MRI diagnose analyzed all images independently and placed regions of interest (ROIs). Intra-class correlation coefficient (ICC) was used to evaluate intra-observer and inter-observer agreement. And Mann-Whitney test was used to assess the differences between the two groups.

Application of intravoxel incoherent motion (IVIM) magnetic resonance imaging in the evaluation of primitive brain tumours

Intravoxel incoherent motion is a potential non-invasive diagnostic tool in brain tumours, without any clear guidelines for its evaluation yet. In our study, we compare intravoxel incoherent motion with dynamic susceptibility contrast magnetic resonance imaging in the quantification of tumour tissue blood perfusion in 28 patients affected by brain tumours, highlighting the issues encountered during the acquisition set-up and post-processing steps. Intravoxel incoherent motion is a new imaging tool and an alternative technique to dynamic susceptibility contrast-magnetic resonance imaging which is of considerable interest at present. This is partly because it does not require the use of a contrast agent and relies on the intrinsic properties of motion in the capillaries of the spins. Compared to dynamic susceptibility contrast-magnetic resonance imaging, the intravoxel incoherent motion technique is also characterised by better resolution because the gadolinium-based contrast agent bolus used in the standard technique results in a variation by more than 50% of the signal coming from the brain. Finally, intravoxel incoherent motion is more sensitive to the incoherent motion that originates from small capillary vessels, while the dynamic susceptibility contrast signal is also contaminated by the input from larger arteries and veins, which may result in an overestimation of the blood volume. Although there are limitations due to the heterogeneity of the sample considered in our study, intravoxel incoherent motion has been shown to be an accurate noninvasive radiological biomarker, useful to distinguish between low and high grade glial tumours.

Intravoxel incoherent motion MRI in the brain: Impact of the fitting model on perfusion fraction and lesion differentiability

PURPOSE

To investigate the effect of the choice of the curve-fitting model on the perfusion fraction (f_IVIM ) with regard to tissue type characterization, correlation with microvascular anatomy, and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters. Several curve-fitting models coexist in intravoxel incoherent motion (IVIM) MRI to derive the (f_IVIM ).

MATERIALS AND METHODS

In all, 29 patients with brain lesions (12 gliomas, 11 meningiomas, three metastases, two gliotic scars, one multiple sclerosis) underwent IVIM-MRI (32 b-values, 0 to 2000 s/mm² ) at 3T. f_IVIM was determined by classic monoexponential, biexponential, and a novel nonnegative least squares (NNLS) fitting in 352 regions of interest (lesion-containing and normal-appearing tissue) and tested their correlation with DCE-MRI kinetic parameters and microvascular anatomy derived from 57 region of interest (ROI)-based biopsies and their capacities to differentiate histologically different lesions.

RESULTS

f_IVIM differed significantly between all three models and all tissue types (monoexponential confidence interval in percent [CI 3.4-3.8]; biexponential [CI 11.21-12.45]; NNLS [CI 2.06-2.60]; all P < 0.001). For all models an increase in f_IVIM was associated with a shift to larger vessels and higher vessel area / tissue area ratio (regression coefficient 0.07-0.52; P = 0.04-0.001). Correlation with kinetic parameters derived from DCE-MRI was usually not significant. Only biexponential fitting allowed differentiation of both gliosis from edema and high- from low-grade glioma (both P < 0.001).

CONCLUSION

The curve-fitting model has an important impact on f_IVIM and its capacity to differentiate tissues. f_IVIM may possibly be used to assess microvascular anatomy and is weakly correlated with DCE-MRI kinetic parameters.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1187-1199.

A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion model

OBJECT

The objective of this study is to propose a modified VARiable PROjection (VARPRO) algorithm specifically tailored for fitting the intravoxel incoherent motion (IVIM) model to diffusion-weighted magnetic resonance imaging (DW-MRI) data from locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

The proposed algorithm is compared with classical non-linear least squares (NLLS) analysis using the Levenberg-Marquardt (LM) algorithm and with two recently proposed algorithms for 'segmented' analysis. These latter two comprise two consecutive steps: first, a subset of parameters is estimated using a portion of data; second, the remaining parameters are estimated using the whole data and the previous estimates. The comparison between the algorithms was based on the [Formula: see text] goodness-of-fit measure: performance analysis was carried out on real data obtained by DW-MRI on 40 LARC patients.

RESULTS

The performance of the proposed algorithm was higher than that of LM in 64 % of cases; 'segmented' methods were poorer than our algorithm in 100 % of cases.

CONCLUSION

The proposed modified VARPRO algorithm can lead to better fit of the IVIM model to LARC DW-MRI data compared to other techniques.

Non-parametric intravoxel incoherent motion analysis in patients with intracranial lesions: Test-retest reliability and correlation with arterial spin labeling

Intravoxel incoherent motion (IVIM) analysis of diffusion imaging data provides biomarkers of true passive water diffusion and perfusion properties. A new IVIM algorithm with variable adjustment of the b-value threshold separating diffusion and perfusion effects was applied for cerebral tissue characterization in healthy volunteers, computation of test-retest reliability, correlation with arterial spin labeling, and assessment of applicability in a small cohort of patients with malignant intracranial masses. The main results of this study are threefold: (i) accounting for regional differences in the separation of the perfusion and the diffusion components improves the reliability of the model parameters; (ii) if differences in the b-value threshold are not accounted for, a significant tissue-dependent systematic bias of the IVIM parameters occurs; (iii) accounting for voxel-wise differences in the b-value threshold improves the correlation with CBF measurements in healthy volunteers and patients. The proposed algorithm provides a robust characterization of regional micro-vascularization and cellularity without a priori assumptions on tissue diffusion properties. The glioblastoma multiforme with its inherently high variability of tumor vascularization and tumor cell density may benefit from a non-invasive clinical characterization of diffusion and perfusion properties.

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The novel IVIM algorithm accounts for regional differences in the separation of the perfusion and the diffusion components.

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The algorithm improves the reliability of IVIM parameters.

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The algorithm improves the correlation with CBF in healthy volunteers and patients.

Modified triexponential analysis of intravoxel incoherent motion for brain perfusion and diffusion

BACKGROUND

To noninvasively obtain more detailed information on brain perfusion and diffusion using modified triexponential analysis.

METHODS

On a 3.0 Tesla MRI, diffusion-weighted imaging of the brain with multiple b-values was performed in healthy volunteers (n = 12). We derived perfusion-related, fast-free, and slow-restricted diffusion coefficients (Dp , Df , and Ds , respectively) and fractions (Fp , Ff , and Fs , respectively) in the frontal and occipital white matter, caudate nucleus, and putamen calculated from triexponential function by a two-step approach. Ds was initially determined using monoexponential function in b-values over 1000 s/mm(2) and was applied to triexponential function. Additionally, the literature value of the diffusion coefficient of free water at 37 °C was assigned to Df . Finally, Dp and fractions were derived using all b-values. Moreover, biexponential analysis was performed and compared with triexponential analysis. We also determined regional cerebral blood flow (rCBF) using arterial spin labeling and assessed its relation with each diffusion parameter.

RESULTS

Significant positive correlations between Dp and rCBF were found in the caudate nucleus (R = 0.84; P = 0.01) and putamen (R = 0.86; P = 0.01), whereas no diffusion parameters were significantly correlated with rCBF on biexponential analysis (P > 0.05 for all).

CONCLUSION

Diffusion analysis with triexponential function enables noninvasive gathering of more detailed information on brain perfusion and diffusion.