A framework for optimizing the acquisition protocol multishell diffusion-weighted imaging for multimodel assessment

Complementary aspects of tissue microstructure can be studied with diffusion-weighted imaging (DWI). However, there is no consensus on how to design a diffusion acquisition protocol for multiple models within a clinically feasible time. The purpose of this study is to provide a flexible framework that is able to optimize the shell acquisition protocol given a set of DWI models. Eleven healthy subjects underwent an extensive DWI acquisition protocol, including 15 candidate shells, ranging from 10 to 3500 s/mm2. The proposed framework aims to determine the optimized acquisition scheme (OAS) with a data-driven procedure minimizing the squared error of model-estimated parameters. We tested the proposed method over five heterogeneous DWI models exploiting both low and high b-values (i.e., diffusion tensor imaging [DTI], free water, intra-voxel incoherent motion [IVIM], diffusion kurtosis imaging [DKI], and neurite orientation dispersion and density imaging [NODDI]). A voxel-level and region of interest (ROI)-level analysis was conducted over the white matter and in 48 fiber bundles, respectively. Results showed that acquiring data for the five abovementioned models via OAS requires 14 min, compared with 35 min for the joint recommended acquisition protocol. The parameters derived from the reference acquisition scheme and the OAS are comparable in terms of estimated values, noise, and tissue contrast. Furthermore, the power analysis showed that the OAS retains the potential sensitivity to group-level differences in the parameters of interest, with the exception of the free water model. Overall, there is a linear correspondence (R2 = 0.91) between OAS and reference-derived parameters. In conclusion, the proposed framework optimizes the shell acquisition scheme for a given set of DWI models (i.e., DTI, free water, IVIM, DKI, and NODDI), combining low and high b-values while saving acquisition time.

A data-driven intravoxel mean diffusivities distribution approach for molecular classifications and MIB-1 prediction of gliomas

BACKGROUND

Measuring non-parametric intravoxel mean diffusivity distributions (MDDs) using magnetic resonance imaging (MRI) is a sensitive method for detecting intracellular diffusivity changes during physiological alterations. Histological and molecular glioma classifications are essential for prognosis and treatment, with distinct water diffusion dynamics among subtypes.

PURPOSE

We developed a data-driven approach using a fully connected network (FCN) to enhance the speed and stability of calculating MDDs across varying SNRs, enable tumor microstructural mapping, and test its reliability in identifying MIB-1 labeling index (LI) levels and molecular status of gliomas.

METHODS

An FCN was trained to learn the mapping between the simulated diffusion decay curves and the ground truth MDDs. We performed 5 000 000 simulation curves with various diffusivity components and random SNR∈ [ 30 , 300 ] $ \in [ {30,\ 300} ]$ . Eighty percent of simulation curves were used for the FCN training, 10% for validation, and the others were external tests for the FCN performance evaluation. In vivo data were collected to evaluate its clinical reliability. One hundred one patients (44 years ± $ \pm $ 14, 67 men) with gliomas and six healthy controls underwent a 3.0 T MRI examination with a spin echo-echo planar imaging (SE-EPI) diffusion-weighted imaging (DWI) sequence. The trained FCN was employed to calculate MDDs of each brain voxel by voxel. We used the Fuzzy C-means algorithm to cluster the MDDs of tumor voxels, facilitating the characterization of distinct glioma tissues. Quantitative assessments were conducted through sectional integrals of the MDDs, demarcated by six bands to derive signal fractions (f n , n = 1 - 6 ${{f}_n},\ n = 1 -6$ ) and diffusivities of the maximum peaks (D p e a k ${{D}_{peak}}$ ). Cosine similarity scores (CSS) were used for MDD similarity. ANOVA and Mann-Whitney U test were used for difference analysis. Logistic regression and area under the receiver operator characteristic curve (AUC) were used for classification evaluation.

RESULTS

The simulation results showed that the FCN-based MDD approach (FCN-MDD) achieved higher CSS than non-negative least squares-based MDD (NNLS-MDD). For in vivo data, the spectra of ET and NET obtained by FCN-MDD are more distinguishable than NNLS-MDD. Fraction maps delineate the characteristics of different tumor tissues (enhancing and non-enhancing tumor, edema, and necrosis).f 3 , f 4 , D p e a k ${{f}_3},\ {{f}_4},{{D}_{peak}}$ showed a positive and negative correlation with MIB-1 respectively (r = 0.568 , r = - 0.521 , r = - 0.654 $r = 0.568,\ r = - 0.521,\ r = - 0.654$ , allp < 0.001 $p < 0.001$ ). The AUC ofD p e a k ${{D}_{peak}}$ for predicting MIB-1 LI levels was 0.900 (95% CI, 0.826-0.974), versus 0.781 (0.677-0.886) of ADC. The highest AUC of isocitrate dehydrogenase (IDH) mutation status, assessed by a logistic regression model (f 1 + f 3 ${{f}_1} + {{f}_3}$ ) was 0.873 (95% CI, 0.802-0.944).

CONCLUSION

The proposed FCN-MDD method was more robust to variations in SNR and less reliant on empirically set regularization values than the NNLS-MDD method. FCN-MDD also enabled qualitative and quantitative evaluation of the composition of gliomas.

Evaluation of Local Vascular Perfusion in the Lower Extremities on Intravoxel Incoherent Motion Imaging before and after Endovascular Therapy

PURPOSE

To evaluate improvement in local vascular perfusion of the lower limbs on intravoxel incoherent motion (IVIM) imaging after endovascular therapy (EVT).

MATERIALS AND METHODS

IVIM imaging was performed on 20 lower limbs of 16 patients with lower extremity arterial diseases before and after EVT. To estimate IVIM, diffusion-weighted lower-limb axial images (number of slices = 25 and slice thickness = 3.5 mm) were acquired using different b values (0, 300, and 1000 s/mm2). IVIM imaging with the simplified IVIM techniques was performed. The perfusion-related coefficient (D* [10-3 mm2/s]), perfusion fraction (f [%]), and D*f product (10-3 mm2/s %) were calculated before and 2-3 days after EVT. The ankle brachial index (ABI), mean D* (10-3 mm2/s), mean f (%), and mean D*f product (10-3 mm2/s %) before and after EVT were compared.

RESULTS

Successful revascularization was achieved in all cases. After EVT, the mean ABI significantly increased from 0.59 ± 0.19 to 0.87 ± 0.15 (p < 0.001, paired t test). The mean D* (10-3 mm2/s) (22.08 ± 3.26 versus 24.87 ± 2.65, p = 0.005, paired t test), and D*f product (10-3 mm2/s%) (551.03 ± 79.02 versus 634.55 ± 76.96, p = 0.002, paired t-test) of the lower limbs significantly increased after EVT, whereas f (%) (25.00 ± 1.28 versus 25.52 ± 1.61, p = 0.261, paired t-test) did not significantly increased after EVT.

CONCLUSION

D* (10-3 mm2/s) and D*f product (10-3 mm2/s %) on IVIM imaging could evaluate improvement in local vascular perfusion of the lower limbs after EVT.

LEVEL OF EVIDENCE

Level 4, Case Series.

Correlation between diffusion-weighted image-derived parameters and dynamic contrast-enhanced magnetic resonance imaging-derived parameters in the orofacial region

Background

Diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) are widely used in the orofacial region. Furthermore, quantitative analyses have proven useful. However, a few reports have described the correlation between DWI-derived parameters and DCE-MRI-derived parameters, and the results have been controversial.

Purpose

To evaluate the correlation among parameters obtained by DWI and DCE-MRI and to compare them between benign and malignant lesions.

Material and Methods

Fifty orofacial lesions were analysed. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) were estimated by DWI. For DCE-MRI, TK model analysis was performed to estimate physiological parameters, for example, the influx forward volume transfer constant into the extracellular-extravascular space (EES) (Ktrans) and fractional volumes of EES and plasma components (ve and vp).

Results

Both ADC and D showed a moderate positive correlation with ve (ρ = 0.640 and 0.645, respectively). Ktrans showed a marginally weak correlation with f (ρ = 0.296), while vp was not correlated with f or D*; therefore, IVIM perfusion-related parameters and TK model perfusion-related parameters were not straightforward. Both D and ve yielded high diagnostic power between benign lesions and malignant tumours with areas under the curve (AUCs) of 0.830 and 0.782, respectively.

Conclusion

Both D and ve were reliable parameters that were useful for the differential diagnosis. In addition, the true diffusion coefficient (D) was affected by the fractional volume of EES.

Highly accelerated multi-shot intravoxel incoherent motion diffusion-weighted imaging in brain enabled by parametric POCS-based multiplexed sensitivity encoding

Recently, intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) has also been demonstrated as an imaging tool for applications in neurological and neurovascular diseases. However, the use of single-shot diffusion-weighted echo-planar imaging for IVIM DWI acquisition leads to suboptimal data quality: for instance, geometric distortion and deteriorated image quality at high spatial resolution. Although the recently commercialized multi-shot acquisition methods, such as multiplexed sensitivity encoding (MUSE), can attain high-resolution and high-quality DWI with signal-to-noise ratio (SNR) performance superior to that of the conventional parallel imaging method, the prolonged scan time associated with multi-shot acquisition is impractical for routine IVIM DWI. This study proposes an acquisition and reconstruction framework based on parametric-POCSMUSE to accelerate the four-shot IVIM DWI with 70% reduction of total scan time (13 min 8 s versus 4 min 8 s). First, the four-shot IVIM DWI scan with 17 b values was accelerated by acquiring only one segment per b value except for b values of 0 and 600 s/mm2 . Second, an IVIM-estimation scheme was integrated into the parametric-POCSMUSE to enable joint reconstruction of multi-b images from under-sampled four-shot IVIM DWI data. In vivo experiments on both healthy subjects and patients show that the proposed framework successfully produced multi-b DW images with significantly higher SNRs and lower reconstruction errors than did the conventional acceleration method based on parallel imaging. In addition, the IVIM quantitative maps estimated from the data produced by the proposed framework showed quality comparable to that of fully sampled MUSE-reconstructed images, suggesting that the proposed framework can enable highly accelerated multi-shot IVIM DWI without sacrificing data quality. In summary, the proposed framework can make multi-shot IVIM DWI feasible in a routine MRI examination, with reasonable scan time and improved geometric fidelity.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies

PURPOSE

The purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI).

METHODS

Forty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student's t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student's t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar's test.

RESULTS

DR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05).

CONCLUSION

RDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

Imaging Techniques and Clinical Application of the Marrow-Blood Barrier in Hematological Malignancies

The pathways through which mature blood cells in the bone marrow (BM) enter the blood stream and exit the BM, hematopoietic stem cells in the peripheral blood return to the BM, and other substances exit the BM are referred to as the marrow-blood barrier (MBB). This barrier plays an important role in the restrictive sequestration of blood cells, the release of mature blood cells, and the entry and exit of particulate matter. In some blood diseases and tumors, the presence of immature cells in the blood suggests that the MBB is damaged, mainly manifesting as increased permeability, especially in angiogenesis. Some imaging methods have been used to monitor the integrity and permeability of the MBB, such as DCE-MRI, IVIM, ASL, BOLD-MRI, and microfluidic devices, which contribute to understanding the process of related diseases and developing appropriate treatment options. In this review, we briefly introduce the theory of MBB imaging modalities along with their clinical applications.

Intravoxel Incoherent Motion Quantification Dependent on Measurement SNR and Tissue Perfusion: A Simulation Study

Background

The intravoxel incoherent motion (IVIM) model extracts both functional and structural information of a tissue using motion-sensitizing gradients.

Objective

The Objective of the present work is to investigate the impact of signal to noise ratio (SNR) and physiologic conditions on the validity of IVIM parameters.

Material and Methods

This study is a simulation study, modeling IVIM at a voxel, and also done 10,000 times for every single simulation. Complex noises with various standard deviations were added to signal in-silico to investigate SNR effects on output validity. Besides, some blood perfusion situations for different tissues were considered based on their physiological range to explore the impacts of blood fraction at each voxel on the validity of the IVIM outputs. Coefficient variation (CV) and bias of the estimations were computed to assess the validity of the IVIM parameters.

Results

This study has shown that the validity of IVIM output parameters highly depends on measurement SNR and physiologic characteristics of the studied organ.

Conclusion

IVIM imaging could be useful if imaging parameters are correctly selected for each specific organ, considering hardware limitations.

Intravoxel incoherent motion for differentiating residual/recurrent tumor from post-treatment change in patients with high-grade glioma

PURPOSE

To investigate the diagnostic value of f derived from IVIM technique and to correlate it with rCBV derived from DSC for the differentiation of residual/recurrent tumor from post-treatment change in patients with high-grade glioma.

MATERIALS AND METHODS

Patients who underwent MR imaging with IVIM and DSC studies for evaluation of high-grade glioma after standard treatment were enrolled in this retrospective study. For qualitative analysis, the f and rCBV maps were interpreted as hypoperfused or hyperperfused in each parameter. Quantitative analysis was performed using ROI analysis in f and rCBV parameters. The lesions were divided into residual/recurrent tumor and post-treatment change groups.

RESULTS

Nineteen patients with high-grade glioma were included. In qualitative analysis, the f-map shows higher sensitivity (100.0%) than rCBV map (92.3%), while the rCBV map shows higher specificity (100.0%) than the f-map (83.3%). In quantitative analysis, the optimal cutoff values of 1.19 for f and 1.06 for rCBV are shown to provide high diagnostic value with high sensitivity (91.7%) for both parameters but slightly higher specificity of rCBV (85.7%) than f (71.4%). The correlation between f and rCBV was good with ICC of 0.810.

CONCLUSION

The f value measured by IVIM technique, non-contrast perfusion technique, has high diagnostic performance and potential to be an alternative method to CBV measured by DSC for differentiation between residual/recurrent tumor and post-treatment change in patients with high-grade glioma.

Quantitative perfusion and water transport time model from multi b-value diffusion magnetic resonance imaging validated against neutron capture microspheres

Purpose

Quantification of perfusion in ml/100 g/min, rather than comparing relative values side-to-side, is critical at the clinical and research levels for large longitudinal and multi-center trials. Intravoxel incoherent motion (IVIM) is a non-contrast magnetic resonance imaging diffusion-based scan that uses a multitude of b -values to measure various speeds of molecular perfusion and diffusion, sidestepping inaccuracy of arterial input functions or bolus kinetics. Questions remain as to the original of the signal and whether IVIM returns quantitative and accurate perfusion in a pathology setting. This study tests a novel method of IVIM perfusion quantification compared with neutron capture microspheres.

Approach

We derive an expression for the quantification of capillary blood flow in ml/100 g/min by solving the three-dimensional Gaussian probability distribution and defining water transport time (WTT) as when 50% of the original water remains in the tissue of interest. Calculations were verified in a six-subject pre-clinical canine model of normocapnia, CO 2 induced hypercapnia, and middle cerebral artery occlusion (ischemic stroke) and compared with quantitative microsphere perfusion.

Results

Linear regression analysis of IVIM and microsphere perfusion showed agreement (slope = 0.55, intercept = 52.5, R 2 = 0.64 ) with a Bland-Altman mean difference of - 11.8 [ - 78,54 ]    ml / 100    g / min . Linear regression between dynamic susceptibility contrast mean transit time and IVIM WTT asymmetry in infarcted tissue was excellent (slope = 0.59 , intercept = 0.3, R 2 = 0.93 ). Strong linear agreement was found between IVIM and reference standard infarct volume (slope = 1.01, R 2 = 0.79 ). The simulation of cerebrospinal fluid (CSF) suppression via inversion recovery returned a blood signal reduced by 82% from combined T1 and T2 effects.

Conclusions

The accuracy and sensitivity of IVIM provides evidence that observed signal changes reflect cytotoxic edema and tissue perfusion and can be quantified with WTT. Partial volume contamination of CSF may be better removed during post-processing rather than with inversion recovery.

Differentiating tumour progression from pseudoprogression in glioblastoma patients: a monoexponential, biexponential, and stretched-exponential model-based DWI study

BACKGROUND

To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseudoprogression in glioblastoma patients.

METHODS

Forty patients with pathologically confirmed glioblastoma exhibiting enhancing lesions after completion of chemoradiation therapy were enrolled in the study, which were then classified as tumour progression and pseudoprogression. All patients underwent conventional and multi-b diffusion-weighted MRI. The apparent diffusion coefficient (ADC) from a monoexponential model, the true diffusion coefficient (D), pseudodiffusion coefficient (D*) and perfusion fraction (f) from a biexponential model, and the distributed diffusion coefficient (DDC) and intravoxel heterogeneity index (α) from a stretched-exponential model were compared between tumour progression and pseudoprogression groups. Receiver operating characteristic curves (ROC) analysis was used to investigate the diagnostic performance of different DWI parameters. Interclass correlation coefficient (ICC) was used to evaluate the consistency of measurements.

RESULTS

The values of ADC, D, DDC, and α values were lower in tumour progression patients than that in pseudoprogression patients (p < 0.05). The values of D* and f were higher in tumour progression patients than that in pseudoprogression patients (p < 0.05). Diagnostic accuracy for differentiating tumour progression from pseudoprogression was highest for α(AUC = 0.94) than that for ADC (AUC = 0.91), D (AUC = 0.92), D* (AUC = 0.81), f (AUC = 0.75), and DDC (AUC = 0.88).

CONCLUSIONS

Multi-b DWI is a promising method for differentiating tumour progression from pseudoprogression with high diagnostic accuracy. In addition, the α derived from stretched-exponential model is the most promising DWI parameter for the prediction of tumour progression in glioblastoma patients.

Integrated intravoxel incoherent motion tensor and diffusion tensor brain MRI in a single fast acquisition

The acquisition of intravoxel incoherent motion (IVIM) data and diffusion tensor imaging (DTI) data from the brain can be integrated into a single measurement, which offers the possibility to determine orientation-dependent (tensorial) perfusion parameters in addition to established IVIM and DTI parameters. The purpose of this study was to evaluate the feasibility of such a protocol with a clinically feasible scan time below 6 min and to use a model-selection approach to find a set of DTI and IVIM tensor parameters that most adequately describes the acquired data. Diffusion-weighted images of the brain were acquired at 3 T in 20 elderly participants with cerebral small vessel disease using a multiband echoplanar imaging sequence with 15 b-values between 0 and 1000 s/mm² and six non-collinear diffusion gradient directions for each b-value. Seven different IVIM-diffusion models with 4 to 14 parameters were implemented, which modeled diffusion and pseudo-diffusion as scalar or tensor quantities. The models were compared with respect to their fitting performance based on the goodness of fit (sum of squared fit residuals, chi² ) and their Akaike weights (calculated from the corrected Akaike information criterion). Lowest chi² values were found using the model with the largest number of model parameters. However, significantly highest Akaike weights indicating the most appropriate models for the acquired data were found with a nine-parameter IVIM-DTI model (with isotropic perfusion modeling) in normal-appearing white matter (NAWM), and with an 11-parameter model (IVIM-DTI with additional pseudo-diffusion anisotropy) in white matter with hyperintensities (WMH) and in gray matter (GM). The latter model allowed for the additional calculation of the fractional anisotropy of the pseudo-diffusion tensor (with a median value of 0.45 in NAWM, 0.23 in WMH, and 0.36 in GM), which is not accessible with the usually performed IVIM acquisitions based on three orthogonal diffusion-gradient directions.

Blood-brain barrier water exchange measurements using FEXI: Impact of modeling paradigm and relaxation time effects

PURPOSE

To evaluate potential modeling paradigms and the impact of relaxation time effects on human blood-brain barrier (BBB) water exchange measurements using FEXI (BBB-FEXI), and to quantify the accuracy, precision, and repeatability of BBB-FEXI exchange rate estimates at 3 T $$ \mathrm{T} $$ .

METHODS

Three modeling paradigms were evaluated: (i) the apparent exchange rate (AXR) model; (ii) a two-compartment model (2 CM $$ 2\mathrm{CM} $$ ) explicitly representing intra- and extravascular signal components, and (iii) a two-compartment model additionally accounting for finite compartmentalT 1 $$ {\mathrm{T}}_1 $$ andT 2 $$ {\mathrm{T}}_2 $$ relaxation times (2 CM r $$ 2{\mathrm{CM}}_r $$ ). Each model had three free parameters. Simulations quantified biases introduced by the assumption of infinite relaxation times in the AXR and2 CM $$ 2\mathrm{CM} $$ models, as well as the accuracy and precision of all three models. The scan-rescan repeatability of all paradigms was quantified for the first time in vivo in 10 healthy volunteers (age range 23-52 years; five female).

RESULTS

The assumption of infinite relaxation times yielded exchange rate errors in simulations up to 42%/14% in the AXR/2 CM $$ 2\mathrm{CM} $$ models, respectively. Accuracy was highest in the compartmental models; precision was best in the AXR model. Scan-rescan repeatability in vivo was good for all models, with negligible bias and repeatability coefficients in grey matter ofRC AXR = 0 . 43 $$ {\mathrm{RC}}_{\mathrm{AXR}}=0.43 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ ,RC 2 CM = 0 . 51 $$ {\mathrm{RC}}_{2\mathrm{CM}}=0.51 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ , andRC 2 CM r = 0 . 61 $$ {\mathrm{RC}}_{2{\mathrm{CM}}_r}=0.61 $$  s - 1 $$ {\mathrm{s}}^{-1} $$ .

CONCLUSION

Compartmental modelling of BBB-FEXI signals can provide accurate and repeatable measurements of BBB water exchange; however, relaxation time and partial volume effects may cause model-dependent biases.

Intravoxel incoherent motion and diffusion kurtosis imaging at 3T MRI: Application to ischemic stroke

BACKGROUND AND PURPOSE

The DKI-IVIM model that incorporates DKI (diffusional kurtosis imaging) into the IVIM (Intravoxel Incoherent Motion) concept was investigated to assess its utility for both enhanced diffusion characterization and perfusion measurements in ischemic stroke at 3 T.

METHODS

Fifteen stroke patients (71 ± 11 years old) were enrolled and DKI-IVIM analysis was performed using 9 b-values from 0 to 1500 s/mm² chosen with the Cramer-Rao-Lower-Bound optimization approach. Pseudo-diffusion coefficient D*, perfusion fraction f, blood flow-related parameter fD*, the diffusion coefficient D and an additional parameter, the kurtosis, K were determined in the ischemic lesion and controlateral normal tissue based on a region of interest approach. The apparent diffusion coefficient (ADC) and arterial spin labelling (ASL) cerebral blood flow (CBF) parameters were also assessed and parametric maps were obtained for all parameters.

RESULTS

Significant differences were observed for all diffusion parameters with a significant decrease for D (p < 0.0001), ADC (p < 0.0001), and a significant increase for K (p < 0.0001) in the ischemic lesions of all patients. f decreased significantly in these regions (p = 0.0002). The fD* increase was not significant (p = 0.56). The same significant differences were found with a motion correction except for fD* (p = 0.47). CBF significantly decreased in the lesions. ADC was significantly positively correlated with D (p < 0.0001) and negatively with K (p = 0.0002); K was also negatively significantly correlated with D (p = 0.01).

CONCLUSIONS

DKI-IVIM model enables for simultaneous cerebral perfusion and enhanced diffusion characterization in an acceptable clinically acquisition time for the ischemic stroke diagnosis with the additional kurtosis factor estimation, that may better reflect the microstructure heterogeneity.

Comprehensive Brain Tumour Characterisation with VERDICT-MRI: Evaluation of Cellular and Vascular Measures Validated by Histology

The aim of this work was to extend the VERDICT-MRI framework for modelling brain tumours, enabling comprehensive characterisation of both intra- and peritumoural areas with a particular focus on cellular and vascular features. Diffusion MRI data were acquired with multiple b-values (ranging from 50 to 3500 s/mm2), diffusion times, and echo times in 21 patients with brain tumours of different types and with a wide range of cellular and vascular features. We fitted a selection of diffusion models that resulted from the combination of different types of intracellular, extracellular, and vascular compartments to the signal. We compared the models using criteria for parsimony while aiming at good characterisation of all of the key histological brain tumour components. Finally, we evaluated the parameters of the best-performing model in the differentiation of tumour histotypes, using ADC (Apparent Diffusion Coefficient) as a clinical standard reference, and compared them to histopathology and relevant perfusion MRI metrics. The best-performing model for VERDICT in brain tumours was a three-compartment model accounting for anisotropically hindered and isotropically restricted diffusion and isotropic pseudo-diffusion. VERDICT metrics were compatible with the histological appearance of low-grade gliomas and metastases and reflected differences found by histopathology between multiple biopsy samples within tumours. The comparison between histotypes showed that both the intracellular and vascular fractions tended to be higher in tumours with high cellularity (glioblastoma and metastasis), and quantitative analysis showed a trend toward higher values of the intracellular fraction (fic) within the tumour core with increasing glioma grade. We also observed a trend towards a higher free water fraction in vasogenic oedemas around metastases compared to infiltrative oedemas around glioblastomas and WHO 3 gliomas as well as the periphery of low-grade gliomas. In conclusion, we developed and evaluated a multi-compartment diffusion MRI model for brain tumours based on the VERDICT framework, which showed agreement between non-invasive microstructural estimates and histology and encouraging trends for the differentiation of tumour types and sub-regions.

Model-based reconstructions for intravoxel incoherent motion and diffusion tensor imaging parameter map estimations

Intravoxel incoherent motion (IVIM) imaging and diffusion tensor imaging (DTI) facilitate noninvasive quantification of tissue perfusion and diffusion. Both are promising biomarkers in various diseases and a combined acquisition is therefore desirable. This comes with challenges, including noisy parameter maps and long scan times, especially for the perfusion fraction f and pseudo-diffusion coefficient D*. A model-based reconstruction has the potential to overcome these challenges. As a first step, our goal was to develop a model-based reconstruction framework for IVIM and combined IVIM-DTI parameter estimation. The IVIM and IVIM-DTI models were implemented in the PyQMRI model-based reconstruction framework and validated with simulations and in vivo data. Commonly used voxel-wise nonlinear least-squares fitting was used as the reference. Simulations with the IVIM and IVIM-DTI models were performed with 100 noise realizations to assess accuracy and precision. Diffusion-weighted data were acquired for IVIM reconstruction in the liver (n = 5), as well as for IVIM-DTI in the kidneys (n = 5) and lower-leg muscles (n = 6) of healthy volunteers. The median and interquartile range (IQR) values of the IVIM and IVIM-DTI parameters were compared to assess bias and precision. With model-based reconstruction, the parameter maps exhibited less noise, which was most pronounced in the f and D* maps, both in the simulations and in vivo. The bias values in the simulations were comparable between model-based reconstruction and the reference method. The IQR was lower with model-based reconstruction compared with the reference for all parameters. In conclusion, model-based reconstruction is feasible for IVIM and IVIM-DTI and improves the precision of the parameter estimates, particularly for f and D* maps.

Pancreatic Mass Characterization Using IVIM-DKI MRI and Machine Learning-Based Multi-Parametric Texture Analysis

Non-invasive characterization of pancreatic masses aids in the management of pancreatic lesions. Intravoxel incoherent motion-diffusion kurtosis imaging (IVIM-DKI) and machine learning-based texture analysis was used to differentiate pancreatic masses such as pancreatic ductal adenocarcinoma (PDAC), pancreatic neuroendocrine tumor (pNET), solid pseudopapillary epithelial neoplasm (SPEN), and mass-forming chronic pancreatitis (MFCP). A total of forty-eight biopsy-proven patients with pancreatic masses were recruited and classified into pNET (n = 13), MFCP (n = 6), SPEN (n = 4), and PDAC (n = 25) groups. All patients were scanned for IVIM-DKI sequences acquired with 14 b-values (0 to 2500 s/mm2) on a 1.5T MRI. An IVIM-DKI model with a 3D total variation (TV) penalty function was implemented to estimate the precise IVIM-DKI parametric maps. Texture analysis (TA) of the apparent diffusion coefficient (ADC) and IVIM-DKI parametric map was performed and reduced using the chi-square test. These features were fed to an artificial neural network (ANN) for characterization of pancreatic mass subtypes and validated by 5-fold cross-validation. Receiver operator characteristics (ROC) analyses were used to compute the area under curve (AUC). Perfusion fraction (f) was significantly higher (p < 0.05) in pNET than PDAC. The f showed better diagnostic performance for PDAC vs. MFCP with AUC:0.77. Both pseudo-diffusion coefficient (D*) and f for PDAC vs. pNET showed an AUC of 0.73. ADC and diffusion coefficient (D) showed good diagnostic performance for pNET vs. MFCP with AUC: 0.79 and 0.76, respectively. In the TA of PDAC vs. non-PDAC, f and combined IVIM-DKI parameters showed high accuracy ≥ 84.3% and AUC ≥ 0.84. Mean f and combined IVIM-DKI parameters estimated that the IVIM-DKI model with TV texture features has the potential to be helpful in characterizing pancreatic masses.

Improvement in local vascular perfusion of the lower extremities on intravoxel incoherent motion imaging: A case report

Intravoxel incoherent motion imaging has its improvement-evaluating ability in lower limb perfusion after endovascular therapy in individuals with lower extremity arterial disease. Here, we present a 70-year-old man with intermittent claudication of the left lower limb, whose microperfusion on intravoxel incoherent motion imaging improved after endovascular therapy. The patient underwent intravoxel incoherent motion imaging of the lower extremities pre- and postendovascular therapy. After endovascular therapy, the left ankle brachial index increased from 0.46 to 1.06. The mean perfusion-related coefficient (10⁻³ mm²/s) of the left lower limb increased from 19.70 ± 3.17 to 24.81 ± 3.41, and mean perfusion fraction (%) of the left lower limb slightly increased from 24.41 ± 0.96% to 25.20 ± 1.89% after endovascular therapy. Therefore, successful revascularization can improve microperfusion on intravoxel incoherent motion imaging in a patient with lower extremity arterial disease.

Intravoxel incoherent motion to differentiate spinal metastasis: A pilot study

Background

To investigate the value of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) to discriminate spinal metastasis from tuberculous spondylitis.

Methods

This study included 50 patients with spinal metastasis (32 lung cancer, 7 breast cancer, 11 renal cancer), and 20 with tuberculous spondylitis. The IVIM parameters, including the single-index model (apparent diffusion coefficient (ADC)-stand), double exponential model (ADCslow, ADCfast, and f), and the stretched-exponential model parameters (distributed diffusion coefficient (DDC) and α), were acquired. Receiver operating characteristic (ROC) and the area under the ROC curve (AUC) analysis was used to evaluate the diagnostic performance. Each parameter was substituted into a logistic regression model to determine the meaningful parameters, and the combined diagnostic performance was evaluated.

Results

The ADCfast and f showed significant differences between spinal metastasis and tuberculous spondylitis (all p &lt; 0.05). The logistic regression model results showed that ADCfast and f were independent factors affecting the outcome (P &lt; 0.05). The AUC values of ADCfast and f were 0.823 (95% confidence interval (CI): 0.719 to 0.927) and 0.876 (95%CI: 0.782 to 0.969), respectively. ADCfast combined with f showed the highest AUC value of 0.925 (95% CI: 0.858 to 0.992).

Conclusions

IVIM MR imaging might be helpful to differentiate spinal metastasis from tuberculous spondylitis, and provide guidance for clinical treatment.

Registration and quantification network (RQnet) for IVIM-DKI analysis in MRI

PURPOSE

A deep learning method is proposed for aligning diffusion weighted images (DWIs) and estimating intravoxel incoherent motion-diffusion kurtosis imaging parameters simultaneously.

METHODS

We propose an unsupervised deep learning method that performs 2 tasks: registration and quantification for intravoxel incoherent motion-diffusion kurtosis imaging analysis. A common registration method in diffusion MRI is based on minimizing dissimilarity between various DWIs, which may result in registration errors due to different contrasts in different DWIs. We designed a novel unsupervised deep learning method for both accurate registration and quantification of various diffusion parameters. In order to generate motion-simulated training data and test data, 17 volunteers were scanned without moving their heads, and 4 volunteers moved their heads during the scan in a 3 Tesla MRI. In order to investigate the applicability of the proposed method to other organs, kidney images were also obtained. We compared the registration accuracy of the proposed method, statistical parametric mapping, and a deep learning method with a normalized cross-correlation loss. In the quantification part of the proposed method, a deep learning method that considered the diffusion gradient direction was used.

RESULTS

Simulations and experimental results showed that the proposed method accurately performed registration and quantification for intravoxel incoherent motion-diffusion kurtosis imaging analysis. The registration accuracy of the proposed method was high for all b values. Furthermore, quantification performance was analyzed through simulations and in vivo experiments, where the proposed method showed the best performance among the compared methods.

CONCLUSION

The proposed method aligns the DWIs and accurately quantifies the intravoxel incoherent motion-diffusion kurtosis imaging parameters.

Multiple B-Value Model-Based Residual Network (MORN) for Accelerated High-Resolution Diffusion-Weighted Imaging

Single-Shot Echo Planar Imaging (SSEPI) based Diffusion Weighted Imaging (DWI) has shortcomings such as low resolution and severe distortions. In contrast, Multi-Shot EPI (MSEPI) provides optimal spatial resolution but increases scan time. This study proposed a Multiple b-value mOdel-based Residual Network (MORN) model to reconstruct multiple b-value high-resolution DWI from undersampled k-space data simultaneously. We incorporated Parallel Imaging (PI) into a residual U-net to reconstruct multiple b-value multi-coil data with the supervision of MUltiplexed Sensitivity-Encoding (MUSE) reconstructed Multi-Shot DWI (MSDWI). Moreover, asymmetric concatenations among different b-values and the combined loss to back propagate helped the feature transfer. After training and validation of the MORN in a dataset of 32 healthy cases, additional assessments were performed on 6 patients with different tumor types. The experimental results demonstrated that the MORN model outperformed conventional PI reconstruction (i.e. SENSE) and two state-of-the-art deep learning methods (SENSE-GAN and VSNet) in terms of PSNR (Peak Signal-to-Noise Ratio), SSIM (Structual SIMilarity) and apparent diffusion coefficient maps. In addition, using the pre-trained model under DWI, the MORN achieved consistent fractional anisotrophy and mean diffusivity reconstructed from multiple diffusion directions. Hence, the proposed method shows potential in clinical application according to the observations on tumor patients as well as images of multiple diffusion directions.

The Hyperintense study: Assessing the effects of induced blood pressure increase and decrease on MRI markers of cerebral small vessel disease: Study rationale and protocol

Background:

Neuroimaging markers of cerebral small vessel disease (SVD) are common in older individuals, but the pathophysiological mechanisms causing these lesions remain poorly understood. Although hypertension is a major risk factor for SVD, the direct causal effects of increased blood pressure are unknown. The Hyperintense study is designed to examine cerebrovascular and structural abnormalities, possibly preceding SVD, in young adults with hypertension. These patients undergo a diagnostic work-up that requires patients to temporarily discontinue their antihypertensive agents, often leading to an increase in blood pressure followed by a decrease once effective medication is restarted. This allows examination of the effects of blood pressure increase and decrease on the cerebral small vessels.

Methods:

Hyperintense is a prospective observational cohort study in 50 hypertensive adults (18–55 years) who will temporarily discontinue antihypertensive medication for diagnostic purposes. MRI and clinical data is collected at four timepoints: before medication withdrawal (baseline), once antihypertensives are largely or completely withdrawn (T = 1), when patients have restarted medication (T = 2) and reached target blood pressure and 1 year later (T = 3). The 3T MRI protocol includes conventional structural sequences and advanced techniques to assess various aspects of microvascular integrity, including blood-brain barrier function using Dynamic Contrast Enhanced MRI, white matter integrity, and microperfusion. Clinical assessments include motor and cognitive examinations and blood sampling.

Discussion:

The Hyperintense study will improve the understanding of the pathophysiological mechanisms following hypertension that may cause SVD. This knowledge can ultimately help to identify new targets for treatment of SVD, aimed at prevention or limiting disease progression.

Interobserver Reliability on Intravoxel Incoherent Motion Imaging in Patients with Acute Ischemic Stroke

BACKGROUND AND PURPOSE

Noninvasive perfusion-weighted imaging with short scanning time could be advantageous in order to determine presumed penumbral regions and subsequent treatment strategy for acute ischemic stroke (AIS). Our aim was to evaluate interobserver agreement and the clinical utility of intravoxel incoherent motion MR imaging in patients with acute ischemic stroke.

MATERIALS AND METHODS

We retrospectively studied 29 patients with AIS (17 men, 12 women; mean age, 75.2 [SD, 12.0 ] years; median, 77 years). Each patient underwent intravoxel incoherent motion MR imaging using a 1.5T MR imaging scanner. Diffusion-sensitizing gradients were applied sequentially in the x, y, and z directions with 6 different b-values (0, 50, 100, 150, 200, and 1000 seconds/mm²). From the intravoxel incoherent motion MR imaging data, diffusion coefficient, perfusion fraction, and pseudodiffusion coefficient maps were obtained using a 2-step fitting algorithm based on the Levenberg-Marquardt method. The presence of decreases in the intravoxel incoherent motion perfusion fraction and pseudodiffusion coefficient values compared with the contralateral normal-appearing brain was graded on a 2-point scale by 2 independent neuroradiologists. Interobserver agreement on the rating scale was evaluated using the κ statistic. Clinical characteristics of patients with a nondecreased intravoxel incoherent motion perfusion fraction and/or pseudodiffusion coefficient rated by the 2 observers were also assessed.

RESULTS

Interobserver agreement was shown for the intravoxel incoherent motion perfusion fraction (κ = 0.854) and pseudodiffusion coefficient (κ = 0.789) maps, which indicated almost perfect and substantial agreement, respectively. Patients with a nondecreased intravoxel incoherent motion perfusion fraction tended to show recanalization of the occluded intracranial arteries more frequently than patients with a decreased intravoxel incoherent motion perfusion fraction.

CONCLUSIONS

Intravoxel incoherent motion MR imaging could be performed in < 1 minute in addition to routine DWI. Intravoxel incoherent motion parameters noninvasively provide feasible, qualitative perfusion-related information for assessing patients with acute ischemic stroke.

Non-Invasive Evaluation of Cerebral Hemodynamic Changes After Surgery in Adult Patients With Moyamoya Using 2D Phase-Contrast and Intravoxel Incoherent Motion MRI

Objective

To explore the feasibility of 2D phase-contrast MRI (PC-MRI) and intravoxel incoherent motion (IVIM) MRI to assess cerebrovascular hemodynamic changes after surgery in adult patients with moyamoya disease (MMD).

Methods

In total, 33 patients with MMD who underwent 2D PC-MRI and IVIM examinations before and after surgery were enrolled. Postsurgical changes in peak and average velocities, average flow, forward volume, and the area of superficial temporal (STA), internal carotid (ICA), external carotid (ECA), and vertebral (VA) arteries were evaluated. The microvascular perfusion status was compared between the hemorrhage and non-hemorrhage groups.

Results

The peak velocity, average flow, forward volume, area of both the ipsilateral STA and ECA, and average velocity of the ipsilateral STA were increased (p &lt; 0.05). The average flow and forward volume of both the ipsilateral ICA and VA and the area of the ipsilateral VA were increased (p &lt; 0.05). The peak velocity, average velocity, average flow and forward volume of the contralateral STA, and the area of the contralateral ICA and ECA were also increased (p &lt; 0.05), whereas the area of the contralateral VA was decreased (p &lt; 0.05). The rf value of the ipsilateral anterior cerebral artery (ACA) supply area was increased (p &lt; 0.05) and more obvious in the non-hemorrhage group (p &lt; 0.05).

Conclusion

Two-dimensional PC-MRI and IVIM may have the potential to non-invasively evaluate cerebrovascular hemodynamic changes after surgery in patients with MMD. An improvement in the microvascular perfusion status is more obvious in patients with ischemic MMD than in patients with hemorrhagic MMD.

Intravoxel Incoherent Motion Magnetic Resonance Imaging Used in Preoperative Screening of High-Risk Patients With Moyamoya Disease Who May Develop Postoperative Cerebral Hyperperfusion Syndrome

Objective

This study aimed to investigate the feasibility of preoperative intravoxel incoherent motion (IVIM) MRI for the screening of high-risk patients with moyamoya disease (MMD) who may develop postoperative cerebral hyperperfusion syndrome (CHS).

Methods

This study composed of two parts. In the first part 24 MMD patients and 24 control volunteers were enrolled. IVIM-MRI was performed. The relative pseudo-diffusion coefficient, perfusion fraction, apparent diffusion coefficient, and diffusion coefficient (rD*, rf, rADC, and rD) values of the IVIM sequence were compared according to hemispheres between MMD patient and healthy control groups. In the second part, 98 adult patients (124 operated hemispheres) with MMD who underwent surgery were included. Preoperative IVIM-MRI was performed. The rD*, rf, rADC, rD, and rfD* values of the IVIM sequence were calculated and analyzed. Operated hemispheres were divided into CHS and non-CHS groups. Patients’ age, sex, Matsushima type, Suzuki stage, and IVIM-MRI examination results were compared between CHS and non-CHS groups.

Results

Only the rf value was significantly higher in the healthy control group than in the MMD group (P < 0.05). Out of 124 operated hemispheres, 27 were assigned to the CHS group. Patients with clinical presentation of Matsushima types I–V were more likely to develop CHS after surgery (P < 0.05). The rf values of the ipsilateral hemisphere were significantly higher in the CHS group than in the non-CHS group (P < 0.05). The rfD* values of the ACA and MCA supply areas of the ipsilateral hemisphere were significantly higher in the CHS group than in the non-CHS group (P < 0.05). Only the rf value of the anterior cerebral artery supply area in the contralateral hemisphere was higher in the CHS group than in the non-CHS group (P < 0.05). The rf values of the middle and posterior cerebral artery supply areas and the rD, rD*, and rADC values of the both hemispheres were not significantly different between the CHS and non-CHS groups (P > 0.05).

Conclusion

Preoperative non-invasive IVIM-MRI analysis, particularly the f-value of the ipsilateral hemisphere, may be helpful in predicting CHS in adult patients with MMD after surgery. MMD patients with ischemic onset symptoms are more likely to develop CHS after surgery.

Feasibility of intravoxel incoherent motion in the assessment of tumor microvasculature and blood-brain barrier integrity: a case-based evaluation of gliomas

OBJECTIVE

To evaluate the feasibility of intravoxel incoherent motion (IVIM) in assessing blood-brain barrier (BBB) integrity and microvasculature in tumoral tissue of glioma patients.

METHODS

Images from 8 high-grade and 4 low-grade glioma patients were acquired on a 3 T MRI scanner. Acquisition protocol included pre- and post-contrast T1- and T2-weighted imaging, FLAIR, dynamic susceptibility contrast (DSC), and susceptibility-weighted imaging (SWI). In addition, IVIM was acquired with 15 b-values and fitted under the non-negative least square (NNLS) model to output the diffusion (D) and pseudo-diffusion (D*) coefficients, perfusion fraction (f), and f times D* (fD*) maps.

RESULTS

IVIM perfusion-related maps were sensitive to (1) blood flow and perfusion alterations within the microvasculature of brain tumors, in agreement with intra-tumoral susceptibility signal (ITSS); (2) enhancing areas of BBB breakdown in agreement with DSC maps as well as areas of BBB abnormality that was not detected on DSC maps; (3) enhancing perfusion changes within edemas; (4) detecting early foci of increased perfusion within low-grade gliomas.

CONCLUSION

The results suggest IVIM may be a promising approach to delineate tumor extension and progression in size, and to predict histological grade, which are clinically relevant information that characterize tumors and guide therapeutic decisions in patients with glioma.

Study of bone marrow microstructure in healthy young adults using intravoxel incoherent motion diffusion-weighted MRI

Bone marrow is one of the most important organs in the human body. The evaluation of bone marrow microstructure and gender-related cellular and capillary networks in healthy young adults can help to better understand the process of bone metabolism. Intravoxel incoherent motion (IVIM) provides both diffusion and perfusion quantifications without requiring intravenous contrast agent injection. In this prospective study, 60 healthy young age-matched volunteers (30 men and 30 women) underwent MRI scans at 1.5 T using multi-b-value diffusion-weighted imaging on sagittal planes covering the lumbar bone marrow. The apparent diffusion coefficient (ADC), true ADC (D), pseudo-ADC (D*), and perfusion fraction (f) were calculated from the diffusion-weighted images using the mono- and bi-exponential models. Lumbar cancellous bone (L2-L4) was selected as the region of interest. An independent t-test was used to detect significant differences in ADC values and IVIM parameters between men and women. The differences in IVIM parameters among the L2, L3, and L4 groups were compared with analysis of variance. The D and f values in women were significantly higher than that in men (p = 0.001, 0.026). However, D* was significantly lower in women than that in men (p = 0.001). Furthermore, there was no significant gender difference for the conventional ADC value (p = 0.186). Moreover, there were no significant differences in the D, f, and D* values among the L2, L3, and L4 vertebras of women or men. IVIM parameters can show differences in bone marrow between young women and men. As a non-invasive method, it can assess bone marrow microstructure, such as cellularity and perfusion.

Monitoring Bevacizumab-Induced Tumor Vascular Normalization by Intravoxel Incoherent Motion Diffusion-Weighted MRI

BACKGROUND

Accurate monitoring of tumor blood vessel normalization progression is beneficial to accurate treatment of patients. At present, there is a lack of safe and noninvasive monitoring methods.

PURPOSE

To serial monitor the vascular normalization time window of tumor antiangiogenesis treatment through intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and histopathological methods.

STUDY TYPE

Exploratory animal study.

POPULATION

Sixty rat C6 glioma models were randomly and equally divided into the control groups (N = 30) and bevacizumab treatment groups (N = 30). Twenty-five for magnetic resonance imaging (MRI) and five for electron microscope testing in each group.

FIELD STRENGTH/SEQUENCE

T1-weighted imaging (T1WI), T2WI with a fast spin echo sequence and IVIM-DWI with a spin-echo echo-planar imaging sequence at 3 T.

ASSESSMENT

IVIM-DWI quantitative parameters (f, D, D*, and fD*) were obtained on days 0, 2, 4, 6, and 8 after bevacizumab treatment. After MRI, the microvessel density (MVD), pericyte coverage, and hypoxia-inducible factor-1α (HIF-1α) were assessed. Electron microscope observation was performed at each time point.

STATISTICAL TESTS

One-way analysis of variance and Student's t-tests were used to compare differences within and between groups. Spearman's correlation coefficient (r) assess the correlation between IVIM and pathological parameters. The intragroup correlation coefficient was determined to assess the repeatability of each IVIM parameter.

RESULTS

The IVIM-DWI perfusion parameters (f and fD*) of the treated group were higher than the control group on days 2 and 4. Compared to the control group, MVD decreased on days 2 and pericyte coverage increased on days 4 in the treatment group. Electron microscopy showed that the tight junctions of the treatment group were prolonged on days 2-4. In the control group, f had the highest correlation with MVD (r = 0.689). In the treated group, f had a good correlation with pericyte coverage (r = 0.557), HIF-1α had a moderately positive correlation with f (r = 0.480) and fD*(r = 0.447).

DATA CONCLUSION

The vascular normalization time window of bevacizumab treatment of glioma was days 2-4 after antiangiogenesis treatment, which could be monitored noninvasively by IVIM-DWI.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 3.

Triexponential Diffusion Analysis of Diffusion-weighted Imaging for Breast Ductal Carcinoma in Situ and Invasive Ductal Carcinoma

Purpose

To obtain detailed information in breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) using triexponential diffusion analysis.

Methods

Diffusion-weighted images (DWI) of the breast were obtained using single-shot diffusion echo-planar imaging with 15 b-values. Mean signal intensities at each b-value were measured in the DCIS and IDC lesions and fitted with the triexponential function based on a two-step approach: slow-restricted diffusion coefficient (D_s) was initially determined using a monoexponential function with b-values > 800 s/mm². The diffusion coefficient of free water at 37°C was assigned to the fast-free diffusion coefficient (D_f). Finally, the perfusion-related diffusion coefficient (D_p) was derived using all the b-values. Furthermore, biexponential analysis was performed to obtain the perfusion-related diffusion coefficient (D^*) and the perfusion-independent diffusion coefficient (D). Monoexponential analysis was performed to obtain the apparent diffusion coefficient (ADC). The sensitivity and specificity of the aforementioned diffusion coefficients for distinguishing between DCIS and IDC were evaluated using the pathological results.

Results

The D_s, D, and ADC of DCIS were significantly higher than those of IDC (P < 0.01 for all). There was no significant correlation between D_p and D_s, but there was a weak correlation between D^* and D. The combination of D_p and D_s showed higher sensitivity and specificity (85.9% and 71.4%, respectively), compared to the combination of D^* and D (81.5% and 33.3%, respectively).

Conclusion

Triexponential analysis can provide detailed diffusion information for breast tumors that can be used to differentiate between DCIS and IDC.

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.

A Fast Protocol for Multiparametric Characterisation of Diffusion in the Brain and Brain Tumours

Multi-parametric tissue characterisation is demonstrated using a 4-minute protocol based on diffusion trace acquisitions. Three diffusion regimes are covered simultaneously: pseudo-perfusion, Gaussian, and non-Gaussian diffusion. The clinical utility of this method for fast multi-parametric mapping for brain tumours is explored. A cohort of 17 brain tumour patients was measured on a 3T hybrid MR-PET scanner with a standard clinical MRI protocol, to which the proposed multi-parametric diffusion protocol was subsequently added. For comparison purposes, standard perfusion and a full diffusion kurtosis protocol were acquired. Simultaneous amino-acid (¹⁸F-FET) PET enabled the identification of active tumour tissue. The metrics derived from the proposed protocol included perfusion fraction, pseudo-diffusivity, apparent diffusivity, and apparent kurtosis. These metrics were compared to the corresponding metrics from the dedicated acquisitions: cerebral blood volume and flow, mean diffusivity and mean kurtosis. Simulations were carried out to assess the influence of fitting methods and noise levels on the estimation of the parameters. The diffusion and kurtosis metrics obtained from the proposed protocol show strong to very strong correlations with those derived from the conventional protocol. However, a bias towards lower values was observed. The pseudo-perfusion parameters showed very weak to weak correlations compared to their perfusion counterparts. In conclusion, we introduce a clinically applicable protocol for measuring multiple parameters and demonstrate its relevance to pathological tissue characterisation.

Assessment of Impaired Cerebrovascular Reactivity in Chronic Cerebral Ischemia using Intravoxel Incoherent Motion Magnetic Resonance Imaging

BACKGROUND

The severity of chronic cerebral ischemia can be assessed using cerebrovascular reactivity (CVR) to acetazolamide (ACZ) challenge, which is measured by single-photon emission computed tomography (SPECT); however, this is an invasive method. We investigated whether intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) can assess impaired CVR in preoperative patients with chronic cerebral ischemia and compared it to SPECT-CVR.

METHODS

Forty-seven patients with unilateral cervical carotid artery stenosis underwent diffusion-weighted MRI with 11 b-values in the range of 0-800 s/mm² and cerebral perfusion SPECT with the ACZ challenge. The perfusion fraction (f) and diffusion coefficient (D) of the IVIM parameters were calculated using a bi-exponential model. The f and D values and these ratios of the ipsilateral middle cerebral artery territory against the contralateral side were compared with the CVR values of the affected side calculated from the SPECT data.

RESULTS

The IVIM-f and D values in the affected side were significantly higher than those in the unaffected side (median: 7.74% vs. 7.45%, p = 0.027; 0.816 vs. 0.801 10^-3mm²/s, p < 0.001; respectively). However, there were no significant correlations between the f or D values and SPECT-CVR values in the affected side. In contrast, the f ratio showed a moderate negative correlation with the SPECT-CVR values (r = -0.40, p = 0.006) and detected impaired CVR (< 18.4%) with a sensitivity/specificity of 0.71/0.90.

CONCLUSION

The IVIM perfusion parameter, f, can noninvasively assess impaired CVR with high sensitivity and specificity in patients with unilateral cervical carotid artery stenosis.

Signal to noise and b-value analysis for optimal intra-voxel incoherent motion imaging in the brain

Intravoxel incoherent motion (IVIM) is a method that can provide quantitative information about perfusion in the human body, in vivo, and without contrast agent. Unfortunately, the IVIM perfusion parameter maps are known to be relatively noisy in the brain, in particular for the pseudo-diffusion coefficient, which might hinder its potential broader use in clinical applications. Therefore, we studied the conditions to produce optimal IVIM perfusion images in the brain. IVIM imaging was performed on a 3-Tesla clinical system in four healthy volunteers, with 16 b values 0, 10, 20, 40, 80, 110, 140, 170, 200, 300, 400, 500, 600, 700, 800, 900 s/mm², repeated 20 times. We analyzed the noise characteristics of the trace images as a function of b-value, and the homogeneity of the IVIM parameter maps across number of averages and sub-sets of the acquired b values. We found two peaks of noise of the trace images as function of b value, one due to thermal noise at high b-value, and one due to physiological noise at low b-value. The selection of b value distribution was found to have higher impact on the homogeneity of the IVIM parameter maps than the number of averages. Based on evaluations, we suggest an optimal b value acquisition scheme for a 12 min scan as 0 (7), 20 (4), 140 (19), 300 (9), 500 (19), 700 (1), 800 (4), 900 (1) s/mm².

Characterisation of microvessel blood velocity and segment length in the brain using multi-diffusion-time diffusion-weighted MRI

Multi-diffusion-time diffusion-weighted MRI can probe tissue microstructure, but the method has not been widely applied to the microvasculature. At long diffusion-times, blood flow in capillaries is in the diffusive regime, and signal attenuation is dependent on blood velocity (v) and capillary segment length (l). It is described by the pseudo-diffusion coefficient (D*=vl/6) of intravoxel incoherent motion (IVIM). At shorter diffusion-times, blood flow is in the ballistic regime, and signal attenuation depends on v, and not l. In theory, l could be estimated using D* and v. In this study, we compare the accuracy and repeatability of three approaches to estimating v, and therefore l: the IVIM ballistic model, the velocity autocorrelation model, and the ballistic approximation to the velocity autocorrelation model. Twenty-nine rat datasets from two strains were acquired at 7 T, with b-values between 0 and 1000 smm^-2 and diffusion times between 11.6 and 50 ms. Five rats were scanned twice to assess scan-rescan repeatability. Measurements of l were validated using corrosion casting and micro-CT imaging. The ballistic approximation of the velocity autocorrelation model had lowest bias relative to corrosion cast estimates of l, and had highest repeatability.

Brain perfusion imaging in neonates

•

MRI is the modality of choice to image and quantify cerebral perfusion.

•

Imaging of neonatal brain perfusion is possible using MRI and ultrasound.

•

Novel ultrafast ultrasound imaging allows for excellent spatiotemporal resolution.

•

Understanding cerebral hemodynamic changes of neonatal adaptation is key.

Abnormal variations of the neonatal brain perfusion can result in long-term neurodevelopmental consequences and cerebral perfusion imaging can play an important role in diagnostic and therapeutic decision-making. To identify at-risk situations, perfusion imaging of the neonatal brain must accurately evaluate both regional and global perfusion. To date, neonatal cerebral perfusion assessment remains challenging. The available modalities such as magnetic resonance imaging (MRI), ultrasound imaging, computed tomography (CT), near-infrared spectroscopy or nuclear imaging have multiple compromises and limitations. Several promising methods are being developed to achieve better diagnostic accuracy and higher robustness, in particular using advanced MRI and ultrasound techniques.

The objective of this state-of-the-art review is to analyze the methodology and challenges of neonatal brain perfusion imaging, to describe the currently available modalities, and to outline future perspectives.

Evaluation of foot hypoperfusion and estimation of percutaneous transluminal angioplasty outcome in patients with critical limb ischemia using intravoxel incoherent motion microperfusion MRI

OBJECTIVES

To emerge hypoperfusion of lower limbs in patients with critical limb ischemia (CLI) using Intravoxel Incoherent Motion microperfusion magnetic resonance imaging (IVIM-MRI). Moreover to examine the ability of IVIM-MRI to differentiate patients with severe peripheral arterial disease (PAD) from normal subjects and evaluate the percutaneous transluminal angioplasty (PTA) results in patients with CLI.

METHODS

Eight patients who presented with CLI and six healthy volunteers were examined. The patients underwent IVIM-MRI of lower extremity before and following PTA. The imaging protocol included sagittal diffusion-weighted (DW) sequences. DW images were analyzed and color parametric maps of the micro-circulation of blood inside the capillary network (D*) were constructed. The studies were evaluated by two observers to define interobserver reproducibility.

RESULTS

Technical success was achieved in all patients (8/8). The mean ankle-brachial index increased from 0.35 ± 0.2 to 0.76 ± 0.25 (p < 0.05). Successful revascularization improved IVIM microperfusion. Mean D* increased from 279.88 ± 13.47 10^-5 mm²/s to 331.51 ± 31 10^-5 mm²/s, following PTA, p < 0.05. Moreover, PAD patients presented lower D* values as compared to healthy individuals (279.88 ± 13.47 10^-5 mm²/s vs 332.47 ± 22.95 10^-5 mm²/s, p < 0.05, respectively). Good interobserver agreement was obtained with an ICC = 0.84 (95% CI 0.64-0.93).

CONCLUSIONS

IVIM-MRI can detect differences in microperfusion between patients with PAD and healthy individuals. Moreover, significant restitution of IVIM microperfusion is found following successful PTA.

ADVANCES IN KNOWLEDGE

IVIM-MRI is a safe, reproducible and effective modality for evaluation of lower limb hypoperfusion in patients with PAD. It seems also to be a helpful tool to detect changes of tissue perfusion in patients with CLI following revascularization.

Associations of increased interstitial fluid with vascular and neurodegenerative abnormalities in a memory clinic sample

The vascular and neurodegenerative processes related to clinical dementia cause cell loss which induces, amongst others, an increase in interstitial fluid (ISF). We assessed microvascular, parenchymal integrity, and a proxy of ISF volume alterations with intravoxel incoherent motion imaging in 21 healthy controls and 53 memory clinic patients - mainly affected by neurodegeneration (mild cognitive impairment, Alzheimer's disease dementia), vascular pathology (vascular cognitive impairment), and presumed to be without significant pathology (subjective cognitive decline). The microstructural components were quantified with spectral analysis using a non-negative least squares method. Linear regression was employed to investigate associations of these components with hippocampal and white matter hyperintensity (WMH) volumes. In the normal appearing white matter, a large f_int (a proxy of ISF volume) was associated with a large WMH volume and low hippocampal volume. Likewise, a large f_int value was associated with a lower hippocampal volume in the hippocampi. Large ISF volume (f_int) was shown to be a prominent factor associated with both WMHs and neurodegenerative abnormalities in memory clinic patients and is argued to play a potential role in impaired glymphatic functioning.

Inducing sterile pyramidal neuronal death in mice to model distinct aspects of gray matter encephalitis

Up to one person in a population of 10,000 is diagnosed once in lifetime with an encephalitis, in 50-70% of unknown origin. Recognized causes amount to 20-50% viral infections. Approximately one third of affected subjects develops moderate and severe subsequent damage. Several neurotropic viruses can directly infect pyramidal neurons and induce neuronal death in cortex and hippocampus. The resulting encephalitic syndromes are frequently associated with cognitive deterioration and dementia, but involve numerous parallel and downstream cellular and molecular events that make the interpretation of direct consequences of sudden pyramidal neuronal loss difficult. This, however, would be pivotal for understanding how neuroinflammatory processes initiate the development of neurodegeneration, and thus for targeted prophylactic and therapeutic interventions. Here we utilized adult male NexCreERT2xRosa26-eGFP-DTA (= 'DTA') mice for the induction of a sterile encephalitis by diphtheria toxin-mediated ablation of cortical and hippocampal pyramidal neurons which also recruits immune cells into gray matter. We report multifaceted aftereffects of this defined process, including the expected pathology of classical hippocampal behaviors, evaluated in Morris water maze, but also of (pre)frontal circuit function, assessed by prepulse inhibition. Importantly, we modelled in encephalitis mice novel translationally relevant sequelae, namely altered social interaction/cognition, accompanied by compromised thermoreaction to social stimuli as convenient readout of parallel autonomic nervous system (dys)function. High resolution magnetic resonance imaging disclosed distinct abnormalities in brain dimensions, including cortical and hippocampal layering, as well as of cerebral blood flow and volume. Fluorescent tracer injection, immunohistochemistry and brain flow cytometry revealed persistent blood-brain-barrier perturbance and chronic brain inflammation. Surprisingly, blood flow cytometry showed no abnormalities in circulating major immune cell subsets and plasma high-mobility group box 1 (HMGB1) as proinflammatory marker remained unchanged. The present experimental work, analyzing multidimensional outcomes of direct pyramidal neuronal loss, will open new avenues for urgently needed encephalitis research.

Simulation of intravoxel incoherent perfusion signal using a realistic capillary network of a mouse brain

PURPOSE

To simulate the intravoxel incoherent perfusion magnetic resonance magnitude signal from the motion of blood particles in three realistic vascular network graphs from a mouse brain.

METHODS

In three networks generated from the cortex of a mouse scanned by two-photon laser microscopy, blood flow in each vessel was simulated using Poiseuille's law. The trajectories, flow speeds and phases acquired by a fixed number of simulated blood particles during a Stejskal-Tanner bipolar pulse gradient scheme were computed. The resulting magnitude signal was obtained by integrating all phases and the pseudo-diffusion coefficient D* was estimated by fitting an exponential signal decay. To better understand the anatomical source of the intravoxel incoherent motion (IVIM) perfusion signal, the above was repeated restricting the simulation to various types of vessel.

RESULTS

The characteristics of the three microvascular networks were respectively vessel lengths (mean ± std. dev.) 67.2 ± 53.6 μm, 59.8 ± 46.2 μm and 64.5 ± 50.9 μm, diameters 6.0 ± 3.5 μm, 5.7 ± 3.6 μm and 6.1 ± 3.7 μm and simulated blood velocity 0.9 ± 1.7 μm/ms, 1.4 ± 2.5 μm/ms and 0.7 ± 2.1 μm/ms. Exponential fitting of the simulated signal decay as a function of b-value resulted in the following D*-values [10-3 mm2 /s]: 31.7, 40.4 and 33.4. The signal decay for low b-values was the largest in the larger vessels, but the smaller vessels and the capillaries accounted for more of the total volume of the networks.

CONCLUSION

This simulation improves the theoretical understanding of the IVIM perfusion estimation method by directly linking the MR IVIM perfusion signal to an ultra-high resolution measurement of the microvascular network and a realistic blood flow simulation.

Bayesian inference using hierarchical and spatial priors for intravoxel incoherent motion MR imaging in the brain: Analysis of cancer and acute stroke

The intravoxel incoherent motion (IVIM) model allows to map diffusion (D) and perfusion-related parameters (F and D*). Parameter estimation is, however, error-prone due to the non-linearity of the signal model, the limited signal-to-noise ratio (SNR) and the small volume fraction of perfusion in the in-vivo brain. In the present work, the performance of Bayesian inference was examined in the presence of brain pathologies characterized by hypo- and hyperperfusion. In particular, a hierarchical and a spatial prior were combined. Performance was compared relative to conventional segmented least squares regression, hierarchical prior only (non-segmented and segmented data likelihoods) and a deep learning approach. Realistic numerical brain IVIM simulations were conducted to assess errors relative to ground truth. In-vivo, data of 11 central nervous system cancer patients and 9 patients with acute stroke were acquired. The proposed method yielded reduced error in simulations for both the cancer and acute stroke scenarios compared to other methods across the whole investigated SNR range. The contrast-to-noise ratio of the proposed method was better or on par compared to the other techniques in-vivo. The proposed Bayesian approach hence improves IVIM parameter estimation in brain cancer and acute stroke.

The diagnostic value of intravoxel incoherent motion imaging in differentiating high-grade from low-grade gliomas: a systematic review and meta-analysis

OBJECTIVE

This meta-analysis was carried out for assessing the accuracy of intravoxel incoherent motion (IVIM) parameters true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) in differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs).

METHODS

Literatures concerning IVIM in the grading of brain gliomas published prior to October 20, 2020, searched in the Embase, PubMed, and Cochrane library. Use the quality assessment of diagnostic accuracy studies 2 (QUADAS 2) to evaluate the quality of studies. We estimated the pooled sensitivity, specificity, and the area under the summary ROC (SROC) curve to identification the accuracy of IVIM parameters D, D*, and f evaluation in grading gliomas.

RESULTS

Totally, 6 articles including 252 brain gliomas conform to the inclusion criteria. The pooled sensitivity of parameters D, D*, and f derived from IVIM were 0.85 (95%Cl, 0.76-0.91), 0.78 (95%Cl, 0.71-0.85), and 0.89 (95%Cl, 0.76-0.96), respectively. The pooled specificity were 0.78 (95%Cl, 0.60-0.90), 0.68 (95%Cl, 0.56-0.79), and 0.88 (95%Cl, 0.76-0.94), respectively. Meanwhile, the AUC of SROC curve were 0.89 (95%Cl, 0.86-0.92) , 0.81 (95%Cl, 0.77-0.84), and 0.94 (95%Cl, 0.92-0.96), respectively.

CONCLUSION

This meta-analysis suggested that IVIM parameters D, D*, and f have moderate or high diagnosis value accuracy in differentiating HGGs from LGGs, and the parameter f has greater sensitivity and specificity. Standardized methodology is warranted to guide the use of this method for clinical decision-making. However, more clinical studies are needed to prove our view.

ADVANCES IN KNOWLEDGE

IVIM parameter f showed greater sensitivity and specificity, as well as excellent performance than parameter D* and D.

Baseline Blood-Brain Barrier Leakage and Longitudinal Microstructural Tissue Damage in the Periphery of White Matter Hyperintensities

OBJECTIVE

To investigate the 2-year change in parenchymal diffusivity, a quantitative marker of microstructural tissue condition, and the relationship with baseline blood-brain barrier (BBB) permeability, in tissue at risk, i.e., the perilesional zone surrounding white matter hyperintensities (WMH) in patients with cerebral small vessel disease (cSVD).

METHODS

Patients with sporadic cSVD (lacunar stroke or mild vascular cognitive impairment) underwent 3T MRI at baseline, including dynamic contrast-enhanced MRI to quantify BBB permeability (i.e., leakage volume and rate) and intravoxel incoherent motion imaging (IVIM), a diffusion technique that provides parenchymal diffusivity D. After 2 years, IVIM was repeated. We assessed the relation between BBB leakage measures at baseline and change in parenchymal diffusivity (∆D) over 2 years in the perilesional zones (divided in 2-mm contours) surrounding WMH.

RESULTS

We analyzed 43 patients (age 68 ± 12 years, 58% male). In the perilesional zones, ∆D increased 0.10% (confidence interval [CI] 0.07-0.013%) (p < 0.01) per 2 mm closer to the WMH. Furthermore, ∆D over 2 years showed a positive correlation with both baseline BBB leakage volume (r = 0.29 [CI 0.06-0.52], p = 0.013) and leakage rate (r = 0.24 [CI 0.02-0.47], p = 0.034).

CONCLUSION

BBB leakage at baseline is related to the 2-year change in parenchymal diffusivity in the perilesional zone of WMH. These results support the hypothesis that BBB impairment might play an early role in subsequent microstructural white matter degeneration as part of the pathophysiology of cSVD.

Optimal Model Mapping for Intravoxel Incoherent Motion MRI

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 (f_p) 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 f_p 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.

Quantification of intravoxel incoherent motion with optimized b-values using deep neural network

PURPOSE

To develop a framework for quantifying intravoxel incoherent motion (IVIM) parameters, where a neural network for quantification and b-values for diffusion-weighted imaging are simultaneously optimized.

METHOD

A deep neural network (DNN) method is proposed for accurate quantification of IVIM parameters from multiple diffusion-weighted images. In addition, optimal b-values are selected to acquire the multiple diffusion-weighted images. The proposed framework consists of an MRI signal generation part and an IVIM parameter quantification part. Monte-Carlo (MC) simulations were performed to evaluate the accuracy of the IVIM parameter quantification and the efficacy of b-value optimization. In order to analyze the effect of noise on the optimized b-values, simulations were performed with five different noise levels. For in vivo data, diffusion images were acquired with the b-values from four b-values selection methods for five healthy volunteers at 3T MRI system.

RESULTS

Experiment results showed that both the optimization of b-values and the training of DNN were simultaneously performed to quantify IVIM parameters. We found that the accuracies of the perfusion coefficient (D_p ) and perfusion fraction (f) were more sensitive to b-values than the diffusion coefficient (D) was. Furthermore, when the noise level changed, the optimized b-values also changed. Therefore, noise level has to be considered when optimizing b-values for IVIM quantification.

CONCLUSION

The proposed scheme can simultaneously optimize b-values and train DNN to minimize quantification errors of IVIM parameters. The trained DNN can quantify IVIM parameters from the diffusion-weighted images obtained with the optimized b-values.

Intravoxel incoherent motion (IVIM) modeling of diffusion MRI during chemoradiation predicts therapeutic response in IDH wildtype glioblastoma

Background:

Prediction of early progression in glioblastoma may provide an opportunity to personalize treatment. Simplified intravoxel incoherent motion (IVIM) MRI offers quantitative estimates of diffusion and perfusion metrics. We investigated whether these metrics, during chemoradiation, could predict treatment outcome.

Methods:

38 patients with newly diagnosed IDH-wildtype glioblastoma undergoing 6-week/30-fraction chemoradiation had standardized post-operative MRIs at baseline (radiation planning), and at the 10th and 20th fractions. Non-overlapping T1-enhancing (T1C) and non-enhancing T2-FLAIR hyperintense regions were independently segmented. Apparent diffusion coefficient (ADC_T1C, ADC_T2-FLAIR) and perfusion fraction (f_T1C, f_T2-FLAIR) maps were generated with simplified IVIM modelling. Parameters associated with progression before or after 6.9 months (early vs late progression, respectively), overall survival (OS) and progression-free survival (PFS) were investigated.

Results:

Higher ADC_T2-FLAIR at baseline [Odds Ratio (OR) = 1.06, 95% CI 1.01–1.15, p = 0.025], lower f_T2-FLAIR at fraction 10 (OR = 2.11, 95% CI 1.04–4.27, p = 0.018), and lack of increase in ADC_T2-FLAIR at fraction 20 compared to baseline (OR = 1.12, 95% CI 1.02–1.22, p = 0.02) were associated with early progression. Combining ADC_T2-FLAIR at baseline, f_T2-FLAIR at fraction 10, ECOG and MGMT promoter methylation status significantly improved AUC to 90.3% compared to a model with only ECOG and MGMT promoter methylation status (p = 0.001). Using multivariable analysis, neither IVIM metrics were associated with OS but higher f_T2-FLAIR at fraction 10 (HR = 0.72, 95% CI 0.56–0.95, p = 0.018) was associated with longer PFS.

Conclusion:

ADC_T2-FLAIR at baseline, its lack of increase from baseline to fraction 20, or f_T2-FLAIR at fraction 10 significantly predicted early progression. f_T2-FLAIR at fraction 10 was associated with PFS.

Diffusion and Perfusion MRI Predicts Response Preceding and Shortly After Radiosurgery to Brain Metastases: A Pilot Study

BACKGROUND AND PURPOSE

To determine the ability of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict long-term response of brain metastases prior to and within 72 hours of stereotactic radiosurgery (SRS).

METHODS

In this prospective pilot study, multiple b-value DWI and T1-weighted DCE-MRI were performed in patients with brain metastases before and within 72 hours following SRS. Diffusion-weighted images were analyzed using the monoexponential and intravoxel incoherent motion (IVIM) models. DCE-MRI data were analyzed using the extended Tofts pharmacokinetic model. The parameters obtained with these methods were correlated with brain metastasis outcomes according to modified Response Assessment in Neuro-Oncology Brain Metastases criteria.

RESULTS

We included 25 lesions from 16 patients; 16 patients underwent pre-SRS MRI and 12 of 16 patients underwent both pre- and early (within 72 hours) post-SRS MRI. The perfusion fraction (f) derived from IVIM early post-SRS was higher in lesions demonstrating progressive disease than in lesions demonstrating stable disease, partial response, or complete response (q = .041). Pre-SRS extracellular extravascular volume fraction, v_e , and volume transfer coefficient, K^trans , derived from DCE-MRI were higher in nonresponders versus responders (q = .041).

CONCLUSIONS

Quantitative DWI and DCE-MRI are feasible imaging methods in the pre- and early (within 72 hours) post-SRS evaluation of brain metastases. DWI- and DCE-MRI-derived parameters demonstrated physiologic changes (tumor cellularity and vascularity) and offer potentially useful biomarkers that can predict treatment response. This allows for initiation of alternate therapies within an effective time window that may help prevent disease progression.

Untangling the diffusion signal using the phasor transform

Separating the decay signal from diffusion-weighted scans into two or more components can be challenging. The phasor technique is well established in the field of optical microscopy for visualization and separation of fluorescent dyes with different lifetimes. The use of the phasor technique for separation of diffusion-weighted decay signals was recently proposed. In this study, we investigate the added value of this technique for fitting decay models and visualization of decay rates. Phasor visualization was performed in five glioblastoma patients. Using simulations, the influence of incorrect diffusivity values and of the number of b-values on fitting a three-component model with fixed diffusivities (dubbed "unmixing") was investigated for both a phasor-based fit and a linear least squares (LLS) fit. Phasor-based intravoxel incoherent motion (IVIM) fitting was compared with nonlinear least squares (NLLS) and segmented fitting (SF) methods in terms of accuracy and precision. The distributions of the parameter estimates of simulated data were compared with those obtained in a healthy volunteer. In the phasor visualizations of two glioblastoma patients, a cluster of points was observed that was not seen in healthy volunteers. The identified cluster roughly corresponded to the enhanced edge region of the tumor of two glioblastoma patients visible on fluid-attenuated inversion recovery (FLAIR) images. For fitting decay models the usefulness of the phasor transform is less pronounced, but the additional knowledge gained from the geometrical configuration of phasor space can aid fitting routines. This has led to slightly improved fitting results for the IVIM model: phasor-based fitting yielded parameter maps with higher precision than the NLLS and SF methods for parameters f and D (interquartile range [IQR] for f: NLLS 27, SF 12, phasor 5.7%; IQR for D: NLLS 0.28, SF 0.18, phasor 0.10 μm² /s). For unmixing, LLS fitting slightly but consistently outperformed phasor-based fitting in all of the tested scenarios.

Intravoxel incoherent motion magnetic resonance imaging: basic principles and clinical applications

The purpose of this article was to show basic principles, acquisition, advantages, disadvantages, and clinical applications of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI). IVIM MRI as a method was introduced in the late 1980s, but recently it started attracting more interest thanks to its applications in many fields, particularly in oncology and neuroradiology. This imaging technique has been developed with the objective of obtaining not only a functional analysis of different organs but also different types of lesions. Among many accessible tools in diagnostic imaging, IVIM MRI aroused the interest of many researchers in terms of studying its applicability in the evaluation of abdominal organs and diseases. The major conclusion of this article is that IVIM MRI seems to be a very auspicious method to investigate the human body, and that nowadays the most promising clinical application for IVIM perfusion MRI is oncology. However, due to lack of standardisation of image acquisition and analysis, further studies are needed to validate this method in clinical practice.

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.